1,463 research outputs found

    Introducing a Data Sliding Mechanism for Cooperative Caching in Manycore Architectures

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    International audienceIn this paper, we propose a new cooperative caching method improving the cache miss rate for manycore micro- architec- tures. The work is motivated by some limitations of recent adaptive cooperative caching proposals. Elastic Cooperative caching (ECC), is a dynamic memory partitioning mechanism that allows sharing cache across cooperative nodes according to the application behavior. However, it is mainly limited with cache eviction rate in case of highly stressed neighbor- hood. Another system, the adaptive Set-Granular Cooperative Caching (ASCC), is based on finer set-based mechanisms for a better adaptability. However, heavy localized cache loads are not efficiently managed. In such a context, we propose a cooperative caching strategy that consists in sliding data through closer neighbors. When a cache receives a storing request of a neighbor's private block, it spills the least recently used private data to a close neighbor. Thus, solicited saturated nodes slide local blocks to their respective neighbors to always provide free cache space. We also propose a new Priority- based Data Replacement policy to decide efficiently which blocks should be spilled, and a new mechanism to choose host destination called Best Neighbor selector. The first analytic performance evaluation shows that the proposed cache management policies reduce by half the average global communication rate. As frequent accesses are focused in the neighboring zones, it efficiently improves on-Chip traffic. Finally, our evaluation shows that cache miss rate is en- hanced: each tile keeps the most frequently accessed data 1- Hop close to it, instead of ejecting them Off-Chip. Proposed techniques notably reduce the cache miss rate in case of high solicitation of the cooperative zone, as it is shown in the performed experiments

    SymbioCity: Smart Cities for Smarter Networks

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    The "Smart City" (SC) concept revolves around the idea of embodying cutting-edge ICT solutions in the very fabric of future cities, in order to offer new and better services to citizens while lowering the city management costs, both in monetary, social, and environmental terms. In this framework, communication technologies are perceived as subservient to the SC services, providing the means to collect and process the data needed to make the services function. In this paper, we propose a new vision in which technology and SC services are designed to take advantage of each other in a symbiotic manner. According to this new paradigm, which we call "SymbioCity", SC services can indeed be exploited to improve the performance of the same communication systems that provide them with data. Suggestive examples of this symbiotic ecosystem are discussed in the paper. The dissertation is then substantiated in a proof-of-concept case study, where we show how the traffic monitoring service provided by the London Smart City initiative can be used to predict the density of users in a certain zone and optimize the cellular service in that area.Comment: 14 pages, submitted for publication to ETT Transactions on Emerging Telecommunications Technologie

    Ad-hoc Stream Adaptive Protocol

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    With the growing market of smart-phones, sophisticated applications that do extensive computation are common on mobile platform; and with consumers’ high expectation of technologies to stay connected on the go, academic researchers and industries have been making efforts to find ways to stream multimedia contents to mobile devices. However, the restricted wireless channel bandwidth, unstable nature of wireless channels, and unpredictable nature of mobility, has been the major road block for wireless streaming advance forward. In this paper, various recent studies on mobility and P2P system proposal are explained and analyzed, and propose a new design based on existing P2P systems, aimed to solve the wireless and mobility issues

    Priority-Based Content Delivery in the Internet of Vehicles through Named Data Networking

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    Named Data Networking (NDN) has been recently proposed as a prominent solution for content delivery in the Internet of Vehicles (IoV), where cars equipped with a variety of wireless communication technologies exchange information aimed to support safety, traffic efficiency, monitoring and infotainment applications. The main NDN tenets, i.e., name-based communication and in-network caching, perfectly fit the demands of time- and spatially-relevant content requested by vehicles regardless of their provenance. However, existing vehicular NDN solutions have not been targeted to wisely ensure prioritized traffic treatment based on the specific needs of heterogeneous IoV content types. In this work, we propose a holistic NDN solution that, according to the demands of data traffic codified in NDN content names, dynamically shapes the NDN forwarding decisions to ensure the appropriate prioritization. Specifically, our proposal first selects the outgoing interface(s) (i.e., 802.11, LTE) for NDN packets and then properly tunes the timing of the actual transmissions. Simulation results show that the proposed enhancements succeed in achieving differentiated traffic treatment, while keeping traffic load under control

    Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

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    Data traffic demand increases at a very fast pace in edge networking environments, with strict requisites on latency and throughput. To fulfil these requirements, among others, this paper proposes a fog storage system that incorporates mobile nodes as content providers. This fog storage system has a hybrid design because it does not only bring data closer to edge consumers but, as a novelty, it also incorporates in the system other relevant functional aspects. These novel aspects are the user data demand, the energy consumption, and the node distance. In this way, the decision whether to replicate data is based on an original edge service managed by an adaptive distance metric for node clustering. The adaptive distance is evaluated from several important system parameters like, distance from consumer to the data storage location, spatio-temporal data popularity, and the autonomy of each battery-powered node. Testbed results evidence that this flexible cluster-based proposal offers a more responsive data access to consumers, reduces core traffic, and depletes in a fair way the available battery energy of edge nodes.info:eu-repo/semantics/acceptedVersio
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