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Proceedings ArticleDOI: 10.1145/3009912.3009916

Efficient Processing of Mobile Crowdsourcing Queries with Multiple Sub-tasks for Facilitating Smart Cities

12 Dec 2016-pp 8
Abstract: The proliferation and ever-increasing popularity of mobile devices have dramatically increased the potential for mobile crowdsourcing across a wide gamut of applications that are relevant to smart cities. While existing works have mostly focused on mobile crowdsourcing for queries involving a single given major task, the issue of addressing complex queries with multiple related large sub-tasks (with spatio-temporal dependencies) has received little attention. In this regard, the key contributions of the paper are three-fold. First, we present a scheme, designated as BMS (Broker-based processing of Multiple Sub-tasks), in which a broker coordinates the processing of multiple related large subtasks in a given query among a set of mobile peers. Second, we propose the DMS (Distributed processing of Multiple Sub-tasks) scheme in which the processing of multiple sub-tasks in a query occurs in a distributed manner without the existence of any brokers. Third, the results of our performance evaluation demonstrate the effectiveness of both of the proposed schemes in terms of relatively low query response times, high query success rates and reasonable communication costs.

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Topics: Crowdsourcing (57%), Mobile device (53%)
References
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Proceedings ArticleDOI: 10.1145/288235.288256
J. Broch1, David A. Maltz1, David B. Johnson1, Yih-Chun Hu1  +1 moreInstitutions (1)
25 Oct 1998-
Abstract: An ad hoc networkis a collwtion of wirelessmobilenodes dynamically forminga temporarynetworkwithouttheuseof anyexistingnetworkirrfrastructureor centralizedadministration.Dueto the limitedtransmissionrange of ~vlrelessnenvorkinterfaces,multiplenetwork“hops”maybe neededfor onenodeto exchangedata ivithanotheracrox thenetwork.Inrecentyears, a ttiery of nelvroutingprotocols~geted specificallyat this environment havebeen developed.but little pcrfomrartwinformationon mch protocol and no ralistic performancecomparisonbehvwrrthem ISavailable. ~Is paper presentsthe results of a derailedpacket-levelsimulationcomparing fourmulti-hopwirelessad hoc networkroutingprotocolsthatcovera range of designchoices: DSDV,TORA, DSR and AODV. \Vehave extended the /~r-2networksimulatorto accuratelymodelthe MACandphysical-layer behaviorof the IEEE 802.1I wirelessLANstandard,includinga realistic wtrelesstransmissionchannelmodel, and present the resultsof simulations of net(vorksof 50 mobilenodes.

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5,118 Citations


Proceedings ArticleDOI: 10.1145/2348543.2348567
Dejun Yang1, Guoliang Xue1, Xi Fang1, Jian Tang2Institutions (2)
22 Aug 2012-
Abstract: Mobile phone sensing is a new paradigm which takes advantage of the pervasive smartphones to collect and analyze data beyond the scale of what was previously possible. In a mobile phone sensing system, the platform recruits smartphone users to provide sensing service. Existing mobile phone sensing applications and systems lack good incentive mechanisms that can attract more user participation. To address this issue, we design incentive mechanisms for mobile phone sensing. We consider two system models: the platform-centric model where the platform provides a reward shared by participating users, and the user-centric model where users have more control over the payment they will receive. For the platform-centric model, we design an incentive mechanism using a Stackelberg game, where the platform is the leader while the users are the followers. We show how to compute the unique Stackelberg Equilibrium, at which the utility of the platform is maximized, and none of the users can improve its utility by unilaterally deviating from its current strategy. For the user-centric model, we design an auction-based incentive mechanism, which is computationally efficient, individually rational, profitable, and truthful. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our incentive mechanisms.

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Topics: Mobile phone (58%), Stackelberg competition (52%), Incentive (51%)

926 Citations


Proceedings ArticleDOI: 10.1109/INFCOM.2012.6195541
Lingjie Duan1, Takeshi Kubo1, Kohei Sugiyama1, Jianwei Huang1  +2 moreInstitutions (2)
25 Mar 2012-
Abstract: This paper analyzes and compares different incentive mechanisms for a client to motivate the collaboration of smartphone users on both data acquisition and distributed computing applications.

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Topics: Mobile computing (57%), Data acquisition (52%)

249 Citations


Open accessJournal ArticleDOI: 10.1109/TMC.2006.165
Takahiro Hara1, Sanjay Kumar MadriaInstitutions (1)
Abstract: In ad hoc networks, due to frequent network partition, data accessibility is lower than that in conventional fixed networks. In this paper, we solve this problem by replicating data items on mobile hosts. First, we propose three replica allocation methods assuming that each data item is not updated. In these three methods, we take into account the access frequency from mobile hosts to each data item and the status of the network connection. Then, we extend the proposed methods by considering aperiodic updates and integrating user profiles consisting of mobile users' schedules, access behavior, and read/write patterns. We also show the results of simulation experiments regarding the performance evaluation of our proposed methods

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Topics: Mobile ad hoc network (64%), Wireless ad hoc network (61%), Network partition (54%) ...read more

202 Citations


Journal ArticleDOI: 10.1145/2729713
Hien To1, Cyrus Shahabi1, Leyla Kazemi2Institutions (2)
Abstract: With the popularity of mobile devices, spatial crowdsourcing is rising as a new framework that enables human workers to solve tasks in the physical world. With spatial crowdsourcing, the goal is to crowdsource a set of spatiotemporal tasks (i.e., tasks related to time and location) to a set of workers, which requires the workers to physically travel to those locations in order to perform the tasks. In this article, we focus on one class of spatial crowdsourcing, in which the workers send their locations to the server and thereafter the server assigns to every worker tasks in proximity to the worker’s location with the aim of maximizing the overall number of assigned tasks. We formally define this maximum task assignment (MTA) problem in spatial crowdsourcing, and identify its challenges. We propose alternative solutions to address these challenges by exploiting the spatial properties of the problem space, including the spatial distribution and the travel cost of the workers. MTA is based on the assumptions that all tasks are of the same type and all workers are equally qualified in performing the tasks. Meanwhile, different types of tasks may require workers with various skill sets or expertise. Subsequently, we extend MTA by taking the expertise of the workers into consideration. We refer to this problem as the maximum score assignment (MSA) problem and show its practicality and generality. Extensive experiments with various synthetic and two real-world datasets show the applicability of our proposed framework.

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Topics: Crowdsourcing (60%), Task (computing) (52%)

134 Citations