Virtual Services in Cloud Computing

Fu, Jicheng; Hao, Wei; Tu, Manghui; Ma, Bin; Baldwin, Joshua; Bastani, Farokh B.

doi:10.1109/services.2010.125

Cited by 17 publications

(10 citation statements)

References 3 publications

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“…To overcome the above issue, in [12] we outlined a bidirectional search algorithm. However, no solutions were provided to implement the algorithm and no evaluations were conducted to investigate its feasibility.…”

Section: Methodsmentioning

confidence: 99%

Handling Planning Failures with Virtual Actions

Tian

et al. 2012

2012 IEEE 24th International Conference on Tools With Artificial Intelligence

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Abstract-Artificial intelligence (AI) planners have been widely used in many fields, such as intelligent agents, autonomous robots, web service compositions, etc. However, existing AI planners share a common problem: When given a problem to solve, they either return a solution if one exists or report that no solution is found. However, simply reporting failure leaves no clues for people to trace the causes of the planning failure. In this paper, we present a novel approach that can propose virtual actions in the event of planning failure. Virtual actions enable traditional planners to succeed and hence return an incomplete plan instead of merely an error message. More importantly, the specifications of the virtual actions suggest what the missing parts may contain, thus providing important clues to users as to the nature of the failure. Experimental results show that our approach constantly returns useful and comprehensible information for humans, thus making AI planning more practical when solving real-world problems.

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Section: Methodsmentioning

confidence: 99%

Handling Planning Failures with Virtual Actions

Tian

et al. 2012

2012 IEEE 24th International Conference on Tools With Artificial Intelligence

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“…Fu et al [6] propose a concept for service composition in cloud computing-the so called virtual services. Virtual services can connect the existing physical services and enable the composition process to succeed.…”

Section: Related Workmentioning

confidence: 99%

Configuration of Services Based on Virtualization

Jiang

Zhu

et al. 2014

2014 Theoretical Aspects of Software Engineering Conference

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Virtualization is fundamental to cloud computing. It allows abstraction centred on services and isolation of lower level functionalities and underlying hardware. Modeling, analyzing and verifying cloud systems necessarily involve virtualization and services. However, there exist few efforts to effectively formalizing virtualization in cloud computing. In this paper, based on services we present an approach for defining virtualization. We discuss some properties of service virtualization under some operations and the correctness of virtual services (virtual services without abnormal behavioral problems). Moreover, we investigate automatic configuration of a service based on virtualization, that is, given a virtualized service, how can we automatically obtain all possible correct virtual services of such a service? The configuration process is to first separate a virtualized service into atomic and correct virtual services and then merge these atomic virtual services into all possible correct virtual services of such a virtualized service. The obtained theoretical results help to formally analyze, verify and configure cloud systems.

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“…For instance, in Amazon EC2, the user is allowed to run up to 20 on-demand or reserved instances, and up to 100 spot instances per region [10]. In this paper, we have considered heterogeneous workload applications from users, characterized based on resource and performance requirements.…”

Section: System Modelmentioning

confidence: 99%

Scalable Analytic Models for Performance Efficiency in the Cloud

Awada

2014

2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing

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This paper presents a scalable model-driven approach to quantify the availability of resources and optimal distribution of tasks over these resources, such that the average response time of tasks is minimized. To reduce the complexity of analysis and solution time, we use an integrated stochastic based approach. To achieve this, first we use clustering algorithm to group the tasks into distinct classes with similar characteristics in terms of resource and performance requirements. Second, we quantify the resource availability of cloud center among three states: active (running), idle (turned on, but not ready), and off (turned off). Third, we develop a queuing model for multiple heterogeneous multicore servers, and formulate and solve the optimal load distribution of tasks for multiple heterogeneous multicore servers in a cloud computing data centers. We derive equations that permit us to find optimal load distribution of tasks that their average response time is minimized. We obtain not only detailed assessment of cloud center performance, but also insights into equilibrium arrangement, capacity planning and power consumption to be kept under control.

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Virtual Services in Cloud Computing

Cited by 17 publications

References 3 publications

Handling Planning Failures with Virtual Actions

Handling Planning Failures with Virtual Actions

Configuration of Services Based on Virtualization

Scalable Analytic Models for Performance Efficiency in the Cloud

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