A fair-rewarded aggregation policy for energy saving in IoT

• Main Authors: Chun-Hao Yang, 楊鈞皓
• Other Authors: Sheng-de Wang
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/vsdyp5

碩士 === 國立臺灣大學 === 電機工程學研究所 === 106 === Clustering algorithms are the most common methods to create long lifetime network topologies. Due to the dynamic nature and randomness of clustering algorithms, the workload of transmission and reception can be amortized by different nodes. However, the main idea behind saving energy is that data aggregation compression can reduce the data to transmit, and the data aggregation policy is to ensure that the most data can be aggregated without being expired. Most of the data aggregation policy discusses their mathematical model without concerning topology and routing protocol, but yet the topology and routing is closely related to data aggregation policy performance and its parameter, such as number of hop to the data sink and rate of incoming packets. This paper proposes a new data aggregation policy utilizing the features of clustering algorithms to better improve energy efficiency and expiration rate. By predicting the expiration of data, our method calculates and compares between the number of expiring and incoming data to decide the moment of transmission. The simulation shows that our transmission energy is 10% to 40% lower than the second best solution and most of the packet drop rate is about 0.5% to 5%.