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text: IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, VOL. XX, NO. XX, XXXXXXX XXXX 9 in this paper in a lab environment. However, the result we VIII. RELATED WORK gathered in this real-world example substantially validates our Mobile phone based sensing algorithms, approaches, and lab simulations. Later, we ran series of experiments to evaluate applications are discussed in [8]. DAM4GSN [20] is an three usecase scenarios presented in Section . We simulated approach based on GSN that is capable of collecting data from those scenarios in a lab environment. The data collecting internal sensors of a mobile phone and sending it to the GSN speciﬁcations are as follows. All the available sensors were middleware. No processing capabilities are provided at the conﬁgured to collect data in following experiments. We con- mobile phone end. Therefore, all the information sensed is sent ducted the experiment both with and without context-aware to the server. This approach is inefﬁcient due to the continuous capabilities activated. We measured CPU, memory, energy, usage of the communication radio of the mobile phone and storage, and network consumption. Results are presented in may also communicate sensor data that are not required or Figures 8d to Figure 8i respectively. To run these experiments, important to the data sensor data consumer [20]. Dynamix [21] we created predeﬁned data set that simulates the relevant use is a plug-and-play context framework for Android. Dynamix behaviour including location changes and activities changes automatically discovers, downloads and installs the plug-ins over time. needed for a given context sensing task. Dynamix is a stand • Scenario 1 (Environmental Monitoring):Bus moves 5 alone application and it tries to understand new environments minutes and stops for 2 minutes. This pattern will con- by using pluggable context discovery and reasoning mecha- tinue for 60 minutes (1.e. 10 stops). The sensing objective nisms. Context discovery is the main functionality in Dynamix. is to collect sensor data only when bus is moving. The One of the most popular type of processing in mobile is total duration of the experiment 6o minutes. activity recognition. Yan et al. [22] have presented an energy- • Scenario 2 (Rehabilitation): The patient performs medi- efﬁcient continuous activity recognition on mobile phones. cally recommended walking exercises for 20 minutes and Choudhury et al. [23] has also developed customs mobile rest for 15 minute. Then, the patient again walks for 15 sensing hardware platform for activity recognition. Activities minutes. The sensing objective is to collect sensor data such as walking, running taking stairs up/down, taking elevator only when the patient is walking. The total duration of up/down, cooking, working on computer, eating, watching TV, the experiment 50 minutes. talking, cycling, using an elliptical trainer, and using a stair • Scenario 3 (Health and Well-being): The user cycles to machine can be detected by using the device. Choudhury et the jogging path for 10 minutes and then she jogs for 30 al. have used sensors such as microphone, light, 3-axis dig- minutes. Next she does some bar exercise for 15 minutes ital accelerometer, barometer temperature, IR and visible+IR before return home by cycling (another 10 minutes). The light, humidity/temperature, Compass, 3D magnetometers, 3D sensing objective is to collect sensor data only when uses gyroscope, and 3D compass to collect data to support their is jogging in the jogging path. The total duration of the algorithms that detect the activities. Lee et al. [24] have experiment is 65 minutes. developed a similarity system. However, instead of processing the data in the mobile device, it sends data to the cloud According to the results presented in Figure 8e to 8i, it by using a smartphone as an intermediate gateway device. is evident that context-aware capabilities can save costs at Another similar approach has been presented by Laukkarinen different levels depending on the scenario, sensing objectives, et al. [25]. They have implemented a distributed middleware conditions, and characteristics. Based on the results gathered for 8-bit micro controller nodes where executing instructions in these experiments, we can conclude that any kind of (e.g. for data processing and event detection) are sent to context-aware functionalities (e.g. time-awareness and social each node using a Process Description Language (PDL). It is awareness) that would reduce the uninterested data collection important to note that all these approaches focus on building and transmission can be helpful to save costs. activity recognition modules. In contrast, we employ an ac- In general, wireless communication radios switching on and tivity recognition module to ﬁlter unnecessary data processing off consumes signiﬁcant amount of energy. If the number of and communication with the intention of reducing all costs. times these radios switched on can be reduced, it helps to CONSORTS-S [26] has also used a similar approach. Instead signiﬁcantly reduce the energy consumptions. As shown in of getting data from external sensors directly into mobile theoretical models, lesser the amount of data is captured, the phones, CONSORTS-S uses a custom made sensor board that less time it will take to transfer the data over the cloud, so connect to the mobile phone using a serial cable which allows the communication radios will only be required for shorter the mobile phone to collect data from external sensors. durations. When wireless radios are not actively transmitting Most mobile sensing applications can be classiﬁed into data, they will also put less workload on the CPU as well due personal and community sensing [8]. Personal sensing appli- to less reads/writes from the storage (which also requires less cations focus on the individuals. On the contrary, community memory). By conducting a number of experiments, we have sensing also termed opportunistic/crowdsensing6 takes advan- comprehensively validated the theoretical models presented in tage of a population of individuals to measure large-scale Section . We have also veriﬁed the importance of context- phenomenon that cannot be measured using single individual. aware capabilities integrated into mobile sensing platforms in In most cases, the population of individuals participating in order to breakdown Big Data into small data so anyone can analyse them and derive knowledge easily with less amount 6In this chapter, we use the terms opportunistic sensing , crowdsensing and of resources and budgets. participatory sensing synonymously.

text: IEEE

label: paragraph

text: TRANSACTIONS

text: ON

text: COMPUTATIONAL

text: SOCIAL

text: SYSTEMS,

text: VOL.

text: XX,

text: NO.

text: XX,

text: XXXXXXX

text: XXXX

text: in

text: this

text: paper

text: in

text: a

text: lab

text: environment.

text: However,

text: the

text: result

text: we

text: VIII.

label: section

text: RELATED

text: WORK

text: gathered

text: in

text: this

text: real-world

text: example

text: substantially

text: validates

text: our

text: Mobile

text: phone

text: based

text: sensing

text: algorithms,

text: approaches,

text: and

text: lab

text: simulations.

text: Later,

text: we

text: ran

text: series

text: of

text: experiments

text: to

text: evaluate

text: applications

text: are

text: discussed

text: in

text: is

text: an

text: three

text: usecase

text: scenarios

text: presented

text: in

text: Section

text: We

text: simulated

text: approach

text: based

text: on

text: GSN

text: that

text: is

text: capable

text: of

text: collecting

text: data

text: from

text: those

text: scenarios

text: in

text: a

text: lab

text: environment.

text: The

text: data

text: collecting

text: internal

text: sensors

text: of

text: a

text: mobile

text: phone

text: and

text: sending

text: it

text: to

text: the

text: GSN

text: speciﬁcations

text: are

text: as

text: follows.

text: All

text: the

text: available

text: sensors

text: were

text: middleware.

text: No

text: processing

text: capabilities

text: are

text: provided

text: at

text: the

text: conﬁgured

text: to

text: collect

text: data

text: in

text: following

text: experiments.

text: We

text: con-

text: mobile

text: phone

text: end.

text: Therefore,

text: all

text: the

text: information

text: sensed

text: is

text: sent

text: ducted

text: the

text: experiment

text: both

text: with

text: and

text: without

text: context-aware

text: to

text: the

text: server.

text: This

text: approach

text: is

text: inefﬁcient

text: due

text: to

text: the

text: continuous

text: capabilities

text: activated.

text: We

text: measured

text: CPU,

text: memory,

text: energy,

text: usage

text: of

text: the

text: communication

text: radio

text: of

text: the

text: mobile

text: phone

text: and

text: storage,

text: and

text: network

text: consumption.

text: Results

text: are

text: presented

text: in

text: may

text: also

text: communicate

text: sensor

text: data

text: that

text: are

text: not

text: required

text: or

text: Figures

text: to

text: Figure

text: respectively.

text: To

text: run

text: these

text: experiments,

text: important

text: to

text: the

text: data

text: sensor

text: data

text: consumer

text: Dynamix

text: we

text: created

text: predeﬁned

text: data

text: set

text: that

text: simulates

text: the

text: relevant

text: use

text: is

text: a

text: plug-and-play

text: context

text: framework

text: for

text: Android.

text: Dynamix

text: behaviour

text: including

text: location

text: changes

text: and

text: activities

text: changes

text: automatically

text: discovers,

text: downloads

text: and

text: installs

text: the

text: plug-ins

text: over

text: time.

text: needed

text: for

text: a

text: given

text: context

text: sensing

text: task.

text: Dynamix

text: is

text: a

text: stand

text: Scenario

text: (Environmental

text: Monitoring):Bus

text: moves

text: alone

text: application

text: and

text: it

text: tries

text: to

text: understand

text: new

text: environments

text: minutes

text: and

text: stops

text: for

text: minutes.

text: This

text: pattern

text: will

text: con-

text: by

text: using

text: pluggable

text: context

text: discovery

text: and

text: reasoning

text: mecha-

text: tinue

text: for

text: minutes

text: stops).

text: The

text: sensing

text: objective

text: nisms.

text: Context

text: discovery

text: is

text: the

text: main

text: functionality

text: in

text: Dynamix.

text: is

text: to

text: collect

text: sensor

text: data

text: only

text: when

text: bus

text: is

text: moving.

text: The

text: One

text: of

text: the

text: most

text: popular

text: type

text: of

text: processing

text: in

text: mobile

text: is

text: total

text: duration

text: of

text: the

text: experiment

text: minutes.

text: activity

text: recognition.

text: Yan

text: et

text: al.

text: have

text: presented

text: an

text: energy-

text: Scenario

text: (Rehabilitation):

text: The

text: patient

text: performs

text: medi-

text: efﬁcient

text: continuous

text: activity

text: recognition

text: on

text: mobile

text: phones.

text: cally

text: recommended

text: walking

text: exercises

text: for

text: minutes

text: and

text: Choudhury

text: et

text: al.

text: has

text: also

text: developed

text: customs

text: mobile

text: rest

text: for

text: minute.

text: Then,

text: the

text: patient

text: again

text: walks

text: for

text: sensing

text: hardware

text: platform

text: for

text: activity

text: recognition.

text: Activities

text: minutes.

text: The

text: sensing

text: objective

text: is

text: to

text: collect

text: sensor

text: data

text: such

text: as

text: walking,

text: running

text: taking

text: stairs

text: up/down,

text: taking

text: elevator

text: only

text: when

text: the

text: patient

text: is

text: walking.

text: The

text: total

text: duration

text: of

text: up/down,

text: cooking,

text: working

text: on

text: computer,

text: eating,

text: watching

text: TV,

text: the

text: experiment

text: minutes.

text: talking,

text: cycling,

text: using

text: an

text: elliptical

text: trainer,

text: and

text: using

text: a

text: stair

text: Scenario

text: (Health

text: and

text: Well-being):

text: The

text: user

text: cycles

text: to

text: machine

text: can

text: be

text: detected

text: by

text: using

text: the

text: device.

text: Choudhury

text: et

text: the

text: jogging

text: path

text: for

text: minutes

text: and

text: then

text: she

text: jogs

text: for

text: al.

text: have

text: used

text: sensors

text: such

text: as

text: microphone,

text: light,

text: dig-

text: minutes.

text: Next

text: she

text: does

text: some

text: bar

text: exercise

text: for

text: minutes

text: ital

text: accelerometer,

text: barometer

text: temperature,

text: IR

text: and

text: visible+IR

text: before

text: return

text: home

text: by

text: cycling

text: (another

text: minutes).

text: The

text: light,

text: humidity/temperature,

text: Compass,

text: magnetometers,

text: sensing

text: objective

text: is

text: to

text: collect

text: sensor

text: data

text: only

text: when

text: uses

text: gyroscope,

text: and

text: compass

text: to

text: collect

text: data

text: to

text: support

text: their

text: is

text: jogging

text: in

text: the

text: jogging

text: path.

text: The

text: total

text: duration

text: of

text: the

text: algorithms

text: that

text: detect

text: the

text: activities.

text: Lee

text: et

text: al.

text: have

text: experiment

text: is

text: minutes.

text: developed

text: a

text: similarity

text: system.

text: However,

text: instead

text: of

text: processing

text: the

text: data

text: in

text: the

text: mobile

text: device,

text: it

text: sends

text: data

text: to

text: the

text: cloud

text: According

text: to

text: the

text: results

text: presented

text: in

text: Figure

text: to

text: it

text: by

text: using

text: a

text: smartphone

text: as

text: an

text: intermediate

text: gateway

text: device.

text: is

text: evident

text: that

text: context-aware

text: capabilities

text: can

text: save

text: costs

text: at

text: Another

text: similar

text: approach

text: has

text: been

text: presented

text: by

text: Laukkarinen

text: different

text: levels

text: depending

text: on

text: the

text: scenario,

text: sensing

text: objectives,

text: et

text: al.

text: They

text: have

text: implemented

text: a

text: distributed

text: middleware

text: conditions,

text: and

text: characteristics.

text: Based

text: on

text: the

text: results

text: gathered

text: for

text: micro

text: controller

text: nodes

text: where

text: executing

text: instructions

text: in

text: these

text: experiments,

text: we

text: can

text: conclude

text: that

text: any

text: kind

text: of

text: (e.g.

text: for

text: data

text: processing

text: and

text: event

text: detection)

text: are

text: sent

text: to

text: context-aware

text: functionalities

text: (e.g.

text: time-awareness

text: and

text: social

text: each

text: node

text: using

text: a

text: Process

text: Description

text: Language

text: (PDL).

text: It

text: is

text: awareness)

text: that

text: would

text: reduce

text: the

text: uninterested

text: data

text: collection

text: important

text: to

text: note

text: that

text: all

text: these

text: approaches

text: focus

text: on

text: building

text: and

text: transmission

text: can

text: be

text: helpful

text: to

text: save

text: costs.

text: activity

text: recognition

text: modules.

text: In

text: contrast,

text: we

text: employ

text: an

text: ac-

text: In

text: general,

text: wireless

text: communication

text: radios

text: switching

text: on

text: and

text: tivity

text: recognition

text: module

text: to

text: ﬁlter

text: unnecessary

text: data

text: processing

text: off

text: consumes

text: signiﬁcant

text: amount

text: of

text: energy.

text: If

text: the

text: number

text: of

text: and

text: communication

text: with

text: the

text: intention

text: of

text: reducing

text: all

text: costs.

text: times

text: these

text: radios

text: switched

text: on

text: can

text: be

text: reduced,

text: it

text: helps

text: to

text: CONSORTS-S

text: has

text: also

text: used

text: a

text: similar

text: approach.

text: Instead

text: signiﬁcantly

text: reduce

text: the

text: energy

text: consumptions.

text: As

text: shown

text: in

text: of

text: getting

text: data

text: from

text: external

text: sensors

text: directly

text: into

text: mobile

text: theoretical

text: models,

text: lesser

text: the

text: amount

text: of

text: data

text: is

text: captured,

text: the

text: phones,

text: CONSORTS-S

text: uses

text: a

text: custom

text: made

text: sensor

text: board

text: that

text: less

text: time

text: it

text: will

text: take

text: to

text: transfer

text: the

text: data

text: over

text: the

text: cloud,

text: so

text: connect

text: to

text: the

text: mobile

text: phone

text: using

text: a

text: serial

text: cable

text: which

text: allows

text: the

text: communication

text: radios

text: will

text: only

text: be

text: required

text: for

text: shorter

text: the

text: mobile

text: phone

text: to

text: collect

text: data

text: from

text: external

text: sensors.

text: durations.

text: When

text: wireless

text: radios

text: are

text: not

text: actively

text: transmitting

text: Most

text: mobile

text: sensing

text: applications

text: can

text: be

text: classiﬁed

text: into

text: data,

text: they

text: will

text: also

text: put

text: less

text: workload

text: on

text: the

text: CPU

text: as

text: well

text: due

text: personal

text: and

text: community

text: sensing

text: Personal

text: sensing

text: appli-

text: to

text: less

text: reads/writes

text: from

text: the

text: storage

text: (which

text: also

text: requires

text: less

text: cations

text: focus

text: on

text: the

text: individuals.

text: On

text: the

text: contrary,

text: community

text: memory).

text: By

text: conducting

text: a

text: number

text: of

text: experiments,

text: we

text: have

text: sensing

text: also

text: termed

text: takes

text: advan-

text: comprehensively

text: validated

text: the

text: theoretical

text: models

text: presented

text: in

text: tage

text: of

text: a

text: population

text: of

text: individuals

text: to

text: measure

text: large-scale

text: Section

text: We

text: have

text: also

text: veriﬁed

text: the

text: importance

text: of

text: context-

text: phenomenon

text: that

text: cannot

text: be

text: measured

text: using

text: single

text: individual.

text: aware

text: capabilities

text: integrated

text: into

text: mobile

text: sensing

text: platforms

text: in

text: In

text: most

text: cases,

text: the

text: population

text: of

text: individuals

text: participating

text: in

text: order

text: to

text: breakdown

text: Big

text: Data

text: into

text: small

text: data

text: so

text: anyone

text: can

text: analyse

text: them

text: and

text: derive

text: knowledge

text: easily

text: with

text: less

text: amount

text: this

text: chapter,

text: we

text: use

text: the

text: terms

text: opportunistic

text: sensing

text: crowdsensing

text: and

text: of

text: resources

text: and

text: budgets.

text: participatory

text: sensing

text: synonymously.


text: IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, VOL. XX, NO. XX, XXXXXXX XXXX 10 crowdsensing applications share a common goal. To date, most accessible over the Internet via RESTful web services. Patti efforts to develop crowdsensing applications have focused et al. [39] have proposed an energy-efﬁcient middleware aims on building monolithic mobile applications that are built at improving energy efﬁciency of public buildings and spaces for speciﬁc requirements [27]. Furthermore, the sensed data exploiting both event-driven and user centric approaches. In generated by the application are often available only within the their work, sensors are used to detect user presence. Then, closed population [28]. However, to realise the greater vision system actuates heating systems accordingly to reduce energy of a collaborative mobile crowdsensing application, we would wastage. need a common platform that facilitates easy development and IX. CONCLUSIONS AND FUTURE WORK deployment of collaborative crowd-sensed applications [29]. Grid-M [30] is a platform for lightweight grid computing. We have presented our C-MOSDEN platform to support on- It is a tailored for embedded and mobile computing devices. demand distributed mobile crowd sensing. Our objective was The middleware is built using Java 2 Micro Edition, and to built a platform that can perform sensing tasks in a collab- an application programming interface (API) is provided to orative and selective manner. For example, the C-MOSDEN connect Java-developed applications in a Grid Computing platform can be remotely conﬁgured to sense only when a environment. This work highlights the importance of providing certain activity occurs (e.g. driving, running, walking). Further, and API based communication channel which enables com- the C-MOSDEN platform supports location-aware sensing munication. As illustrated in Figure 1, mobile nodes work (e.g. sense only when a user enters to a particular building). similar to grid computing, where they work together to collect Moreover, the platform has the capability to autonomously sensors data as instructed by the cloud based IoT middleware select which communication channel (e.g. WiFi or 3G) to use or by their own peers (e.g. other mobile sensing platform to send the data to the cloud based on context information nodes). Zhang et al. [31] have developed a middleware on top such as battery level and availability. The proposed platform of TinyOS (tinyos.net) for TelosB sensors. The data fusion collects only the data that are relevant to the data consumers, components are designed as agents which they migrate form thereby reducing the data storage requirements and processing one node to another. Such migration is an efﬁcient technique requirements. We discussed three different real-world use case in term of resource utilization. Data fusion consumes the scenarios where the proposed platform can offer signiﬁcant resources only when a given node required to process data. advantages. It was shown to facilitate the efﬁcient and ef- Otherwise the agents moves on to another node on demand. fective mobile crowd sensing functionality at a minimum We simulate such behaviour in C-MOSDEN where plugins cost. Through a series of experimentations and evaluations, are installed when needed and uninstall when not needed. we showed the importance of selective sensing through the Another agent-based sensing platform has been proposed by reduction of computational requirements. In general, through Sun and Nakata [32]. Budde et al. [33] have proposed a selective sensing, we were able to successfully reduce the framework that allows to discover smart objects in the Internet energy consumption, network communication requirements of Things. The framework allows smart objects and services and storage requirements. Although the context-aware func- to be registered by providing metadata where it later allows tionalities have generated a small amount of overhead, it was searching and selection. Mori et al. [34] has proposed a revealed that the cost savings and beneﬁts far outweighed cloud-based mobile phone sensing middleware [35] that can the increased complexity. In future works, we are planning collectively sense the environment as group of participants. to enrich C-MOSDEN with privacy preserving data analytics however, if there are more participants present in a given capabilities. region that expected, the task will be selectively assigned REFERENCES to the most appropriate participants by considering context [1] C. Perera, C. Liu, S. Jayawardena, and M. Chen, “A survey on internet information such as remaining energy, exact location, and so of things from industrial market perspective,” Access, IEEE, vol. 2, pp. on. Their approach is also focusing on reducing unnecessary 1660–1679, 2014. amount of data capturing and communication. [2] Y. Zhang, R. Yu, S. Xie, W. Yao, Y. Xiao, and M. Guizani, “Home m2m networks: Architectures, standards, and qos improvement,” Communica- NORS [36] is an open source platform that enables par- tions Magazine, IEEE, vol. 49, no. 4, pp. 44–52, April 2011. ticipatory sensing using mobile phones. It mainly focuses on [3] R. Yu, Y. Zhang, L. Song, and W. Yao, “Joint optimization of power, collecting data instead of processing. The platform includes packet forwarding and reliability in mimo wireless sensor networks,” external sensors, mobile phones, and a cloud service for Mobile Networks and Applications, vol. 16, no. 6, pp. 760–770, 2011. [Online]. Available: http://dx.doi.org/10.1007/s11036-010-0265-3 data storage. Sharing data among of mobile phones is not [4] A. Zaslavsky, C. Perera, and D. Georgakopoulos, “Sensing as a service supported. In contract, C-MOSDEN is capable of peer to and big data,” in International Conference on Advances in Cloud peer communication as well as cloud based communication. Computing (ACC-2012), Bangalore, India, July 2012, pp. 21–29. [5] H. Sundmaeker, P. Guillemin, P. Friess, and S. Woelfﬂe, “Vi- USense [37] is client-side middleware that opportunistically sion and challenges for realising the internet of things,” European and passively (i.e. without human intervention) performance Commission Information Society and Media, Tech. Rep., March sensing tasks in crowd sensing fashion. It uses XML deﬁni- 2010, http://www.internet-of-things-research.eu/pdf/IoT Clusterbook March 2010.pdf [Accessed on: 2011-10-10]. tions to explain a ‘moment’ where the middleware needs to [6] F. Xu, F. Liu, H. Jin, and A. Vasilakos, “Managing performance overhead start sensing and stop sensing. The ‘moment’ are composed of virtual machines in cloud computing: A survey, state of the art, and with a bunch of condition such as location, time, and so on. future directions,” Proceedings of the IEEE, vol. 102, no. 1, pp. 11–31, Jan 2014. Similarly, SENSE-SATION [38] also gathers and stores sensor [7] C. Perera, A. Zaslavsky, P. Christen, and D. Georgakopoulos, “Sensing information using mobile phones and make them directly as a service model for smart cities supported by internet of things,” ##LTLine## ##LTLine## ##LTLine##

text: IEEE

text: TRANSACTIONS

text: ON

text: COMPUTATIONAL

text: SOCIAL

text: SYSTEMS,

text: VOL.

text: XX,

text: NO.

text: XX,

text: XXXXXXX

text: XXXX

text: crowdsensing

text: applications

text: share

text: a

text: common

text: goal.

text: To

text: date,

text: most

text: accessible

text: over

text: the

text: Internet

text: via

text: RESTful

text: web

text: services.

text: Patti

text: efforts

text: to

text: develop

text: crowdsensing

text: applications

text: have

text: focused

text: et

text: al.

text: have

text: proposed

text: an

text: energy-efﬁcient

text: middleware

text: aims

text: on

text: building

text: monolithic

text: mobile

text: applications

text: that

text: are

text: built

text: at

text: improving

text: energy

text: efﬁciency

text: of

text: public

text: buildings

text: and

text: spaces

text: for

text: speciﬁc

text: requirements

text: Furthermore,

text: the

text: sensed

text: data

text: exploiting

text: both

text: event-driven

text: and

text: user

text: centric

text: approaches.

text: In

text: generated

text: by

text: the

text: application

text: are

text: often

text: available

text: only

text: within

text: the

text: their

text: work,

text: sensors

text: are

text: used

text: to

text: detect

text: user

text: presence.

text: Then,

text: closed

text: population

text: However,

text: to

text: realise

text: the

text: greater

text: vision

text: system

text: actuates

text: heating

text: systems

text: accordingly

text: to

text: reduce

text: energy

text: of

text: a

text: collaborative

text: mobile

text: crowdsensing

text: application,

text: we

text: would

text: wastage.

text: need

text: a

text: common

text: platform

text: that

text: facilitates

text: easy

text: development

text: and

text: IX.

text: CONCLUSIONS

text: AND

text: FUTURE

text: WORK

text: deployment

text: of

text: collaborative

text: crowd-sensed

text: applications

text: Grid-M

text: is

text: a

text: platform

text: for

text: lightweight

text: grid

text: computing.

text: We

text: have

text: presented

text: our

text: C-MOSDEN

text: platform

text: to

text: support

text: on-

text: It

text: is

text: a

text: tailored

text: for

text: embedded

text: and

text: mobile

text: computing

text: devices.

text: demand

text: distributed

text: mobile

text: crowd

text: sensing.

text: Our

text: objective

text: was

text: The

text: middleware

text: is

text: built

text: using

text: Java

text: Micro

text: Edition,

text: and

text: to

text: built

text: a

text: platform

text: that

text: can

text: perform

text: sensing

text: tasks

text: in

text: a

text: collab-

text: an

text: application

text: programming

text: interface

text: (API)

text: is

text: provided

text: to

text: orative

text: and

text: selective

text: manner.

text: For

text: example,

text: the

text: C-MOSDEN

text: connect

text: Java-developed

text: applications

text: in

text: a

text: Grid

text: Computing

text: platform

text: can

text: be

text: remotely

text: conﬁgured

text: to

text: sense

text: only

text: when

text: a

text: environment.

text: This

text: work

text: highlights

text: the

text: importance

text: of

text: providing

text: certain

text: activity

text: occurs

text: (e.g.

text: driving,

text: running,

text: walking).

text: Further,

text: and

text: API

text: based

text: communication

text: channel

text: which

text: enables

text: com-

text: the

text: C-MOSDEN

text: platform

text: supports

text: location-aware

text: sensing

text: munication.

text: As

text: illustrated

text: in

text: Figure

text: mobile

text: nodes

text: work

text: (e.g.

text: sense

text: only

text: when

text: a

text: user

text: enters

text: to

text: a

text: particular

text: building).

text: similar

text: to

text: grid

text: computing,

text: where

text: they

text: work

text: together

text: to

text: collect

text: Moreover,

text: the

text: platform

text: has

text: the

text: capability

text: to

text: autonomously

text: sensors

text: data

text: as

text: instructed

text: by

text: the

text: cloud

text: based

text: IoT

text: middleware

text: select

text: which

text: communication

text: channel

text: (e.g.

text: WiFi

text: or

text: to

text: use

text: or

text: by

text: their

text: own

text: peers

text: (e.g.

text: other

text: mobile

text: sensing

text: platform

text: to

text: send

text: the

text: data

text: to

text: the

text: cloud

text: based

text: on

text: context

text: information

text: nodes).

text: Zhang

text: et

text: al.

text: have

text: developed

text: a

text: middleware

text: on

text: top

text: such

text: as

text: battery

text: level

text: and

text: availability.

text: The

text: proposed

text: platform

text: of

text: TinyOS

text: (tinyos.net)

text: for

text: TelosB

text: sensors.

text: The

text: data

text: fusion

text: collects

text: only

text: the

text: data

text: that

text: are

text: relevant

text: to

text: the

text: data

text: consumers,

text: components

text: are

text: designed

text: as

text: agents

text: which

text: they

text: migrate

text: form

text: thereby

text: reducing

text: the

text: data

text: storage

text: requirements

text: and

text: processing

text: one

text: node

text: to

text: another.

text: Such

text: migration

text: is

text: an

text: efﬁcient

text: technique

text: requirements.

text: We

text: discussed

text: three

text: different

text: real-world

text: use

text: case

text: in

text: term

text: of

text: resource

text: utilization.

text: Data

text: fusion

text: consumes

text: the

text: scenarios

text: where

text: the

text: proposed

text: platform

text: can

text: offer

text: signiﬁcant

text: resources

text: only

text: when

text: a

text: given

text: node

text: required

text: to

text: process

text: data.

text: advantages.

text: It

text: was

text: shown

text: to

text: facilitate

text: the

text: efﬁcient

text: and

text: ef-

text: Otherwise

text: the

text: agents

text: moves

text: on

text: to

text: another

text: node

text: on

text: demand.

text: fective

text: mobile

text: crowd

text: sensing

text: functionality

text: at

text: a

text: minimum

text: We

text: simulate

text: such

text: behaviour

text: in

text: C-MOSDEN

text: where

text: plugins

text: cost.

text: Through

text: a

text: series

text: of

text: experimentations

text: and

text: evaluations,

text: are

text: installed

text: when

text: needed

text: and

text: uninstall

text: when

text: not

text: needed.

text: we

text: showed

text: the

text: importance

text: of

text: selective

text: sensing

text: through

text: the

text: Another

text: agent-based

text: sensing

text: platform

text: has

text: been

text: proposed

text: by

text: reduction

text: of

text: computational

text: requirements.

text: In

text: general,

text: through

text: Sun

text: and

text: Nakata

text: Budde

text: et

text: al.

text: have

text: proposed

text: a

text: selective

text: sensing,

text: we

text: were

text: able

text: to

text: successfully

text: reduce

text: the

text: framework

text: that

text: allows

text: to

text: discover

text: smart

text: objects

text: in

text: the

text: Internet

text: energy

text: consumption,

text: network

text: communication

text: requirements

text: of

text: Things.

text: The

text: framework

text: allows

text: smart

text: objects

text: and

text: services

text: and

text: storage

text: requirements.

text: Although

text: the

text: context-aware

text: func-

text: to

text: be

text: registered

text: by

text: providing

text: metadata

text: where

text: it

text: later

text: allows

text: tionalities

text: have

text: generated

text: a

text: small

text: amount

text: of

text: overhead,

text: it

text: was

text: searching

text: and

text: selection.

text: Mori

text: et

text: al.

text: has

text: proposed

text: a

text: revealed

text: that

text: the

text: cost

text: savings

text: and

text: beneﬁts

text: far

text: outweighed

text: cloud-based

text: mobile

text: phone

text: sensing

text: middleware

text: that

text: can

text: the

text: increased

text: complexity.

text: In

text: future

text: works,

text: we

text: are

text: planning

text: collectively

text: sense

text: the

text: environment

text: as

text: group

text: of

text: participants.

text: to

text: enrich

text: C-MOSDEN

text: with

text: privacy

text: preserving

text: data

text: analytics

text: however,

text: if

text: there

text: are

text: more

text: participants

text: present

text: in

text: a

text: given

text: capabilities.

text: region

text: that

text: expected,

text: the

text: task

text: will

text: be

text: selectively

text: assigned

text: REFERENCES

text: to

text: the

text: most

text: appropriate

text: participants

text: by

text: considering

text: context

text: C.

text: Perera,

text: C.

text: Liu,

text: S.

text: Jayawardena,

text: and

text: M.

text: Chen,

text: “A

text: survey

text: on

text: internet

text: information

text: such

text: as

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text: exact

text: location,

text: and

text: so

text: of

text: things

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text: IEEE,

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text: pp.

text: on.

text: Their

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text: Y.

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text: source

text: platform

text: that

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text: par-

text: tions

text: Magazine,

text: IEEE,

text: vol.

text: no.

text: pp.

text: April

text: ticipatory

text: sensing

text: using

text: mobile

text: phones.

text: It

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text: on

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text: Yu,

text: Y.

text: Zhang,

text: L.

text: Song,

text: and

text: W.

text: Yao,

text: “Joint

text: optimization

text: of

text: power,

text: collecting

text: data

text: instead

text: of

text: processing.

text: The

text: platform

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text: packet

text: forwarding

text: and

text: reliability

text: in

text: mimo

text: wireless

text: sensor

text: networks,”

text: external

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text: mobile

text: phones,

text: and

text: a

text: cloud

text: service

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text: Networks

text: and

text: Applications,

text: vol.

text: no.

text: pp.

text: [Online].

text: Available:

text: data

text: storage.

text: Sharing

text: data

text: among

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text: mobile

text: phones

text: is

text: not

text: A.

text: Zaslavsky,

text: C.

text: Perera,

text: and

text: D.

text: Georgakopoulos,

text: “Sensing

text: as

text: a

text: service

text: supported.

text: In

text: contract,

text: C-MOSDEN

text: is

text: capable

text: of

text: peer

text: to

text: and

text: big

text: data,”

text: in

text: International

text: Conference

text: on

text: Advances

text: in

text: Cloud

text: peer

text: communication

text: as

text: well

text: as

text: cloud

text: based

text: communication.

text: Computing

text: Bangalore,

text: India,

text: July

text: pp.

text: H.

text: Sundmaeker,

text: P.

text: Guillemin,

text: P.

text: Friess,

text: and

text: S.

text: Woelfﬂe,

text: “Vi-

text: USense

text: is

text: client-side

text: middleware

text: that

text: opportunistically

text: sion

text: and

text: challenges

text: for

text: realising

text: the

text: internet

text: of

text: things,”

text: European

text: and

text: passively

text: (i.e.

text: without

text: human

text: intervention)

text: performance

text: Commission

text: Information

text: Society

text: and

text: Media,

text: Tech.

text: Rep.,

text: March

text: sensing

text: tasks

text: in

text: crowd

text: sensing

text: fashion.

text: It

text: uses

text: XML

text: deﬁni-

text: Clusterbook

text: March

text: [Accessed

text: on:

text: tions

text: to

text: explain

text: a

text: ‘moment’

text: where

text: the

text: middleware

text: needs

text: to

text: F.

text: Xu,

text: F.

text: Liu,

text: H.

text: Jin,

text: and

text: A.

text: Vasilakos,

text: “Managing

text: performance

text: overhead

text: start

text: sensing

text: and

text: stop

text: sensing.

text: The

text: ‘moment’

text: are

text: composed

text: of

text: virtual

text: machines

text: in

text: cloud

text: computing:

text: A

text: survey,

text: state

text: of

text: the

text: art,

text: and

text: with

text: a

text: bunch

text: of

text: condition

text: such

text: as

text: location,

text: time,

text: and

text: so

text: on.

text: future

text: directions,”

text: Proceedings

text: of

text: the

text: IEEE,

text: vol.

text: no.

text: pp.

text: Jan

text: Similarly,

text: SENSE-SATION

text: also

text: gathers

text: and

text: stores

text: sensor

text: C.

text: Perera,

text: A.

text: Zaslavsky,

text: P.

text: Christen,

text: and

text: D.

text: Georgakopoulos,

text: “Sensing

text: information

text: using

text: mobile

text: phones

text: and

text: make

text: them

text: directly

text: as

text: a

text: service

text: model

text: for

text: smart

text: cities

text: supported

text: by

text: internet

text: of

text: things,”

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##


text: References (1) Osman Balci and Coskun Kocabas. Rapid thermal annealing of graphene-metal contact. Applied Physics Letters, 101(24):243105, 2012. (2) Wei Li, Yiran Liang, Dangmin Yu, Lianmao Peng, Kurt P Pernstich, Tian Shen, AR Hight Walker, Guangjun Cheng, Christina A Hacker, Curt A Richter, et al. Ultraviolet/ozone treat- ment to reduce metal-graphene contact resistance. Applied Physics Letters, 102(18):183110, 2013. (3) Seul Ki Hong, Sang Chul Jeon, Wan Sik Hwang, and Byung Jin Cho. Resistance analysis and device design guideline for graphene rf transistors. 2D Materials, 2(3):034011, 2015. (4) A Venugopal, L Colombo, and EM Vogel. Contact resistance in few and multilayer graphene devices. Applied Physics Letters, 96(1):013512, 2010. (5) Seung Min Song, Taek Yong Kim, One Jae Sul, Woo Cheol Shin, and Byung Jin Cho. Im- provement of graphene metal contact resistance by introducing edge contacts at graphene under metal. Applied Physics Letters, 104(18):183506, 2014. doi: http://dx.doi.org/10.1063/ 1.4875709. URL http://scitation.aip.org/content/aip/journal/apl/ 104/18/10.1063/1.4875709. (6) K Nagashio, T Nishimura, K Kita, and A Toriumi. Metal/graphene contact as a performance killer of ultra-high mobility graphene analysis of intrinsic mobility and contact resistance. In Electron Devices Meeting (IEDM), 2009 IEEE International, pages 1–4. IEEE, 2009. (7) Teng Ma, Wencai Ren, Zhibo Liu, Le Huang, Lai-Peng Ma, Xiuliang Ma, Zhiyong Zhang, Lan-Mao Peng, and Hui-Ming Cheng. Repeated Growth-Etching-Regrowth for Large-Area Defect-Free Single-Crystal Graphene by Chemical Vapor Deposition. ACS NANO, 8(12): 12806–12813, DEC 2014. ISSN 1936-0851. doi: {10.1021/nn506041t}. 12

text: References

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text: Balci

text: and

text: Coskun

text: Kocabas.

text: Rapid

text: thermal

text: annealing

text: of

text: graphene-metal

text: contact.

text: Applied

text: Physics

text: Letters,

text: Wei

text: Li,

text: Yiran

text: Liang,

text: Dangmin

text: Yu,

text: Lianmao

text: Peng,

text: Kurt

text: P

text: Pernstich,

text: Tian

text: Shen,

text: AR

text: Hight

text: Walker,

text: Guangjun

text: Cheng,

text: Christina

text: A

text: Hacker,

text: Curt

text: A

text: Richter,

text: et

text: al.

text: Ultraviolet/ozone

text: treat-

text: ment

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text: metal-graphene

text: contact

text: resistance.

text: Applied

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text: transistors.

text: Materials,

text: A

text: Venugopal,

text: L

text: Colombo,

text: and

text: EM

text: Vogel.

text: Contact

text: resistance

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text: and

text: multilayer

text: graphene

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text: Applied

text: Physics

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text: Min

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text: Taek

text: Yong

text: Kim,

text: One

text: Jae

text: Sul,

text: Woo

text: Cheol

text: Shin,

text: and

text: Byung

text: Jin

text: Cho.

text: Im-

text: provement

text: of

text: graphene

text: metal

text: contact

text: resistance

text: by

text: introducing

text: edge

text: contacts

text: at

text: graphene

text: under

text: metal.

text: Applied

text: Physics

text: Letters,

text: doi:

text: URL

text: K

text: Nagashio,

text: T

text: Nishimura,

text: K

text: Kita,

text: and

text: A

text: Toriumi.

text: Metal/graphene

text: contact

text: as

text: a

text: performance

text: killer

text: of

text: ultra-high

text: mobility

text: graphene

text: analysis

text: of

text: intrinsic

text: mobility

text: and

text: contact

text: resistance.

text: In

text: Electron

text: Devices

text: Meeting

text: (IEDM),

text: IEEE

text: International,

text: pages

text: IEEE,

text: Teng

text: Ma,

text: Wencai

text: Ren,

text: Zhibo

text: Liu,

text: Le

text: Huang,

text: Lai-Peng

text: Ma,

text: Xiuliang

text: Ma,

text: Zhiyong

text: Zhang,

text: Lan-Mao

text: Peng,

text: and

text: Hui-Ming

text: Cheng.

text: Repeated

text: Growth-Etching-Regrowth

text: for

text: Large-Area

text: Defect-Free

text: Single-Crystal

text: Graphene

text: by

text: Chemical

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text: Deposition.

text: ACS

text: NANO,

text: DEC

text: ISSN

text: doi:


text: − different samples used (S and S ) are shown in Fig. 5. The ’D’ peak at 1350 cm 1(’D’ peak) 1 2 qualitatively indicates the number of defects in the graphene sample.24 A simple comparison of the peak intensities indicate that S has a higher defect density. From the expression developed 2 by ?, it is seen that S has an order of magnitude higher defect density than S . The three most 2 1 commonly used metals, namely Pt, Au, and Pd with work functions 5.65 eV, 5.40 eV, and 5.22 eV respectively were chosen to fabricate devices using the two kinds of graphene. Figures 6 shows the contact resistivity extracted from TLM measurements. It can be seen that irrespective of the metal used, contact resistivity is lower when the graphene ﬁlm is defective by a factor of 2. In con- trast, the sheet resistance increases with defect density, making the inverse dependence of contact resistivity on defect density, an intriguing observation. From the I -V of the individual devices, D G the ﬁeld effect mobility was extracted and the residual carrier concentration was calculated us- ing equation Eq. (1) (details on the extaction and ﬁt are presented in the supplementary material). Comparing the values obtained using the constant mobility ﬁt, it was seen that the sample S with 2 · − higher defects has a mobility of 1200 cm2/V s and a intrinsic carrier concentration of 1E13 cm 2, · − while sample S had a mobility of 16310 cm2/V s and a carrier concentration of 2.5E12 cm 2. 1 D G 2D 400 1350 1580 2700 S2 S1 350 300 250 200 150 Defective 100 50 0 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 Wave number (1/cm) Figure 5: Raman spectrum obtained on samples S and S . The ’D’ peak intensity, which can be 1 2 used to quantitatively determine the defect density indicates an order of magnitude higher defect density in S than in S . 2 1 8 )stinu .bra( stnuoC ##LTFigure## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine##

text: different

text: samples

text: used

text: (S

text: and

text: S

text: are

text: shown

text: in

text: Fig.

text: The

text: ’D’

text: peak

text: at

text: cm

text: peak)

text: qualitatively

text: indicates

text: the

text: number

text: of

text: defects

text: in

text: the

text: graphene

text: A

text: simple

text: comparison

text: of

text: the

text: peak

text: intensities

text: indicate

text: that

text: S

text: has

text: a

text: higher

text: defect

text: density.

text: From

text: the

text: expression

text: developed

text: by

text: it

text: is

text: seen

text: that

text: S

text: has

text: an

text: order

text: of

text: magnitude

text: higher

text: defect

text: density

text: than

text: S

text: The

text: three

text: most

text: commonly

text: used

text: metals,

text: namely

text: Pt,

text: Au,

text: and

text: Pd

text: with

text: work

text: functions

text: eV,

text: eV,

text: and

text: eV

text: respectively

text: were

text: chosen

text: to

text: fabricate

text: devices

text: using

text: the

text: two

text: kinds

text: of

text: graphene.

text: Figures

text: shows

text: the

text: contact

text: resistivity

text: extracted

text: from

text: TLM

text: measurements.

text: It

text: can

text: be

text: seen

text: that

text: irrespective

text: of

text: the

text: metal

text: used,

text: contact

text: resistivity

text: is

text: lower

text: when

text: the

text: graphene

text: ﬁlm

text: is

text: defective

text: by

text: a

text: factor

text: of

text: In

text: con-

text: trast,

text: the

text: sheet

text: resistance

text: increases

text: with

text: defect

text: density,

text: making

text: the

text: inverse

text: dependence

text: of

text: contact

text: resistivity

text: on

text: defect

text: density,

text: an

text: intriguing

text: observation.

text: From

text: the

text: I

text: -V

text: of

text: the

text: individual

text: devices,

text: D

text: G

text: the

text: ﬁeld

text: effect

text: mobility

text: was

text: extracted

text: and

text: the

text: residual

text: carrier

text: concentration

text: was

text: calculated

text: us-

text: ing

text: equation

text: Eq.

text: (details

text: on

text: the

text: extaction

text: and

text: ﬁt

text: are

text: presented

text: in

text: the

text: supplementary

text: material).

text: Comparing

text: the

text: values

text: obtained

text: using

text: the

text: constant

text: mobility

text: ﬁt,

text: it

text: was

text: seen

text: that

text: the

text: sample

text: S

text: with

text: higher

text: defects

text: has

text: a

text: mobility

text: of

text: s

text: and

text: a

text: intrinsic

text: carrier

text: concentration

text: of

text: cm

text: while

text: sample

text: S

text: had

text: a

text: mobility

text: of

text: s

text: and

text: a

text: carrier

text: concentration

text: of

text: cm

text: D

text: G

text: Defective

text: Wave

text: number

text: Figure

text: Raman

text: spectrum

text: obtained

text: on

text: samples

text: S

text: and

text: S

text: The

text: ’D’

text: peak

text: intensity,

text: which

text: can

text: be

text: used

text: to

text: quantitatively

text: determine

text: the

text: defect

text: density

text: indicates

text: an

text: order

text: of

text: magnitude

text: higher

text: defect

text: density

text: in

text: S

text: than

text: in

text: S

text: )stinu

text: .bra(

text: stnuoC

text: ##LTFigure##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

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text: ##LTLine##

text: ##LTLine##

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text: X104 Pt 4 3 2 Defective 1 X104 Au 1.2 0.9 0.6 Defective 0.3 X103 Pd 4 3 2 Defective 1 -1.5 Car-1rier co-0n.5centra0tion n0.5 x10121 cm-21.5 0 Figure 6: Effect of metal work function and graphene defect density on contact resistivity. The − contact resistivity obtained at carrier concentration varying from -1.5 - 1.5 x 1012 cm 2 are plotted for three metals namely Pt, Au and Pd in decreasing order of their metal work functions. The values with the standard deviation are displayed as bands in each plot. For each metal, the con- tact resistivity of graphene with two different defect densities are plotted. From the ﬁgure it is clearly seen that under the same metal, the graphene with higher defect density has a lower resis- tivity. Moreover, under this architecture, the resistivity shows a linear relation with the metal work function. The contact conductivity (G ) of graphene has been modeled by Xia et al.19 as follows, c G = (4e2/h)T M (2a) c total M = (∆E /πh¯V )W (2b) f f M = M + M (2c) total V G CNP M = (E /πh¯V )W (2d) CNP ex f √ E = h¯v πn (2e) ex f 0 where M is the quantum number of modes on graphene, T is the transmission probability from metal to graphene in the bulk, e is the electronic charge, E is the Fermi level at a given gate F voltage and E is the Fermi level of intrinsic graphene, V is the Fermi velocity, h¯ is the reduced ex f planks constant, and W is the channel width. The quantum number of modes in graphene M is related to ∆E as described in Eq. (2c), where ∆E is the energy difference between the actual f f 9 mµ-Ω ytivitsiseR tcatnoC ##LTFigure## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine##

font: default

text: Pt

text: Defective

text: Au

text: Defective

text: Pd

text: Defective

text: Figure

text: Effect

label: caption

text: of

text: metal

text: work

text: function

text: and

text: graphene

text: defect

text: density

text: on

text: contact

text: resistivity.

text: The

text: contact

text: resistivity

text: obtained

text: at

text: carrier

text: concentration

text: varying

text: from

text: x

text: cm

text: are

text: plotted

text: for

text: three

text: metals

text: namely

text: Pt,

text: Au

text: and

text: Pd

text: in

text: decreasing

text: order

text: of

text: their

text: metal

text: work

text: functions.

text: The

text: values

text: with

text: the

text: standard

text: deviation

text: are

text: displayed

text: as

text: bands

text: in

text: each

text: plot.

text: For

text: each

text: metal,

text: the

text: con-

text: tact

text: resistivity

text: of

text: graphene

text: with

text: two

text: different

text: defect

text: densities

text: are

text: plotted.

text: From

text: the

text: ﬁgure

text: it

text: is

text: clearly

text: seen

text: that

text: under

text: the

text: same

text: metal,

text: the

text: graphene

text: with

text: higher

text: defect

text: density

text: has

text: a

text: lower

text: resis-

text: tivity.

text: Moreover,

text: under

text: this

text: architecture,

text: the

text: resistivity

text: shows

text: a

text: linear

text: relation

text: with

text: the

text: metal

text: work

text: function.

text: The

text: contact

text: conductivity

text: (G

text: of

text: graphene

text: has

text: been

text: modeled

text: by

text: Xia

text: et

text: as

text: follows,

text: c

text: G

text: M

text: c

text: total

text: M

text: (∆E

text: /πh¯V

text: )W

text: f

text: f

text: M

text: M

text: M

text: total

text: V

text: G

text: CNP

text: M

text: (E

text: /πh¯V

text: )W

text: CNP

text: ex

text: f

text: E

text: h¯v

text: πn

text: ex

text: f

text: where

text: M

text: is

text: the

text: quantum

text: number

text: of

text: modes

text: on

text: graphene,

text: T

text: is

text: the

text: transmission

text: probability

text: from

text: metal

text: to

text: graphene

text: in

text: the

text: bulk,

text: e

text: is

text: the

text: electronic

text: charge,

text: E

text: is

text: the

text: Fermi

text: level

text: at

text: a

text: given

text: gate

text: F

text: voltage

text: and

text: E

text: is

text: the

text: Fermi

text: level

text: of

text: intrinsic

text: graphene,

text: V

text: is

text: the

text: Fermi

text: velocity,

text: h¯

text: is

text: the

text: reduced

text: ex

text: f

text: planks

text: constant,

text: and

text: W

text: is

text: the

text: channel

text: width.

text: The

text: quantum

text: number

text: of

text: modes

text: in

text: graphene

text: M

text: is

text: related

text: to

text: ∆E

text: as

text: described

text: in

text: Eq.

text: where

text: ∆E

text: is

text: the

text: energy

text: difference

text: between

text: the

text: actual

text: f

text: f

text: mµ-Ω

text: ytivitsiseR

text: tcatnoC

text: ##LTFigure##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

text: ##LTLine##

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text: Fermi level in the system (E ) and charge nuetrality point energy (E ). In intrinsic graphene, F CNP the carrier concentration drops to zero at E = 0 due to vanishing density of states, and the con- F ductance drops to the minimum conductance level (σ = 2e2/h¯). However, CVD grown graphene gets unintentionally doped and is usually defective leading to higher conductance at the CNP. This increased conductance at the CNP is due to additional number of conductance modes made avail- able due to the defects in the sample. Hence the total number of modes in the graphene channel is M = M + M , where M is the number of modes at a particular E , obtained as total V G CNP V G F described before and M is the number of modes in the channel due to the presence of defects. CNP If the carrier concentration at CNP (n ) is known, the excess number of modes at CNP can be 0 calculated as mentioned in equation set Eq. (2). Using the residual carrier concentration extracted previously on both the samples and using the Eq. (2), the E on the defective graphene was higher than the other by 0.3 meV, resulting ex ∗ in M (B) = 2 M (A). The contact resistivity ratio of the two samples with Pt at the CNP CNP CNP, as seen from the Fig. 6, was only slightly higher than 2 indicating that the change in number of modes(M) under the defective graphene could be the dominant reason for the reduction in the contact resistivity in defective graphene. However, it should be noted that introducing defects to reduce contact resistivity might adversely affect the device performance as the uniform distribution of defects in graphene has a degrading effect on the charge mobilities.25 While such a method of reducing the contact resistivity would beneﬁt sensing applications, whose sensitivity improves with defect density the ﬁlm, high speed logic applications might be affected due to mobility degradation. Hence, it is important to choose the right defect density to be introduced in the material such that a right balance obtained between the channel resistance and the contact resistivity and thereby satisfying the application requirements. Since such an observation is not unique to graphene, but also many other 2D materials, these results hence offer an interesting route to further reduce contact resistivity to atomically-thin devices by selective defect engineering. Also, in the quest to ﬁnd the most suitable material for graphene contacts, several metals have been previously explored in the literature.7,10,26,27 There are considerable number of contradicting reports and there is no ﬁnal 10

text: Fermi

text: level

text: in

text: the

text: system

text: (E

text: and

text: charge

text: nuetrality

text: point

text: energy

text: (E

text: In

text: intrinsic

text: graphene,

text: F

text: CNP

text: the

text: carrier

text: concentration

text: drops

text: to

text: zero

text: at

text: E

text: due

text: to

text: vanishing

text: density

text: of

text: states,

text: and

text: the

text: con-

text: F

text: ductance

text: drops

text: to

text: the

text: minimum

text: conductance

text: level

text: (σ

text: However,

text: CVD

text: grown

text: graphene

text: gets

text: unintentionally

text: doped

text: and

text: is

text: usually

text: defective

text: leading

text: to

text: higher

text: conductance

text: at

text: the

text: CNP.

text: This

text: increased

text: conductance

text: at

text: the

text: CNP

text: is

text: due

text: to

text: additional

text: number

text: of

text: conductance

text: modes

text: made

text: avail-

text: able

text: due

text: to

text: the

text: defects

text: in

text: the

text: sample.

text: Hence

text: the

text: total

text: number

text: of

text: modes

text: in

text: the

text: graphene

text: channel

text: is

text: M

text: M

text: M

text: where

text: M

text: is

text: the

text: number

text: of

text: modes

text: at

text: a

text: particular

text: E

text: obtained

text: as

text: total

text: V

text: G

text: CNP

text: V

text: G

text: F

text: described

text: before

text: and

text: M

text: is

text: the

text: number

text: of

text: modes

text: in

text: the

text: channel

text: due

text: to

text: the

text: presence

text: of

text: defects.

text: CNP

text: If

text: the

text: carrier

text: concentration

text: at

text: CNP

text: (n

text: is

text: known,

text: the

text: excess

text: number

text: of

text: modes

text: at

text: CNP

text: can

text: be

text: calculated

text: as

text: mentioned

text: in

text: equation

text: set

text: Eq.

text: Using

text: the

text: residual

text: carrier

text: concentration

text: extracted

text: previously

text: on

text: both

text: the

text: samples

text: and

text: using

text: the

text: Eq.

text: the

text: E

text: on

text: the

text: defective

text: graphene

text: was

text: higher

text: than

text: the

text: other

text: by

text: meV,

text: resulting

text: ex

text: in

text: M

text: (B)

text: M

text: (A).

text: The

text: contact

text: resistivity

text: ratio

text: of

text: the

text: two

text: samples

text: with

text: Pt

text: at

text: the

text: CNP

text: CNP

text: CNP,

text: as

text: seen

text: from

text: the

text: Fig.

text: was

text: only

text: slightly

text: higher

text: than

text: indicating

text: that

text: the

text: change

text: in

text: number

text: of

text: modes(M)

text: under

text: the

text: defective

text: graphene

text: could

text: be

text: the

text: dominant

text: reason

text: for

text: the

text: reduction

text: in

text: the

text: contact

text: resistivity

text: in

text: defective

text: graphene.

text: However,

text: it

text: should

text: be

text: noted

text: that

text: introducing

text: defects

text: to

text: reduce

text: contact

text: resistivity

text: might

text: adversely

text: affect

text: the

text: device

text: performance

text: as

text: the

text: uniform

text: distribution

text: of

text: defects

text: in

text: graphene

text: has

text: a

text: degrading

text: effect

text: on

text: the

text: charge

text: While

text: such

text: a

text: method

text: of

text: reducing

text: the

text: contact

text: resistivity

text: would

text: beneﬁt

text: sensing

text: applications,

text: whose

text: sensitivity

text: improves

text: with

text: defect

text: density

text: the

text: ﬁlm,

text: high

text: speed

text: logic

text: applications

text: might

text: be

text: affected

text: due

text: to

text: mobility

text: degradation.

text: Hence,

text: it

text: is

text: important

text: to

text: choose

text: the

text: right

text: defect

text: density

text: to

text: be

text: introduced

text: in

text: the

text: material

text: such

text: that

text: a

text: right

text: balance

text: obtained

text: between

text: the

text: channel

text: resistance

text: and

text: the

text: contact

text: resistivity

text: and

text: thereby

text: satisfying

text: the

text: application

text: requirements.

text: Since

text: such

text: an

text: observation

text: is

text: not

text: unique

text: to

text: graphene,

text: but

text: also

text: many

text: other

text: materials,

text: these

text: results

text: hence

text: offer

text: an

text: interesting

text: route

text: to

text: further

text: reduce

text: contact

text: resistivity

text: to

text: atomically-thin

text: devices

text: by

text: selective

text: defect

text: engineering.

text: Also,

text: in

text: the

text: quest

text: to

text: ﬁnd

text: the

text: most

text: suitable

text: material

text: for

text: graphene

text: contacts,

text: several

text: metals

text: have

text: been

text: previously

text: explored

text: in

text: the

text: There

text: are

text: considerable

text: number

text: of

text: contradicting

text: reports

text: and

text: there

text: is

text: no

text: ﬁnal


text: 2 Jayant Murthy 3.0 2.0 1.0 0.0 0.0 1.0 2.0 3.0 Observed E(B - V) Figure 2. The correlation between the E(B-V) from Schlegel et al. (1998) and the modelled E(B-V) is shown as a density plot for Model 1 (red lines) and Model 2. Figure 1. Observed ﬂuxes in the FUV (top) and NUV (bottom) GALEX bands. The brightest stars are plotted as + symbols with the width of the symbol proportional to the log of the brightness out that the scattering may be more complex with a pos- at the respective wavelength. Black areas were not observed by sible reverse scattering component but the data have not GALEX. yet been good enough to support added complexity in the scattering function. Henry (1977) showed that the interstellar radiation ﬁeld nately, the FUV detector had already failed by this time so in the UV could be calculated through an integration over there are very few FUV observations at low latitudes. the stars in a standard catalog. In this work, I have used Murthy (2014b) used the GALEX data to construct the Hipparcos catalog (Perryman et al. 1997) which con- maps of the diﬀuse background in both the FUV and NUV ◦ bands at 0.1 spatial resolution with the foreground emission tains over 100,000 stars with the spectral type, B and V magnitude and distance of each star. I modelled the spec- (airglow and zodiacal light) subtracted (Fig. 1). The 1000 trum of each star using template spectra from Castelli & brightest stars are overplotted on the images as + signs with Kurucz (2004) with the translation from spectral type to the size of the symbol proportional to the log of the bright- model number as per their instructions(cid:63). I then calculated ness. Gould’s Belt is prominent in both bands as are halos the observed E(B - V) from the cataloged B and V magni- around a number of bright stars (Murthy & Henry 2011). tudes and the intrinsic (B - V) and ﬁnally the unreddened A full description of the methodology in the production of ﬂux from each star assuming the Milky Way extinction curve these maps is given in the paper and the maps are available of Draine (2003). This is the source function in my model: from the High Level Science Products (HLSP) data reposi- the number of photons from each star at the wavelength of tory(cid:63) at the Space Telescope Science Institute. interest. 3 MODELLING I have tried two dust distributions in order to explore The radiative transfer problem in galaxies has been re- their eﬀects on the scattered light. In the ﬁrst (Model 1), viewed by Steinacker et al. (2013) with the much simpler I have assumed that the gas density at the Galactic plane − problem of scattering only addressed in their Section 5.1. (n[H]) is 1 atom cm 3, independent of longitude. In the sec- The problem can be broken into three parts: the stellar dis- ond (Model 2), I scaled the dust to match the observed E(B tribution; the dust distribution; and the scattering function. - V) from Schlegel et al. (1998) in Model 2. In both cases, I Photons are emitted by the stars and are scattered by the assumed that there was a cavity of radius 80 pc around the interstellar dust to the detector. The scattering function is Sun, corresponding to the Local Bubble (Welsh et al. 2010), commonly assumed to be the Henyey-Greenstein function and that the dust fell oﬀ from the Galactic plane with a (Henyey & Greenstein 1941) which is dependent on two scale height of 125 pc (Marshall et al. 2006). I have plot- free parameters: the albedo or ≡reﬂectivity (a) and the phase ted the correlation between the observed and the modelled function asymmetry factor (g < cos(θ) >), where g = 0 im- E(B - V) for the two models in Fig. 2. My purpose in im- plies that the grains scatter isotropically and g = 1 implies plementing these diﬀerent models was to explore the factors fully forward scattering grains. Draine (2003) has pointed (cid:63) https://archive.stsci.edu/prepds/uv-bkgd/ (cid:63) http://www.stsci.edu/hst/observatory/crds/castelli kurucz atlas.html MNRAS 000, 1–12 (2015) )V - B(E ledoM pro Fit TRIAL version ##LTFigure## ##LTFigure## ##LTFigure## ##LTFigure## ##LTFigure## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine## ##LTLine##

text: Jayant

text: Murthy

text: Observed

text: E(B

text: V)

text: Figure

text: The

text: correlation

text: between

text: the

text: E(B-V)

text: from

text: Schlegel

text: et

text: al.

text: and

text: the

text: modelled

text: E(B-V)

text: is

text: shown

text: as

text: a

text: density

text: plot

text: for

text: Model

text: (red

text: lines)

text: and

text: Model

text: Figure

text: Observed

text: ﬂuxes

text: in

text: the

text: FUV

text: (top)

text: and

text: NUV

text: (bottom)

text: GALEX

text: bands.

text: The

text: brightest

text: stars

text: are

text: plotted

text: as

text: symbols

text: with

text: the

text: width

text: of

text: the

text: symbol

text: proportional

text: to

text: the

text: log

text: of

text: the

text: brightness

text: out

text: that

text: the

text: scattering

text: may

text: be

text: more

text: complex

text: with

text: a

text: pos-

text: at

text: the

text: respective

text: wavelength.

text: Black

text: areas

text: were

text: not

text: observed

text: by

text: sible

text: reverse

text: scattering

text: component

text: but

text: the

text: data

text: have

text: not

text: GALEX.

text: yet

text: been

text: good

text: enough

text: to

text: support

text: added

text: complexity

text: in

text: the

text: scattering

text: function.

text: Henry

text: showed

text: that

text: the

text: interstellar

text: radiation

text: ﬁeld

text: nately,

text: the

text: FUV

text: detector

text: had

text: already

text: failed

text: by

text: this

text: time

text: so

text: in

text: the

text: UV

text: could

text: be

text: calculated

text: through

text: an

text: integration

text: over

text: there

text: are

text: very

text: few

text: FUV

text: observations

text: at

text: low

text: latitudes.

text: the

text: stars

text: in

text: a

text: standard

text: catalog.

text: In

text: this

text: work,

text: I

text: have

text: used

text: Murthy

text: used

text: the

text: GALEX

text: data

text: to

text: construct

text: the

text: Hipparcos

text: catalog

text: (Perryman

text: et

text: al.

text: which

text: con-

text: maps

text: of

text: the

text: diﬀuse

text: background

text: in

text: both

text: the

text: FUV

text: and

text: NUV

text: bands

text: at

text: spatial

text: resolution

text: with

text: the

text: foreground

text: emission

text: tains

text: over

text: stars

text: with

text: the

text: spectral

text: type,

text: B

text: and

text: V

text: magnitude

text: and

text: distance

text: of

text: each

text: star.

text: I

text: modelled

text: the

text: spec-

text: (airglow

text: and

text: zodiacal

text: light)

text: subtracted

text: (Fig.

text: The

text: trum

text: of

text: each

text: star

text: using

text: template

text: spectra

text: from

text: Castelli

text: brightest

text: stars

text: are

text: overplotted

text: on

text: the

text: images

text: as

text: signs

text: with

text: Kurucz

text: with

text: the

text: translation

text: from

text: spectral

text: type

text: to

text: the

text: size

text: of

text: the

text: symbol

text: proportional

text: to

text: the

text: log

text: of

text: the

text: bright-

text: model

text: number

text: as

text: per

text: their

text: I

text: then

text: calculated

text: ness.

text: Gould’s

text: Belt

text: is

text: prominent

text: in

text: both

text: bands

text: as

text: are

text: halos

text: the

text: observed

text: E(B

text: V)

text: from

text: the

text: cataloged

text: B

text: and

text: V

text: magni-

text: around

text: a

text: number

text: of

text: bright

text: stars

text: (Murthy

text: Henry

text: tudes

text: and

text: the

text: intrinsic

text: (B

text: V)

text: and

text: ﬁnally

text: the

text: unreddened

text: A

text: full

text: description

text: of

text: the

text: methodology

text: in

text: the

text: production

text: of

text: ﬂux

text: from

text: each

text: star

text: assuming

text: the

text: Milky

text: Way

text: extinction

text: curve

text: these

text: maps

text: is

text: given

text: in

text: the

text: paper

text: and

text: the

text: maps

text: are

text: available

text: of

text: Draine

text: This

text: is

text: the

text: source

text: function

text: in

text: my

text: model:

text: from

text: the

text: High

text: Level

text: Science

text: Products

text: (HLSP)

text: data

text: reposi-

text: the

text: number

text: of

text: photons

text: from

text: each

text: star

text: at

text: the

text: wavelength

text: of

text: at

text: the

text: Space

text: Telescope

text: Science

text: Institute.

text: interest.

text: MODELLING

text: I

text: have

text: tried

text: two

text: dust

text: distributions

text: in

text: order

text: to

text: explore

text: The

text: radiative

text: transfer

text: problem

text: in

text: galaxies

text: has

text: been

text: re-

text: their

text: eﬀects

text: on

text: the

text: scattered

text: light.

text: In

text: the

text: ﬁrst

text: (Model

text: viewed

text: by

text: Steinacker

text: et

text: al.

text: with

text: the

text: much

text: simpler

text: I

text: have

text: assumed

text: that

text: the

text: gas

text: density

text: at

text: the

text: Galactic

text: plane

text: problem

text: of

text: scattering

text: only

text: addressed

text: in

text: their

text: Section

text: (n[H])

text: is

text: atom

text: cm

text: independent

text: of

text: longitude.

text: In

text: the

text: sec-

text: The

text: problem

text: can

text: be

text: broken

text: into

text: three

text: parts:

text: the

text: stellar

text: dis-

text: ond

text: (Model

text: I

text: scaled

text: the

text: dust

text: to

text: match

text: the

text: observed

text: E(B

text: tribution;

text: the

text: dust

text: distribution;

text: and

text: the

text: scattering

text: function.

text: V)

text: from

text: Schlegel

text: et

text: al.

text: in

text: Model

text: In

text: both

text: cases,

text: I

text: Photons

text: are

text: emitted

text: by

text: the

text: stars

text: and

text: are

text: scattered

text: by

text: the

text: assumed

text: that

text: there

text: was

text: a

text: cavity

text: of

text: radius

text: pc

text: around

text: the

text: interstellar

text: dust

text: to

text: the

text: detector.

text: The

text: scattering

text: function

text: is

text: Sun,

text: corresponding

text: to

text: the

text: Local

text: Bubble

text: (Welsh

text: et

text: al.

text: commonly

text: assumed

text: to

text: be

text: the

text: Henyey-Greenstein

text: function

text: and

text: that

text: the

text: dust

text: fell

text: oﬀ

text: from

text: the

text: Galactic

text: plane

text: with

text: a

text: (Henyey

text: Greenstein

text: which

text: is

text: dependent

text: on

text: two

text: scale

text: height

text: of

text: pc

text: (Marshall

text: et

text: al.

text: I

text: have

text: plot-

text: free

text: parameters:

text: the

text: albedo

text: or

text: ≡reﬂectivity

text: (a)

text: and

text: the

text: phase

text: ted

text: the

text: correlation

text: between

text: the

text: observed

text: and

text: the

text: modelled

text: function

text: asymmetry

text: factor

text: (g

text: cos(θ)

text: where

text: g

text: im-

text: E(B

text: V)

text: for

text: the

text: two

text: models

text: in

text: Fig.

text: My

text: purpose

text: in

text: im-

text: plies

text: that

text: the

text: grains

text: scatter

text: isotropically

text: and

text: g

text: implies

text: plementing

text: these

text: diﬀerent

text: models

text: was

text: to

text: explore

text: the

text: factors

text: fully

text: forward

text: scattering

text: grains.

text: Draine

text: has

text: pointed

text: kurucz

text: atlas.html

text: MNRAS

text: )V

text: B(E

text: ledoM

text: pro

text: Fit

text: TRIAL

text: version

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