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TOWARD OPTIMAL ALLOCATION OF LOCATION DEPENDENT TASKS IN CROWDSENSING Jingtao Yao Lab of Cyberspace Computing Shanghai Jiao Tong University
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WHY I CHOOSE THIS PAPER It is a paper for crowdsensing. It is a paper published by InfoCom 2014. It is a paper that studies the task allocation problem in crowdsensing.
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ABSTRACT Introduction Problem Formulation Prove Hardness Local Ratio and LRBA Theoretical Analysis Pricing Sensing Task Numerical Result
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INTRODUCTION Small-sized portable mobile devices are becoming extremely prevailing nowadays, that accelerates the emergence of crowdsensing applications. Existing works: Crowdsensing for specific sensing application Unified platform Incentive-based mechanism This paper: Focus on location dependent task allocation
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INTRODUCTION This paper’s contributions are three folds. Study the problem of allocating location dependent tasks and show that the formulated problem is NP-hard. Design an efficient approximation algorithm, namely local ratio based algorithm(LRBA) to solve the proposed allocation problem and show that LRBA is a 5−approximate algorithm. Design a pricing mechanism based on bargaining theory.
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PROBLEM FORMULATION Users u i, Task t j, Position P tj, Task set T i, Shortest Path P(T i ) Total time D(P(T i )), Time budget B i, times of Tasks l j Reward R ij, Decision variable x ij
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PROVE HARDNESS One mobile users G(V,E) cost for edge and rewards for node Orienteering problem, NP-hard problem
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LOCAL RATIO AND LRBA
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(A) Transforming the original MRP problem
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LOCAL RATIO AND LRBA (B) Solving the orienteering problem of each user forwards f’ I−1 (y) to denote the reward function at the beginning of iteration I, and f I (y) the modified reward function at iteration I. where solve the orienteering problem associated with user u I O I denote the assignment
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LOCAL RATIO AND LRBA that is Iteration continued.
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LOCAL RATIO AND LRBA (C) Refining the final assignment backwards. Note that in the second process, each sensing task may be allocated to multiple users at different iterations.
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A EXAMPLE
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THEORETICAL ANALYSIS
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PRICING SENSING TASK the probability that mobile user u i would accept the agreement
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NUMERICAL RESULT
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THANK FOR LISTENING !
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