|عنوان فارسی مقاله:||تکنولوژی توزیع منابع هوشمند برای Desktop-as-a-Service در محیط ابر|
|عنوان انگلیسی مقاله:||Intelligent Resource Allocation Technique For Desktop-as-a-Service in Cloud Environment|
|رشته های مرتبط:||مهندسی کامپیوتر و فناوری اطلاعات، اینترنت و شبکه های گسترده، هوش مصنوعی|
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The specialty of desktop-as-a-service cloud computing is that user can access their desktop and can execute applications in virtual desktops on remote servers. Resource management and resource utilization are most significant in the area of desktop-as-a-service, cloud computing; however, handling a large amount of clients in the most efficient manner poses important challenges. Especially deciding how many clients to handle on one server, and where to execute the user applications at each time is important. This is because we have to ensure maximum resource utilization along with user data confidentiality, customer satisfaction, scalability, minimum Service level agreement (SLA) violation etc. Assigning too many users to one server leads to customer dissatisfaction, while assigning too little leads to higher investments costs. So we have taken into consideration these two situations also. We study different aspects to optimize the resource usage and customer satisfaction. Here in this paper We proposed Intelligent Resource Allocation (IRA) Technique which assures the above mentioned parameters like minimum SLA violation. For this, priorities are assigned to user requests based on their SLA Factors in order to maintain their confidentiality. The results of the paper indicate that by applying IRA Technique to the already existing overbooking mechanism will improve the performance of the system with significant reduction in SLA violation.
Cloud computing refers technology that facilitate functionality of an IT Infrastructure, IT platform or an IT product to be exposed as a set of services in a seamlessly scalable model so that the consumers of these services can use what they really want and pay for only those services that they use (Pay per use).Cloud computing is about moving services, computation or data–for cost and business advantageoff–site to an internal or external, location transparent, centralized facility. By making data available in the cloud, it can be more easily and ubiquitously accessed, often at much lower cost, increasing its value by enabling opportunities for enhanced collaboration, integration and analysis on a shared common platform. The definition of cloud computing as per Gartner is “A style of computing where massively scalable IT facilitate capabilities are delivered as a service to external customers using internal technologies”. The Cloud computing services such as Amazon’s Elastic are widely available today, offering computing resources on demand. Thanks to such advances and ubiquitous network availability, the thin client computing paradigm is enjoying increasing popularity. Originally intended for wired LAN environments this paradigm is repeating its success in a mobile context. A study from ABI Research forecasts a US$20 billion turnover surrounding services directly associated with mobile cloud computing by the end of 2014. Clearly, when applications are offloaded, the mobile terminal only needs to present audiovisual output to users and convey user input to remote servers, considerably reducing the client device’s computational complexity. Consequently, applications can run as-is, without requiring (many) scaled-down versions for mobile devices. Several popular applications, such as Google Docs and Microsoft Live, already execute on servers in the cloud. The ability to access applications in the cloud is referred to as software as a service (SaaS).There has been a rapid adoption of “cloud” platforms for online applications such as email, photo/video galleries and file storage in academia and industry. The next frontier for these user communities will be to transition their “traditional distributed desktops” that have dedicated hardware and software installations into “virtual desktop clouds” (VDCs) that are accessible via thinclients. Moreover, in the not so distant future, we can envisage home users signing-up for virtual desktops (VDs) with a VD Cloud Service Provider (CSP) providing Desktop-as-a-Service (DaaS) as a utility. Current desktop-as-a-service computing deployments are typically operational in corporate local area network (LAN) environments, which are highly controlled environments offering fixed and stable bandwidth availability to a relative small, well-known user base. Extending desktop-as-a-service computing to wide area network (WAN) environments, which comprise a large, geographically distributed customer base, where users are potential.connected through unreliable wireless network connections, involves a number of novel challenges. Strategies are needed to improve resource utilization and/or customer satisfaction in WAN environments in the most efficient manner. Cloud computing  is an enabler for this kind of service. Unlike most current cloud services, the applications are not accessed through a web browser (e.g. Google Apps Cloud Service), but through a thin client protocol (e.g., Microsoft Remote Desktop Protocol (RDP)  or Virtual Network Computing (VNC) ). This way, legacy applications must not be rebuilt to be offered by the envisioned service. Current cloud platforms fulfill the hardware requirements for implementing DaaS. However, an emerging category of mobile applications including augmented reality, rich sensing, and multimedia editing pose stringent requirements on delays. Current cloud management systems can’t meet user expectations for these applications, especially in terms of latency. A clear need exists for novel cloud management algorithms that consider the specific requirements of thin client computing. system architecture implements such algorithms in the service manager’s selfmanagement component. The manager can be implemented as part of existing cloud management systems such as OpenNebula , OpenStack, and Eucalyptus. Figure 1 shows Existing architecture. Simplified OS image management (that is, re-using an OS image among users to reduce the storage per user) and application management are essential for the service to scale. Our system builds a VD from a shared golden image from the OS database and augments it with personal settings for example, by using a copy-onwrite solution with UnionFS (http://unionfs.filesystems.org). Multilayer VDs simplify the complexity of upgrading the golden image without causing broken dependencies or conflicts.To improve DaaS usability, we could combine DaaS with application virtualization technologies such as Softricity and Microsoft App-V. The system would then dynamically deliver applications to the user’s VD without having to install, configure, and update them. This approach further reduces the complexity of upgrading golden OS images because applications aren’t installed in the user’s VD and thus can’t be broken.