Title
REPC: Reliable and efficient participatory computing for mobile devices
Abstract
Smartphones and mobile devices have greatly penetrated the daily lives of many people. While participatory/pervasive sensing has gained wide adoptions by leveraging various onboard sensors on mobile devices, another powerful resource, the computational power on these mobile devices has been less frequently harnessed by researchers and practitioners. To fill this gap, we propose in this work the modeling, analysis, and implementation of participatory computing. Specifically, we propose REPC, a generic randomized task assignment framework for the participatory computing paradigm, which guarantees the overall system performance with close to minimal workload at individual participating devices. To achieve these design objectives, we model the intrinsic relationship between the workload of individual devices and the probability they complete their assigned tasks. Based on our modeling results, we analyze the maximal system capacity for any given participatory computing system and derive the minimal workload for individual participating devices to achieve the overall system performance requirement. We have fully implemented our design on the Android platform and demonstrated its performance through a representative participatory computing application. Extensive experiments and simulation results demonstrate that our design is able to achieve more than 90% task completion ratios with only 10% system overhead in practice.
Year
DOI
Venue
2014
10.1109/SAHCN.2014.6990361
SECON
Keywords
Field
DocType
mobile devices,smartphones,reliable and efficient participatory computing,individual participating devices,daily lives,repc,android platform,smart phones,generic randomized task assignment framework,onboard sensors,task completion ratios,mobile computing,android (operating system)
Computer science,Mobile device,Citizen journalism,Distributed computing
Conference
ISSN
Citations 
PageRank 
2473-0440
7
0.44
References 
Authors
13
8
Name
Order
Citations
PageRank
Zheng Dong1519.62
Linghe Kong277072.44
Peng Cheng3148185.79
Liang He418211.82
Yu Gu 0001533322.96
Lu Fang634355.27
Ting Zhu740730.63
Cong Liu878056.17