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Reconfigurable middleware architectures for large scale sensor networks

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/10297

Reconfigurable middleware architectures for large scale sensor networks

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Title: Reconfigurable middleware architectures for large scale sensor networks
Author: Brennan, Sean M.
Advisor(s): Maccabe, Arthur B.
Committee Member(s): He, Wenbo
Jayaweera, Sudharman
Cai, Michael
Department: University of New Mexico. Dept. of Computer Science
Subject: SENSIX framework
wireless sensor networks
object-oriented programming
LC Subject(s): Wireless sensor networks--Programming.
Object-oriented programming (Computer science)
Middleware.
Degree Level: Doctoral
Abstract: Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration.
Graduation Date: December 2009
URI: http://hdl.handle.net/1928/10297


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