Optimization of Elastic Cloud Brokerage Mechanisms for Future Telecommunication Service Environments

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Cloud computing mechanisms and cloud-based services are currently revolutionizing Web as well as telecommunication service platforms and service offerings. Apart from providing infrastructures, platforms and software as a service, mechanism for dynamic allocation of compute and storage resources on-demand, commonly termed as “elastic cloud computing” account for the most important cloud computing functionalities. Resource elasticity allows not only for efficient internal compute and storage resource consumption, but also, through so called hybrid cloud computing mechanisms, for dynamic utilization of external resources on-demand. This capability is especially useful in order to cost-efficiently cope with peakworkloads, allowing service providers to significantly reduce usually required over-provisioned service infrastructures, allowing for “pay-per-use” cost models. With a steadily growing number of cloud providers and with the proliferation of unified cloud computing interfaces, service providers are given free choice of flexibly selecting and utilizing cloud resources from different cloud providers. Cloud brokering systems allow for dynamic selection and utilization of cloud computing resources based on functional (e.g. QoS, SLA, energy consumption) as well as nonfunctional criteria (e.g. costs). The presented work focuses on enhanced cloud brokering mechanisms for telecommunication service platforms, enabling quality telecommunication service assurance, still optimizing cloud resources consumption, i.e. saving costs and energy. Furthermore this work shows that by combining cloud brokering mechanisms with standardized telecommunication service brokering mechanisms an even greater benefit for telecommunication service providers can be achieved as this enables an even better cost-efficiency since different user segments can seamlessly be served by allocating different cloud resources to them in a policy-driven manner

Energy-efficient Nature-Inspired techniques in Cloud computing datacenters

Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure as a Service (IaaS) is the capability provided to the consumer by enabling smarter access to the processing, storage, networks, and other fundamental computing resources, where the consumer can deploy and run arbitrary software including operating systems and applications. The resources are sometimes available in the form of Virtual Machines (VMs). Cloud services are provided to the consumers based on the demand, and are billed accordingly. Usually, the VMs run on various datacenters, which comprise of several computing resources consuming lots of energy resulting in hazardous level of carbon emissions into the atmosphere. Several researchers have proposed various energy-efficient methods for reducing the energy consumption in datacenters. One such solutions are the Nature-Inspired algorithms. Towards this end, this paper presents a comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud datacenters. A taxonomy is followed focusing on three key dimension in the literature including virtualization, consolidation, and energy-awareness. A qualitative review of each techniques is carried out considering key goal, method, advantages, and limitations. The Nature-Inspired algorithms are compared based on their features to indicate their utilization of resources and their level of energy-efficiency. Finally, potential research directions are identified in energy optimization in data centers. This review enable the researchers and professionals in Cloud computing datacenters in understanding literature evolution towards to exploring better energy-efficient methods for Cloud computing datacenters