MP-DNA: A novel distributed replica placement heuristic for WMNs

Abstract

Content replication and placement is an area that has been well explored in the scope of Content Delivery Networks (CDNs), but has received relatively less attention from the research community when it comes to Wireless Mesh Networks (WMNs). There are a number of Replica Placement Algorithms (RPAs) that are specifically designed for CDNs. But they do not consider the special features of wireless networks. In this paper, we propose a new heuristic called MP-DNA (Multiple Partitions per Delegate Node Assignment). We study the problem of optimal content replication and placement in WMNs. In our model, each mesh router acts as a replica server with limited storage capacity. The challenge is to replicate content as close as possible to the requesting clients and thus reduce the access latency per object, while minimizing the number of replicas. We formulate this problem in terms of combinatorial optimization and propose a novel, distributed, scalable heuristic for content replication. Using simulation tests, we demonstrate that MP-DNA is scalable, performing well with respect to the number of replica servers and the number of objects. Furthermore, MP-DNA can achieve a performance close to the Greedy-Global heuristic, with a significant reduction in running time, mean throughput and storage space required.