On the Minimization of Handover Decision Instability in Wireless Local Area Networks

TL;DR

This paper introduces HODSTAT, a hysteresis-based technique for WLAN handover decisions that reduces unnecessary handovers, improves stability, and enhances network performance by balancing connection quality and handover costs.

Contribution

The paper proposes a novel hysteresis margin approach combined with utility functions to minimize handover instability in WLANs, outperforming existing methods.

Findings

HODSTAT significantly reduces unnecessary handovers.

The approach improves network stability and user experience.

Simulation results show superior performance over other methods.

Abstract

This paper addresses handover decision instability which impacts negatively on both user perception and network performances. To this aim, a new technique called The HandOver Decision STAbility Technique (HODSTAT) is proposed for horizontal handover in Wireless Local Area Networks (WLAN) based on IEEE 802.11standard. HODSTAT is based on a hysteresis margin analysis that, combined with a utilitybased function, evaluates the need for the handover and determines if the handover is needed or avoided. Indeed, if a Mobile Terminal (MT) only transiently hands over to a better network, the gain from using this new network may be diminished by the handover overhead and short usage duration. The approach that we adopt throughout this article aims at reducing the minimum handover occurrence that leads to the interruption of network connectivity (this is due to the nature of handover in WLAN which is a break before make which causes additional delay and packet loss). To this end, MT rather performs a handover only if the connectivity of the current network is threatened or if the performance of a neighboring network is really better comparing the current one with a hysteresis margin. This hysteresis should make a tradeoff between handover occurrence and the necessity to change the current network of attachment. Our extensive simulation results show that our proposed algorithm outperforms other decision stability approaches for handover decision algorithm.