Conference Proceeding Article
In-network processing, involving operations such as filtering, compression and fusion, is widely used in sensor networks to reduce the communication overhead. In many tactical and stream-oriented wireless network applications, both link bandwidth and node energy are critically constrained resources and in-network processing itself imposes non-negligible computing cost. In this work, we have developed a unified and distributed closed-loop control framework that computes both a) the optimal level of sensor stream compression performed by a forwarding node, and b) the best set of nodes where the stream processing operators should be deployed. Our framework extends the Network Utility Maximization (NUM) paradigm, where resource sharing among competing applications is modeled as a form of distributed utility maximization. We also show how our model can be adapted to more realistic cases, where in-network compression may be varied only discretely, and where a fusion operation cannot be fractionally distributed across multiple nodes.This research was sponsored by US Army Research laboratory and the UK Ministry of Defence and was accomplished under Agreement Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US Army Research Laboratory, the U.S. Government, the UK Ministry of Defense, or the UK Government. The US and UK Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
Software and Cyber-Physical Systems
Distributed computing in sensor systems: 5th IEEE International Conference, DCOSS 2009, Marina del Rey, CA, USA, June 8-10, 2009: Proceedings
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ESWARAN, Sharanya; JOHNSON, Matthew; MISRA, Archan; and LA PORTA, Thomas.
Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multi-hop Wireless Networks. (2009). Distributed computing in sensor systems: 5th IEEE International Conference, DCOSS 2009, Marina del Rey, CA, USA, June 8-10, 2009: Proceedings. 87-102. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/667
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