A Self-adaptive hierarchical monitoring mechanism for Clouds

Katsaros, Georgios; Kousiouris, George; Gogouvitis, Spyridon V.; Kyriazis, Dimosthenis; Menychtas, Andreas; Varvarigou, Theodora

doi:10.1016/j.jss.2011.11.1043

Cited by 76 publications

(39 citation statements)

References 5 publications

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“…Constraints family (30) guarantees that exactly one local monitoring strategy is selected for each BC (note that "No Monitoring" is one of the possible local monitoring strategies, e.g., when no applicable monitors are available for some BCs). For example, assume that there are 10 possible local monitoring strategies for the video conversion service N 2 in Fig.…”

Section: Global Optimisationmentioning

confidence: 99%

“…Response time, among various QoS dimensions, is of particular significance in quality management for SBSs. The increase in the number of time-constrained applications in the cloud, e.g., interactive and multimedia SBSs, is also driving the needs for response time management for SBSs [30]. The management of response time is the basis for the management of other QoS dimensions.…”

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confidence: 99%

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Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

Han

Yang

et al. 2014

IIEEE Trans. Software Eng.

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Abstract-When operating in volatile environments, service-based systems (SBSs) that are dynamically composed from component services must be monitored in order to guarantee timely and successful delivery of outcomes in response to user requests. However, monitoring consumes resources and very often impacts on the quality of the SBSs being monitored. Such resource and system costs need to be considered in formulating monitoring strategies for SBSs. The critical path of a composite SBS, i.e., the execution path in the service composition with the maximum execution time, is of particular importance in cost-effective monitoring as it determines the response time of the entire SBS. In volatile operating environments, the critical path of an SBS is probabilistic, as every execution path can be critical with a certain probability, i.e., its criticality. As such, it is important to estimate the criticalities of different execution paths when deciding which parts of the SBS to monitor. Furthermore, cost-effective monitoring also requires management of the trade-off between the benefit and cost of monitoring. In this paper, we propose CriMon, a novel approach to formulating and evaluating monitoring strategies for SBSs. CriMon first calculates the criticalities of the execution paths and the component services of an SBS and then, based on those criticalities, generates the optimal monitoring strategy considering both the benefit and cost of monitoring. CriMon has two monitoring strategy formulation methods, namely local optimisation and global optimisation. In-lab experimental results demonstrate that the response time of an SBS can be managed cost-effectively through CriMon-based monitoring. The effectiveness and efficiency of the two monitoring strategy formulation methods are also evaluated and compared.

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Section: Global Optimisationmentioning

confidence: 99%

mentioning

confidence: 99%

Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

Han

Yang

et al. 2014

IIEEE Trans. Software Eng.

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“…Monitoring systems that use computing resources have been are search topic of interest for many years. Gregory et al [23] proposed a monitoring mechanism for computing resources in the cloud computing environment, as shown in Figure 3. However, their research does not go as far as suggesting a monitoring service tailored to the manufacturing system.…”

Section: Cloud Computing and Monitoring Systemmentioning

confidence: 99%

G-Cloud Monitor: A Cloud Monitoring System for Factory Automation for Sustainable Green Computing

Jeong

Park

2014

Sustainability

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Green and cloud computing (G-cloud) are new trends in all areas of computing. The G-cloud provides an efficient function, which enables users to access their programs, systems and platforms at anytime and anyplace. Green computing can also yield greener technology by reducing power consumption for sustainable environments. Furthermore, in order to apply user needs to the system development, the user characteristics are regarded as some of the most important factors to be considered in product industries. In this paper, we propose a cloud monitoring system to observe and manage the manufacturing system/factory automation for sustainable green computing. For monitoring systems, we utilized the resources in the G-cloud environments, and hence, it can reduce the amount of system resources and devices, such as system power and processes. In addition, we propose adding a user profile to the monitoring system in order to provide a user-friendly function. That is, this function allows system configurations to be automatically matched to the individual's requirements, thus increasing efficiency.

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“…To this end, [15] proposes a self-adaptive hierarchical monitoring mechanism for clouds. Implemented at the Platform as a Service layer, it allows monitoring the QoS parameters based on SLA for business benefits.…”

Section: Adapting Qos Management and Governance To Multi-cloud Systemsmentioning

confidence: 99%

Multi-dimensional Model Driven Policy Generation

Ouedraogo

Biennier

2014

Communications in Computer and Information Science

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Abstract. As Cloud Computing provides agile and scalable IT infrastructure, QoS-assured services and customizable computing environment, it increases the call for agile and dynamic deployment and governance environments over multi-cloud infrastructure. By now, governance and Non Functional Properties (such as security, QoS…) are managed in a static way, limiting the global benefits of deploying service-based information system over multi-cloud environments. To overcome this limit, we propose a contextualised policy generation process to allow both an agile management NFP in a multi-cloud context and a secured deployment of the service-based information system. The last step of this Model Driven Policy Engineering approach uses policies as Model@runtime to select, compose, deploy and orchestrate NFP management functions depending on the exact execution context. Moreover, a dynamic governance loop including autonomic KPI management is used to control continuously the governance results.

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A Self-adaptive hierarchical monitoring mechanism for Clouds

Cited by 76 publications

References 5 publications

Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

G-Cloud Monitor: A Cloud Monitoring System for Factory Automation for Sustainable Green Computing

Multi-dimensional Model Driven Policy Generation

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