TOWARD OPTIMAL ALLOCATION OF LOCATION DEPENDENT TASKS IN CROWDSENSING Jingtao Yao Lab of Cyberspace Computing Shanghai Jiao Tong University
WHY I CHOOSE THIS PAPER It is a paper for crowdsensing. It is a paper published by InfoCom It is a paper that studies the task allocation problem in crowdsensing.
ABSTRACT Introduction Problem Formulation Prove Hardness Local Ratio and LRBA Theoretical Analysis Pricing Sensing Task Numerical Result
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
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.
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
PROVE HARDNESS One mobile users G(V,E) cost for edge and rewards for node Orienteering problem, NP-hard problem
LOCAL RATIO AND LRBA
(A) Transforming the original MRP problem
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
LOCAL RATIO AND LRBA that is Iteration continued.
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.
A EXAMPLE
THEORETICAL ANALYSIS
PRICING SENSING TASK the probability that mobile user u i would accept the agreement
NUMERICAL RESULT
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