VM scheduling strategies based on artificial intelligence in Cloud Testing

Zheng, Yang; Cai, Lizhi; Huang, Shidong; Wang, Zhihong

doi:10.1109/snpd.2014.6888746

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…In a cloud‐based environment, it is necessary to maximize the resource utilization and to improve system load balance . Therefore, resource allocator module exists.…”

Section: The Proposed Architecturementioning

confidence: 99%

“…In a cloud-based environment, it is necessary to maximize the resource utilization and to improve system load balance. 39 Therefore, resource allocator module exists. Resource allocator module assigns task to the available virtual machines to execute the task in such a way to improve hardware and software resources utilization and guarantee load balance.…”

Section: Resource Allocator Modulementioning

confidence: 99%

See 1 more Smart Citation

Automated parallel GUI testing as a service for mobile applications

Ali

Maghawry

Badr

2018

J Software Evolu Process

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Recently, testing mobile applications is gaining much attention due to the widespread of smartphones and the tremendous number of mobile applications development. It is essential to test mobile applications before being released for the public use. Graphical user interface (GUI) testing is a type of mobile applications testing conducted to ensure the proper functionality of the GUI components. Typically, GUI testing requires a lot of effort and time whether manual or automatic. Cloud computing is an emerging technology that can be used in the software engineering field to overcome the defects of the traditional testing approaches by using cloud computing resources. As a result, testing‐as‐a‐service is introduced as a service model that conducts all testing activities in a fully automated manner. In this paper, a system for mobile applications GUI testing based on testing‐as‐a‐service architecture is proposed. The proposed system performs all testing activities including automatic test case generation and simultaneous test execution on multiple virtual nodes for testing Android‐based applications. The proposed system reduces testing time and meets fast time‐to market constraint of mobile applications. Moreover, the proposed system architecture addresses many issues such as maximizing resource utilization, continuous monitoring to ensure system reliability, and applying fault‐tolerance approach to handle occurrence of any failure.

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“…In a cloud‐based environment, it is necessary to maximize the resource utilization and to improve system load balance . Therefore, resource allocator module exists.…”

Section: The Proposed Architecturementioning

confidence: 99%

Section: Resource Allocator Modulementioning

confidence: 99%

Automated parallel GUI testing as a service for mobile applications

Ali

Maghawry

Badr

2018

J Software Evolu Process

View full text Add to dashboard Cite

show abstract

“…From the virtualization standpoint, the main concern for VM deployment seems to have been with scheduling strategies [14], but not with the chosen VM technology itself [15]. An exception can be made for the Kuo proposal [16], which bases its deployment on the OpenStack framework.…”

Section: Related Workmentioning

confidence: 99%

An agile container-based approach to TaaS

Verdugo¹,

Salvachiua

Huecas³

2017

2017 56th FITCE Congress

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Current cloud deployment scenarios imply a need for fast testing of user oriented software in diverse, heterogeneous and often unknown hardware and network environments, making it difficult to ensure optimal or reproducible in-site testing. The current paper proposes the use of container based lightweight virtualization with a ready-to-run, just-intime deployment strategy in order to minimize time and resources needed for streamlined multicomponent prototyping in PaaS systems. To that end, we will study a specific case of use consisting of providing end users with pre-tested custom prepackaged and preconfigured software, guaranteeing the viability of the aforementioned custom software, the syntactical integrity of the provided deployment system, the availability of needed dependencies as well as the sanity check of the already deployed and running software. From an architectural standpoint, by using standard, common use deployment packages as Chef or Puppet hosted in parallellizable workloads over readyto-run Docker images, we can minimize the time required for full-deployment multicomponent systems testing and validation, as well as wrap the commonly provided features via a user-accessible RESTful API. The proposed infrastructure is currently available and freely accessible as part of the FIWARE EU initiative, and is open to third party collaboration and extension from a FOSS perspective.

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“…To address this problem, many heuristic algorithms are applied to optimize the process of resource scheduling. Y. Zheng, et al [28] introduced VM scheduling strategies based on artificial intelligence to save energy, balance load and improve QoS performance. J. T. Tsai, et al [20] explored an improved differential evolution algorithm based on the proposed cost and time models in cloud computing environment to optimize task scheduling and resource allocation.…”

Section: Related Workmentioning

confidence: 99%

An Approach to Resource Scheduling based on User Expectation in Cloud Testing

Qian¹

2017

IJPE

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Cloud testing, with the features of automatic deployment, parallel submission, on-demand distribution and timely response, has been widely favored by many users. Therefore, it is crucial to reduce energy consumption, satisfy user requirement and timely response to user requests for resources, which are guaranteed by a good resource scheduling scheme. The requirements and benefits between user and provider of cloud testing are comprehensively measured in this work. On one hand, in order to meet the expectations of different users for the finish time and cost of their tasks, the definition of user expectation is introduced and then a dynamic pricing model is constructed to achieve the flexible conversion between time and cost. On the other hand, genetic algorithm is employed to implement resource scheduling in cloud testing, which can shorten the running time of all tasks on the cloud testing platform to improve the efficiency and reduce the load as greatly as possible. Finally, comparative experiments show that the scheme proposed in this work is feasible and efficient.

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VM scheduling strategies based on artificial intelligence in Cloud Testing

Cited by 8 publications

References 12 publications

Automated parallel GUI testing as a service for mobile applications

Automated parallel GUI testing as a service for mobile applications

An agile container-based approach to TaaS

An Approach to Resource Scheduling based on User Expectation in Cloud Testing

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