388 research outputs found

    Energy-efficient caching for Video-on-Demand in Fixed-Mobile Convergent networks

    Get PDF
    The success of novel bandwidth-consuming multimedia services such as Video-on-Demand (VoD) is leading to a tremendous growth of the Internet traffic. Content caching can help to mitigate such uncontrolled growth by storing video content closer to the users in core, metro and access network nodes. So far, metro and especially access networks supporting mobile and fixed users have evolved independently, leveraging logically (and often also physically) separate infrastructures; this means that mobile users cannot access caches placed in the fixed access network (and vice-versa), even if they are geographically close to them, and energy consumption implications of such undesired effect must be investigated. We define an optimization problem modeling an energy-efficient placement of caches in core, metro and fixed/mobile access nodes of the network. Then, we show how the evolution towards a Fixed-Mobile Converged metro/access network, where fixed and mobile users can share caches, can reduce the energy consumed for VoD content delivery

    Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks

    Get PDF
    Caching and multicasting are two promising methods to support massive content delivery in multi-tier wireless networks. In this paper, we consider a random caching and multicasting scheme with caching distributions in the two tiers as design parameters, to achieve efficient content dissemination in a two-tier large-scale cache-enabled wireless multicasting network. First, we derive tractable expressions for the successful transmission probabilities in the general region as well as the high SNR and high user density region, respectively, utilizing tools from stochastic geometry. Then, for the case of a single operator for the two tiers, we formulate the optimal joint caching design problem to maximize the successful transmission probability in the asymptotic region, which is nonconvex in general. By using the block successive approximate optimization technique, we develop an iterative algorithm, which is shown to converge to a stationary point. Next, for the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region. We show that the game has a unique Nash equilibrium (NE) and develop an iterative algorithm, which is shown to converge to the NE under a mild condition. Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.Comment: 30 pages, 6 pages, submitted to IEEE GLOBECOM 2017 and IEEE Trans. Commo

    An Optimized Multi-Layer Resource Management in Mobile Edge Computing Networks: A Joint Computation Offloading and Caching Solution

    Full text link
    Nowadays, data caching is being used as a high-speed data storage layer in mobile edge computing networks employing flow control methodologies at an exponential rate. This study shows how to discover the best architecture for backhaul networks with caching capability using a distributed offloading technique. This article used a continuous power flow analysis to achieve the optimum load constraints, wherein the power of macro base stations with various caching capacities is supplied by either an intelligent grid network or renewable energy systems. This work proposes ubiquitous connectivity between users at the cell edge and offloading the macro cells so as to provide features the macro cell itself cannot cope with, such as extreme changes in the required user data rate and energy efficiency. The offloading framework is then reformed into a neural weighted framework that considers convergence and Lyapunov instability requirements of mobile-edge computing under Karush Kuhn Tucker optimization restrictions in order to get accurate solutions. The cell-layer performance is analyzed in the boundary and in the center point of the cells. The analytical and simulation results show that the suggested method outperforms other energy-saving techniques. Also, compared to other solutions studied in the literature, the proposed approach shows a two to three times increase in both the throughput of the cell edge users and the aggregate throughput per cluster

    Caching Placement Strategies for Dynamic Content Delivery in Metro Area Networks

    Get PDF
    Video-on-Demand (VoD) traffic explosion has been one of the main driving forces behind the recent Internet evolution from a traditional connection-centric architecture towards the new content-centric paradigm. To cope with this evolution, caching of VoD contents closer to the users in core, metro and even metro-access optical network equipment is regarded to be a prime solution that could help mitigating this traffic growth. However, the optimal caches placement and dimensioning is not univocal, especially in the context of a dynamic network, as it depends on various parameters, such as network topology, users behavior and content popularity. In this paper, we focus on a dynamic VoD content delivery scenario in a metropolitan network implementing different caching strategies. We evaluate the performance of the various caching strategies in terms of network-capacity occupation showing the savings in resource occupation in each of the network segments. We also evaluate the effect of the distribution of the storage capacity on the overall average number of hops of all requests. The obtained numerical results show that, in general, a significant amount of network resources can be saved by enabling content caching near to end-users. Moreover, we show that blindly providing caching capability in access nodes may result unnecessary, whereas a balanced storage distribution between access and metro network segments provides the best performance

    The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve

    Full text link
    With the introduction of caching capabilities into small cell networks (SCNs), new backaul management mechanisms need to be developed to prevent the predicted files that are downloaded by the at the small base stations (SBSs) to be cached from jeopardizing the urgent requests that need to be served via the backhaul. Moreover, these mechanisms must account for the heterogeneity of the backhaul that will be encompassing both wireless backhaul links at various frequency bands and a wired backhaul component. In this paper, the heterogeneous backhaul management problem is formulated as a minority game in which each SBS has to define the number of predicted files to download, without affecting the required transmission rate of the current requests. For the formulated game, it is shown that a unique fair proper mixed Nash equilibrium (PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates the desired PMNE. Simulation results show that the performance of the proposed approach can be close to that of the ideal optimal algorithm while it outperforms a centralized greedy approach in terms of the amount of data that is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication
    • …
    corecore