Reconfigurable middleware architectures for large scale sensor networks

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.

Name thesis:degree_name

Computer Science

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Department of Computer Science

Year

2009

Author dc:creator

• Brennan, Sean M.

Contributors dc:contributor

• Maccabe, Arthur B.
• He, Wenbo
• Jayaweera, Sudharman
• Cai, Michael

• wireless sensor networks
• object-oriented programming
• SENSIX framework

Language dc:language

English

Identifier

https://digitalrepository.unm.edu/cs_etds/46

OAI identifier oai:identifier

oai:digitalrepository.unm.edu:cs_etds-1045