
Proceedings Paper
Explicit solutions to analytical models of cross-layer protocol optimization in wireless sensor networksFormat | Member Price | Non-Member Price |
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Paper Abstract
The work is based on the interactions among the nodes of a wireless sensor network (WSN) to cooperatively process
data from multiple sensors. Quality-of-service (QoS) metrics are associated with the quality of fused information:
throughput, delay, packet error rate, etc. A multivariate point process (MVPP) model of discrete random events in
WSNs establishes stochastic characteristics of optimal cross-layer protocols. In previous work by the author, discreteevent,
cross-layer interactions in the MANET protocol are modeled in very general analytical terms with a set of
concatenated design parameters and associated resource levels by multivariate point processes (MVPPs).
Characterization of the "best" cross-layer designs for the MANET is formulated by applying the general theory of
martingale representations to controlled MVPPs. Performance is described in terms of concatenated protocol parameters
and controlled through conditional rates of the MVPPs. Assumptions on WSN characteristics simplify the dynamic
programming conditions to yield mathematically tractable descriptions for the optimal routing protocols. Modeling
limitations on the determination of closed-form solutions versus iterative explicit solutions for ad hoc WSN controls are
presented.
Paper Details
Date Published: 19 May 2009
PDF: 14 pages
Proc. SPIE 7352, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, 735209 (19 May 2009); doi: 10.1117/12.820501
Published in SPIE Proceedings Vol. 7352:
Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
Stephen Mott; John F. Buford; Gabriel Jakobson, Editor(s)
PDF: 14 pages
Proc. SPIE 7352, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, 735209 (19 May 2009); doi: 10.1117/12.820501
Show Author Affiliations
William S. Hortos, Associates in Communication Engineering Research and Technology (United States)
Published in SPIE Proceedings Vol. 7352:
Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
Stephen Mott; John F. Buford; Gabriel Jakobson, Editor(s)
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