CAREER: Collaborative Signal and Information Processing in Sensor Networks

点击翻译按钮获取中文摘要

This proposal presents a career development plan for integrating research and education. The researchcomponent of this program focuses on the study of collaborative signal and information processing (CSIP)algorithms as well as the supporting computing models and protocols in sensor networks. The educationalcomponent is aimed at enhancing the newly created computer engineering program of the departmentthrough innovative curriculum development, active student mentoring, and by incorporating research findingsinto classroom teaching. The project consolidates research and educational efforts, responds to theunique challenges presented by sensor networks, and contributes significantly to the PI's career development.A sensor network forms a loosely-coupled distributed environment where collaborative processing amongmultiple sensor nodes is essential in order to compensate for each other's limited capability in sensing, processing,power supply, and to tolerate faults. The extremely constraint resources of sensor networks havepresented unique challenges to CSIP, the biggest of which is the contradictory requirements between energyefficiency and fault tolerance. While energy-efficient approaches try to limit the redundancy such thatminimum amount of energy is required for fulfilling a certain task, redundancy is needed for providingfault tolerance since sensors might be faulty, malfunctioning, or even malicious. A balance has to be struckbetween these two objectives.Intellectual Merit: An integrated research plan is proposed that tackles the unique challenges presentedby sensor networks. This plan concerns not only the development of effective processing algorithms, italso studies the design of supporting computing paradigms and protocols which play an important role infacilitating the collaborative processing. In particular, the research plan focusses on three themes:First, the design, evaluation and implementation of a new paradigm, the mobile-agent-based paradigm,for realizing collaborative processing in sensor networks. In this model, instead of each sensor node sendinglocal information to a processing center for integration, as is typical in a client/server-based computing, theintegration code is moved to the sensor nodes through mobile agents. We discuss the potential of mobileagent-based collaborative processing in providing progressive accuracy while maintaining certain degree offault tolerance. Second, the development and evaluation of a decentralized reactive clustering protocol tohelp adapt to the changing environment. Due to the sheer amount of nodes deployed, collaboration is usuallycarried out among nodes within the same cluster. We propose a decentralized reactive clustering (DRC)protocol in which the clustering procedure is initiated only when events are detected. Performance gain interms of energy consumption and network lifetime is analyzed. Third, the study of distributed optimizationfor in-network data processing. We tackle the challenging CSIP problems including multiple target/eventdetection and unknown target/event identification and develop decentralized algorithms that achieve bothenergy-efficiency and bandwidth-efficiency advantages, as well as detection performance gain compared toits centralized counterpart.Broader Impact: The PI is dedicated to excellence in teaching and enthusiastic student mentoring.CSIP in sensor networks, as one of the areas that integrate multidisciplinary characteristics, will be usedas an experimental concentration area to initiate innovative curriculum design, which helps bring in uniquefeatures to increase the quality and visibility of the newly established computer engineering program ofthe department. Although sensor networks have revealed great potential in CSIP, the extremely constraintresources have largely limited their practical deployment. The performance evaluation of computing models,protocols, and processing algorithms for CSIP would help understand the capability of sensor networks aswell as provide theoretical guide in the design of CSIP algorithms. Both the research and educational resultswill be made available through the Twiki collaboration platform on the Internet.1