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Mobility-aware caching for content-centric wireless networks: modeling and methodology

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TLDR
This article presents a general framework for mobility-aware caching in CCWNs, and key properties of user mobility patterns that are useful for content caching are first identified, and then different design methodologies for mobility -aware caching are proposed.
Abstract
As mobile services are shifting from connection- centric communications to content-centric communications, content-centric wireless networking emerges as a promising paradigm to evolve the current network architecture Caching popular content at the wireless edge, including base stations and user terminals, provides an effective approach to alleviate the heavy burden on backhaul links, as well as lower delays and deployment costs In contrast to wired networks, a unique characteristic of content-centric wireless networks (CCWNs) is the mobility of mobile users While it has rarely been considered by existing works on caching design, user mobility contains various helpful side information that can be exploited to improve caching efficiency at both BSs and user terminals In this article, we present a general framework for mobility-aware caching in CCWNs Key properties of user mobility patterns that are useful for content caching are first identified, and then different design methodologies for mobility-aware caching are proposed Moreover, two design examples are provided to illustrate the proposed framework in detail, and interesting future research directions are identified

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Citations
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A Survey on Mobile Edge Computing: The Communication Perspective

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
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A Survey on Mobile Edge Computing: The Communication Perspective

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
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A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

TL;DR: This survey makes an exhaustive review on the state-of-the-art research efforts on mobile edge networks, including definition, architecture, and advantages, and presents a comprehensive survey of issues on computing, caching, and communication techniques at the network edge.
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A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms: Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet

TL;DR: A comprehensive survey of emerging computing paradigms from the perspective of end-edge-cloud orchestration is presented to discuss state-of-the-art research in terms of computation offloading, caching, security, and privacy.
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Mobility-Aware Edge Caching and Computing in Vehicle Networks: A Deep Reinforcement Learning

TL;DR: A deep reinforcement learning with the multi-timescale framework to tackle the grand challenges of the vehicular networks and proposes the mobility-aware reward estimation for the large timescale model to mitigate the complexity due to the large action space.
References
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Understanding individual human mobility patterns

TL;DR: In this article, the authors study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period and find that the individual travel patterns collapse into a single spatial probability distribution, indicating that humans follow simple reproducible patterns.
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Fundamental Limits of Caching

TL;DR: This paper proposes a novel coded caching scheme that exploits both local and global caching gains, leading to a multiplicative improvement in the peak rate compared with previously known schemes, and argues that the performance of the proposed scheme is within a constant factor of the information-theoretic optimum for all values of the problem parameters.
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FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers

TL;DR: This work shows that the uncoded optimum file assignment is NP-hard, and develops a greedy strategy that is provably within a factor 2 of the optimum, and provides an efficient algorithm achieving a provably better approximation ratio of 1-1/d d, where d is the maximum number of helpers a user can be connected to.
Journal ArticleDOI

Impact of Human Mobility on Opportunistic Forwarding Algorithms

TL;DR: A simplified model based on the renewal theory is used to study how the parameters of the distribution impact the performance in terms of the delivery delay of well-founded opportunistic forwarding algorithms in the context of human-carried devices.
Journal ArticleDOI

Stochastic properties of the random waypoint mobility model

TL;DR: The random waypoint model is a commonly used mobility model for simulations of wireless communication networks and some of its fundamental stochastic properties are investigated, including the transition length and time of a mobile node between two waypoints, the spatial distribution of nodes, and the direction angle at the beginning of a movement transition.
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