An efficient QoS-constrained data aggregation and processing approach in distributed wireless sensor networks

Zhu, J; Papavassiliou, S; Kafetzoglou, S; Yang, J

dc.contributor.author	Zhu, J	en
dc.contributor.author	Papavassiliou, S	en
dc.contributor.author	Kafetzoglou, S	en
dc.contributor.author	Yang, J	en
dc.date.accessioned	2014-03-01T02:43:54Z
dc.date.available	2014-03-01T02:43:54Z
dc.date.issued	2006	en
dc.identifier.issn	15301346	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31550
dc.subject	Data Aggregation	en
dc.subject	Energy Efficient	en
dc.subject	Modeling and Simulation	en
dc.subject	Performance Metric	en
dc.subject	Quality of Service	en
dc.subject	Satisfiability	en
dc.subject	Sensor Network	en
dc.subject	Sensor Nodes	en
dc.subject	On The Fly	en
dc.subject	Wireless Sensor Network	en
dc.subject.other	Constrained optimization	en
dc.subject.other	Data processing	en
dc.subject.other	Distributed computer systems	en
dc.subject.other	Feature extraction	en
dc.subject.other	Telecommunication traffic	en
dc.subject.other	Wireless sensor networks	en
dc.subject.other	Data aggregation	en
dc.subject.other	Distributed wireless sensor networks	en
dc.subject.other	Sensor nodes	en
dc.subject.other	Traffic loads	en
dc.subject.other	Quality of service	en
dc.title	An efficient QoS-constrained data aggregation and processing approach in distributed wireless sensor networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ISCC.2006.33	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ISCC.2006.33	en
heal.identifier.secondary	1691038	en
heal.publicationDate	2006	en
heal.abstract	In this paper an efficient Quality of Service (QoS)-constrained data aggregation and processing approach for distributed wireless sensor networks is introduced and evaluated. The objective of the proposed approach is to aggregate data on the fly at intermediate sensor nodes in order to improve the operational efficiency and effectiveness of the sensor networks, while at the same time still satisfying the latency and measurement quality constraints. One of the key features of the proposed approach is that the task QoS requirements are taken into account to determine when and where to perform the aggregation in a distributed fashion. The performance of the proposed approach is analyzed and evaluated, through modeling and simulation, under different data aggregation scenarios and traffic loads. The impact of several design parameters and tradeoffs on various critical network and application related performance metrics, such as the energy efficiency and end-to-end latency, are also evaluated and discussed. © 2006 IEEE.	en
heal.journalName	Proceedings - International Symposium on Computers and Communications	en
dc.identifier.doi	10.1109/ISCC.2006.33	en
dc.identifier.spage	257	en
dc.identifier.epage	262	en