18,762 research outputs found

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

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    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

    Content placement in 5G‐enabled edge/core data center networks resilient to link cut attacks

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    High throughput, resilience, and low latency requirements drive the development of 5G-enabled content delivery networks (CDNs) which combine core data centers (cDCs) with edge data centers (eDCs) that cache the most popular content closer to the end users for traffic load and latency reduction. Deployed over the existing optical network infrastructure, CDNs are vulnerable to link cut attacks aimed at disrupting the overlay services. Planning a CDN to balance the stringent service requirements and increase resilience to attacks in a cost-efficient way entails solving the content placement problem (CPP) across the cDCs and eDCs. This article proposes a framework for finding Pareto-optimal solutions with minimal user-to-content distance and maximal robustness to targeted link cuts, under a defined budget. We formulate two optimization problems as integer linear programming (ILP) models. The first, denoted as K-best CPP with minimal distance (K-CPP-minD), identifies the eDC/cDC placement solutions with minimal user-to-content distance. The second performs critical link set detection to evaluate the resilience of the K-CPP-minD solutions to targeted fiber cuts. Extensive simulations verify that the eDC/cDC selection obtained by our models improves network resilience to link cut attacks without adversely affecting the user-to-content distances or the core network traffic mitigation benefits.publishe

    Revisiting core traffic growth in the presence of expanding CDNs

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    Traffic growth forecasts announce a dramatic future for core networks, struggling to keep the pace of traffic augmentation. Internet traffic growth primarily stems from the proliferation of cloud services and the massive amounts of data distributed by the content delivery networks (CDNs) hosting these services. In this paper, we investigate the evolution of core traffic in the presence of growing CDNs. Expanding the capacities of existing data centers (DCs) directly translates the forecasted compound-annual-growth-rate (CAGR) of user traffic to the CAGR of carried core link traffic. On the other hand, expanding CDNs by building new geographically dispersed DCs can significantly reduce the predicted core traffic growth rates by placing content closer to the users. However, reducing DC-to-user traffic by building new DCs comes at a trade-off with increasing inter-DC content synchronization traffic. Thus, the resulting overall core traffic growth will depend on the types of services supported and their associated synchronization requirements. In this paper, we present a long-term evolution study to assess the implications of different CDN expansion strategies on core network traffic growth considering a mix of services in proportions and growth rates corresponding to well-known traffic forecasts. Our simulations indicate that CDNs may have significant incentive to build more DCs, depending on the service types they offer, and that current alarming traffic predictions may be somewhat overestimated in core networks in the presence of expanding CDNs. (C) 2019 The Authors. Published by Elsevier B.V.The research leading to these results has received funding from the European Commission for the H2020-ICT-2016-2 METRO-HAUL project (G.A. 761727) and it has been partially funded by the Spanish national project ONOFRE-2(TEC2017-84423-C3-1-P, MINECO/AEI/FEDER, UE)

    Intraoperative detection of blood vessels with an imaging needle during neurosurgery in humans

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    Intracranial hemorrhage can be a devastating complication associated with needle biopsies of the brain. Hemorrhage can occur to vessels located adjacent to the biopsy needle as tissue is aspirated into the needle and removed. No intraoperative technology exists to reliably identify blood vessels that are at risk of damage. To address this problem, we developed an “imaging needle” that can visualize nearby blood vessels in real time. The imaging needle contains a miniaturized optical coherence tomography probe that allows differentiation of blood flow and tissue. In 11 patients, we were able to intraoperatively detect blood vessels (diameter, \u3e500 μm) with a sensitivity of 91.2% and a specificity of 97.7%. This is the first reported use of an optical coherence tomography needle probe in human brain in vivo. These results suggest that imaging needles may serve as a valuable tool in a range of neurosurgical needle interventions

    Wireless Communications in the Era of Big Data

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    The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

    Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

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    The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

    Impact of the Net Neutrality Repeal on Communication Networks

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    Network neutrality is the principle of treating equally all Internet traffic regardless of its source, destination, content, application or other related distinguishing metrics. Under net neutrality, Internet service providers (ISPs) are compelled to charge all content providers (CPs) the same per Gbps rate despite the growing profit achieved by CPs. In this paper, we study the impact of the repeal of net neutrality on communication networks by developing a techno-economic Mixed Integer Linear Programming (MILP) model to maximize the potential profit ISPs can achieve by offering their services to CPs. We consider an ISP that offers CPs different classes of service representing typical video content qualities. The MILP model maximizes the ISP profit by optimizing the prices of the different classes according to the users’ demand sensitivity to the change in price, referred to as Price Elasticity of Demand (PED). We analyze how PED impacts the profit in different CP delivery scenarios in cloud-fog architectures. The results show that the repeal of net neutrality can potentially increase ISPs profit by a factor of 8 with a pricing scheme that discriminates against data intensive content. Also, the repeal of net neutrality positively impacts the network energy efficiency by reducing the core network power consumption by 55% as a result of suppressing data intensive content compared to the net neutrality scenario
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