Integrated Risk Analysis for a Commercial Computing Service in Utility Computing

Recent technological advances in Grid computing enable the virtualization and dynamic delivery of computing services on demand to realize utility computing. In utility computing, computing services will always be available to the users whenever the need arises, similar to the availability of real-world utilities, such as electrical power, gas, and water. With this new outsourcing service model, users are able to define their service needs through Service Level Agreements (SLAs) and only have to pay when they use the services. They do not have to invest on or maintain computing infrastructures themselves and are not constrained to specific computing service providers. Thus, a commercial computing service will face two new challenges: (i) what are the objectives or goals it needs to achieve in order to support the utility computing model, and (ii) how to evaluate whether these objectives are achieved or not. To address these two new challenges, this paper first identifies four essential objectives that are required to support the utility computing model: (i) manage wait time for SLA acceptance, (ii) meet SLA requests, (iii) ensure reliability of accepted SLA, and (iv) attain profitability. It then describes two evaluation methods that are simple and intuitive: (i) separate and (ii) integrated risk analysis to analyze the effectiveness of resource management policies in achieving the objectives. Evaluation results based on simulation successfully demonstrate the applicability of separate and integrated risk analysis to assess policies in terms of the objectives. These evaluation results which constitute an a posteriori risk analysis of policies can later be used to generate an a priori risk analysis of policies by identifying possible risks for future utility computing situations.     

Formulating and managing viable SLAs in cloud computing from a small to medium service provider's viewpoint: A state-of-the-art review

In today's competitive world, service providers need to be customer-focused and proactive in their marketing strategies to create consumer awareness of their services. Cloud computing provides an open and ubiquitous computing feature in which a large random number of consumers can interact with providers and request services. In such an environment, there is a need for intelligent and efficient methods that increase confidence in the successful achievement of business requirements. One such method is the Service Level Agreement (SLA), which is comprised of service objectives, business terms, service relations, obligations and the possible action to be taken in the case of SLA violation. Most of the emphasis in the literature has, until now, been on the formation of meaningful SLAs by service consumers, through which their requirements will be met. However, in an increasingly competitive market based on the cloud environment, service providers too need a framework that will form a viable SLA, predict possible SLA violations before they occur, and generate early warning alarms that flag a potential lack of resources. This is because when a provider and a consumer commit to an SLA, the service provider is bound to reserve the agreed amount of resources for the entire period of that agreement – whether the consumer uses them or not. It is therefore very important for cloud providers to accurately predict the likely resource usage for a particular consumer and to formulate an appropriate SLA before finalizing an agreement. This problem is more important for a small to medium cloud service provider which has limited resources that must be utilized in the best possible way to generate maximum revenue. A viable SLA in cloud computing is one that intelligently helps the service provider to determine the amount of resources to offer to a requesting consumer, and there are number of studies on SLA management in the literature. The aim of this paper is two-fold. First, it presents a comprehensive overview of existing state-of-the-art SLA management approaches in cloud computing, and their features and shortcomings in creating viable SLAs from the service provider's viewpoint. From a thorough analysis, we observe that the lack of a viable SLA management framework renders a service provider unable to make wise decisions in forming an SLA, which could lead to service violations and violation penalties. To fill this gap, our second contribution is the proposal of the Optimized Personalized Viable SLA (OPV-SLA) framework which assists a service provider to form a viable SLA and start managing SLA violation before an SLA is formed and executed. The framework also assists a service provider to make an optimal decision in service formation and allocate the appropriate amount of marginal resources. We demonstrate the applicability of our framework in forming viable SLAs through experiments. From the evaluative results, we observe that our framework helps a service provider to form viable SLAs and later to manage them to effectively minimize possible service violation and penalties.     

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

Due to the large variety in computing resources and, consequently, the large number of different types of service level agreements (SLAs), computing resource markets face the problem of a low market liquidity. Restricting the number of different resource types to a small set of standardized computing resources seems to be the appropriate solution to counteract this problem. Standardized computing resources are defined through an SLA template. An SLA template defines the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing research results have only introduced static SLA templates so far, the SLA templates cannot reflect changes in user needs and market structures. To address this shortcoming, we present a novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings of users. It allows Cloud users to define mappings between a public SLA template, which is available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates are adapted to the demand of Cloud users, we also analyze the costs and benefits of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, we investigate how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics within adaptation methods allows balancing the costs and benefits of the SLA mapping approach.     

SLA negotiation and enforcement policies for revenue maximization and client classification in cloud providers

In Cloud Computing markets, owners of computing resources negotiate with their potential clients to sell computing power. The terms of the Quality of Service (QoS) to be provided as well as the economic conditions are established in a Service-Level Agreement (SLA). The common objective of a Cloud provider is to maximize its economic profit. However, there are situations in which providers must differentiate the SLAs with respect to the type of client that is willing to access the resources or the agreed QoS, e.g. when the hardware resources are shared between users of the company that own the resources and external users.This article proposes two sets of policies to manage SLAs with respect to the business objectives of a Cloud provider: Revenue Maximization or classification of clients. The criterion to classify clients is established according to the relationship between client and provider (external user, internal or another privileged relationship) and the QoS that the client purchases (cheap contracts or extra QoS by paying an extra fee). The validity of the policies is demonstrated through exhaustive experiments.     

An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments

Cloud computing is a newly emerged computing infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business process management and virtualization. An important characteristic of Cloud-based services is the provision of non-functional guarantees in the form of Service Level Agreements (SLAs), such as guarantees on execution time or price. However, due to system malfunctions, changing workload conditions, hard- and software failures, established SLAs can be violated. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are needed. In this paper we present a self-manageable architecture for SLA-based service virtualization that provides a way to ease interoperable service executions in a diverse, heterogeneous, distributed and virtualized world of services. We demonstrate in this paper that the combination of negotiation, brokering and deployment using SLA-aware extensions and autonomic computing principles are required for achieving reliable and efficient service operation in distributed environments.     

Resource management for bursty streams on multi-tenancy cloud environments

The number of applications that need to process data continuously over long periods of time has increased significantly over recent years. The emerging Internet of Things and Smart Cities scenarios also confirm the requirement for real time, large scale data processing. When data from multiple sources are processed over a shared distributed computing infrastructure, it is necessary to provide some Quality of Service (QoS) guarantees for each data stream, specified in a Service Level Agreement (SLA). SLAs identify the price that a user must pay to achieve the required QoS, and the penalty that the provider will pay the user in case of QoS violation. Assuming maximization of revenue as a Cloud provider’s objective, then it must decide which streams to accept for storage and analysis; and how many resources to allocate for each stream. When the real-time requirements demand a rapid reaction, dynamic resource provisioning policies and mechanisms may not be useful, since the delays and overheads incurred might be too high. Alternatively, idle resources that were initially allocated for other streams could be re-allocated, avoiding subsequent penalties. In this paper, we propose a system architecture for supporting QoS for concurrent data streams to be composed of self-regulating nodes. Each node features an envelope process for regulating and controlling data access and a resource manager to enable resource allocation, and selective SLA violations, while maximizing revenue. Our resource manager, based on a shared token bucket, enables: (i) the re-distribution of unused resources amongst data streams; and (ii) a dynamic re-allocation of resources to streams likely to generate greater profit for the provider. We extend previous work by providing a Petri-net based model of system components, and we evaluate our approach on an OpenNebula-based Cloud infrastructure.     

Non-Intrusive Elastic Query Processing in the Cloud

Cloud computing is a very promising paradigm of service-oriented computing. One major benefit of cloud computing is its elasticity, i.e., the system＇s capacity to provide and remove resources automatically at runtime. For that, it is essential to design and implement an efficient and effective technique that takes full advantage of the system＇s potential flexibility. This paper presents a non-intrusive approach that monitors the performance of relational database management systems in a cloud infrastructure, and automatically makes decisions to maximize the efficiency of the provider＇s environment while still satisfying agreed upon ＂service level agreements＂ （SLAs）. Our experiments conducted on Amazon＇s cloud infrastructure, confirm that our technique is capable of automatically and dynamically adjusting the system＇s allocated resources observing the SLA.     

SLA based resource allocation policies in autonomic environments

Nowadays, large service centers provide computational capacity to many customers by sharing a pool of IT resources. The service providers and their customers negotiate utility based Service Level Agreement (SLA) to determine the costs and penalties on the base of the achieved performance level. The system is often based on a multi-tier architecture to serve requests and autonomic techniques have been implemented to manage varying workload conditions. The service provider would like to maximize the SLA revenues, while minimizing its operating costs. The system we consider is based on a centralized network dispatcher which controls the allocation of applications to servers, the request volumes at various servers and the scheduling policy at each server. The dispatcher can also decide to turn ON or OFF servers depending on the system load. This paper designs a resource allocation scheduler for such multi-tier autonomic environments so as to maximize the profits associated with multiple class SLAs. The overall problem is NP-hard. We develop heuristic solutions by implementing a local-search algorithm. Experimental results are presented to demonstrate the benefits of our approach.     

A Service Level Agreement Language for Dynamic Electronic Services

This paper proposes a novel language for Service Level Agreements (SLAs) for dynamic and spontaneous electronic services. In a cross-organizational setting, it is important for customers of a service to obtain, monitor and enforce quality of service (QoS) guarantees by service providers, usually expressed in the form of SLAs. Since the supervision and management of SLAs and the provisioning of corresponding systems should be automated for economic reasons, we need a formal language to define an SLA. If, moreover, providers and customers want to sign custom-made SLAs, the SLA language, correspondingly, must provide a large degree of flexibility.The SLA language described in this paper aims at providing the needed flexibility by means of an XML-based representation and a runtime system for SLAs. Using this language, parties to an SLA can describe how parameters are measured and computed from raw metrics, the guarantees they want with respect to those parameters and the involvement of third parties to, e.g., independently verify SLA compliance.     

Fairness in secure computing protocols based on incentives

Cloud computing is based on utility and consumption of computer resources. To solve the security issues in cloud computing, secure computing protocols are often used. Recently, rational parties as a new kind of parties are proposed, who wish to maximize their utilities in secure computing protocols. The utility definitions in most previous rational secure computing protocols derive from prisoner’s dilemma game (PD game). In two-party rational computing protocols, parties decide to send their shares according to their utilities. Recently, we revisit the incentives for rational parties in secure computing protocols and give new utility definitions according to them. We find that the new utility definition is not similar to PD game any more. We discuss two-party and multi-party cases, respectively, and prove that parties have incentives to send their share to others. Furthermore, we also prove that parties can maximize their utilities in both cases.     

A fuzzy Grid-QoS framework for obtaining higher grid resources availability

A computational grid ensures the on-demand delivery of computing resources, in a security-aware, shared, scalable, and standards-based computing environment. A major concern is how to evolve a general and an encompassing framework that guarantees users’ satisfaction measured as Quality of Services (QoS). To obtain a higher QoS, effective QoS perceived by subscribers (users) must conform to specified QoS agreements in the Service Level Agreements (SLAs) document—a legal contract between the Grid Services Provider (GSP) and users. Sometimes the effective user QoS does not conform to the specifications in the SLA because of the vagueness in linguistic definitions in the SLA. Existing approaches overcommitted resources to meet QoS. In this paper, we propose a fuzzy logic framework for calibrating a grid resources user-QoS that addresses the vagueness in linguistic definitions of the SLA document without overcommitting grid resources.     

Fault-tolerant Service Level Agreement lifecycle management in clouds using actor system

Automated Service Level Agreements (SLAs) have been proposed for cloud services as contracts used to record the rights and obligations of service providers and their customers. Automation refers to the electronic formalized representation of SLAs and the management of their lifecycle by autonomous agents. Most recently, SLA automated management is becoming increasingly of importance. In previous work, we have elaborated a utility architecture that optimizes resource deployment according to business policies, as well as a mechanism for optimization in SLA negotiation. We take all that a step further with the application of actor systems as an appropriate theoretical model for fine-grained, yet simplified and practical, monitoring of massive sets of SLAs. We show that this is a realistic approach for the automated management of the complete SLA lifecycle, including negotiation and provisioning, but focus on monitoring as the driver of contemporary scalability requirements. Our proposed work separates the agreement’s fault-tolerance concerns and strategies into multiple autonomous layers that can be hierarchically combined into an intuitive, parallelized, effective and efficient management structure.     

Dynamic SLAs management in service oriented environments

The increasing adoption of service oriented architectures across different administrative domains, forces service providers to use effective mechanisms and strategies of resource management in order for them to be able to guarantee the quality levels their customers demands during service provisioning. Service level agreements (SLA) are the most common mechanism used to establish agreements on the quality of a service (QoS) between a service provider and a service consumer. The WS-Agreement specification, developed by the Open Grid Forum, is a Web Service protocol to establish agreements on the QoS level to be guaranteed in the provision of a service. The committed agreement cannot be modified during service provision and is effective until all activities pertaining to it are finished or until one of the signing party decides to terminate it. In B2B scenarios where several service providers are involved in the composition of a service, and each of them plays both the parts of provider and customer, several one-to-one SLAs need to be signed. In such a rigid context the global QoS of the final service can be strongly affected by any violation on each single SLA. In order to prevent such violations, SLAs need to adapt to any possible needs that might come up during service provision. In this work we focus on the WS-Agreement specification and propose to enhance the flexibility of its approach. We integrate new functionality to the protocol that enable the parties of a WS-Agreement to re-negotiate and modify its terms during the service provision, and show how a typical scenario of service composition can benefit from our proposal.     

云环境下基于SLA的优化资源分配研究

针对云计算环境下如何高效分配资源,实现资源供应者利润最大化这一难题,提出了一种基于服务级别协议（SLA）的动态云资源分配策略。该策略通过将SLA中的计算力、网络带宽、数据存储等属性作为优化参数,构造了一种服务请求与资源的映射模型,同时设计相应的效用函数,并结合改进的与模拟退火算法相融合的混合粒子群算法（SA-PSO）,实现云环境下的优化资源分配。实验分析结果表明,基于SLA参数的SA-PSO算法具有更好的全局最优值,在给定虚拟资源相同情况下,调用该算法完成用户任务实现的利润更高。     

Brokering of risk‐aware service level agreements in grids

Service level agreements (SLAs) are facilitators for widening the commercial uptake of Grid technology. They provide explicit statements of expectation and obligation between service consumers and providers. However, without the ability to assess the probability that an SLA might fail, commercial uptake will be restricted, since neither party will be willing to agree. Therefore, risk assessment mechanisms are critical to increase confidence in Grid technology usage within the commercial sector. This paper presents an SLA brokering mechanism with risk assessment support, which evaluates the probability of SLA failure. WS‐Agreement and risk metrics are used to facilitate SLA creation between service consumers and providers within a typical Grid resource usage scenario. An evaluation is conducted to examine risk models, the performance of the broker's implementation as well as a comparison of its capabilities against similar SLA‐based solutions from the literature. Copyright © 2011 John Wiley & Sons, Ltd.     

Feedback-based optimization of a private cloud

The optimization problem addressed by this paper involves the allocation of resources in a private cloud such that cost to the provider is minimized (through the maximization of resource sharing) while attempting to meet all client application requirements (as specified in the SLAs). At the heart of any optimization based resource allocation algorithm, there are two models: one that relates the application level quality of service to the given set of resources and one that maps a given service level and resource consumption to profit metrics. In this paper we investigate the optimization loop in which each application’s performance model is dynamically updated at runtime to adapt to the changes in the system. These changes could be perturbations in the environment that had not been included in the model. Through experimentation we show that using these tracking models in the optimization loop will result in a more accurate optimization and thus result in the generation of greater profit.     

Optimal precomputation for mapping service level agreements in grid computing

A complicated task running on the grid system is usually made up of many services, each of which typically offers a better service quality at a higher cost. Mapping service level agreements (SLAs) optimally is to find the most appropriate quality level for each service such that the overall SLA of a task is achieved at the minimum cost. This paper considers mapping the execution time SLA in the case of the discrete cost function, which is an NP-hard problem. Due to the high computation of mapping SLAs, we propose a precomputation scheme that makes the selection of each individual service level in advance for every possible SLA requirement, which can reduce the request response time greatly. We use a (1+ε)-approximation method, whose solution for any time bound is at most (1+ε) times of the optimal cost. Simulation results demonstrate the superiority of our method compared with others.     

The WSLA Framework: Specifying and Monitoring Service Level Agreements for Web Services

We describe a novel framework for specifying and monitoring Service Level Agreements (SLA) for Web Services. SLA monitoring and enforcement become increasingly important in a Web Service environment where enterprise applications and services rely on services that may be subscribed dynamically and on-demand. For economic and practical reasons, we want an automated provisioning process for both the service itself as well as the SLA managment system that measures and monitors the QoS parameters, checks the agreed-upon service levels, and reports violations to the authorized parties involved in the SLA management process. Our approach to these issues is presented in this paper. The Web Service Level Agreement (WSLA) framework is targeted at defining and monitoring SLAs for Web Services. Although WSLA has been designed for a Web Services environment, it is applicable as well to any inter-domain management scenario, such as business process and service management, or the management of networks, systems and applications in general. The WSLA framework consists of a flexible and extensible language based on XML Schema and a runtime architecture comprising several SLA monitoring services, which may be outsourced to third parties to ensure a maximum of objectivity. WSLA enables service customers and providers to unambiguously define a wide variety of SLAs, specify the SLA parameters and the way they are measured, and relate them to managed resource instrumentations. Upon receipt of an SLA specification, the WSLA monitoring services are automatically configured to enforce the SLA. An implementation of the WSLA framework, termed SLA Compliance Monitor, is publicly available as part of the IBM Web Services Toolkit.     

Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems

Resource management remains one of the main issues of cloud computing providers because system resources have to be continuously allocated to handle workload fluctuations while guaranteeing Service Level Agreements (SLA) to the end users. In this paper, we propose novel capacity allocation algorithms able to coordinate multiple distributed resource controllers operating in geographically distributed cloud sites. Capacity allocation solutions are integrated with a load redirection mechanism which, when necessary, distributes incoming requests among different sites. The overall goal is to minimize the costs of allocated resources in terms of virtual machines, while guaranteeing SLA constraints expressed as a threshold on the average response time. We propose a distributed solution which integrates workload prediction and distributed non-linear optimization techniques. Experiments show how the proposed solutions improve other heuristics proposed in literature without penalizing SLAs, and our results are close to the global optimum which can be obtained by an oracle with a perfect knowledge about the future offered load.     

QoS in grid computing

Grid computing is already a mainstream paradigm for resource-intensive scientific applications, but it also promises to become the future model for enterprise applications. The grid enables resource sharing and dynamic allocation of computational resources, thus increasing access to distributed data, promoting operational flexibility and collaboration, and allowing service providers to scale efficiently to meet variable demands. Large-scale grids are complex systems composed of thousands of components from disjoined domains. Planning the capacity to guarantee quality of service (QoS) in such environments is a challenge because global service-level agreements (SLAs) depend on local SLAs. We provide a motivating example for grid computing in an enterprise environment and then discuss the how resource allocation affects SLAs.