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

Multicriteria Resource Brokering in Cloud Computing for Streaming Service

By leveraging cloud computing such as Infrastructure as a Service (IaaS), the outsourcing of computing resources used to support operations, including servers, storage, and networking components, is quite beneficial for various providers of Internet application. With this increasing trend, resource allocation that both assures QoS via Service Level Agreement (SLA) and avoids overprovisioning in order to reduce cost becomes a crucial priority and challenge in the design and operation of complex service-based platforms such as streaming service. On the other hand, providers of IaaS also concern their profit performance and energy consumption while offering these virtualized resources. In this paper, considering both service-oriented and infrastructure-oriented criteria, we regard this resource allocation problem as Multicriteria Decision Making problem and propose an effective trade-off approach based on goal programming model. To validate its effectiveness, a cloud architecture for streaming application is addressed and extensive analysis is performed for related criteria. The results of numerical simulations show that the proposed approach strikes a balance between these conflicting criteria commendably and achieves high cost efficiency

Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Conceptual Service Level Agreement Mechanism to Minimize the SLA Violation with SLA Negotiation Process in Cloud Computing Environment

تُستخدم الخدمة عبر الإنترنت لتكون بمثابة الدفع لكل استخدام في الحوسبة السحابية. لا يحتاج مستخدم الخدمة إلى عقد طويل مع مزودي الخدمات السحابية. اتفاقية مستوى الخدمة (SLAs) هي تفاهمات تم تحديدها بين مزودي الخدمة السحابية وغيرهم ، على سبيل المثال ، مستخدم الخدمة أو المشغل الوسيط أو المشغلين المراقبين. نظرًا لأن الحوسبة السحابية هي تقنية مستمرة تقدم العديد من الخدمات لتطبيقات الأعمال الأساسية وأنظمة قابلة للتكيف لإدارة الاتفاقيات عبر الإنترنت تعتبر مهمة تحافظ على اتفاقية مستوى الخدمةو جودة الخدمة لمستخدم السحابة. إذا فشل مزود الخدمة في الحفاظ على الخدمة المطلوبة ، فإن اتفاقية مستوى الخدمة تعتبر انتهاكًا لاتفاقية مستوى الخدمة. الهدف الرئيسي هو تقليل انتهاكات اتفاقية مستوى الخدمة (SLA) للحفاظ على جودة الخدمة لمستخدمي السحابة. في هذه المقالة البحثية ، اقترحنا صندوق أدوات للمساعدة في إجراء تبادل اتفاقية مستوى الخدمة مع مزودي الخدمة والذي سيمكن العميل السحابي من الإشارة إلى متطلبات جودة الخدمة واقترح خوارزمية بالإضافة إلى نموذج التفاوض من اجل التفاوض على الطلب مع الخدمة لمقدمي الخدمة لإنتاج اتفاقية أفضل بين مقدم الخدمة ومستهلك الخدمة السحابية. وبالتالي ، يمكن للإطار الذي تمت مناقشته تقليل انتهاكات اتفاقية مستوى الخدمة وكذلك خيبات الأمل في المفاوضات وتوسيع نطاق كفاية التكلفة. علاوة على ذلك ، فإن مجموعة أدوات اتفاقية مستوى الخدمة المقترحة منتجة بشكل إضافي للعملاء حتى يتمكن العملاء من تأمين سداد قيمة معقولة مقابل تقليل جودة الخدمة أو وقت التنازل. يوضح هذا البحث أنه يمكن الحفاظ على مستوى الضمان في موفري الخدمات السحابية من خلال نقل الخدمات دون انقطاع من منظور العميل.Online service is used to be as Pay-Per-Use in Cloud computing. Service user need not be in a long time contract with cloud service providers. Service level agreements (SLAs) are understandings marked between a cloud service providers and others, for example, a service user, intermediary operator, or observing operators. Since cloud computing is an ongoing technology giving numerous services to basic business applications and adaptable systems to manage online agreements are significant. SLA maintains the quality-of-service to the cloud user. If service provider fails to maintain the required service SLA is considered to be SLA violated. The main aim is to minimize the SLA violations for maintain the QoS of their cloud users. In this research article, a toolbox is proposed to help the procedure of exchanging of a SLA with the service providers that will enable the cloud client in indicating service quality demands and an algorithm as well as Negotiation model is also proposed to negotiate the request with the service providers to produce a better agreement between service provider and cloud service consumer. Subsequently, the discussed framework can reduce SLA violations as well as negotiation disappointments and have expanded cost-adequacy. Moreover, the suggested SLA toolkit is additionally productive to clients so clients can secure a sensible value repayment for diminished QoS or conceding time. This research shows the assurance level in the cloud service providers can be kept up by as yet conveying the services with no interruption from the client's perspectiv

Resource management in a containerized cloud : status and challenges

Cloud computing heavily relies on virtualization, as with cloud computing virtual resources are typically leased to the consumer, for example as virtual machines. Efficient management of these virtual resources is of great importance, as it has a direct impact on both the scalability and the operational costs of the cloud environment. Recently, containers are gaining popularity as virtualization technology, due to the minimal overhead compared to traditional virtual machines and the offered portability. Traditional resource management strategies however are typically designed for the allocation and migration of virtual machines, so the question arises how these strategies can be adapted for the management of a containerized cloud. Apart from this, the cloud is also no longer limited to the centrally hosted data center infrastructure. New deployment models have gained maturity, such as fog and mobile edge computing, bringing the cloud closer to the end user. These models could also benefit from container technology, as the newly introduced devices often have limited hardware resources. In this survey, we provide an overview of the current state of the art regarding resource management within the broad sense of cloud computing, complementary to existing surveys in literature. We investigate how research is adapting to the recent evolutions within the cloud, being the adoption of container technology and the introduction of the fog computing conceptual model. Furthermore, we identify several challenges and possible opportunities for future research

Capacity Allocation for Clouds with Parallel Processing, Batch Arrivals, and Heterogeneous Service Requirements

Problem Definition: Allocating sufficient capacity to cloud services is a challenging task, especially when demand is time-varying, heterogeneous, contains batches, and requires multiple types of resources for processing. In this setting, providers decide whether to reserve portions of their capacity to individual job classes or to offer it in a flexible manner. Methodology/results: In collaboration with Huawei Cloud, a worldwide provider of cloud services, we propose a heuristic policy that allocates multiple types of resources to jobs and also satisfies their pre-specified service level agreements (SLAs). We model the system as a multi-class queueing network with parallel processing and multiple types of resources, where arrivals (i.e., virtual machines and containers) follow time-varying patterns and require at least one unit of each resource for processing. While virtual machines leave if they are not served immediately, containers can join a queue. We introduce a diffusion approximation of the offered load of such system and investigate its fidelity as compared to the observed data. Then, we develop a heuristic approach that leverages this approximation to determine capacity levels that satisfy probabilistic SLAs in the system with fully flexible servers. Managerial Implications: Using a data set of cloud computing requests over a representative 8-day period from Huawei Cloud, we show that our heuristic policy results in a 20% capacity reduction and better service quality as compared to a benchmark that reserves resources. In addition, we show that the system utilization induced by our policy is superior to the benchmark, i.e., it implies less idling of resources in most instances. Thus, our approach enables cloud operators to both reduce costs and achieve better performance