Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features

Wireless Sensor Networks (WSNs) have acquired new features recently, i.e., both the sensor and the antenna of a node can be directional. This brings new challenges to the Connected Coverage (CoCo) problem, where a finite set of targets needs to be monitored by some active sensor nodes, and the conne...

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Main Authors: Liu, Yang, Han, Kai., Xiang, Liu., Luo, Jun.
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/98263
http://hdl.handle.net/10220/12364
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-982632020-05-28T07:18:11Z Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features Liu, Yang Han, Kai. Xiang, Liu. Luo, Jun. School of Computer Engineering International symposium on Mobile Ad Hoc Networking and Computing (13th : 2012) DRNTU::Engineering::Computer science and engineering Wireless Sensor Networks (WSNs) have acquired new features recently, i.e., both the sensor and the antenna of a node can be directional. This brings new challenges to the Connected Coverage (CoCo) problem, where a finite set of targets needs to be monitored by some active sensor nodes, and the connectivity of these active nodes with the sink must be retained at the same time. In this paper, we study the Minimum-Energy Connected Coverage (MeCoCo) problem in WSNs with Omni-directional (O) and Directional (D) features, aiming at minimizing the total energy cost of both sensing and connectivity. Considering different combinations of O and D features, we study the MeCoCo problem under four cases, namely: O-Antenna and O-Sensor (OAOS), O-Antenna and D-Sensor (OADS), D-Antenna and D-Sensor (DADS), as well as D-Antenna and O-Sensor (DAOS). We prove that the MeCoCo problem is NP-hard under all these cases, and present approximation algorithms with provable approximation ratios. In particular, we propose a constant-approximation for OAOS, and polylogarithmic approximations for all other cases. Finally, we conduct extensive simulations and the results strongly confirm the effectiveness of our approach. 2013-07-26T03:49:34Z 2019-12-06T19:52:55Z 2013-07-26T03:49:34Z 2019-12-06T19:52:55Z 2012 2012 Conference Paper Han, K., Xiang, L., Luo, J., & Liu, Y. (2012). Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features. 2012 13th ACM international symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '12). https://hdl.handle.net/10356/98263 http://hdl.handle.net/10220/12364 10.1145/2248371.2248386 en © 2012 ACM.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Liu, Yang
Han, Kai.
Xiang, Liu.
Luo, Jun.
Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
description Wireless Sensor Networks (WSNs) have acquired new features recently, i.e., both the sensor and the antenna of a node can be directional. This brings new challenges to the Connected Coverage (CoCo) problem, where a finite set of targets needs to be monitored by some active sensor nodes, and the connectivity of these active nodes with the sink must be retained at the same time. In this paper, we study the Minimum-Energy Connected Coverage (MeCoCo) problem in WSNs with Omni-directional (O) and Directional (D) features, aiming at minimizing the total energy cost of both sensing and connectivity. Considering different combinations of O and D features, we study the MeCoCo problem under four cases, namely: O-Antenna and O-Sensor (OAOS), O-Antenna and D-Sensor (OADS), D-Antenna and D-Sensor (DADS), as well as D-Antenna and O-Sensor (DAOS). We prove that the MeCoCo problem is NP-hard under all these cases, and present approximation algorithms with provable approximation ratios. In particular, we propose a constant-approximation for OAOS, and polylogarithmic approximations for all other cases. Finally, we conduct extensive simulations and the results strongly confirm the effectiveness of our approach.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Liu, Yang
Han, Kai.
Xiang, Liu.
Luo, Jun.
format Conference or Workshop Item
author Liu, Yang
Han, Kai.
Xiang, Liu.
Luo, Jun.
author_sort Liu, Yang
title Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
title_short Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
title_full Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
title_fullStr Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
title_full_unstemmed Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
title_sort minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features
publishDate 2013
url https://hdl.handle.net/10356/98263
http://hdl.handle.net/10220/12364
_version_ 1681058151137280000