Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Y. Yen, Runhe Huang, and Xingshe Zhou. 2015. Mobile Crowd Sensing and Computing: The Review of an Emerging Human-Powered Sensing Paradigm. ACM Computing Surveys, 48: 7.

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[2]

Makhlouf Hadji and Djamal Zeghlache. 2012. Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds. In Proceedings of the 2012 IEEE Fifth International Conference on Cloud Computing, 876--882.

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Index Terms

Poster: Towards a Multitask Worker Recruitment Framework for Mobile Crowdsensing
1. Computing methodologies
  1. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Optimization algorithms
2. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work
  2. Ubiquitous and mobile computing

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Published In

MobiSys '16 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion

June 2016

172 pages

ISBN:9781450344166

DOI:10.1145/2938559

General Chairs:
Rajesh Balan
Singapore Management University
,
Archan Misra
Singapore Management University
,
Program Chairs:
Landon Cox
Duke University
,
Yutaka Arakawa
NAIST
,
Xia Zhou
Dartmouth College
,
Robert LiKamWa
Rice University

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGOPS: ACM Special Interest Group on Operating Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2016

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MobiSys'16

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SIGMOBILE

MobiSys'16: The 14th Annual International Conference on Mobile Systems, Applications, and Services

June 25 - 30, 2016

Singapore, Singapore

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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Index Terms

Recommendations

TaskMe: multi-task allocation in mobile crowd sensing

Multi-task Allocation Under Multiple Constraints in Mobile Crowdsensing

Multi-task Allocation Based on Edge Interaction Assistance in Mobile Crowdsensing