Autonomic Power Aware Cloud Resources Orchestration Architecture for Web Applications

Endless resources provisioning illusion is the mainstay for cloud computing paradigm. However, the unpredictable volatility nature involving web applications workload demand would highly hinder cloud computing platforms performance, furthermore, expose cloud resources for possible devastation. Accordingly, this work proposes autonomic power aware SLA-oriented cloud resources orchestration two-tier architecture. Despite complexity and uncertainties of the workload fluctuations, the proposed architecture geared for leveraging cloud system resources utilization, ensuring explicit guarantees on web applications’ responsiveness obligations, meanwhile achieving power consumption minimization objectives. The proposed architecture consolidates heuristic methodologies along with control theory approaches in a resource orchestration hierarchical structure. Firstly, an autonomic global controller is presented. The proposed global controller exploits heuristic methodology for mapping virtual machines (VMs) to the appreciate cloud resources in accordance to heuristic multidimensional objectives based placement strategy. Secondly, a proactive fuzzy-logic based local controller is proposed. The proposed local controller aimed at in confronting workloads' sustainable fluctuations via proactive amendment for the placement and provisioning schedules. Furthermore, the proposed local controller oriented towards maintaining active power management policy especially during transient peak of usage, thereby mitigating overall costs, and extending resources capacity and performance capabilities. Simulation results and comparisons demonstrate that the proposed architecture significantly surpasses previous approaches in terms of total energy consumption, furthermore maintaining web applications SLAs objectives despite dynamic workload scenarios.