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

Modèle de confiance et ontologie probabiliste pilotés par réseaux bayésiens pour la gestion des accords de services dans l’environnement de services infonuagiques

L’infonuage est un nouveau paradigme de services informatiques disponibles à la demande qui a connu une croissance fulgurante au cours de ces dix dernières années. Le fournisseur du modèle de déploiement public des services infonuagiques décrit le service à fournir, le prix, les pénalités en cas de violation des spécifications à travers un document. Ce document s’appelle le contrat de niveau de service (SLA). La signature de ce contrat par le client et le fournisseur scelle la garantie de la qualité de service à recevoir. Ceci impose au fournisseur de gérer efficacement ses ressources afin de respecter ses engagements. Malheureusement, la violation des spécifications du SLA se révèle courante, généralement en raison de l’incertitude sur le comportement du client qui peut produire un nombre variable de requêtes vu que les ressources lui semblent illimitées. Ce comportement peut, dans un premier temps, avoir un impact direct sur la disponibilité du service. Dans un second temps, des violations à répétition risquent d'influer sur le niveau de confiance du fournisseur et sur sa réputation à respecter ses engagements. Pour faire face à ces problèmes, nous avons proposé un cadre d’applications piloté par réseau bayésien qui permet, premièrement, de classifier les fournisseurs dans un répertoire en fonction de leur niveau de confiance. Celui-ci peut être géré par une entité tierce. Un client va choisir un fournisseur dans ce répertoire avant de commencer à négocier le SLA. Deuxièmement, nous avons développé une ontologie probabiliste basée sur un réseau bayésien à entités multiples pouvant tenir compte de l’incertitude et anticiper les violations par inférence. Cette ontologie permet de faire des prédictions afin de prévenir des violations en se basant sur les données historiques comme base de connaissances. Les résultats obtenus montrent l’efficacité de l’ontologie probabiliste pour la prédiction de violation dans l’ensemble des paramètres SLA appliqués dans un environnement infonuagique.Cloud Computing is a new paradigm of IT on-demand services which has experienced tremendous growth over the past decade. The provider of Cloud computing services describes the service to be provided, its cost, and penalties for service violations within a document. This document is called Service Level Agreement (SLA). The signature of this contract by the customer and the provider guarantees the quality of service received by the customer. It also entails the provider to manage its resources efficiently to meet its commitments. Unfortunately, the SLA violation is common; it is usually caused by uncertainty about customer behavior that can make variable number of requests assuming that resources are boundless. This behavior may have an impact on the availability of the service, thus its related SLA. Repeated SLA violations will definitively have an impact on the trust level that the customer has about the provider that might no longer enjoys a good reputation in meeting its commitments. To cope with these problems, we have proposed a Framework driven by a Bayesian network that allows, first, to classify the suppliers in a Cloud directory according to their trust level. This directory can be managed by a third party entity, in which a client will choose a provider before starting SLA negotiation. Secondly, we have developed a probabilistic ontology, based on a Multi-Entity Bayesian network, which takes into account uncertainty, in the customer behavior, and makes predictions by inference; these predictions help preventing SLA violations based on historical data.. The results show the effectiveness of the probabilistic ontology for the prediction of SLA violations in a Cloud Computing environment

ADVANCED SLA MANAGEMENT IN CLOUD COMPUTING

The advent of high-performance technologies and the increase in volume of data used by organizations led to the need for migration from an internal structure to Cloud environment. The continuous development of tools, methods and techniques have expanded the understanding of the various functions, structures and processes related to Cloud Computing. However, the increase in computing power led to the development and use of more complex models, including this scope the complexity of Service Level Agreements (SLA). The need for understanding at a high level of SLAs established between customers and service providers in Cloud led to different studies on the definition and standardization of these agreements. Nowadays, cloud computing technologies are becoming more and more popular, especially with respect to data storage. However, the processes used to determine the Cloud Service Agreements do not consider the final customer\u2019s needs, considering only the supply capacity of the service provider. For these reasons, the development of service agreements that meets the needs of customers should be designed in order to increase the usability of Cloud environments, and enabling the discovery of new areas of application in accordance with market demand. In this context, the use of ontologies that describes the information that composes each type of service, and thus enable an understanding of the agreements reached, is configured as an approach to be considered. Moreover, the generalization and abstraction of information that can be observed in different services allows a broader vision for managing SLAs. For these reasons, this thesis aims to find innovative methods for the composition of Service Level Agreements in Cloud Computing. In particular, the methods presented allow demonstrate the convergence of several consolidated techniques in research on Cloud SLA using a new approach that considers new demands on Cloud and allows control of the established agreements, in addition to effectively ensure the application of the concept of XaaS (everything as a service). The originality of the approach allows the registration, search, composition and control of services in Cloud using the same structure. The new approach presented in this thesis allows the understanding of the impact of the new services requested by customers, giving the provider the possibility of simulating the use of the necessary resources to meet the new services\u2019 requests. From the presentation of a conceptual framework we can demonstrate the use of our approach through the examples of different situations presented in the real world and considering the new market possibilities

A framework for SLA-centric service-based Utility Computing

Nicht angegebenService oriented Utility Computing paves the way towards realization of service markets, which promise metered services through negotiable Service Level Agreements (SLA). A market does not necessarily imply a simple buyer-seller relationship, rather it is the culmination point of a complex chain of stake-holders with a hierarchical integration of value along each link in the chain. In service value chains, services corresponding to different partners are aggregated in a producer-consumer manner resulting in hierarchical structures of added value. SLAs are contracts between service providers and service consumers, which ensure the expected Quality of Service (QoS) to different stakeholders at various levels in this hierarchy. \emph{This thesis addresses the challenge of realizing SLA-centric infrastructure to enable service markets for Utility Computing.} Service Level Agreements play a pivotal role throughout the life cycle of service aggregation. The activities of service selection and service negotiation followed by the hierarchical aggregation and validation of services in service value chain, require SLA as an enabling technology. \emph{This research aims at a SLA-centric framework where the requirement-driven selection of services, flexible SLA negotiation, hierarchical SLA aggregation and validation, and related issues such as privacy, trust and security have been formalized and the prototypes of the service selection model and the validation model have been implemented. } The formal model for User-driven service selection utilizes Branch and Bound and Heuristic algorithms for its implementation. The formal model is then extended for SLA negotiation of configurable services of varying granularity in order to tweak the interests of the service consumers and service providers. %and then formalizing the requirements of an enabling infrastructure for aggregation and validation of SLAs existing at multiple levels and spanning % along the corresponding service value chains. The possibility of service aggregation opens new business opportunities in the evolving landscape of IT-based Service Economy. A SLA as a unit of business relationships helps establish innovative topologies for business networks. One example is the composition of computational services to construct services of bigger granularity thus giving room to business models based on service aggregation, Composite Service Provision and Reselling. This research introduces and formalizes the notions of SLA Choreography and hierarchical SLA aggregation in connection with the underlying service choreography to realize SLA-centric service value chains and business networks. The SLA Choreography and aggregation poses new challenges regarding its description, management, maintenance, validation, trust, privacy and security. The aggregation and validation models for SLA Choreography introduce concepts such as: SLA Views to protect the privacy of stakeholders; a hybrid trust model to foster business among unknown partners; and a PKI security mechanism coupled with rule based validation system to enable distributed queries across heterogeneous boundaries. A distributed rule based hierarchical SLA validation system is designed to demonstrate the practical significance of these notions

Modelling Service Level Agreements for Business Process Outsourcing Services

Many proposals to model service level agreements (SLAs) have been elaborated in order to automate different stages of the service lifecycle such as monitoring, implementation or deployment. All of them have been designed for computational services and are not well–suited for other types of services such as business process outsourcing (BPO) services. However, BPO services suported by process–aware information systems could also benefit from modelling SLAs in tasks such as performance monitoring, human resource assignment or process configuration. In this paper, we identify the requirements for modelling such SLAs and detail how they can be faced by combining techniques used to model computational SLAs, business processes, and process performance indicators. Furthermore, our approach has been validated through the modelling of several real BPO SLAsMinisterio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-5906Junta de Andalucía P12-TIC-186

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches

SLA violation prediction : a machine learning perspective

Le cloud computing réduit les coûts de maintenance des services et permet aux utilisateurs d'accéder à la demande aux services sans devoir être impliqués dans des détails techniques d'implémentation. Le lien entre un fournisseur de services cloud et un client est régi par une Validation du Niveau Service (VNS) qui définit pour chaque service le niveau et le coût associé. La VNS contient habituellement des paramètres spécifiques et un niveau minimum de qualité pour chaque élément du service qui est négocié entre les deux parties. Cependant, une ou plusieurs des conditions convenues dans une VNS pourraient être violées en raison de plusieurs problèmes tels que des problèmes techniques occasionnels. Du point de vue d'apprentissage automatique, le problème de la prédiction de violation de la VNS équivaut à un problème de classification binaire. Nous avons exploré deux modèles de classification en apprentissage automatique lors de cette thèse. Il s’agit des modèles de classification de Bayes naïve et de Forêts Aléatoires afin de prédire des violations futures d’une certaine tâche utilisant ses traits caractéristiques. Comparativement aux travaux précédents sur la prédiction d'une violation de la VNS, nos modèles ont été entraînés sur des ensembles de données réels introduisant ainsi de nouveaux défis. Nous avons validé le tout en utilisant Google Cloud Cluster trace comme avec l’ensemble de données. Les violations de la VNS étant des évènements rares 2.2 %, leur classification automatique reste une tâche difficile. Un modèle de classification aura en effet une forte tendance à prédire la classe dominante au détriment des classes rares. Pour répondre à ce problème, il existe plusieurs méthodes de ré-échantillonages telles que Random Over-Sampling, Under-Sampling, SMOTH, NearMiss, One-sided Selection, Neighborhood Cleaning Rule. Il est donc possible de les combiner afin de ré-équilibrer le jeu de données.Cloud computing reduces the maintenance costs of services and allows users to access on demand services without being involved in technical implementation details. The relationship between a cloud provider and a customer is governed with a Service Level Agreement (SLA) that is established to define the level of the service and its associated costs. SLA usually contains specific parameters and a minimum level of quality for each element of the service that is negotiated between a cloud provider and a customer. However, one or more than one of the agreed terms in an SLA might be violated due to several issues such as occasional technical problems. Violations do happen in real world. In terms of availability, Amazon Elastic Cloud faced an outage in 2011 when it crashed and many large customers such as Reddit and Quora were down for more than one day. As SLA violation prediction benefits both user and cloud provider, in recent years, cloud researchers have started investigating models that are capable of prediction future violations. From a Machine Learning point of view, the problem of SLA violation prediction amounts to a binary classification problem. In this thesis, we explore two Machine Learning classification models: Naive Bayes and Random Forest to predict future violations using features of a submitted task. Unlike previous works on SLA violation prediction or avoidance, our models are trained on a real world dataset which introduces new challenges. We validate our models using Google Cloud Cluster trace as the dataset. Since SLA violations are rare events in real world 2.2 %, the classification task becomes more challenging because the classifier will always have the tendency to predict the dominant class. In order to overcome this issue, we use several re-sampling methods such as Random Over-Sampling, Under-Sampling, SMOTH, NearMiss, One-sided Selection, Neighborhood Cleaning Rule and an ensemble of them to re-balance the dataset