Power-Aware Localized Routing in Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
An Energy-Aware QoS Routing Protocol for Wireless Sensor Networks
ICDCSW '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Parametric probabilistic sensor network routing
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
The impact of spatial correlation on routing with compression in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Aggregation in sensor networks with a user-provided quality of service goal
Information Sciences: an International Journal
Computer Networks: The International Journal of Computer and Telecommunications Networking
MVSink: Incrementally Building In-Network Aggregation Trees
EWSN '09 Proceedings of the 6th European Conference on Wireless Sensor Networks
Adaptive and energy efficient clustering architecture for dynamic sensor networks
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
QoS parameterization algorithm in data collection for wireless sensor networks
Proceedings of the 5th ACM symposium on QoS and security for wireless and mobile networks
Real-time data aggregation in contention-based wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Journal of Network and Computer Applications
Proceedings of the 16th European Conference on Pattern Languages of Programs
MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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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.