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Optimizing wireless sensor networks.

Lai, Wei.

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Optimizing wireless sensor networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optimizing wireless sensor networks./
作者:	Lai, Wei.
面頁冊數:	121 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5376.
Contained By:	Dissertation Abstracts International67-09B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3232903
ISBN:	9780542868580

Optimizing wireless sensor networks.
Lai, Wei.

Optimizing wireless sensor networks. - 121 p.

Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5376.

Thesis (Ph.D.)--Boston University, 2007.

Wireless Sensor Networks are formed by small battery-powered devices that combine sensors, microprocessors, and radios used to communicate with each other; thereby enabling the monitoring and control of various physical systems. Due to severe resource constraints efficient resource allocation has emerged as a critical concern and motivates the work in this thesis.

ISBN: 9780542868580Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Optimizing wireless sensor networks.
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500 $a Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5376.
500 $a Adviser: Ioannis Ch. Paschalidis.
502 $a Thesis (Ph.D.)--Boston University, 2007.
520 $a Wireless Sensor Networks are formed by small battery-powered devices that combine sensors, microprocessors, and radios used to communicate with each other; thereby enabling the monitoring and control of various physical systems. Due to severe resource constraints efficient resource allocation has emerged as a critical concern and motivates the work in this thesis.
520 $a The first topic studied is that of devising energy-aware transmission and routing policies for large-scale wireless sensor networks. The problem is formulated as maximizing a utility function of transmissions subject to fairness constraints. A novel decomposition method is proposed and is shown to converge in finite time to a policy that is asymptotically optimal in the regime of low transmission power levels. It is also established that the utility maximization problem is solvable in polynomial time. The proposed framework can handle network lifetime constraints and accommodate node failures.
520 $a The second topic concerns the development of a capability for sensor networks to determine the physical location of their nodes. A systematic framework for designing a stochastic indoor location detection system is introduced. The location detection problem is posed as a hypothesis testing problem over a discretized space. An optimization methodology is put forth to deploy the network in order to minimize the probability of error. A special-purpose algorithm that is able to solve large instances efficiently is proposed.
520 $a The last topic addresses routing in the presence of noisy wireless channels and nodes that may "sleep" to preserve energy. The objective is to determine the best path from each node to a single gateway in order to balance the expected energy consumption against the latency probability. Large deviation techniques are relied upon to approximate these performance metrics and the energy vs. latency trade-off is formulated as an optimization problem. Solution methodologies developed include a centralized global optimization algorithm and a distributed algorithm. The proposed methodology can also optimize over the fraction of time sensor nodes remain in a "sleep" state (duty cycle).
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