Cloudifying Desktops – A Taxonomy for Desktop Virtualization

Compared to traditional desktops, the implementation of desktop virtualization can leverage cost reductions and enable desktop access via mobile devices. Consequently, researchers and practitioners increasingly focus on virtualized desktops and Desktop as a Service (DaaS). However, a consistent definition for these technologies and the related delivery models does not exist yet. Therefore, we conducted a literature analysis which revealed that optimized resource allocation and performant DaaS infrastructures are the primary topics in research. Afterward, we developed a taxonomy to categorize extant virtual desktop delivery models and propose a holistic definition as theoretical framework for DaaS

Profit Renting Schema for cloud Service Providers in Cloud Computing

Cloud computing is a classification of web computing and with respect to request computing where shared assets and data are given to the client's on-request. Profit is the most critical variable from the cloud service provider and it is essentially dictated by the setup of a cloud profit stage under given market request. A solitary long haul leasing plan is generally used to design a cloud stage, which can't ensure the quality of administration however prompts to genuine asset squander. To beat the disadvantages of single leasing plan, Double asset RR Renting plan is composed which is the blend of both here and now and long haul leasing. Twofold asset leasing plan ensures the quality of administration as well as lessen the asset squander. In which queuing model is utilized for occupation booking. Twofold asset leasing RR conspire not just gives the Qos to the clients by utilizing load adjusting round robin calculation additionally expand profit than single leasing plan. Thirdly, a profit intensification issue is anticipated the twofold leasing arrangement and the streamlined course of action of a cloud stage is gotten by dealing with the profit help issue. Finally, a movement of calculations coordinated to break down the profit of our proposed arrange with that of the single leasing arrangement. The results exhibit that our arrangement can't simply guarantee the organization way of all requesting, furthermore get more profit than the last

A service broker for Intercloud computing

This thesis aims at assisting users in finding the most suitable Cloud resources taking into account their functional and non-functional SLA requirements. A key feature of the work is a Cloud service broker acting as mediator between consumers and Clouds. The research involves the implementation and evaluation of two SLA-aware match-making algorithms by use of a simulation environment. The work investigates also the optimal deployment of Multi-Cloud workflows on Intercloud environments

A Unified Algorithm for Virtual Desktops Placement in Distributed Cloud Computing

Distributed cloud has been widely adopted to support service requests from dispersed regions, especially for large enterprise which requests virtual desktops for multiple geodistributed branch companies. The cloud service provider (CSP) aims to deliver satisfactory services at the least cost. CSP selects proper data centers (DCs) closer to the branch companies so as to shorten the response time to user request. At the same time, it also strives to cut cost considering both DC level and server level. At DC level, the expensive long distance inter-DC bandwidth consumption should be reduced and lower electricity price is sought. Inside each tree-like DC, servers are trying to be used as little as possible so as to save equipment cost and power. In nature, there is a noncooperative relation between the DC level and server level in the selection. To attain these objectives and capture the noncooperative relation, multiobjective bilevel programming is used to formulate the problem. Then a unified genetic algorithm is proposed to solve the problem which realizes the selection of DC and server simultaneously. The extensive simulation shows that the proposed algorithm outperforms baseline algorithm in both quality of service guaranteeing and cost saving