User satisfaction as a significant antecedent to
user loyalty has been highlighted by many researchers in market based literature's. 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
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