16,304 research outputs found

    Resource allocation in the cloud for video-on-demand applications using multiple cloud service providers

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    Abstract Video-on-demand (VoD) applications have become extensively used nowadays. YouTube is one of the most extensively used VoD application. These applications are used for various purposes like entertainment, education, media, etc., of all age groups. Earlier, these applications were supported by private data centers and application servers. Sufficient infrastructure had to be bought and maintained, to support the demand even during unexpected peak times. This approach caused huge loss of resources when the demand is normal as a large portion of the resources remained idle. To overcome this, VoD application providers moved to the cloud, to host their video content’s. This approach reduced the wastage of resources and the maintenance cost of the VoD application provider. The problem is to determine the number of resources to handle the demand while maintaining QoS for every instance. We have designed two algorithms in this paper, namely the multiple cloud resource allocation (MCRA) algorithm and the hybrid MCRA algorithm. Most of the cloud service providers (CSPs) basically provide two types of resource allocation schemes: (i) the reservation scheme and (ii) the on-demand scheme. The reservation scheme provides time-based tariff prices, where the discount is provided for the resources depending on their quantity and reservation time. This scheme is used in the MCRA algorithm to reduce the cost of the VoD application provider. In Hybrid MCRA algorithm both the reservation scheme and on-demand scheme are implemented, to overcome the drawbacks of the MCRA algorithm which are under-subscription and over-subscription. We have analyzed both the algorithms in terms of cost and allocation of resources. These algorithms can help allocate resources in of cloud for VoD applications in a cost-effective way and at the same time not compromise on the QoS of the video content

    A Cloud Infrastructure for Multimedia Conferencing Applications

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    Conferencing enables the conversational exchange of media between several parties. Conferencing applications are among important enterprise applications nowadays. However, fine grained scalability and elasticity remain quite elusive for multimedia conferencing applications, although they are key to efficiency in the resource usage. Cloud computing is an emerging paradigm for provisioning network, storage, and computing resources on demand using a pay-per-use model. Cloud-based conferencing services can inherent several benefits such as resource usage efficiency, scalability and easy introduction of different types of conferences. This thesis relies on a recently proposed business model for cloud-based conferencing. The model has the following roles: conferencing substrate provider, conferencing infrastructure provider, conferencing platform provider, conferencing service provider, and broker. Conferencing substrates are generally atomic and served as elementary building blocks (e.g. signalling, mixing) of conferencing applications. They can be virtualized and shared among several conferencing applications for resource efficiency purposes. Multiple conferencing substrates provided by different conferencing substrate providers can be combined to build a conferencing service (e.g. a dial-out signalling substrate and an audio mixer substrate can be composed to build a dial-out audio conference service). This thesis focuses on the conferencing infrastructure provider and conferencing substrate provider roles. It proposes a virtualized cloud infrastructure for multimedia conferencing applications. This infrastructure relies on fine grained conferencing substrates (e.g. dial-out signalling, dial-in signalling, audio mixer, video mixer, floor control, etc.) and offers several advantages in addition to fine grained scalability and elasticity (e.g. assembling substrates on the fly to build new conferencing applications). An architecture is proposed to realize the roles of conferencing infrastructure provider, conferencing substrate provider and their interactions. A resource allocation mechanism for conferencing substrates is also proposed. We have also built a prototype with Xen as the virtualization platform and validated the architecture. Performance has also been evaluated

    MorphoSys: efficient colocation of QoS-constrained workloads in the cloud

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    In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.National Science Foundation (0720604, 0735974, 0820138, 0952145, 1012798

    MORPHOSYS: efficient colocation of QoS-constrained workloads in the cloud

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    In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the IaaS provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MorphoSys: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of workloads. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. The results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MorphoSys.First author draf

    Dynamic Resource Management in Clouds: A Probabilistic Approach

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    Dynamic resource management has become an active area of research in the Cloud Computing paradigm. Cost of resources varies significantly depending on configuration for using them. Hence efficient management of resources is of prime interest to both Cloud Providers and Cloud Users. In this work we suggest a probabilistic resource provisioning approach that can be exploited as the input of a dynamic resource management scheme. Using a Video on Demand use case to justify our claims, we propose an analytical model inspired from standard models developed for epidemiology spreading, to represent sudden and intense workload variations. We show that the resulting model verifies a Large Deviation Principle that statistically characterizes extreme rare events, such as the ones produced by "buzz/flash crowd effects" that may cause workload overflow in the VoD context. This analysis provides valuable insight on expectable abnormal behaviors of systems. We exploit the information obtained using the Large Deviation Principle for the proposed Video on Demand use-case for defining policies (Service Level Agreements). We believe these policies for elastic resource provisioning and usage may be of some interest to all stakeholders in the emerging context of cloud networkingComment: IEICE Transactions on Communications (2012). arXiv admin note: substantial text overlap with arXiv:1209.515
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