Enhancing Mobile Data Offloading With In-Network Caching

Enhancing Mobile Data Offloading With In-Network Caching

Xu Zhang (Xi'an University of Technology, China), Yue Cao (University of Northumbria, UK), Linyu Peng (Waseda University, Japan) and Junhuai Li (Xian University of Technology, China)
Copyright: © 2019 |Pages: 21
DOI: 10.4018/978-1-5225-7570-2.ch010

Abstract

This chapter discusses the most recent solutions for accelerating mobile data delivery, focusing on the different issues for achieving this goal. These issues include the efficiency of mobile data offloading and in-network caching. By characterizing different offloading options from the aspect offloading efficiency, dynamically offloading cellular traffic onto cost-effective options is able to achieve great performance gains. On the other hand, with concerns on tightly coupled dependency on original data sources, mobile users could easily suffer from the scarcity of content object resources. Researchers further account for the possibility of decoupling content availability dependency from original content sources. And a key enabling factor could be the recently emerged technology (i.e., in-network caching) whereby the emerging information-centric networking (ICN) performs its critical functionalities. Coupling ICN with mobile cellular network could be an attractive solution in order to resolve the tension between the tremendous growth of mobile content traffic and backhaul bottleneck.
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2. Mobile Data Offloading Open Research Issues

Cellular traffic data has been observed a dramatic increase globally. The proliferation of mobile device (e.g., smartphones, tablets) plays a key role in such massive growth, largely driven by the popularity of online social networking services. In fact, end users are more than ever in huger for data-intensive applications, e.g., video streaming, etc. However, it is commonly believed that the cellular capacity is being overloaded already and advanced cellular technologies (4G, LTE) cannot scale up enough to satisfy such appetite (Cisco, 2017).

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