Adaptive localized QoS-constrained data aggregation and processing in distributed sensor networks

Zhu, J; Papavassiliou, S; Yang, J

dc.contributor.author	Zhu, J	en
dc.contributor.author	Papavassiliou, S	en
dc.contributor.author	Yang, J	en
dc.date.accessioned	2014-03-01T01:23:32Z
dc.date.available	2014-03-01T01:23:32Z
dc.date.issued	2006	en
dc.identifier.issn	1045-9219	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17010
dc.subject	Data aggregation	en
dc.subject	Distributed networks	en
dc.subject	Quality of service	en
dc.subject	Sensor networks	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Computer simulation	en
dc.subject.other	Constraint theory	en
dc.subject.other	Data processing	en
dc.subject.other	Distributed computer systems	en
dc.subject.other	Mobile computing	en
dc.subject.other	Quality of service	en
dc.subject.other	Topology	en
dc.subject.other	Adaptive data collection algorithm	en
dc.subject.other	Data aggregation	en
dc.subject.other	End-to-end latency constraints	en
dc.subject.other	Sensor data fusion	en
dc.title	Adaptive localized QoS-constrained data aggregation and processing in distributed sensor networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TPDS.2006.114	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TPDS.2006.114	en
heal.language	English	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 investigated and analyzed. 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, based on the availability of local only information. Data aggregation is performed on the fly at intermediate sensor nodes, while at the same time the end-to-end latency constraints are satisfied. Furthermore, a localized adaptive data collection algorithm performed at the source nodes is developed that balances the design tradeoffs of delay, measurement accuracy, and buffer overflow, for given QoS requirements. 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 energy efficiency, network lifetime, end-to-end latency, and data loss are also evaluated and discussed. © 2006 IEEE.	en
heal.publisher	IEEE COMPUTER SOC	en
heal.journalName	IEEE Transactions on Parallel and Distributed Systems	en
dc.identifier.doi	10.1109/TPDS.2006.114	en
dc.identifier.isi	ISI:000239249800004	en
dc.identifier.volume	17	en
dc.identifier.issue	9	en
dc.identifier.spage	923	en
dc.identifier.epage	933	en