Cawsac cost aware workload scheduling and admission control for distributed cloud data centers

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Cawsac cost aware workload scheduling and admission control for distributed cloud data centers +91-9994232214,7806844441, ieeeprojectchennai@gmail.com, www.projectsieee.com, www.ieee-projects-chennai.com IEEE PROJECTS 2016-2017 ----------------------------------- Contact:+91-9994232214,+91-7806844441 Email: ieeeprojectchennai@gmail.com

Ingénierie

CAWSAC: Cost-Aware Workload Scheduling and Admission Control for
Distributed Cloud Data Centers
Abstract:
Multiple heterogeneous applications concurrently run in distributed cloud data
centers (CDCs) for better performance and lower cost. There is a highly
challenging problem of how to minimize the total cost of a CDCs provider in a
market where the bandwidth and energy cost show geographical diversity. To
solve the problem, this paper first proposes a revenue-based workload admission
control method to judiciously admit requests by considering factors including
priority, revenue and the expected response time. Then, this paper presents a
cost-aware workload scheduling method to jointly optimize the number of active
servers in each CDC, and the selection of Internet service providers for the CDCs
provider. Finally, trace-driven simulation results demonstrate that the proposed
methods can greatly reduce the total cost and increase the throughput of the
CDCs provider in comparison to existing methods. Note to Practitioners-
A cloud provider deploys its applications in geographically distributed CDCs to
improve stability and reliability. For cost and performance, each CDC provides
services through multiple ISPs that deliver traffic between millions of users and
the CDCs provider. The geographical diversity of the bandwidth and energy cost
brings the CDCs provider a big challenge of how to minimize the bandwidth and
energy cost of the CDCs provider. This paper first proposes a revenue-based
workload admission control method to selectively admit requests. Then, this
paper proposes a cost-aware workload scheduling method to allocate requests

among multiple available Internet service providers connecting to distributed
CDCs. The scheduling strategy can intelligently dispatch requests, and achieve
lower cost and higher throughput for the CDCs provider.

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