Queue-Optimized Scheduling for Data-Centric Wireless Sensor Networks

• Main Authors: Chih-Yen Su, 蘇智彥
• Other Authors: Hung-Yun Hsieh
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/g7xy72

碩士 === 國立臺灣大學 === 電信工程學研究所 === 107 === Stability condition for the communication system is an important issue for wireless communication. In this thesis, we formulate a general model and analytical framework for wireless sensor networks (WSN) by considering data compression and the data dropping. For most of the wireless sensor networks, seldom of them focus on the correlation between each sample in nature. We consider the statistic value of compressed data and its property. We use the Lyapunov theorem to guarantee the stable state for the system when applying data compression. Under the stability condition, the main target in our research is to minimize the time average of the queue length. First of all, we transform the time average objectives function and constraints to general convex function form. We propose the optimal scheduling algorithm which decides the time resource and dropped data in every scheduling period. Applying data compression may meet the stability condition if the original condition is unstable. The dropping process can save 4.3% of the queue length. Secondly, we solve the minimum time average energy cost problem. We extend the general Lyapunov function by adding the penalty function. We propose the new energy-aware scheduling algorithm, including the time ratio decision, dropped data decision, and compression option decision. Compared to the baseline, our proposed optimal scheduling method can save 40% to 50% time average of energy consumption but the average queue length increases about 30%. Thus, this optimal method can increase energy efficiency by adding some additional storage memory to the queue.