DocumentCode
1759417
Title
Decreasing Impact of SLA Violations:A Proactive Resource Allocation Approachfor Cloud Computing Environments
Author
Morshedlou, Hossein ; Meybodi, Mohammad Reza
Author_Institution
Dept. of Comput. Eng. & Inf. Sci., AmirKabir Univ. of Technol., Tehran, Iran
Volume
2
Issue
2
fYear
2014
fDate
April-June 2014
Firstpage
156
Lastpage
167
Abstract
User satisfaction as a significant antecedent to user loyalty has been highlighted by many researchers in market based literatures. SLA violation as an important factor can decrease users´ satisfaction level. The amount of this decrease depends on user´s characteristics. Some of these characteristics are related to QoS requirements and announced to service provider through SLAs. But some of them are unknown for service provider and selfish users are not interested to reveal them truly. Most the works in literature ignore considering such characteristics and treat users just based on SLA parameters. So, two users with different characteristics but similar SLAs have equal importance for the service provider. In this paper, we use two user´s hidden characteristics, named willingness to pay for service and willingness to pay for certainty, to present a new proactive resource allocation approach with aim of decreasing impact of SLA violations. New methods based on learning automaton for estimation of these characteristics are provided as well. To validate our approach we conducted some numerical simulations in critical situations. The results confirm that our approach has ability to improve users´ satisfaction level that cause to gain in profitability.
Keywords
cloud computing; contracts; resource allocation; QoS requirements; SLA violations; cloud computing environment; proactive resource allocation approach; profitability; quality of service; service level agreements; service provider; user characteristics; user satisfaction; Cloud computing; Decision making; Learning automata; Market research; Profitability; Quality of service; Resource management; Users satisfaction level; cloud service; learning automaton; resource allocation; willingness to pay;
fLanguage
English
Journal_Title
Cloud Computing, IEEE Transactions on
Publisher
ieee
ISSN
2168-7161
Type
jour
DOI
10.1109/TCC.2014.2305151
Filename
6734676
Link To Document