An energy efficient service composition mechanism using a hybrid
meta-heuristic algorithm in a mobile cloud environment
Abstract
By increasing mobile devices in technology and human life, using a
runtime and mobile services has gotten more complex along with the
composition of a large number of atomic services. Different services are
provided by mobile cloud components to represent the non-functional
properties as Quality of Service (QoS), which is applied by a set of
standards. On the other hand, the growth of the energy-source
heterogeneity in mobile clouds is an emerging challenge according to the
energy-saving problem in mobile nodes. To mobile cloud service
composition as an NP-Hard problem, an efficient selection method should
be taken by problem using optimal energy-aware methods that can extend
the deployment and interoperability of mobile cloud components. Also, an
energy-aware service composition mechanism is required to preserve high
energy saving scenarios for mobile cloud components. In this paper, an
energy-aware mechanism is applied to optimize mobile cloud service
composition using a hybrid Shuffled Frog Leaping Algorithm and Genetic
Algorithm (SFGA). Experimental results capture that the proposed
mechanism improves the feasibility of the service composition with
minimum energy consumption, response time, and cost for mobile cloud
components against some current algorithms.