Service Level Agreement Negotiation Research Articles

A Broker-based Framework for Integrated SLA-Aware SaaS Provisioning

In the service landscape, the issues of service selection, negotiation of Service Level Agreements (SLA), and SLA-compliance monitoring have typically been used in separate and disparate ways, which affect the quality of the services that consumers obtain from their providers. In this work, we propose a broker-based framework to deal with these concerns in an integrated manner for Software as a Service (SaaS) provisioning. The SaaS Broker selects a suitable SaaS provider on behalf of the service consumer by using a utility-driven selection algorithm that ranks the QoS offerings of potential SaaS providers. Then, it negotiates the SLA terms with that provider based on the quality requirements of the service consumer. The monitoring infrastructure observes SLA-compliance during service delivery by using measurements obtained from third-party monitoring services. We also define a utility-based bargaining decision model that allows the service consumer to express her sensitivity for each of the negotiated quality attributes and to evaluate the SaaS provider offer in each round of negotiation. A use-case with few quality attributes and their respective utility functions illustrates the approach.

A Broker-based Framework for Integrated SLA-Aware SaaS Provisioning

In the service landscape, the issues of service selection, negotiation of Service Level Agreements (SLA), and SLA-compliance monitoring have typically been used in separate and disparate ways, which affect the quality of the services that consumers obtain from their providers. In this work, we propose a broker-based framework to deal with these concerns in an integrated mannerfor Software as a Service (SaaS) provisioning. The SaaS Broker selects a suitable SaaS provider on behalf of the service consumer by using a utility-driven selection algorithm that ranks the QoS offerings of potential SaaS providers. Then, it negotiates the SLA terms with that provider based on the quality requirements of the service consumer. The monitoring infrastructure observes SLA-compliance during service delivery by using measurements obtained from third-party monitoring services. We also define a utility-based bargaining decision model that allows the service consumer to express her sensitivity for each of the negotiated quality attributes and to evaluate the SaaS provider offer in each round of negotiation. A use-case with few quality attributes and their respective utility functions illustrates the approach.

Green Service Level Agreement (GSLA) framework for cloud computing

As the organizations are shifting their workload on cloud computing, the demand of cloud services has increased tremendously. With the increased usage of cloud data centers, there is huge consumption of energy (power and heat), contributing to high operational costs and carbon footprints to the environment. So far, research has been carried out to optimize energy usage for cloud resources. However, most of the work on energy optimization is centered on the operational phase of a data center. This paper focuses on energy reduction at Service Level Agreement (SLA) level. Cloud resources are provisioned with Green SLA aware cloud resource reservation (GSLACRR) algorithm. This work proposes Green Service Level Agreement (GSLA) template and negotiation strategies for cloud services. It offers cloud resource services in an energy efficient manner to the users.

An Automated Semantic Negotiation for Cloud Service Level Agreements

Mostly, cloud agreements are signed between the consumer and the provider using online click-through agreements. Several issues and conflicts exist in the negotiation of cloud agreement terms due to the legal and ambiguous terms in Service Level Agreements (SLA). Semantic knowledge applied during the formation and negotiation of SLA can overcome these issues. Cloud SLA negotiation consists of numerous activities such as formation of SLA templates, publishing it in registry, verification and validation of SLA, monitoring for violation, logging and reporting and termination. Though these activities are interleaved with each other, semantic synchronization is still lacking. To overcome this, a novel SLA life cycle using semantic knowledge to automate the cloud negotiation has been formulated. Semantic web platform using ontologies is designed, developed and evaluated. The resultant platform increases the task efficiency of the consumer and the provider during negotiation. Precision and recall scores for Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) SLAs were calculated. And it reveals that applying semantic knowledge helps the extraction of meaningful answers from the cloud actors.

Towards Automated SLA Management for Service Delivery in SOA-based Environments

The services landscape is changing with the growing adoption by businesses of the Service Oriented Architecture (SOA), the migration of business solutions to the cloud, and the proliferation of smartphones and Internet-enabled handheld devices to consume services. To meet their business goals, organizations increasingly demand services, which can satisfy their functional and non-functional requirements. Service Level Agreements (SLAs) are seen as the means to guarantee the continuity in service provisioning and required levels of service. In this paper, we propose a framework for service provisioning, which aims at providing support for automated SLA negotiation and management. The Service Broker component carries out SLA negotiation with selected service-providers on behalf of service-consumers. Multi-rounds of negotiations are very often required to reach an agreement. In each round, the negotiating parties bargain on multiple SLA parameters by trying to maximize their global utility functions. The monitoring infrastructure is in charge of observing SLA compliance monitoring using measurements obtained from independent third party monitoring services.

Identifying Relevant Socio-Theoretic Foundations for Supporting Multi-Issue IT Cloudsourcing Negotiations

Service level agreement (SLA) negotiations involving cloud-based information technology (IT) service providers and customers are now commonplace. Although historical research on negotiation has often relied on economic foundations, the important nature of IT service levels to organizations’ operational effectiveness suggests that negotiation complexities in the context of cloud-based outsourcing (or cloudsourcing ) cannot be well understood by relying on economic perspectives alone. To that end, this paper reports on experiments designed to determine the relevance of competing sociotheoretic frameworks as they pertain to IT cloudsourcing negotiations. Contributions include a rigorous examination of hypotheses derived from social exchange theory, equity theory, learning theory, and the win–win theories of negotiation. Additional contributions include the development of methodological constructs (using the Euclidean geometry) that reflect the complex nature of IT cloudsourcing SLAs, i.e., that they are composed of numerous service category contract clauses where negotiation tradeoffs within a service category as well as across service categories are possible. We find strong support for the relevance of the social exchange theory to IT cloudsourcing negotiations, as well as moderate support for the win-win theories of negotiation. Our conclusions provide clear directions for extending our work into the realm of negotiation support systems, and we rely on our findings to conjecture that IT cloudsourcing negotiation is a unique context for sociotheoretic negotiation research due to the inherent importance of information technologies to organizations’ operational effectiveness.

A multi-agent protocol for service level agreement negotiation in cloud federations

The emergence of complex cloud services and the growing number of QoS metrics entail the need of automation to transform business requirements into QoS constraints. Furthermore, in the emergent context of Cloud Federations providers need to share knowledge to improve interoperability when negotiating SLA Service Level Agreements. Intelligent software agents are capable of supporting activities related to SLA negotiation, as well as sharing knowledge into large-scale distributed environments. Since they are usually provided with different ontologies, understanding the meaning of the messages requires the availability of common, global ontologies among customers and providers. In order to deal with this issue, we discuss a multi-agent SLA negotiation protocol which does not need a common global agent ontology. The protocol takes into account different concerns related to the understanding of semantic and technical terms, and the knowledge about the agent abilities on semantic and technical terms are shared among the Cloud Federation.

An Autonomous Time-Dependent SLA Negotiation Strategy for Cloud Computing

Cloud service level agreement negotiation is a process of joint decision-making between cloud clients and providers to resolve their conflicting objectives. With the advances of cloud technology, operations such as discovery, scaling, monitoring and decommissioning are accomplished automatically. Therefore,negotiationbetweencloudclientsandproviderscanbeabottleneckifitiscarriedoutmanually. Our objective is to propose a state-of-the-art solution to automate the negotiation process for cloud environments and specifically infrastructure as a service category. The proposed negotiation strategy is based on a time-dependent tactic. For cloud providers, the strategy uniquely considers utilization of resources when generating new offers and automatically adjusts the tactic’s parameters to concedemoreonthepriceoflessutilizedresources.Inaddition,whilethepreviousnegotiationstrategiesinliteraturetrustofferedqualityofservicevaluesregardlessoftheirdependability,ourproposed strategy is capable of assessing reliability of offers received from cloud providers. Furthermore, to find the right configuration of the time-dependent tactic in cloud computing environments, we investigate the effect of modifying parameters such as initial offer value and deadline on negotiation outputsthatincluderatioofdealsmade,andinequalityindex.Theproposednegotiationstrategyistested with different workloads and in diverse market conditions to show how the time-dependent tactic’s settings can dynamically adapt to help cloud providers increase their profits.

A Negotiation Framework for the Cloud Management System using Similarity and Gale Shapely Stable Matching Approach

One of the major issues in emerging cloud management system needs the efficient service level agreement negotiation framework, with an optimal negotiation strategy. Most researchers focus mainly on the atomic service negotiation model, with the assistance of the Agent Controller in the broker part to reduce the total negotiation time, and communication overhead to some extent. This research focuses mainly on composite service negotiation, to further minimize both the total negotiation time and communication overhead through the pre-request optimization of broker strategy. The main objective of this research work is to introduce an Automated Dynamic Service Level Agreement Negotiation Framework (ADSLANF), which consists of an Intelligent Third-party Broker for composite service negotiation between the consumer and the service provider. A broker consists of an Intelligent Third-party Broker Agent, Agent Controller and Additional Agent Controller for managing and controlling its negotiation strategy. The Intelligent third-party broker agent manages the composite service by assigning its atomic services to multiple Agent Controllers. Using the Additional Agent Controllers, the Agent Controllers manage the concurrent negotiation with multiple service providers. In this process, the total negotiation time value is reduced partially. Further, the negotiation strategy is optimized in two stages, viz., Classified Similarity Matching (CSM) approach, and the Truncated Negotiation Group Gale Shapely Stable Matching (TNGGSSM) approach, to minimize the communication overhead.

Building a medical research cloud in the EASI‐CLOUDS project

SummaryThe demand for Information Technology (IT) resources is constantly growing in the scientific area. The ability to store and process increasing amounts of data has transformed many research disciplines like the life sciences, which now rely on complex data processing and data analytics. Cloud computing can provide researchers with scalable and easy‐to‐use hardware and software resources and allows on‐demand access to services, tools, or even complete work environments.The European research project EASI‐CLOUDS has developed a service delivery platform with special regard to service integration, monitoring and management, and the negotiation of service level agreements. In order to demonstrate the capabilities of the platform, a medical‐use case was devised and implemented in close partnership with the Charité University Hospital that has a high demand for computing resources, especially in the field of magnetic resonance imaging‐related diagnostics of brain diseases. This use case can serve as a blueprint for the development of cloud‐based services for medical research. Copyright © 2015 John Wiley & Sons, Ltd.

Capacity-driven utility model for service level agreement negotiation of cloud services

Dynamic customers’ requirements and providers’ resources availability in the Cloud market make it inadequate static approaches to guarantee Quality of Service (QoS) levels and to define pricing. In this context, negotiation guided by dynamic information is a viable way to achieve high satisfaction levels for both contract parties. We propose to exploit capacity planning to support bilateral negotiation processes with the aim of optimizing the utility for service providers, by avoiding contracts that could incur in Service Level Agreements (SLAs) violations, keeping, at the same time, competitive prices. The proposed technique exploits a non-additive utility function defined in the region of acceptable SLA proposals, taking into account desired QoS and expected resources availability, costs and penalties. The experimental analysis shows the benefit of the proposed dynamic approach with respect to static ones in a scenario characterized by a set of customers and differentiated classes of applications provided by a cloud environment.

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.

Analysis of a trust model for SLA negotiation and enforcement in cloud markets

Online Reputation Systems help mitigate the information asymmetry between clients and providers in Cloud Computing Markets. However, those systems raise two main drawbacks: the disagreement for assuming the cost of ownership of such services and their vulnerability to reputation attacks from dishonest parties that want to increase their reputation. This article faces both problems by describing a decentralised (peer-to-peer) trust model that does not require the intervention of a central entity to manage it. This model includes mechanisms to allow participants to avoid dishonest behaviour from other peers: each client statistically analyses the external reports about providers and updates the trustworthiness of the peers. The trustworthiness values will be used to negotiate prices in later transactions. The trust model is then incorporated in the Service-Level Agreement negotiation and enforcement processes, prioritising trusted clients over non-trusted clients to minimise the consequences of low Quality of Service in relation to the trust of the provider, and incentivise accurate trust reports from the clients. Finally, this article evaluates and discusses the validity of the trust model under different attacks from dishonest clients and providers.

A Framework for Negotiating Service Level Agreement of Cloud-based Services

Abstract Cloud-based services have become the backbone of IT industry nowadays and the promising technology that offers a commoditized service to the software, the platform and the infrastructure where they are delivered as a service. Because several providers have started to offer a vast diversity of Cloud services, Cloud customers became unable to decide whose services they should use and what is the basis for their selection. Therefore, a legal contract is necessarily needed for negotiating these both Cloud parties. This contract is referred to Service Level Agreement (SLA). A SLA negotiation between Cloud parties assists in defining the Quality of Service (QoS) requirements of critical service-based processes. In addition, the role of third party in the negotiation process that is represented in Cloud broker will recommend customers to achieve the required service efficiently when negotiating with multiple providers. Currently, there is no framework that can allow customers to evaluate Cloud offerings and rank them based on their interests. Thus it is important to have a methodology that might map the customers’ requirements referred as Service Level Objectives (SLO) with the most reliable Cloud service. In this work, we address this problem by presenting a proposed framework that intends to empower customers to evaluate and select between the different Cloud service offerings. This proposed framework aims to formalize the SLA with precise and unambiguous definition of services key performance indicators (KPIs) to support automated negotiation on the details of the agreement for both contracted parties. Our reasoning evaluation of proposed framework proved the importance of negotiation process for both Cloud parties in mapping the Cloud services with the customers’ requirements.

An Analytical Model for Resource Characterization and Parameter Estimation for DAG-Based Jobs for Homogeneous Systems

High Performance Computing (HPC) systems demand and consume a significant amount of resources (e.g. server, storage, electrical energy) resulting in high operational costs, reduced reliability, and sometimes leading to waste of scarce natural resources. On one hand, the most important issue for these systems is achieving high performance, while on the other hand, the rapidly increasing resource costs appeal to effectively predict the resource requirements to ensure efficient services in the most optimized manner. The resource requirement prediction for a job thus becomes important for both the service providers as well as the consumers for ensuring resource management and to negotiate Service Level Agreements (SLAs), respectively, in order to help make better job allocation decisions. Moreover, the resource requirement prediction can even lead to improved scheduling performance while reducing the resource waste. This work presents an analytical model estimating the required resources for the modular job execution. The analysis identifies the number of processors required and the maximum and minimum bounds on the turnaround time and energy consumed. Simulation study reveals that the scheduling algorithms integrated with the proposed analytical model helps in improving the average throughput and the average energy consumption of the system. As the work predicts the resource requirements, it can even play an important role in Service-Oriented Architectures (SOA) like Cloud computing or Grid computing.

A Service Broker Model for Cloud based Render Farm Selection

Cloud computing is gaining popularity in the 3D Animation industry for rendering the 3D images. Rendering is an inevitable task in creating the 3d animated scenes. It is a process where the scene files to be animated is read and converted into 3D photorealistic images automatically. Since it is a computationally intensive task, this process consumes the majority of the time taken for 3D images production. As the scene files could be processed in parallel, clusters of computers called render farms can be used to speed up the rendering process. The advantage of using Cloud based render farms is that it is scalable and can be availed on demand. One of the important challenges faced by the 3D studios is the comparison and selection of the cloud based render farm service provider who could satisfy their functional and the non functional Quality of Service (QoS) requirements. In this paper we propose, a frame work for Cloud Service Broker (CSB) responsible for the selection and provision of the cloud based render farm. The Cloud Service Broker matches the functional and the non functional Quality of Service requirements (QoS) of the user with the service offerings of the render farm service providers and helps the user in selecting the right service provider using an aggregate utility function. The CSB also facilitates the process of Service Level Agreement (SLA) negotiation and monitoring by the third party monitoring services.

The Implementation of SLA Mechanism in Manufacturing Grid

. In MG environment, resource consumers choose the optimal resource service according to their non-functional demands for quality of service (QoS) in terms of service execution time, reliability, and availability. Non-functional requirements of QoS can be organized and managed by utilizing Service Level Agreement (SLA) standards. In this study, architectures with QoS oriented mechanism with four layers for MG on the basis of SLA are provided. On the basis of the QoS oriented architectures, the management processes of SLA creation, negotiation and matching, monitoring and verification are discussed. Finally, a simple case is provided.

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.

Semantic-enabled CARE Resource Broker (SeCRB) for managing grid and cloud environment

Grid computing is mainly helpful for executing high-performance computing applications. However, conventional grid resources sometimes fail to offer a dynamic application execution environment and this increases the rate at which the job requests of users are rejected. Integrating emerging virtualization technologies in grid and cloud computing facilitates the provision of dynamic virtual resources in the required execution environment. Resource brokers play a significant role in managing grid and cloud resources as well as identifying potential resources that satisfy users' application requests. This research paper proposes a semantic-enabled CARE Resource Broker (SeCRB) that provides a common framework to describe grid and cloud resources, and to discover them in an intelligent manner by considering software, hardware and quality of service (QoS) requirements. The proposed semantic resource discovery mechanism classifies the resources into three categories viz., exact, high-similarity subsume and high-similarity plug-in regions. To achieve the necessary user QoS requirements, we have included a service level agreement (SLA) negotiation mechanism that pairs users' QoS requirements with matching resources to guarantee the execution of applications, and to achieve the desired QoS of users. Finally, we have implemented the QoS-based resource scheduling mechanism that selects the resources from the SLA negotiation accepted list in an optimal manner. The proposed work is simulated and evaluated by submitting real-world bio-informatics and image processing application for various test cases. The result of the experiment shows that for jobs submitted to the resource broker, job rejection rate is reduced while job success and scheduling rates are increased, thus making the resource management system more efficient.

Self-adaptive service level agreement monitoring in cloud environments1

Cloud Service Providers offer access to hardware and software resources across the Internet. Cloud Service Providers and their clients negotiate Service Level Agreements SLA that specify terms and conditions of services. To ensure that an SLA is being honored by all parties the service is monitored. This paper proposes a monitoring approach that automatically adapts the monitoring process in realtime, based on user-specified policies. The monitor can both adapt the frequency of measurements and monitoring mode: active and passive. Active mode uses an external, trusted monitoring service. Passive mode minimizes interaction with an external monitoring service, relying instead on a mutual commit protocol to ensure SLA compliance. Monitor adaptation is determined by levels of perceived risk, defined by a user's policy. The self-adaptive SLA monitoring framework is realized using agent technology and is implemented and tested in the AgentScape middleware.