8,301 research outputs found

    On Autonomic HPC Clouds

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    Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.The long tail of science using HPC facilities is looking nowadays to instant available HPC Clouds as a viable alternative to the long waiting queues of supercomputing centers. While the name of HPC Cloud is suggesting a Cloud service, the current HPC-as-a-Service is mainly an offer of bar metal, better named cluster-on-demand. The elasticity and virtualization benefits of the Clouds are not exploited by HPC-as-a-Service. In this paper we discuss how the HPC Cloud offer can be improved from a particular point of view, of automation. After a reminder of the characteristics of the Autonomic Cloud, we project the requirements and expectations to what we name Autonomic HPC Clouds. Finally, we point towards the expected results of the latest research and development activities related to the topics that were identified.The work related to Autonomic HPC Clouds is supported by the European Commission under grant agreement H2020-6643946 (CloudLightning). The CLoudLightning project proposal was prepared by eight partner institutions, three of them as earlier partners in the COST Action IC1305 NESUS, benefiting from its inputs for the proposal. The section related to Autonomic Clouds is supported by the Romanian UEFISCDI under grant agreement PN-II-ID-PCE-2011- 3-0260 (AMICAS)

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    Atomicity and non-anonymity in population-like games for the energy efficiency of hybrid-power HetNets

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    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, the user–base station (BS) association problem is addressed to reduce grid consumption in heterogeneous cellular networks (HetNets) powered by hybrid energy sources (grid and renewable energy). The paper proposes a novel distributed control scheme inspired by population games and designed considering both atomicity and non-anonymity – i.e., describing the individual decisions of each agent. The controller performance is considered from an energy–efficiency perspective, which requires the guarantee of appropriate qualityof-service (QoS) levels according to renewable energy availability. The efficiency of the proposed scheme is compared with other heuristic and optimal alternatives in two simulation scenarios. Simulation results show that the proposed approach inspired by population games reduces grid consumption by 12% when compared to the traditional best-signal-level association policy.Peer ReviewedPostprint (author's final draft

    Dynamic selection of redundant web services

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    In the domain of Web Services, it is not uncommon to find redundant services that provide functionalities to the clients. Services with the same functionality can be clustered into a group of redundant services. Respectively, if a service offers different functionalities, it belongs to more than one group. Having various Web Services that are able to handle the client's request suggests the necessity of a mechanism that selects the most appropriate Web Service at a given moment of time. This thesis presents an approach, Virtual Web Services Layer, for dynamic service selection based on virtualization on the server side. It helps managing redundant services in a transparent manner as well as allows adding services to the system at run-time. In addition, the layer assures a level of security since the consumers do not have direct access to the Web Services. Several selection techniques are applied to increase the performance of the system in terms of load-balancing, dependability, or execution time. The results of the experiments show which selection techniques are appropriate when different QoS criteria of the services are known and how the correctness of this information influences on the decision-making process

    Atomicity and non-anonymity in population-like games for the energy efficiency of hybrid-power HetNets

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    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, the user–base station (BS) association problem is addressed to reduce grid consumption in heterogeneous cellular networks (HetNets) powered by hybrid energy sources (grid and renewable energy). The paper proposes a novel distributed control scheme inspired by population games and designed considering both atomicity and non-anonymity – i.e., describing the individual decisions of each agent. The controller performance is considered from an energy–efficiency perspective, which requires the guarantee of appropriate qualityof-service (QoS) levels according to renewable energy availability. The efficiency of the proposed scheme is compared with other heuristic and optimal alternatives in two simulation scenarios. Simulation results show that the proposed approach inspired by population games reduces grid consumption by 12% when compared to the traditional best-signal-level association policy.Peer ReviewedPostprint (author's final draft
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