Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/98263
Title: | Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features | Authors: | Liu, Yang Han, Kai. Xiang, Liu. Luo, Jun. |
Keywords: | DRNTU::Engineering::Computer science and engineering | Issue Date: | 2012 | Source: | 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). | Conference: | International symposium on Mobile Ad Hoc Networking and Computing (13th : 2012) | Abstract: | 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. | URI: | https://hdl.handle.net/10356/98263 http://hdl.handle.net/10220/12364 |
DOI: | 10.1145/2248371.2248386 | Schools: | School of Computer Engineering | Rights: | © 2012 ACM. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Conference Papers |
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