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Register a new userAchieving Energy Efficiency in Cloud Brokering
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Added by
Lin Wang
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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The proliferation of cloud providers has brought substantial interoperability complexity to the public cloud market, in which cloud brokering has been playing an important role. However, energy-related issues for public clouds have not been well addressed in the literature. In this paper, we claim that the broker is also situated in a perfect position where necessary actions can be taken to achieve energy efficiency for public cloud systems, particularly through job assignment and scheduling. We formulate the problem by a mixed integer program and prove its NP-hardness. Based on the complexity analysis, we simplify the problem by introducing admission control on jobs. In the sequel, optimal job assignment can be done straightforwardly and the problem is transformed into improving job admission rate by scheduling on two coupled phases: data transfer and job execution. The two scheduling phases are further decoupled and we develop efficient scheduling algorithm for each of them. Experimental results show that the proposed solution can achieve significant reduction on energy consumption with admission rates improved as well, even in large-scale public cloud systems.
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In an altruistic DISH protocol, additional nodes called altruists are deployed in a multi-channel ad hoc network to achieve energy efficiency while still maintaining the original throughput-delay performance. The responsibility of altruists is to constantly monitor the control channel and awaken other (normal) nodes when necessary (to perform data transmissions). Altruists never sleep while other nodes sleep as far as possible. This technical report proves three properties related to this cooperative protocol. The first is the conditions for forming an unsafe pair (UP) in an undirected graph. The second is the necessary and sufficient conditions for full cooperation coverage to achieve the void of multi-channel coordination (MCC) problems. The last is the NP-hardness of determining the minimum number and locations of altruistic nodes to achieve full cooperation coverage.
Recent measurement studies show that there are massively distributed hosting and computing infrastructures deployed in the Internet. Such infrastructures include large data centers and organizations computing clusters. When idle, these resources can readily serve local users. Such users can be smartphone or tablet users wishing to access services such as remote desktop or CPU/bandwidth intensive activities. Particularly, when they are likely to have high latency to access, or may have no access at all to, centralized cloud providers. Today, however, there is no global marketplace where sellers and buyers of available resources can trade. The recently introduced marketplaces of Amazon and other cloud infrastructures are limited by the network footprint of their own infrastructures and availability of such services in the target country and region. In this article we discuss the potentials for a federated cloud marketplace where sellers and buyers of a number of resources, including storage, computing, and network bandwidth, can freely trade. This ecosystem can be regulated through brokers who act as service level monitors and auctioneers. We conclude by discussing the challenges and opportunities in this space.
With the proliferation of mobile applications, Mobile Cloud Computing (MCC) has been proposed to help mobile devices save energy and improve computation performance. To further improve the quality of service (QoS) of MCC, cloud servers can be deployed locally so that the latency is decreased. However, the computational resource of the local cloud is generally limited. In this paper, we design a threshold-based policy to improve the QoS of MCC by cooperation of the local cloud and Internet cloud resources, which takes the advantages of low latency of the local cloud and abundant computational resources of the Internet cloud simultaneously. This policy also applies a priority queue in terms of delay requirements of applications. The optimal thresholds depending on the traffic load is obtained via a proposed algorithm. Numerical results show that the QoS can be greatly enhanced with the assistance of Internet cloud when the local cloud is overloaded. Better QoS is achieved if the local cloud order tasks according to their delay requirements, where delay-sensitive applications are executed ahead of delay-tolerant applications. Moreover, the optimal thresholds of the policy have a sound impact on the QoS of the system.
Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.
Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns of privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon, and Microsoft. Community Cloud Computing makes use of the principles of Digital Ecosystems to provide a paradigm for Clouds in the community, offering an alternative architecture for the use cases of Cloud Computing. It is more technically challenging to deal with issues of distributed computing, such as latency, differential resource management, and additional security requirements. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.
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