Soft Computing-Based Schemes for Handover Management in Future Networks

Soft Computing-Based Schemes for Handover Management in Future Networks

Sandeep Bassi, Punam Rattan, Pooja Dhand
Copyright: © 2022 |Pages: 18
DOI: 10.4018/IJIRR.300291
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Abstract

The progression to next generation networks is replete with abundant co-existing technologies. To comply with the always best connected paradigm, several vertical handover decision approaches have been proposed in literature, using advanced techniques and tools. This paper discusses the application of soft computing techniques in the vertical handover decision-making process with emphasis on the state-of-the-art techniques. For a comprehensive evaluation, the algorithms are classified into three sets based on the soft computing technique used, namely fuzzy logic, machine learning, and evolutionary algorithms, and representative handover algorithms in each group are discussed. These papers are categorized in a well-defined structure to bring out their contribution, to underline the pretermitted notions, and to bring forth the emerging issues for future research. This paper summarizes the soft computing concepts and reviews its applications in candidate network selection, QoE enhancement, and reducing the unnecessary handovers.
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Introduction

Recent advances in technologies have witnessed the emergence of mobile and wireless networks, including mobile ad hoc networks, vehicular networks, 5G cellular networks, etc., which have the probability to facilitate several novel mobile and wireless services and applications(Agiwal et al.,2016), (Fersi et al., 2013). We have transcended into an era where computers are essentially involved in our daily lives(Augusto,2010). The incessant technological advancements in ICT (Information and Communications Technology) has initiated the development of computing devices of various types to be embedded in different devices that we interface with and use(Aztiria et al.,2011).The rapidly growing network of connected objects such as home appliances, actuators, electronic gadgets that are able to accumulate and transfer data using in-built sensors has evolved into IoT(Internet of Things)(Čolaković&Hadžialić,2018).The IoT with smart objects of computational and communication capabilities built into everyday things has immense applications in our daily lives(Guo et al.,2012). In a similar sense AmI (Ambient Intelligence) that is built upon pervasive computing, ubiquitous computing, context awareness has enabled an environment where technology gradually disappears into the surroundings and provides integrated solutions(Cook et al., 2009),(Liu, et al.,2017).

The Internet architecture is the backbone for these services and needs to be constantly updated to offset the future challenges (Al-Fuqaha et al., 2015).In order to realize these contemporary paradigms, the requisite features are gradually developed and integrated into the infrastructure, thereby transforming it into an infrastructure for providing constant connectivity for these services. The demand for constant connectivity necessitates the adoption of wireless technologies. The increased adoption of wireless technologies is basically due to factors such as increased proliferation and access of smart devices, availability of multifarious networking interfaces and availability of numerous wireless heterogeneous technologies, like, LTE, Wi-Fi, wireless interoperability for microwave access (WiMAX) and Universal Mobile Telecommunication System (UMTS)(Tuncer et al.,2012). The next-generation networks portray a heterogeneous environment with the prevalence of diverse access networks technologies that vary in terms of latency, throughput, cost or bandwidth(Mahmood et al.,2018) .With the unprecedented rise in user demands for bandwidth and the meteoric rise in the number of bandwidth warranting applications such as video streaming and multimedia, the extents of the current systems are being tested(Tehrani et al., 2014).Many applications also expend huge amounts of network resources and create several significant issues for heterogeneous wireless networks. These include mobility management, interoperability, Quality of Service and provision of Quality of Experience (QoE) .The challenge is to provide robust services in hugely dynamic environments and to develop applications and lightweight algorithms which are intelligent and self adaptive.

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