Event-triggered distributed optimization in sensor networks

Many problems in sensor networks can be formulated as optimization problems. Existing distributed optimization algorithms typically rely on choosing a step size to ensure convergence. In this case, the communication between sensor nodes occurs each time the computations are carried out. Since in sen...

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Bibliographic Details
Published in:2009 International Conference on Information Processing in Sensor Networks pp. 49 - 60
Main Authors: Wan, Pu, Lemmon, Michael D.
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 13.04.2009
IEEE
Series:ACM Conferences
Subjects:
Broadcasting
Communication system control
Computer networks
Computer systems organization > Architectures > Distributed architectures
Convergence
Distributed algorithms
Distributed computing
Hardware > Communication hardware, interfaces and storage
Message passing
Networks
Networks > Network services > Network management
Networks > Network types > Mobile networks
Networks > Network types > Wireless access networks
Routing
Scalability
Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Communications management
Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Process management > Process synchronization
Software and its engineering > Software organization and properties > Software system structures > Distributed systems organizing principles
Wireless sensor networks
ISBN:1424451086, 9781424451081
Online Access:Get full text
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Summary:Many problems in sensor networks can be formulated as optimization problems. Existing distributed optimization algorithms typically rely on choosing a step size to ensure convergence. In this case, the communication between sensor nodes occurs each time the computations are carried out. Since in sensor networks, the energy required for communication can be significantly greater than the energy required to perform computation, it would be beneficial if we can somehow separate communication and computation. This paper presents such a distributed algorithm called the event-triggered algorithm. Under event triggering, each agent broadcasts to its neighbors when a local “error” signal exceeds a state dependent threshold. We give a general class of problems in sensor networks where the event-triggered algorithm can be used. In particular, this paper uses the data gathering problem as an example. We propose an event-triggered distributed algorithm and prove its convergence. Simulation results show that the proposed algorithm reduces the number of message exchanges by two orders of magnitude compared to commonly used dual decomposition algorithms. It also enjoys better scalability with respect to the depth of the tree and the maximum branch number of the tree.
ISBN:1424451086
9781424451081
DOI:10.5555/1602165.1602172