Reputation-guided Evolutionary Scheduling Algorithm for Independent Tasks in inter-Clouds Environments

Self-adaptation provides software with flexibility to different behaviours (configurations) it incorporates and the (semi-) autonomous ability to switch between these behaviours in response to changes. To empower clouds with the ability to capture and respond to quality feedback provided by users at runtime, we propose a reputation guided genetic scheduling algorithm for independent tasks. Current resource management services consider evolutionary strategies to improve the performance on resource allocation procedures or tasks scheduling algorithms, but they fail to consider the user as part of the scheduling process. Evolutionary computing offers different methods to find a near-optimal solution. In this paper we extended previous work with new optimisation heuristics for the problem of scheduling. We show how reputation is considered as an optimisation metric, and analyse how our metrics can be considered as upper bounds for others in the optimisation algorithm. By experimental comparison, we show our techniques can lead to optimised results.Peer Reviewe

Keynote 1: Mobile cloud and green computing

AbstractMobile devices (smart phones, tablets, laptops, embedded boards, robots) can serve as ‘dumb’ terminals for cloud computing services over intelligent network. Mobile cloud has emerged as a new cloud computing platform that ‘puts cloud into a pocket’. Important issues include optimizing the scheduling and transport schemes, access management, and application optimization, for mobile devices to achieve energy saving. This talk will first introduce the development of mobile cloud computing and describe some applications involving multimedia, vision/recognition, graphics, gaming, text processing. Next, it will present the transmission, computation, and sensing challenges of green computing in mobile cloud. It will also discuss the possible solutions from various perspectives. Energy savings for task outsourcing and location based services will be discussed in detail. ‘Crowd computing’ combines mobile devices and social interactions to achieve large-scale distributed computation. Examples include task farming, participatory and opportunistic crowd-sourced sensing. One particular emerging concept is the ‘vehicular cloud’. For example, traffic lights in a congested area could be rescheduled by running the rescheduling code (controlled by municipality) on the collective computational platform provided by the cars