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
Energy aware lossless data compression
Proceedings of the 1st international conference on Mobile systems, applications and services
Energy-aware lossless data compression
ACM Transactions on Computer Systems (TOCS)
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks
IEEE Transactions on Mobile Computing
Data Gathering with Tunable Compression in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
A Generalised Energy-Efficient Time-Based Communication Protocol for Wireless Sensor Networks
International Journal of Internet Protocol Technology
Context-aware cluster-based hierarchical protocol for Wireless Sensor Networks
International Journal of Ad Hoc and Ubiquitous Computing
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
DPLC: dynamic packet length control in wireless sensor networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
An energy efficient clustering protocol for routing in Wireless Sensor Network
International Journal of Ad Hoc and Ubiquitous Computing
An adaptive blind algorithm for energy balanced data propagation in wireless sensors networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
In-network aggregation techniques for wireless sensor networks: a survey
IEEE Wireless Communications
IEEE Journal on Selected Areas in Communications
International Journal of Ad Hoc and Ubiquitous Computing
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Wireless Sensor Networks WSNs consist of inexpensive low-power miniature sensing devices with severe power constraints, necessitating energy-efficient solutions for networking operations. Major prior art proposals have been primarily directed towards minimising the communication cost, either implicitly assuming away the computation overhead as being negligible, or radically trading against it. However, in computation-bound scenarios, dealing with a large volume of data, such simplifying assumptions or radical measures tend to be inefficient. In this paper, we investigate the problem of minimising the overall energy needed to send data from a set of sensor nodes to a single destination, where each node is in charge of a mission. Two types of missions are defined: sensing and decision making; while source nodes are only in charge of sensing, relay nodes can carry out both missions simultaneously. More specifically, given a node's current backlog and its latest view on the relevant portion of the data-gathering tree, taking on the decision-making mission involves deriving an online trade-off between energy costs of compression and communication, and deciding between sending data either in the raw mode or alternatively compressed with a feasible optimal compression ratio. The used data compression technique depends on the type of application and the spatiotemporal correlation in the packets. Simulation experiments reveal that, compared with previous methods, the proposed scheme exhibits superior energy efficiency with an additional 36% reduction of the costs.