Cost–benefit analysis of an SLA mapping approach for defining standardized Cloud computing goods

2013 IEEE Seventh International Symposium on Service-Oriented System Engineering

Brandić

Altmann

2013

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

Section: Standardized Resources In Electronic Markets: An Overviewmentioning

confidence: 99%

“…The adaptation method named "maximum method" [30] is applied and a set of new public SLA templates is created (or the existing set updated). As described in [8], unlike private SLA templates, a public SLA template defines single parameter values for SLOs instead of ranges of acceptable values.…”

Section: A Simulation Environment and Testbedmentioning

confidence: 99%

Maximizing Liquidity in Cloud Markets through Standardization of Computational Resources

2013 IEEE Seventh International Symposium on Service-Oriented System Engineering

Brandić

Altmann

2013

“…These include low market liquidity (caused by broad resource variability and a low number of market participants) [23], a fragmented array of independent providers, and few standard mechanisms for unilateral provider adoption and use. In order to address these challenges and create a Cloud marketplace, a Cloud market should be dynamic and adapt to the current needs of its participants (consumers and providers) as well as address the impact(s) these requirements have upon the market itself.…”

Section: Vision: a Self-aware Autonomic Cloud Market Platformmentioning

confidence: 99%

Towards Self-Awareness in Cloud Markets: A Monitoring Methodology

2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing

Haas

Caton

et al. 2011

Self Cite

Abstract-Currently, the Cloud landscape is a fragmented, static and shapeless market that hinders the paradigm's ability to fulfil its promise of ubiquitous computing on tap and as a commodity. In this paper, we present our vision of an autonomic self-aware Cloud market platform, and argue that autonomic market platforms for Clouds can step up to the challenge of today's status quo. As our first steps towards achieving this vision, we present a market monitoring methodology, which includes a series of realistic market goals, sets of extractable metrics from a market platform and how to map (i.e. combine and transform) metrics to access goal performance such that autonomic adaption of the market could be undertaken. We have extended a known market simulator for distributed infrastructures (GridSim) with relevant sensors. To demonstrate the usefulness of our approach, we simulate a sudden cease in demand for goods in our market platform.

“…Many electronic marketplaces suffer from challenging situations [3]. Namely, due to the static nature of existing Cloud markets, they cannot react on dynamic change of user requirements.…”

Section: Introductionmentioning

confidence: 99%

“…However, the approach has also several shortcomings. Namely, after the new public SLA templates are derived, users must create additional SLA mappings before using them, which incurs cost [3]. As a result, although new public SLA templates reflect their requirements in a larger extent, users might prefer keeping the old public SLA templates in order to avoid additional cost.…”

Section: Introductionmentioning

confidence: 99%

Cost-Efficient Utilization of Public SLA Templates in Autonomic Cloud Markets

2011 Fourth IEEE International Conference on Utility and Cloud Computing

Maurer

Emeakaroha

et al. 2011

Abstract-Dynamic and self-adaptable markets are fundamental for the successful implementation of the Cloud computing paradigm where computing resources are provided on demand and dynamically to the heterogeneous user base. Usually, in Cloud markets, contracts between traders are established using Service Level Agreements (SLAs), which include objectives of service usage. However, Cloud markets face challenges, which are usually not evident in other market types, such as non-standardized goods and large variety of resource types offered on the market, resulting in low number of matches of consumers' bids and providers' asks. Moreover, existing Cloud market mechanisms are usually static and cannot react on dynamic change of user requirements. To counteract these problems, we propose an adaptive approach for autonomically deriving public SLA templates (i.e., templates for generation of electronic contracts) based on user requirements. Although this approach brings many benefits, it also incurs cost to users, since they must adapt specifications of their requirements in order to match automatically generated public SLA templates. In this paper, we reduce this cost by autonomically modifying specifications of user requirements. We introduce a method for adapting public SLA templates not only in respect to definitions of SLA attributes, but also to attribute values. Based on an appropriate utility and cost model, we evaluate the approach and show that it significantly improves the performance of the adaptive SLA template technique.