Add‐net: adaptive dichotomy based network‐centric cellular to Wi‐Fi offloading. Issue 3 (1st February 2017)

• Record Type: Journal Article
• Authors: Venkataraman, Hrishikesh; Dutta, Amit; Joshi, Avinash
• Is Part Of: IET communications. Volume 11:Issue 3(2017)
• Page Start: 318
• Page End: 325
• Publication Date: 2017-02-01
• Subjects: cellular radio -- wireless LAN -- telecommunication traffic -- quality of experience -- computational complexity -- trees (mathematics); add‐net -- adaptive dichotomy based network‐centric cellular to Wi‐Fi offloading -- Wi‐Fi hotspot -- subscriber visibility -- quality of experience -- QoE -- network‐centric near‐real‐time mechanism -- nondeterministic problem -- adaptive dichotomic classification based mechanism -- computational complexity -- binary tree -- subscriber profile intelligent selection; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2015.0958
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Over last 4–5 years, there has been an exponential increase in the amount of traffic transmitted over cellular network. Importantly, with humongous increase in the Wi‐Fi hotspots across many places, subscribers tend to manually switch from cellular to Wi‐Fi network. However, in this process, the operator loses the visibility of subscribers, and is not able to control the congestion in network, and importantly, is not able to provide a guaranteed quality of experience (QoE) to the subscribers. In this study, a network‐centric near‐real‐time mechanism is proposed for maintaining QoE among the subscribers but is found to be a non‐deterministic problem. Importantly, an adaptive dichotomic classification based mechanism is proposed and investigated for offloading the cellular subscribers to Wi‐Fi network, while keeping the computational complexity to less than O (log( n )), where n is the number of nodes in a binary tree. Further, an algorithm is proposed for intelligent selection of subscriber profile that would enable faster completion of the offloading process. An extensive simulation of the proposed algorithm and comparison with state‐of‐the‐art mechanisms reveal up to seven time reduction in computational time; with additional performance increase occurring with increasing number of subscribers.