Date of Award

Summer 2006

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical & Computer Engineering

Program/Concentration

Electrical and Computer Engineering

Committee Director

James F. Leathrum, Jr.

Committee Member

Lee A. Belfore II

Committee Member

Min Song

Call Number for Print

Special Collections LD4331.E55 K349 2006

Abstract

Mobile sensors provide a safe, cost effective method for gathering information in hazardous environments. When the hazardous environment is either unexplored, such as the surface of Mars, or unanticipated, such as the result of chemical contamination, it is desirable for a system to gather information with a minimal amount of outside control (localization, decision control, etc.) and prepositioned sensors. If one takes a look at the number of the sensors deployed on a scale, at the lower end is the sole, multipurpose sensor unit. The upper end deals with hordes of inexpensive, expendable sensors. In the middle, a cluster of a reasonable number of sensors has benefits. This thesis speaks of the pros and cons of a small set of sensors and reveals how different its behavior is in comparison with systems at either ends of the scale, in terms of coverage, fault tolerance, and cost effectiveness. This thesis presents the concept of a sensor cloud as a tightly coupled, mobile sensor cluster. The primary characteristics of a sensor cloud are defined in terms of connectivity and coverage. Secondary characteristics like degrees of motion, density and fault tolerance are also laid out. The model of a sensor cloud was derived by extracting commonalities from several of the concepts of sensor collections published in the past. The different kinds of cloud management such as mobility, control and power are discussed. To facilitate development, an operational model for the sensor cloud is developed. The model supports development of control algorithms focused on specific operational needs. Several algorithms are presented within the context of the operational model. Actions such as deployment and navigation are discussed in detail at both the individual sensor level and at the cloud level. Performance parameters such as cloud build up and navigation times are compared for the algorithms and presented.

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DOI

10.25777/30wy-ff36

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