30,765 research outputs found
Policy-based techniques for self-managing parallel applications
This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined
An Energy Sharing Game with Generalized Demand Bidding: Model and Properties
This paper proposes a novel energy sharing mechanism for prosumers who can
produce and consume. Different from most existing works, the role of individual
prosumer as a seller or buyer in our model is endogenously determined. Several
desirable properties of the proposed mechanism are proved based on a
generalized game-theoretic model. We show that the Nash equilibrium exists and
is the unique solution of an equivalent convex optimization problem. The
sharing price at the Nash equilibrium equals to the average marginal disutility
of all prosumers. We also prove that every prosumer has the incentive to
participate in the sharing market, and prosumers' total cost decreases with
increasing absolute value of price sensitivity. Furthermore, the Nash
equilibrium approaches the social optimal as the number of prosumers grows, and
competition can improve social welfare.Comment: 16 pages, 7 figure
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
Distributed Apportioning in a Power Network for providing Demand Response Services
Greater penetration of Distributed Energy Resources (DERs) in power networks
requires coordination strategies that allow for self-adjustment of
contributions in a network of DERs, owing to variability in generation and
demand. In this article, a distributed scheme is proposed that enables a DER in
a network to arrive at viable power reference commands that satisfies the DERs
local constraints on its generation and loads it has to service, while, the
aggregated behavior of multiple DERs in the network and their respective loads
meet the ancillary services demanded by the grid. The Net-load Management
system for a single unit is referred to as the Local Inverter System (LIS) in
this article . A distinguishing feature of the proposed consensus based
solution is the distributed finite time termination of the algorithm that
allows each LIS unit in the network to determine power reference commands in
the presence of communication delays in a distributed manner. The proposed
scheme allows prioritization of Renewable Energy Sources (RES) in the network
and also enables auto-adjustment of contributions from LIS units with lower
priority resources (non-RES). The methods are validated using
hardware-in-the-loop simulations with Raspberry PI devices as distributed
control units, implementing the proposed distributed algorithm and responsible
for determining and dispatching realtime power reference commands to simulated
power electronics interface emulating LIS units for demand response.Comment: 7 pages, 11 Figures, IEEE International Conference on Smart Grid
Communication
Adaptive structured parallelism for computational grids
Algorithmic skeletons abstract commonly-used patterns of parallel computation, communication, and interaction. They provide top-down design composition and control inheritance throughout the whole structure. Parallel programs are expressed by interweaving parameterised skeletons analogously to the way sequential structured programs are constructed.
This design paradigm, known as structured parallelism, provides a high-level parallel programming method which allows the abstract description of programs and fosters portability. That is to say, structured parallelism requires the description of the algorithm rather than its implementation, providing a clear and consistent meaning across platforms while their associated structure depends on the particular implementation. By decoupling the structure from the meaning of a parallel program, it benefits entirely from any performance improvements in the systems infrastructure
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Resilient network dimensioning for optical grid/clouds using relocation
In this paper we address the problem of dimensioning infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We will provide an overview of our work in this area, and in particular focus on how to design the resulting grid/cloud to be resilient against network link and/or server site failures. To this end, we will exploit relocation: under failure conditions, a request may be sent to an alternate destination than the one under failure-free conditions. We will provide a comprehensive overview of related work in this area, and focus in some detail on our own most recent work. The latter comprises a case study where traffic has a known origin, but we assume a degree of freedom as to where its end up being processed, which is typically the case for e. g., grid applications of the bag-of-tasks (BoT) type or for providing cloud services. In particular, we will provide in this paper a new integer linear programming (ILP) formulation to solve the resilient grid/cloud dimensioning problem using failure-dependent backup routes. Our algorithm will simultaneously decide on server and network capacity. We find that in the anycast routing problem we address, the benefit of using failure-dependent (FD) rerouting is limited compared to failure-independent (FID) backup routing. We confirm our earlier findings in terms of network capacity savings achieved by relocation compared to not exploiting relocation (order of 6-10% in the current case studies)
Risk adjustment for hospital use using social security data: cross sectional small area analysis
OBJECTIVES: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. DESIGN: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. SETTING: Northern Ireland. MAIN OUTCOME MEASURE: Intensity of use of inpatient services. RESULTS: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. CONCLUSIONS: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula
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