Towards Self-Awareness in Cloud Markets: A Monitoring Methodology

Breskovic, Ivan; Haas, Christian; Caton, Simon; Brandić, Ivona

doi:10.1109/dasc.2011.38

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…Early theoretical work, inspired by Paul Horn's autonomic computing 'manifesto' [13] and referring to the original 'self-*' characteristics of autonomic systems, served as groundwork for a wide range of prototypical implementations of self-managing mechanisms for various computer system structures, including service--based applications and clouds [7]. Existing self-adaptation mechanisms typically implement control feedback loops, such as MAPE-K 7 [16] or CADA 8 [11], where the monitoring activity acts as a trigger for adaptation: whenever monitored variables move beyond pre-specified bounds, this triggers adaptation (for example, re-balancing of workloads) in an attempt to restore normality.…”

Section: Monitoring and Adaptationmentioning

confidence: 99%

Towards a framework for monitoring cloud application platforms as sensor networks

2014

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With the continued growth in software environments on cloud application platforms, self-management at the Platform-as-a-Service (PaaS) level has become a pressing concern, and the run-time monitoring, analysis and detection of critical situations are all fundamental requirements if we are to achieve autonomic behaviour in complex PaaS environments. In this paper we focus on cloud application platforms offering their customers a range of generic built-in re-usable services. By identifying key characteristics of these complex dynamic systems, we compare cloud application platforms to distributed sensor networks, and investigate the viability of exploiting these similarities with a case study. We treat cloud data storage services as "virtual" sensors constantly emitting monitoring data, such as numbers of connections and storage space availability, which are then analysed by the central component of a monitoring framework so as to detect and react to SLA violations. We discuss the potential benefits, as well as some shortcomings, of adopting this approach.

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Section: Monitoring and Adaptationmentioning

confidence: 99%

Towards a framework for monitoring cloud application platforms as sensor networks

2014

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“…Due to the large variety in services and vast number of service providers, the Cloud market is currently fragmented and inefficient [3], [4]. To counteract this issue, electronic marketplaces for trading Cloud services were introduced with the goal of facilitating trading in the heterogeneous environment.…”

Section: Introductionmentioning

confidence: 99%

“…However, today's Cloud landscape is static and cannot adequately adapt to the active user participation, i.e., dynamic user base and changes in user requirements for services [4], [5], [6]. In particular, due to the large variety of Cloud services and the vast number of market participants, Cloud marketplaces often suffer from low liquidity, i.e., the probability to sell or purchase a service, thus disadvantaging new providers and repelling potential consumers [4]. Moreover, although most of the existing marketplaces use Service Level Agreements (SLAs) to express and negotiate user requirements and offers for services, there exists no general standard for their specification.…”

Section: Introductionmentioning

confidence: 99%

Automatic SLA Matching and Provider Selection in Grid and Cloud Computing Markets

Redl

Breskovic

Brandić

et al. 2012

2012 ACM/IEEE 13th International Conference on Grid Computing

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Abstract-Cloud computing is a novel computing paradigm that offers data, software, and hardware services in a manner similar to traditional utilities such as water, electricity, and telephony. Usually, in Cloud and Grid computing, contracts between traders are established using Service Level Agreements (SLAs), which include objectives of service usage. However, due to the rapidly growing number of service offerings and the lack of a standard for their specification, manual service selection is a costly task, preventing the successful implementation of ubiquitous computing on demand. In order to counteract these issues, automatic methods for matching SLAs are necessary. In this paper, we introduce a method for finding semantically equal SLA elements from differing SLAs by utilizing several machine learning algorithms. Moreover, we utilize this method to enable automatic selection of optimal service offerings for Cloud and Grid users. Finally, we introduce a framework for automatic SLA management, present a simulation-based evaluation, and demonstrate several significant benefits of our approach for Cloud and Grid users.

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“…Another example is the self-organizing resource allocation mechanism for dynamic application layer networks [43]. The largest step towards this vision, however, is proposed by Breskovic et al [10], [16], who use the autonomic MAPE loop in the context of electronic markets to automatically adapt the market platform to changed environmental conditions based upon a given concept of "performance". As possible form of adaptations, the authors specify market's institutional (i.e., economical) properties (e.g., pricing rules and allocation policies) and properties and the underlying software/hardware infrastructure.…”

Section: Cloud Markets In Researchmentioning

confidence: 99%

Maximizing Liquidity in Cloud Markets through Standardization of Computational Resources

Breskovic

Brandić

Altmann

2013

2013 IEEE Seventh International Symposium on Service-Oriented System Engineering

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Abstract-Low liquidity in cloud markets can result in market instability and inefficiency, preventing the successful implementation of ubiquitous computing on demand. To circumvent this issue, it has been suggested to channel demand and supply into a limited number of standardized services. These standardized services can even be automatically adapted to user requirements with the goal of continuously improving market performance. In this paper, we focus on answering how many standardized services should be placed in the market. This work is based on a new definition of liquidity for cloud resources, which in turn has been derived from liquidity definitions of financial markets. Using a simulation framework, we evaluate our method for estimating the optimal quantity of standardized services with respect to market liquidity and demonstrate the benefits of this approach in terms of increase in market efficiency and decrease in users' cost of participation in the market. The methods presented in this paper have the potential to be applied in other electronic markets as well.Keywords-Service level agreement, electronic markets, cloud economics, autonomic computing, standardized goods, market modeling, market liquidity, IT services I. INTRODUCTION Common to utility computing, cloud computing and grid computing is that they offer computational resources (e.g., software, hardware and computing platform services) in a manner similar to utilities, such as water, electricity and telephony, without regard to where the services are hosted or how they are delivered [4], [15]. However, the current cloud market is fragmented and static, hindering the paradigm's ability to fulfill its promise of ubiquitous computing on demand and as a commodity. In order to address this issue, electronic markets for trading and/or allocating computational resources (i.e., grid and cloud services) have been proposed [1], [38].In cloud markets, computational services are described by service parameters and quality of service (QoS) objectives. Each setting of a service, i.e., configuration of parameters, desired values of QoS objectives, and combinations of these elements, defines a new service (also called "computational resource"). Due to a great number of available settings, markets suffer from a vast diversity and heterogeneity of computational resources.In addition to this, computational resources are characterized by a high dynamism and a high fungibility. Resource dynamism is a result of a large resource variability, a dynamic user base, diverse user behavior in the market, and the

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Towards Self-Awareness in Cloud Markets: A Monitoring Methodology

Cited by 12 publications

References 27 publications

Towards a framework for monitoring cloud application platforms as sensor networks

Towards a framework for monitoring cloud application platforms as sensor networks

Automatic SLA Matching and Provider Selection in Grid and Cloud Computing Markets

Maximizing Liquidity in Cloud Markets through Standardization of Computational Resources

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