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A Collaborative Framework for In-network Video Caching in Mobile Networks

TLDR
In this paper, a dynamic collaborative video caching framework is proposed to improve the end-user experience and reduce the Internet access cost for mobile network operators by decomposing the caching problem into a content placement subproblem and a source selection subproblem.
Abstract
Due to explosive growth of online video content in mobile wireless networks, in-network caching is becoming increasingly important to improve the end-user experience and reduce the Internet access cost for mobile network operators. However, caching is a difficult problem due to the very large number of online videos and video requests,limited capacity of caching nodes, and limited bandwidth of in-network links. Existing solutions that rely on static configurations and average request arrival rates are insufficient to handle dynamic request patterns effectively. In this paper, we propose a dynamic collaborative video caching framework to be deployed in mobile networks. We decompose the caching problem into a content placement subproblem and a source-selection subproblem. We then develop SRS (System capacity Reservation Strategy) to solve the content placement subproblem, and LinkShare, an adaptive traffic-aware algorithm to solve the source selection subproblem. Our framework supports congestion avoidance and allows merging multiple requests for the same video into one request. We carry extensive simulations to validate the proposed schemes. Simulation results show that our SRS algorithm achieves performance within 1-3% of the optimal values and LinkShare significantly outperforms existing solutions.

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Citations
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Journal ArticleDOI

On the Complexity of Optimal Content Placement in Hierarchical Caching Networks

TL;DR: This paper study's goal is to reduce the server load by serving as many requests as possible by the caches in multiple-level hierarchical caching networks, and develops an algorithm achieving a provably better approximation ratio than the best-known counterparts.
Proceedings ArticleDOI

Achieving near-optimal traffic engineering in hybrid Software Defined Networks

TL;DR: This paper investigates traffic engineering (TE) in H-SDN, where the SDN controller strategically routes SDN traffic so as to optimize the TE performance over all network links shared with uncontrollable conventional traffic.
Journal ArticleDOI

Congestion Avoidance and Load Balancing in Content Placement and Request Redirection for Mobile CDN

TL;DR: This work develops an on-line algorithm to efficiently decide content placement and request redirection for the BS-based mobile CDN, and employs the stochastic optimization model to minimize the long-term time-average transmission cost under network stability constraints.
Journal ArticleDOI

Optimizing Video Request Routing in Mobile Networks with Built-in Content Caching

TL;DR: This work proposes a hop-by-hop routing protocol, which implements the optimization solutions by generating a set of flow-splitting and routing decisions for each router/caching node, and significantly outperform existing routing schemes under various system settings.
Proceedings ArticleDOI

EPCache: In-network video caching for LTE core networks

TL;DR: This work proposes EPCache, a novel in-network video caching framework for LTE core networks, which addresses the following key questions: what to cache, i.e., how to select in-system video library; how to cache; and how to distribute the selected video library.
References
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Traffic Engineering

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