This paper provides a more detailed analysis of the proposed link stability estimation algorithm, extends the simulation results, and also proposes an application of the link stability estimation scheme to routing protocols of mobile ad hoc networks. NOTICE: this is the author's version of a work that was accepted for publication in Journal of Network and Computer Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Abstract -Link stability issue is significant in many aspects, especially for the route selection process in mobile ad-hoc networks (MANETs). Most previous works focus on the link stability in static environments, with fixed sampling windows which are only suitable for certain network topologies. In this paper, we propose a scheme to estimate the link stability based on link connectivity changes, which can be performed on the network layer, without the need of peripheral devices or low layer data. We adopt a variable sized sampling window and propose a method to estimate the link transition rates. The estimation scheme is not restricted to specific network topologies or mobility models. After that, we propose a routing method which adjusts its operating mode based on the estimated link stability. Simulation results show that the proposed scheme can provide correct estimation in both stationary and non-stationary scenarios, and the presented routing protocol outperforms conventional routing schemes without link stability estimation.
In REF , the authors present a routing strategy by adopting a variable sized sampling window to calculate link transition rates and, thus, estimate the link stability on the basis of link connectivity changes.
Link stability estimation based on link connectivity changes in mobile ad-hoc networks
J. Netw. Comput. Appl.
J. Netw. Comput. Appl.
Computer Science