76 research outputs found

    A Swiss Army Knife for Online Caching in Small Cell Networks

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    We consider a dense cellular network, in which a limited-size cache is available at every base station (BS). Coordinating content allocation across the different caches can lead to significant performance gains, but is a difficult problem even when full information about the network and the request process is available. In this paper we present qLRU-Δ, a general-purpose online caching policy that can be tailored to optimize different performance metrics also in presence of coordinated multipoint transmission techniques. The policy requires neither direct communication among BSs, nor a priori knowledge of content popularity and, under stationary request processes, has provable performance guarantees

    Similarity Caching: Theory and Algorithms

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    International audienceThis paper focuses on similarity caching systems, in which a user request for an object o that is not in the cache can be (partially) satisfied by a similar stored object o , at the cost of a loss of user utility. Similarity caching systems can be effectively employed in several application areas, like multimedia retrieval, recommender systems, genome study, and machine learning training/serving. However, despite their relevance, the behavior of such systems is far from being well understood. In this paper, we provide a first comprehensive analysis of similarity caching in the offline, adversarial, and stochastic settings. We show that similarity caching raises significant new challenges, for which we propose the first dynamic policies with some optimality guarantees. We evaluate the performance of our schemes under both synthetic and real request traces

    A\c{C}AI: Ascent Similarity Caching with Approximate Indexes

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    Similarity search is a key operation in multimedia retrieval systems and recommender systems, and it will play an important role also for future machine learning and augmented reality applications. When these systems need to serve large objects with tight delay constraints, edge servers close to the end-user can operate as similarity caches to speed up the retrieval. In this paper we present A\c{C}AI, a new similarity caching policy which improves on the state of the art by using (i) an (approximate) index for the whole catalog to decide which objects to serve locally and which to retrieve from the remote server, and (ii) a mirror ascent algorithm to update the set of local objects with strong guarantees even when the request process does not exhibit any statistical regularity

    On distributed mobile edge computing

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    Mobile Cloud Computing (MCC) has been proposed to offload the workloads of mobile applications from mobile devices to the cloud in order to not only reduce energy consumption of mobile devices but also accelerate the execution of mobile applications. Owing to the long End-to-End (E2E) delay between mobile devices and the cloud, offloading the workloads of many interactive mobile applications to the cloud may not be suitable. That is, these mobile applications require a huge amount of computing resources to process their workloads as well as a low E2E delay between mobile devices and computing resources, which cannot be satisfied by the current MCC technology. In order to reduce the E2E delay, a novel cloudlet network architecture is proposed to bring the computing and storage resources from the remote cloud to the mobile edge. In the cloudlet network, each mobile user is associated with a specific Avatar (i.e., a dedicated Virtual Machine (VM) providing computing and storage resources to its mobile user) in the nearby cloudlet via its associated Base Station (BS). Thus, mobile users can offload their workloads to their Avatars with low E2E delay (i.e., one wireless hop). However, mobile users may roam among BSs in the mobile network, and so the E2E delay between mobile users and their Avatars may become worse if the Avatars remain in their original cloudlets. Thus, Avatar handoff is proposed to migrate an Avatar from one cloudlet into another to reduce the E2E delay between the Avatar and its mobile user. The LatEncy aware Avatar handDoff (LEAD) algorithm is designed to determine the location of each mobile user\u27s Avatar in each time slot in order to minimize the average E2E delay among all the mobile users and their Avatars. The performance of LEAD is demonstrated via extensive simulations. The cloudlet network architecture not only facilitates mobile users in offloading their computational tasks but also empowers Internet of Things (IoT). Popular IoT resources are proposed to be cached in nearby brokers, which are considered as application layer middleware nodes hosted by cloudlets in the cloudlet network, to reduce the energy consumption of servers. In addition, an Energy Aware and latency guaranteed dynamic reSourcE caching (EASE) strategy is proposed to enable each broker to cache suitable popular resources such that the energy consumption from the servers is minimized and the average delay of delivering the contents of the resources to the corresponding clients is guaranteed. The performance of EASE is demonstrated via extensive simulations. The future work comprises two parts. First, caching popular IoT resources in nearby brokers may incur unbalanced traffic loads among brokers, thus increasing the average delay of delivering the contents of the resources. Thus, how to balance the traffic loads among brokers to speed up IoT content delivery process requires further investigation. Second, drone assisted mobile access network architecture will be briefly investigated to accelerate communications between mobile users and their Avatars

    Core Network Design of Software Defined Radio Testbed

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    The 4th generation of cellular system (LTE) does not inherit the traditional voice (circuit-switched) capabilities from its predecessors. Instead it relies on its high speed packet-switched core network with IMS (IP Multimedia Subsystem) for voice capabilities. Even though there are temporary solutions available until LTE gets its full deployment and coverage, operators are looking for a long term solution known as VoIMS which uses VoIP with SIP protocol for voice in the LTE network (VoLTE) through the IMS domain. The scope of this thesis work is to design, implement and verify the working of the core network for an LTE type software defined radio (SDR) testbed which is able to initiate, maintain and terminate voice and data connections. First step in this regard is to search and select the tools, programs and technologies that fulfil the network requirement in terms of network performance and user satisfaction. Next is to build, configure and verify the network operations of the designed network. As SDRs are used for testing purposes, the core network is also designed in correspondence to that, i.e., it is a test (lab) core network with configurations that are simple to implement and do not require coding implementation. The core network makes use of the virtualization technology and is realized with the help of open-source solutions, i.e., protocols and technologies that are customizable as required and does not require licensing for their use. These functionalities are implemented with the help of OpenSIPS, an open-source SIP server, DHCP and DNS servers. Demonstration of the core network verifies that successful voice and video call can be made between registered users on two different networks, running VoIP client software on different operating system platforms. The core network provides features such as voice, video, instant messaging, presence, dynamic IP assignment, IP address to name resolution and mobility
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