Compressed data aggregation for energy efficient wireless sensor networks

Xiang, L; Luo, J; Vasilakos, A

dc.contributor.author	Xiang, L	en
dc.contributor.author	Luo, J	en
dc.contributor.author	Vasilakos, A	en
dc.date.accessioned	2014-03-01T02:47:19Z
dc.date.available	2014-03-01T02:47:19Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33070
dc.subject	Approximate Algorithm	en
dc.subject	Data Aggregation	en
dc.subject	Energy Consumption	en
dc.subject	Energy Efficient	en
dc.subject	Wireless Sensor Network	en
dc.subject.other	Aggregation schemes	en
dc.subject.other	Compressed sensing	en
dc.subject.other	Data aggregation	en
dc.subject.other	Data collection	en
dc.subject.other	Energy efficient	en
dc.subject.other	Greedy heuristics	en
dc.subject.other	Joint routing	en
dc.subject.other	Large-scale problem	en
dc.subject.other	Mixed-Integer Programming	en
dc.subject.other	Multi-hop networking	en
dc.subject.other	Np-completeness	en
dc.subject.other	Optimal solutions	en
dc.subject.other	Optimization problems	en
dc.subject.other	Small scale	en
dc.subject.other	Wireless communications	en
dc.subject.other	Energy efficiency	en
dc.subject.other	Energy utilization	en
dc.subject.other	Integer programming	en
dc.subject.other	MESH networking	en
dc.subject.other	Optimization	en
dc.subject.other	Sensors	en
dc.subject.other	Signal processing	en
dc.subject.other	Wireless ad hoc networks	en
dc.subject.other	Wireless telecommunication systems	en
dc.subject.other	Wireless sensor networks	en
dc.title	Compressed data aggregation for energy efficient wireless sensor networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/SAHCN.2011.5984932	en
heal.identifier.secondary	http://dx.doi.org/10.1109/SAHCN.2011.5984932	en
heal.identifier.secondary	5984932	en
heal.publicationDate	2011	en
heal.abstract	As a burgeoning technique for signal processing, compressed sensing (CS) is being increasingly applied to wireless communications. However, little work is done to apply CS to multihop networking scenarios. In this paper, we investigate the application of CS to data collection in wireless sensor networks, and we aim at minimizing the network energy consumption through joint routing and compressed aggregation. We first characterize the optimal solution to this optimization problem, then we prove its NP-completeness. We further propose a mixed-integer programming formulation along with a greedy heuristic, from which both the optimal (for small scale problems) and the near-optimal (for large scale problems) aggregation trees are obtained. Our results validate the efficacy of the greedy heuristics, as well as the great improvement in energy efficiency through our joint routing and aggregation scheme. © 2011 IEEE.	en
heal.journalName	2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011	en
dc.identifier.doi	10.1109/SAHCN.2011.5984932	en
dc.identifier.spage	46	en
dc.identifier.epage	54	en