GA-Based Resource Augmentation Negotation for Energy-Optimised Mobile Ad-hoc Cloud

Abstract

Mobile and cloud computing are two areas which are rapidly expanding in terms of use case and functionality. An ad-hoc mobile cloud can be constructed upon local devices, where devices work together and share resources, aspects such as energy and costs may be minimised. This paper builds on previous work which proposed an end-to-end system whereby user applications may be profiled for their resource consumption locally and then if augmentation is required, they may negotiate with a local mobile ad-hoc cloud for optimum energy and resource utilisation. The contribution of this paper focuses upon a novel and adapted Genetic Algorithm approach to resource negotiation in order to further enable energy-optimised resource augmentation for Mobile Ad-hoc clouds.