Adaptive data management for cloud-based wireless mesh networks

Abstract

In recent years, there has been considerable interest in developing and using wireless mesh networks. Compared to wireless local area networks, wireless mesh networks are more flexible because wireless mesh routers are interconnected by wireless links. In addition, they can be much easier to install and maintain, especially in environments where cables are difficult to install. Inspired by cloud computing, the aim of this project is to investigate a cloud-based wireless mesh network with adaptive data storage functions for storing data dynamically and flexibly in a wireless environment. In particular, a person-based adaptive data management scheme and a group-based adaptive data management scheme were designed. The person-based adaptive data management scheme seeks to provide upload/download functions for mesh clients, and adaptively moves files along with the movements of the owner to enhance access efficiency. The group-based adaptive data management scheme seeks to determine how the data resources/files should be stored and replicated in the wireless mesh routers such that the overall access cost can be minimized. Both a heuristic algorithm and a genetic algorithm were investigated. To support a cloud-based wireless mesh network, a distributed file system called MeshFS was also developed. A key technical challenge is to develop a lightweight software system that can be implemented over memory-limited wireless mesh network environments. MeshFS integrates scattered storage resources from wireless mesh routers to provide a mountable file system with fault-tolerant capabilities and cloud computing-like storage functions.