Adaptive localized QoS-constrained data aggregation and processing in distributed sensor networks
Data aggregation, Distributed networks, Quality of service, Sensor networks
IEEE Transactions on Parallel and Distributed Systems
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.
Original Publication Date
DOI of published version
Zhu, Jin; Papavassiliou, Symeon; and Yang, Jie, "Adaptive localized QoS-constrained data aggregation and processing in distributed sensor networks" (2006). Faculty Publications. 2763.