Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks
In-network processing is touted as a key technology to eliminate data redundancy and minimize data transmission, which are crucial to saving energy in wireless sensor networks (WSNs). Specifically, operators participating in in-network processing are mapped to nodes in a sensor network. They receive...
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sg-ntu-dr.10356-977122020-05-28T07:41:33Z Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks Lu, Zongqing Wen, Yonggang Fan, Rui Tan, Su-Lim Biswas, Jit School of Computer Engineering DRNTU::Engineering::Computer science and engineering In-network processing is touted as a key technology to eliminate data redundancy and minimize data transmission, which are crucial to saving energy in wireless sensor networks (WSNs). Specifically, operators participating in in-network processing are mapped to nodes in a sensor network. They receive data from downstream operators, process them and route the output to either the upstream operator or the sink node. The objective of operator tree placement is to minimize the total energy consumed in performing in-network processing. Two types of placement algorithms, centralized and distributed, have been proposed. A problem with the centralized algorithm is that it does not scale to large WSN's, because each sensor node is required to know the complete topology of the network. A problem with the distributed algorithm is their high message complexity. In this paper, we propose a heuristic algorithm to place a treestructured operator graph, and present a distributed implementation to optimize in-network processing cost and reduce the communication overhead. We prove a tight upper bound on the minimum in-network processing cost, and show that the heuristic algorithm has better performance than a canonical greedy algorithm. Simulation-based evaluations demonstrate the superior performance of our heuristic algorithm. We also give an improved distributed implementation of our algorithm that has a message overhead of O(M) per node, which is much less than the O(√NM log2 M) and O(√NM) complexities for two previously proposed algorithms, Sync and MCFA, respectively. Here, N is the number of network nodes and M is the size of the operator tree. 2013-12-05T07:01:21Z 2019-12-06T19:45:47Z 2013-12-05T07:01:21Z 2019-12-06T19:45:47Z 2013 2013 Journal Article Lu, Z., Wen, Y., Fan, R., Tan, S. L., & Biswas, J. (2013). Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks. IEEE journal on selected areas in communications, 31(4), 743-755. 0733-8716 https://hdl.handle.net/10356/97712 http://hdl.handle.net/10220/18113 10.1109/JSAC.2013.130411 en IEEE journal on selected areas in communications |
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DRNTU::Engineering::Computer science and engineering Lu, Zongqing Wen, Yonggang Fan, Rui Tan, Su-Lim Biswas, Jit Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
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In-network processing is touted as a key technology to eliminate data redundancy and minimize data transmission, which are crucial to saving energy in wireless sensor networks (WSNs). Specifically, operators participating in in-network processing are mapped to nodes in a sensor network. They receive data from downstream operators, process them and route the output to either the upstream operator or the sink node. The objective of operator tree placement is to minimize the total energy consumed in performing in-network processing. Two types of placement algorithms, centralized and distributed, have been proposed. A problem with the centralized algorithm is that it does not scale to large WSN's, because each sensor node is required to know the complete topology of the network. A problem with the distributed algorithm is their high message complexity. In this paper, we propose a heuristic algorithm to place a treestructured operator graph, and present a distributed implementation to optimize in-network processing cost and reduce the communication overhead. We prove a tight upper bound on the minimum in-network processing cost, and show that the heuristic algorithm has better performance than a canonical greedy algorithm. Simulation-based evaluations demonstrate the superior performance of our heuristic algorithm. We also give an improved distributed implementation of our algorithm that has a message overhead of O(M) per node, which is much less than the O(√NM log2 M) and O(√NM) complexities for two previously proposed algorithms, Sync and MCFA, respectively. Here, N is the number of network nodes and M is the size of the operator tree. |
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School of Computer Engineering |
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School of Computer Engineering Lu, Zongqing Wen, Yonggang Fan, Rui Tan, Su-Lim Biswas, Jit |
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Article |
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Lu, Zongqing Wen, Yonggang Fan, Rui Tan, Su-Lim Biswas, Jit |
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Lu, Zongqing |
title |
Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
title_short |
Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
title_full |
Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
title_fullStr |
Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
title_full_unstemmed |
Toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
title_sort |
toward efficient distributed algorithms for in-network binary operator tree placement in wireless sensor networks |
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2013 |
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https://hdl.handle.net/10356/97712 http://hdl.handle.net/10220/18113 |
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1681057796329570304 |