Abstract
To enable in situ autonomous embedded wireless sensor network (EWSN) dynamic optimizations, this chapter proposes an online EWSN optimization methodology that extends static design time parameter tuning. It first presents a review of related work and then provides an overview of dynamic optimization methodology. The chapter also presents online lightweight optimization algorithms/heuristics for the dynamic optimization methodology. The dynamic optimization module determines the sensor node's operating state (tunable parameter value settings) using an online optimization algorithm, such as greedy and a simulated annealing algorithms. The dynamic profiler module records profiling statistics (e.g., wireless channel condition, number of dropped packets, packet size, radio transmission power), and the profiling statistics processing module performs any necessary data processing. The chapter gives experimental results for online optimization algorithms. These results evaluate the greedy and SA algorithms in terms of solution quality and the percentage of state space explored.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
