DOTNET PROJECT
A
Trust-Based Agent Learning Model for Service Composition in Mobile Cloud
Computing Environments (IEEE 2019)
Abstract:
Mobile cloud computing has the features of
resource constraints, openness, and uncertainty which leads to the high
uncertainty on its quality of service (QoS) provision and serious security
risks. Therefore, when faced with complex service requirements, an efficient
and reliable service composition approach is extremely important. In addition,
preference learning is also a key factor to improve user experiences. In order
to address them, this paper introduces a three-layered trust-enabled service
composition model for the mobile cloud computing systems. Based on the fuzzy
comprehensive evaluation method, we design a novel and integrated trust
management model. Service brokers are equipped with a learning module enabling
them to better analyze customers' service preferences, especially in cases when
the details of a service request are not totally disclosed. Because traditional
methods cannot totally reflect the autonomous collaboration between the mobile
cloud entities, a prototype system based on the multi-agent platform JADE is
implemented to evaluate the efficiency of the proposed strategies. The
experimental results show that our approach improves the transaction success
rate and user satisfaction.
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