Authors:
Laiping Zhao
and
Kouichi Sakurai
Affiliation:
Kyushu University, Japan
Keyword(s):
Net Revenue, Server Management, Failure Prediction, State Transition.
Related
Ontology
Subjects/Areas/Topics:
Cloud Computing
;
Cloud Computing Architecture
;
Cloud Computing Enabling Technology
;
Cloud Middleware Frameworks
;
Economics (ROI, Costs, CAPEX/OPEX,…)
;
Fundamentals
;
Monitoring of Services, Quality of Service, Service Level Agreements
;
Platforms and Applications
Abstract:
As failures are becoming frequent due to the increasing scale of data centers, Service Level Agreement (SLA) violation often occurs at a cloud provider, thereby affecting the normal operation of job requests and incurring high penalty cost. To this end, we examine the problem of managing a server farm in a way that reduces the penalty caused by server failures according to an Infrastructure-as-a-Service model. We incorporate the malfunction and recovery states into the server management process, and improve the cost efficiency of server management by leveraging the failure predictors. We also design a utility model describing the expected net revenue obtained from providing service. The basic idea is that, a job could be rejected or migrate to another server if a negative utility is anticipated. The formal and experimental analysis manifests our expected net revenue improvement.