Evaluating Mobility Pattern Space Routing for DTNs

TL;DR

This paper introduces MobySpace, a high-dimensional Euclidean space-based routing algorithm for DTNs that leverages nodes' mobility patterns to improve routing performance in partitioned networks.

Contribution

It proposes a novel MobySpace routing scheme based on mobility patterns and evaluates its effectiveness using real mobility traces in ambient networking scenarios.

Findings

MobySpace achieves good routing performance compared to other algorithms.

High connection time nodes benefit most from MobySpace routing.

Homogeneity of mobility patterns significantly affects routing success.

Abstract

Because a delay tolerant network (DTN) can often be partitioned, the problem of routing is very challenging. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high-dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and the large scale evaluation of this routing scheme in the context of ambient networking by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visit of nodes for each possible location. We show that the MobySpace can achieve good performance compared to that of the other algorithms we implemented, especially when we perform routing on the nodes that have a high connection time. We determine that the degree of homogeneity of mobility patterns of nodes has a high impact on routing. And finally, we study the ability of nodes to learn their own mobility patterns.