期刊
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
卷 26, 期 12, 页码 3236-3249出版社
IEEE COMPUTER SOC
DOI: 10.1109/TPDS.2014.2386343
关键词
Wireless sensor networks; task allocation; fault tolerance; particle swarm optimization; primary/backup
资金
- National Basic Research Program of China [2009CB320503]
- 2009CB320503 [61103175, 61401100, 61300102]
- Fujian Province Key Laboratory of Network Computing and Intelligent Information Processing Project [2009J1007]
- Key Project of Chinese Ministry of Education [212086]
- Fujian Natural Science Funds for Distinguished Young Scholar [2014J06017]
- Program for New Century Excellent Talents in Fujian Province University [JA13021]
- Fujian Province High School Science Fund for Distinguished Young Scholars [JA12016]
- Natural Science Foundation of Fujian Province [2013J01235, 2014J01233]
- Grants-in-Aid for Scientific Research [26280027] Funding Source: KAKEN
One of challenging issues for task allocation problem in wireless sensor networks (WSNs) is distributing sensing tasks rationally among sensor nodes to reduce overall power consumption and ensure these tasks finished before deadlines. In this paper, we propose a soft real-time fault-tolerant task allocation algorithm (FTAOA) for WSNs in using primary/backup (P/B) technique to support fault tolerance mechanism. In the proposed algorithm, the construction process of discrete particle swarm optimization (DPSO) is achieved through adopting a binary matrix encoding form, minimizing tasks execution time, saving node energy cost, balancing network load, and defining a fitness function for improving scheduling effectiveness and system reliability. Furthermore, FTAOA employs passive backup copies overlapping technology and is capable to determinate the mode of backup copies adaptively through scheduling primary copies as early as possible and backup copies as late as possible. To improve resource utilization, we allocate tasks to the nodes with high performance in terms of load, energy consumption, and failure ratio. Analysis and simulation results show the feasibility and effectiveness of FTAOA. FTAOA can strike a good balance between local solution and global exploration and achieve a satisfactory result within a short period of time.
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