期刊
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
卷 59, 期 1, 页码 77-84出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCE.2013.6490244
关键词
Wireless Sensor Networks; Sink Mobility; Clustering; Energy Consumption; Network Lifetime
资金
- National Natural Science Foundation of China [61173072, 61271240, 61232016]
- Natural Science Foundation of Jiangsu Province [BK2012461]
- industrial Strategic Technology Development Program by the MKE Korea [10041740]
- Nanjing University of Information Science and Technology [S8110246001]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- National Research Foundation of Korea (NRF)
- Korea government (MEST) [2011-0030823]
- National Research Foundation of Korea [2011-0030079, 2011-0030823] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment(1).
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