Paper Info
Title
Guideme: Routes Coordination Of Participating Agents In Mobile Crowd Sensing Platforms
Abstract
With the recent trend in Mobile Crowd Sensing (MCS), i.e., using the power of crowds to assist in completing spatio-temporal sensory tasks, the pool of resources suitable for sensor systems has expanded to include already roaming devices. In this work, we present a model of MCS, in which agents share their journey information and allow the platform to guide them through their journey, completing spatio-temporal tasks on their way, in return for monetary rewards.In this paper, we formulate the task allocation problem as a routes coordination problem for participating agents. We define an optimal routing algorithm for a single agent, with an objective to maximize the rewards collected from performing tasks, which is used to define a 1/2-approximation algorithm to coordinate the routes of multiple agents. The algorithm is accompanied with an incentive compatible, rational, and cash-positive payment mechanism, which guarantees that an agent's truthful participation is an ex-post Nash equilibrium strategy, in an optimal setting. Finally, we analyze the defined mechanisms theoretically, and evaluate their performance experimentally using real mobility traces from urban environments.
Year
DOI
Venue
2017
10.1109/BigData.2017.8258420
2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)
Keywords
DocType
ISSN
crowdsensing, routing, routes coordination, task allocation, incentives
Conference
2639-1589
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Christine Bassem152.84
Azer Bestavros23791764.82