Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Bluetooth revealed: the insider's guide to an open specification for global wireless communication
Bluetooth revealed: the insider's guide to an open specification for global wireless communication
Simultaneous optimization for concave costs: single sink aggregation or single source buy-at-bulk
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)
Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)
Latency constrained aggregation in sensor networks
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
MobiHoc '11 Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing
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In-network aggregation has become a promising technique for improving the energy efficiency of wireless sensor networks. Aggregating data at various nodes in the network results in a reduction in the amount of bits transmitted over the network, and hence, saves energy. In this paper, we focus on another important aspect of aggregation, i.e., delay performance. In conjunction with link scheduling, in-network aggregation can reduce the delay by lessening the demands for wireless resources and thus expediting data transmissions. We formulate the problem that minimizes the sum delay of sensed data, and analyze the performance of optimal scheduling with innetwork aggregation in tree networks under the node-exclusive interference model. We provide a system wide lower bound on the delay and use it as a benchmark for evaluating different scheduling policies. We numerically evaluate the performance of myopic and non-myopic scheduling policies, where myopic one considers only the current system state for a scheduling decision while non-myopic one simulates future system states. We show that the one-step non-myopic policies can substantially improve the delay performance. In particular, the proposed nonmyopic greedy scheduling achieves a good tradeoff between performance and implementability.