43,710 research outputs found
Reducing Electricity Demand Charge for Data Centers with Partial Execution
Data centers consume a large amount of energy and incur substantial
electricity cost. In this paper, we study the familiar problem of reducing data
center energy cost with two new perspectives. First, we find, through an
empirical study of contracts from electric utilities powering Google data
centers, that demand charge per kW for the maximum power used is a major
component of the total cost. Second, many services such as Web search tolerate
partial execution of the requests because the response quality is a concave
function of processing time. Data from Microsoft Bing search engine confirms
this observation.
We propose a simple idea of using partial execution to reduce the peak power
demand and energy cost of data centers. We systematically study the problem of
scheduling partial execution with stringent SLAs on response quality. For a
single data center, we derive an optimal algorithm to solve the workload
scheduling problem. In the case of multiple geo-distributed data centers, the
demand of each data center is controlled by the request routing algorithm,
which makes the problem much more involved. We decouple the two aspects, and
develop a distributed optimization algorithm to solve the large-scale request
routing problem. Trace-driven simulations show that partial execution reduces
cost by for one data center, and by for geo-distributed
data centers together with request routing.Comment: 12 page
Economic Optimization of Fiber Optic Network Design in Anchorage
Presented to the Faculty of the University of Alaska Anchorage
in Partial Fulfillment of the Requirements for the Degree of
MASTER OF SCIENCE, ENGINEERING MANAGEMENTThe wireline telecommunications industry is currently involved in an evolution. Growing bandwidth demands are putting pressure on the capabilities of outdated copper based networks. These demands are being meet by replacing these copper based networks with fiber optic networks. Unfortunately, telecommunications decision makers are tasked with figuring out how best to deploy these networks with little ability to plan, organize, lead, or control these large projects.
This project introduces a novel approach to designing fiber optic access networks. By leveraging well known clustering and routing techniques to produce sound network design, decision makers will better understand how to divide service areas, where to place fiber, and how much fiber should be placed. Combining this output with other typical measures of costs and revenue, the decision maker will also be able to focus on the business areas that will provide the best outcome when undertaking this transformational evolution of physical networks.Introduction / Background / Clustering, Routing, and the Model / Results and Analysis / Conclusion / Reference
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