Data Collection Mechanism Based on Wavelet Multi-Resolution for Opportunistic Social Networks

Abstract

With the shaping of universal computing concept and the development of microelectronics technology, the mobile terminal devices have the strong functions of computing, storage and communication. The opportunistic social networks composed of a large number of terminal devices can be widely used in various scenarios by deploying them anytime and anywhere. One of its most important tasks is to collect data in order to communicate between people and things. The existing researches mainly focus on routing strategies that aim to improve the performance of data collection by optimizing the routing algorithm. However, the inherent characteristics of the opportunistic social networks such as the intermittent communication opportunities make it difficult to improve routing performance because nodes can not get global network topology information. In order to solve this problem, we should establish an efficient data collection mechanism based on wavelet multi-resolution to improve the efficiency of data collection from the source, which mainly studies the multi-resolution compression storage method of node data, the spatial multi-resolution data hierarchical storage framework, and the multi-resolution data management mechanism of mobile node. The experimental results show that the multi-resolution communication mode based on integer wavelet transform can greatly reduce the amount of data in the network and the energy consumption of nodes, and it is beneficial to the data collection of opportunistic social networks.