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    杜扬, 黄河, 孙玉娥, 李凡长, 朱艳琴, 黄刘生. 地理位置相关移动感知系统任务分配问题研究[J]. 计算机研究与发展, 2014, 51(11): 2374-2381. DOI: 10.7544/issn1000-1239.2014.20131070
    引用本文: 杜扬, 黄河, 孙玉娥, 李凡长, 朱艳琴, 黄刘生. 地理位置相关移动感知系统任务分配问题研究[J]. 计算机研究与发展, 2014, 51(11): 2374-2381. DOI: 10.7544/issn1000-1239.2014.20131070
    Du Yang, Huang He, Sun Yu'e, Li Fanzhang, Zhu Yanqin, Huang Liusheng. A Location-Based Task Assignment Mechanism for Mobile Phone Sensing[J]. Journal of Computer Research and Development, 2014, 51(11): 2374-2381. DOI: 10.7544/issn1000-1239.2014.20131070
    Citation: Du Yang, Huang He, Sun Yu'e, Li Fanzhang, Zhu Yanqin, Huang Liusheng. A Location-Based Task Assignment Mechanism for Mobile Phone Sensing[J]. Journal of Computer Research and Development, 2014, 51(11): 2374-2381. DOI: 10.7544/issn1000-1239.2014.20131070

    地理位置相关移动感知系统任务分配问题研究

    A Location-Based Task Assignment Mechanism for Mobile Phone Sensing

    • 摘要: 随着智能手机应用的普及,移动感知技术已被认为是一种高效且成本低廉的环境数据收集方式.移动感知系统中地理位置相关的最优任务分配问题是一个NP难问题.为了解决该问题,提出了一种多项式时间的近似最优的任务分配算法.该算法首先引入了单位圆盘模型中移动划分的思想,将整个监测地理空间划分为若干个子区间,并使得子区间内的最优分配方案的集合是划分前最优解的〖SX(〗1〖〗1+ε〖SX)〗,这表明所设计的近似算法是一个多项式时间近似机制.随后,证明了最优任务分配问题在每个子区间内是多项式时间可解的,并设计了枚举算法求出该问题的最优解.最后,仿真实验结果表明所设计的近似最优任务分配算法的实际性能与理论分析相吻合.

       

      Abstract: In recent years, mobile phone sensing application has been regarded as a new paradigm which makes use of the smartphones to get the ubiquitous environment data. Most of the mobile phone sensing task assignment problems are based on the locations of the smartphone users. Unfortunately, the location-based optimal task assignment problem in mobile phone sensing system is an NP-hard problem. To solve this challenge, we study the optimal location-based task assignment problem for mobile phone sensing system, and propose a polynomial time approximation algorithm in this paper. The proposed approximation algorithm first introduces the shifting method for unit disk model into the task assignment problem of mobile phone sensing, and divides the sensing area into many sub-areas. We can prove that the union of the optimal task assignment solution in each sub-area is 〖SX(〗1〖〗1+ε〖SX)〗 of the optimal solution in the whole area, which illustrates the presented algorithm is a polynomial-time approximation scheme (PTAS). Then, we also prove that the optimal assignment problem in each sub-area is polynomial-time solvable, and design an enumeration method to get the optimal solution in the sub-area. Finally, the simulation results show that the practical performance of the proposed near optimal task assignment algorithm corroborates the theoretical analysis.

       

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