JACIII Vol.23 No.6 pp. 1063-1072
doi: 10.20965/jaciii.2019.p1063


Enhanced Intersystem Handover Algorithm for Heterogeneous Wireless Networks

Topside E. Mathonsi*, Okuthe P. Kogeda**, and Thomas O. Olwal*

*Tshwane University of Technology
Staatsartillerie Road, Pretoria West, Pretoria 0001, South Africa

**Department of Computer Science & Informatics, University of the Free State
Bloemfontein 9300, South Africa

October 8, 2018
July 25, 2019
November 20, 2019
FAHP, GPT, IH algorithm, MADM, MOORA

Current and future wireless network architectures consist of several access technologies to support numerous traffic types and enable mobile devices to be connected anytime, anywhere. However, providing a rapid seamless connectivity and service continuity between such various access technologies remains a challenge. This is mainly because the previously proposed handover algorithms have failed to predict the future values of the measured received signal strength needed for rapid handover process. In addition, existing handover algorithms are not adaptable to the changes of the network conditions and user preferences. This leads to erroneous network selection, packet loss, and ping-pong effect due to high-ranking abnormality. In this study, an intersystem handover (IH) algorithm has been designed by integrating grey prediction theory, multiple-attribute decision making, fuzzy analytic hierarchy process, and multi-objective optimization ratio analysis. Network Simulator 2 has been applied to evaluate the performance of the proposed IH algorithm when compared to the fuzzy logic-based vertical handover (FLBVH) algorithm and the adaptive neuro-fuzzy inference system (ANFIS) algorithm. On average, the proposed IH algorithm has shown 1.1 s handover delay, 5% packet loss, 1.6% probability of ping-pong effect, and 97.8% better throughput performance than the ANFIS algorithm and FLBVH algorithm, respectively, for a 100-s time interval.

Cite this article as:
T. Mathonsi, O. Kogeda, and T. Olwal, “Enhanced Intersystem Handover Algorithm for Heterogeneous Wireless Networks,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.6, pp. 1063-1072, 2019.
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Last updated on Feb. 17, 2020