87,814 research outputs found

    Big Data Caching for Networking: Moving from Cloud to Edge

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    In order to cope with the relentless data tsunami in 5G5G wireless networks, current approaches such as acquiring new spectrum, deploying more base stations (BSs) and increasing nodes in mobile packet core networks are becoming ineffective in terms of scalability, cost and flexibility. In this regard, context-aware 55G networks with edge/cloud computing and exploitation of \emph{big data} analytics can yield significant gains to mobile operators. In this article, proactive content caching in 55G wireless networks is investigated in which a big data-enabled architecture is proposed. In this practical architecture, vast amount of data is harnessed for content popularity estimation and strategic contents are cached at the BSs to achieve higher users' satisfaction and backhaul offloading. To validate the proposed solution, we consider a real-world case study where several hours of mobile data traffic is collected from a major telecom operator in Turkey and a big data-enabled analysis is carried out leveraging tools from machine learning. Based on the available information and storage capacity, numerical studies show that several gains are achieved both in terms of users' satisfaction and backhaul offloading. For example, in the case of 1616 BSs with 30%30\% of content ratings and 1313 Gbyte of storage size (78%78\% of total library size), proactive caching yields 100%100\% of users' satisfaction and offloads 98%98\% of the backhaul.Comment: accepted for publication in IEEE Communications Magazine, Special Issue on Communications, Caching, and Computing for Content-Centric Mobile Network

    European Law and Regulation of Mobile Net Neutrality

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    Mobile is a rapidly growing and potentially major element of the future Internet, and its environment cannot be sensibly considered in isolation from fixed networks [2]. A note on terminology: Europe uses the term Mobile Network Operators (MNOs) while the United States uses 'wireless' Internet Service Providers (ISPs) [3]. 'Wireless' is somewhat more open in the United States. In Europe, mobile has always made special pleading for forms of self-regulation, as we will see. The article introduces mobile broadband, then considers net neutrality in the fixed environment including the new laws passed in November 2009 in the European Parliament, before considering the mobile net neutrality debate, the degree of price control regulation exerted on European mobiles and the MNOs' vigorous rear-guard anti-regulation defence. Finally, I look at the effects of this regulatory asymmetry and whether MNO calls for mobile to be treated differently from other ISPs can be justified. I conclude by examining what the effect of price and content control on mobile is likely to be for incentives for fixed ISPs and produce a result that I describe as the 'fixed' strategy

    Will SDN be part of 5G?

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    For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

    Software for Wearable Devices: Challenges and Opportunities

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    Wearable devices are a new form of mobile computer system that provides exclusive and user-personalized services. Wearable devices bring new issues and challenges to computer science and technology. This paper summarizes the development process and the categories of wearable devices. In addition, we present new key issues arising in aspects of wearable devices, including operating systems, database management system, network communication protocol, application development platform, privacy and security, energy consumption, human-computer interaction, software engineering, and big data.Comment: 6 pages, 1 figure, for Compsac 201

    IEEE Access special section editorial: Artificial intelligence enabled networking

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    With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)
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