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

© 2017 Elsevier Ltd 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

The Need of an Optimal QoS Repository and Assessment Framework in Forming a Trusted Relationship in Cloud: A Systematic Review

© 2017 IEEE. Due to the cost-effectiveness and scalable features of the cloud the demand of its services is increasing every next day. Quality of Service (QOS) is one of the crucial factor in forming a viable Service Level Agreement (SLA) between a consumer and the provider that enable them to establish and maintain a trusted relationship with each other. SLA identifies and depicts the service requirements of the user and the level of service promised by provider. Availability of enormous service solutions is troublesome for cloud users in selecting the right service provider both in terms of price and the degree of promised services. On the other end a service provider need a centralized and reliable QoS repository and assessment framework that help them in offering an optimal amount of marginal resources to requested consumer. Although there are number of existing literatures that assist the interaction parties to achieve their desired goal in some way, however, there are still many gaps that need to be filled for establishing and maintaining a trusted relationship between them. In this paper we tried to identify all those gaps that is necessary for a trusted relationship between a service provider and service consumer. The aim of this research is to present an overview of the existing literature and compare them based on different criteria such as QoS integration, QoS repository, QoS filtering, trusted relationship and an SLA

Comparing time series with machine learning-based prediction approaches for violation management in cloud SLAs

© 2018 In cloud computing, service level agreements (SLAs) are legal agreements between a service provider and consumer that contain a list of obligations and commitments which need to be satisfied by both parties during the transaction. From a service provider's perspective, a violation of such a commitment leads to penalties in terms of money and reputation and thus has to be effectively managed. In the literature, this problem has been studied under the domain of cloud service management. One aspect required to manage cloud services after the formation of SLAs is to predict the future Quality of Service (QoS) of cloud parameters to ascertain if they lead to violations. Various approaches in the literature perform this task using different prediction approaches however none of them study the accuracy of each. However, it is important to do this as the results of each prediction approach vary according to the pattern of the input data and selecting an incorrect choice of a prediction algorithm could lead to service violation and penalties. In this paper, we test and report the accuracy of time series and machine learning-based prediction approaches. In each category, we test many different techniques and rank them according to their order of accuracy in predicting future QoS. Our analysis helps the cloud service provider to choose an appropriate prediction approach (whether time series or machine learning based) and further to utilize the best method depending on input data patterns to obtain an accurate prediction result and better manage their SLAs to avoid violation penalties

An Approach of QoS Evaluation for Web Services Design With Optimized Avoidance of SLA Violations

Quality of service (QoS) is an official agreement that governs the contractual commitments between service providers and consumers in respect to various nonfunctional requirements, such as performance, dependability, and security. While more Web services are available for the construction of software systems based upon service-oriented architecture (SOA), QoS has become a decisive factor for service consumers to choose from service providers who provide similar services. QoS is usually documented on a service-level agreement (SLA) to ensure the functionality and quality of services and to define monetary penalties in case of any violation of the written agreement. Consequently, service providers have a strong interest in keeping their commitments to avoid and reduce the situations that may cause SLA violations.However, there is a noticeable shortage of tools that can be used by service providers to either quantitively evaluate QoS of their services for the predication of SLA violations or actively adjust their design for the avoidance of SLA violations with optimized service reconfigurations. Developed in this dissertation research is an innovative framework that tackles the problem of SLA violations in three separated yet connected phases. For a given SOA system under examination, the framework employs sensitivity analysis in the first phase to identify factors that are influential to system performance, and the impact of influential factors on QoS is then quantitatively measured with a metamodel-based analysis in the second phase. The results of analyses are then used in the third phase to search both globally and locally for optimal solutions via a controlled number of experiments. In addition to technical details, this dissertation includes experiment results to demonstrate that this new approach can help service providers not only predicting SLA violations but also avoiding the unnecessary increase of the operational cost during service optimization

A centralised cloud services repository (CCSR) framework for optimal cloud service advertisement discovery from heterogenous web portals

© 2013 IEEE. A cloud service marketplace is the first point for a consumer to discovery, select and possible composition of different services. Although there are some private cloud service marketplaces, such as Microsoft Azure, that allow consumers to search service advertainment belonging to a given vendor. However, due to an increase in the number of cloud service advertisement, a consumer needs to find related services across the worldwide web (WWW). A consumer mostly uses a search engine such as Google, Bing, for the service advertisement discovery. However, these search engines are insufficient in retrieving related cloud services advertainments on time. There is a need for a framework that effectively and efficiently discovery of the related service advertisement for ordinary users. This paper addresses the issue by proposing a user-friendly harvester and a centralised cloud service repository framework. The proposed Centralised Cloud Service Repository (CCSR) framework has two modules - Harvesting as-a-Service (HaaS) and the service repository module. The HaaS module allows users to extract real-time data from the web and make it available to different file format without the need to write any code. The service repository module provides a centralised cloud service repository that enables a consumer for efficient and effective cloud service discovery. We validate and demonstrate the suitability of our framework by comparing its efficiency and feasibility with three widely used open-source harvesters. From the evaluative result, we observe that when we harvest a large number of services advertisements, the HaaS is more efficient compared with the traditional harvesting tools. Our cloud services advertisements dataset is publicly available for future research at: http://cloudmarketregistry.com/cloud-market-registry/home.html

Generic Methods for Adaptive Management of Service Level Agreements in Cloud Computing

The adoption of cloud computing to build and deliver application services has been nothing less than phenomenal. Service oriented systems are being built using disparate sources composed of web services, replicable datastores, messaging, monitoring and analytics functions and more. Clouds augment these systems with advanced features such as high availability, customer affinity and autoscaling on a fair pay-per-use cost model. The challenge lies in using the utility paradigm of cloud beyond its current exploit. Major trends show that multi-domain synergies are creating added-value service propositions. This raises two questions on autonomic behaviors, which are specifically ad- dressed by this thesis. The first question deals with mechanism design that brings the customer and provider(s) together in the procurement process. The purpose is that considering customer requirements for quality of service and other non functional properties, service dependencies need to be efficiently resolved and legally stipulated. The second question deals with effective management of cloud infrastructures such that commitments to customers are fulfilled and the infrastructure is optimally operated in accordance with provider policies. This thesis finds motivation in Service Level Agreements (SLAs) to answer these questions. The role of SLAs is explored as instruments to build and maintain trust in an economy where services are increasingly interdependent. The thesis takes a wholesome approach and develops generic methods to automate SLA lifecycle management, by identifying and solving relevant research problems. The methods afford adaptiveness in changing business landscape and can be localized through policy based controls. A thematic vision that emerges from this work is that business models, services and the delivery technology are in- dependent concepts that can be finely knitted together by SLAs. Experimental evaluations support the message of this thesis, that exploiting SLAs as foundations for market innovation and infrastructure governance indeed holds win-win opportunities for both cloud customers and cloud providers

An Approach of SLA Violation Prediction and QoS Optimization using Regression Machine Learning Techniques

Along with the acceptance of Service-Oriented Architecture (SOA) as a promising style of software design, the role that Quality of Service (QoS) plays in the success of SOA-based software systems has become much more significant than ever before. When QoS is documented as a Service-Level Agreement (SLA), it specifies the commitment between a service provider and a client, as well as monetary penalties in case of any SLA violations. To avoid and reduce the situations that may cause SLA violations, service providers need tools to intuitively analyze if their service design provokes SLA violations and to automatically guide them preventing SLA violations. Due to the dynamic nature of service interaction during the operation of SOA-based software systems, the avoidance of SLA violations requires prompt detection of potential violations before prevention takes place at real-time. To overcome the low latency time in practice, this thesis research develops an approach of using Machine Learning techniques to not only predict SLA violations but also prevent them by means of optimization. This research discusses the algorithm and framework, along with the results of the experiments, which will help to examine its usefulness for service providers working on the construction and refinement of services

SLA management of non-computational services.

El incremento en el uso de arquitecturas orientadas a servicios en los últimos 15 años ha propiciado la propuesta de numerosas técnicas para automatizar y dar soporte al uso de dichos servicios. Un elemento fundamental en la provisión de servicios es el Acuerdo de Nivel de Servicio (ANS), donde se formalizan los requisitos y garantías de consumidor y proveedor respecto del rendimiento del servicio. Las propuestas para servicios computacionales, además de proveer modelos formales para describirlos, proponen la automatización de las diferentes etapas del ciclo de vida del ANS, tales como la negociación de las garantías para crear un ANS, el despliegue de servicios basados en el ANS, o la gestión de los recursos para cumplir las garantías provistas en el mismo. Sin embargo, en los servicios tradicionales, no computacionales, es decir, los servicios que no son ejecutados por recursos computacionales, tales como los servicios de logística o de desarrollo de software, la gestión de sus ANSs todavía se realiza por medios ad-hoc. Así, las soluciones existentes no pueden ser reutilizadas por diferentes servicios. Y, en la mayoría de los casos, esta gestión se hace de manera manual (p.e. revisión de los objetivos acordados en los ANSs de servicios de transporte), por lo que la evaluación de estos ANSs es susceptible a errores y se suele retrasar respecto a la ejecución del servicio (p.e. cuando el ANS ha finalizado), por lo que no se pueden tomar acciones preventivas para evitar el incumplimiento del ANS o estas acciones no son rentables. En estos escenarios, aparecen, además, acuerdos marco para un periodo largo (p.e. 1 aõ), durante el cual pueden aparecen ANSs relacionados con éste para un periodo más específico y el análisis de la coherencia entre acuerdos marco y acuerdos específicos es complicada de hacer durante la ejecución del servicio. En esta tesis, nos proponemos automatizar parcialmente la gestión de los ANSs de servicios no computacionales. Así, por un lado, proponemos que los modelos para servicios computacionales se extiendan a servicios no computacionales, de manera que permitan describir la operativa del servicio y sus garantías. Y, por otro lado, basado en estos modelos, proporcionamos el diseño de operaciones para gestionar el ciclo de vida de los ANS. Concretamente, estas operaciones se basan en las fases de despligue y evaluación del ANS. De forma específica, esta tesis propone tres contribuciones principales. Primero, (A) extender iAgree para dar soporte al modelado de los ANS de servicios no computacionales. Segundo, (B) dar soporte al ciclo de vida de dichos ANS mediante la formalización de las operaciones citadas (configuración del servicio basada en el ANS y monitorización del mismo) y, a partir de estas operaciones, implementamos una arquitectura de referencia para estas operaciones. Y, por último, (C) proveemos el modelado de la relación entre acuerdos marco y específicos que relacione sus términos junto con la formalización de las operaciones para el análisis que aparecen entre ellos. Otros aspectos del ciclo de vida del servicio y del ANS, como la gestión de los recursos para mejorar el rendimiento del servicio o el uso de técnicas (como machine learning) para la predicción del cumplimiento de los ANSs están fuera del contexto de esta tesis, pero se plantean como futuras líneas de extensión. Este trabajo se ha basado en ANSs reales de diferentes dominios, tales como servicios de Transporte y Logística, proveedores de Cloud or outsourcing de desarrollo TIC, que se han utilizado para validar las propuestas. Además, las contribuciones presentadas se han aplicado en el contexto de proyectos reales de soporte de sistemas TIC.The rise of computational services in the last 15 years brought the proposal of a number of techniques to automate and support their enactment. One key element in services is the Service Level Agreement (SLA), where the requirements of service customer are matched with the performance levels from the service provider to define service level guarantees and related responsibilities. The proposals from computational domains are oriented to automate the different stages in the SLA Lifecycle, such as the negotiation of terms which will form the SLA, the deployment of services based on the SLA artifact or the management of computational resources to accomplish SLA goals on runtime. However, traditional non-computational services, that is, services which are not performed by computational resources, such as logistics or software development services, are still supported by ad-hoc mechanisms. Therefore, the existing solutions for the management of their SLAs cannot be reused for other services. This management is usually manually performed (e.g.: reviewing of the goals of an SLA in transport service), so their evaluation is error-prone and delayed regarding the service execution (e.g.: when the SLA is finished), so preemptive actions to avoid SLA violations cannot be taken or/and are expensive to perform. Furthermore, these SLAs are sometimes described on a long term basis (frame agreements), and related SLAs can appear for a shorter term (specific agreements) and the analysis of the validity among them is complex to perform on runtime. In this dissertation, we aim at partially automate the management of SLAs in noncomputational services. On the one hand, we suggest that existing models for computational services can be extended to non computational services and enable the description of the service operative and their guarantees. And, on the other hand, we provide a design for operations to partially support the SLA Lifecycle, based on the previous models. Specifically, these operations are mainly focused on the deployment and fulfillment stages of the SLA. Therefore, the contributions of this dissertation are three. First, (A) providing a model to describe Service Level Agreements of non computational services, as an extension of iAgree, an existing model for SLAs of computational services. Second side, (B) supporting the SLA Lifecycle with the design of the aforementioned operations (service configuration based on SLA and monitoring of SLA) and implementing a reference architecture for such operations. And, lastly, (C) providing a model for frame and specific agreements which relates their terms and formalises the analysis operations among them. Other related operations of the service lifecycle as the management of resources to improve service performance or the use of novel techniques (such as machine learning) to predict the SLA accomplishment are out of the scope of this thesis but planned as future line of extension. The current dissertation has been based on real SLAs from different domains, such as Transport & Logistics, public Cloud providers or IT Maintenance outsourcing, which have been used to validate the proposal. And, furthermore, the contributions have been applied in the context of real IT Maintenance outsourcing projects