Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (1): 152-162.doi: 10.23940/ijpe.20.01.p16.152162

• Orginal Article • Previous Articles    

Task Replica Assignment in Mobile Self-Organized Crowdsensing

Xiaohui Weiab*(), Bingyi Sunab, and Jiaxu Cuiab   

  1. aCollege of Computer Science and Technology, Jilin University, Changchun, 130012, China
    bKey Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: Xiaohui Wei
  • About author:

    Xiaohui Wei is currently a professor and the dean of the College of Computer Science and Technology at Jilin University, where he is also the director of the High-Performance Computing Center. His current major research interests include resource scheduling for large distributed systems, infrastructure level virtualization, large-scale data processing systems, and fault-tolerant computing.

    Bingyi Sun received her BS degree from the College of Computer Science and Technology (CCST) at Jilin University in 2013. She is currently working toward a PhD in computer science at Jilin University. Her research interests include cloud computing, mobile cloud computing, and mobile crowdsensing.

    Jiaxu Cui received his BSc and MS degrees in software engineering from Jilin University in 2013 and 2016, respectively. He is now a PhD candidate in the College of Computer Science and Technology at Jilin University. His main research interests are related to Bayesian optimization, structure optimization, and graph representation learning.

  • Supported by:
    This work was supported in part by the National Natural Science Foundation of China (NSFC) (No. 61772228).


In modern society, people carry mobile devices everywhere. However, these mobile devices often stay in an idle status, which leads to wasted resources. Thus, many researchers have sought methods to place tasks on idle mobile devices to avoid resource waste. In this paper, we propose three cooperative algorithms. The first algorithm is employed to find credible participants, which is the foundation of the latter two algorithms. The second and third algorithms are task replica assignment algorithms based on credible participants in mobile self-organized crowdsensing, and they are used in offline and online situations, respectively. The latter two algorithms adopt the greedy strategy and include constraints in assignment strategy for replicas. The experiments show that the proposed algorithms dramatically increase the probability of finding accurate results, increasing from slightly more than 0.6 for the original algorithms to nearly 0.98, even though the proposed algorithms have slightly longer average execution times.

Key words: crowdsensing, mobile self-organized network, task replica assignment, credit value, opportunistic sensing