Energy-Aware Routing and Relay Sensors Placing Algorithms in Wireless Sensor Networks

博士 === 國立交通大學 === 資訊科學與工程研究所 === 100 === In WSNs, there are spatially distributed sensors which cooperatively monitor environmental conditions, such as humidity, pressure, temperature, motion, or vibration, at different locations. Energy-aware routing, message ferry routing andrelay placing...

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Bibliographic Details
Main Authors: Chang, Jyh-Huei, 張志輝
Other Authors: Jan, Rong-Hong
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/49466659835322369888
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Summary:博士 === 國立交通大學 === 資訊科學與工程研究所 === 100 === In WSNs, there are spatially distributed sensors which cooperatively monitor environmental conditions, such as humidity, pressure, temperature, motion, or vibration, at different locations. Energy-aware routing, message ferry routing andrelay placing problems are important research issues in wireless sensor networks. In this dissertation, we design several efficient algorithms in wireless sensor networks, including two kinds of energy-aware cluster-based routing algorithms, two kinds of message ferry routing algorithms, and a relay placing algorithm. In energy-aware routing problem, cluster-based routing protocols have special advantages that help enhance both scalability and efficiency of the routing protocol. Likewise, finding the best way to arrange clustering so as to maximize the network's lifetime is now an important research topic in the field of wireless sensor networks. For energy-aware routing problem, we propose an energy-aware cluster-based routing algorithm (ECRA) for wireless sensor networks to maximize the network's lifetime. The ECRA selects some nodes as cluster-heads to construct Voronoi diagram and rotates the cluster-head to balance the load in each cluster. A two-tier architecture (ECRA-2T) is also proposed to enhance the performance of the ECRA. The simulations show that both the ECRA-2T and ECRA algorithms outperform other routing schemes such as direct communication, static clustering and LEACH. This strong performance stems from the fact that the ECRA and ECRA-2T rotate intra-cluster-heads to balance the load to all nodes in the sensor networks. The ECRA-2T also leverages the benefits of short transmission distances for most cluster-heads in the lower tier. In message ferry routing problem, some particular environments such as battlefield, disaster recovery and wide area surveillance, most existing routing algorithms will fail to deliver messages to their destinations. Thus, it is an important research issue of how to deliver data in disconnected wireless sensor networks. For message ferry routing problem, we propose two efficient message ferry routing algorithms in partitioned and buffer-limited wireless sensor networks, denoted as MFRA1 and MFRA2. MFRA1 and MFRA2 fix the overflow by partitioning the initial visit sequence into some sub-sequences such that the ferry visits the overflow node twice in the resulting sequence. The above process will continue until a feasible solution is found. Simulation results show that both MFRA1 and MFRA2 are better than other schemes in terms of the amount of data loss, because the other schemes neglect the case of sensor overflow. In relay placing problem, randomly deployed sensor networks often make initial communication gaps inside the deployed area, even in an extremely high density network. How to add relay sensors such that the underlying graph is connected and the number of relay sensors added is minimized is an important problem in wireless sensor networks. For relay placing problem, we propose an efficient relay sensors placing algorithm (ERSPA) for disconnected wireless sensor networks. Compared with the minimum spanning tree algorithm and the greedy algorithm, ERSPA achieves better performance in terms of the number of relay sensors added. Simulation results show that the average number of relay sensors added by the minimal spanning tree algorithm is approximately two times that of the ERSPA algorithm. This is because ERSPA places the relay sensors in optimal places to connect the maximum number of initial connected sub-graphs such that the average number of relaysensors can be minimized.