Spanning Tree Based Topology Control For Data Collecting In Predictable Delay-Tolerant Networks

In predictable delay tolerant networks (PDTNs), the network topology is known a priori or can be predicted over time such as vehicular networks based on public buses or trains and space planet network. Previous DTN research mainly focuses on routing and data access. However, data collecting are used widely in PDTNs and it is very important in practical application, how to maintain the dynamic topology of this type of PDTNs becomes crucial. In this paper, a spanning tree (ST) based topology control method for data collecting in PDTNs is proposed. The PDTN is modeled as layered space-time directed graph which includes spatial, temporal and energy cost information, which can be simplified as reduced aggregated directed graph. The topology control problem is defined as constructing a ST that the total energy cost of the ST is minimized and the time delay threshold is satisfied. We propose three heuristic algorithms based on layered space-time directed graph and reduced aggregated directed graph to solve the defined problem, and compare them in terms of energy cost and time delay. Extensive simulation experiments demonstrate that the proposed algorithms can guarantee data transmission effectively, reduce the network energy consumption significantly, and shorten the time delay of data transmission. (C) 2016 Elsevier B.V. All rights reserved.