Service Level Agreement Parameters Research Articles

Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

The cloud service level agreement (SLA) manage the relationship between service providers and consumers in cloud computing. SLA is an integral and critical part of modern era IT vendors and communication contracts. Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers, the SLA emerges as a key aspect between the consumers and providers. Continuous monitoring of Quality of Service (QoS) attributes is required to implement SLAs because of the complex nature of cloud communication. Many other factors, such as user reliability, satisfaction, and penalty on violations are also taken into account. Currently, there is no such policy of cloud SLA monitoring to minimize SLA violations. In this work, we have proposed a cloud SLA monitoring policy by dividing a monitoring session into two parts, for critical and non-critical parameters. The critical and non-critical parameters will be decided on the interest of the consumer during SLA negotiation. This will help to shape a new comprehensive SLA based Proactive Resource Allocation Approach (RPAA) which will monitor SLA at runtime, analyze the SLA parameters and try to find the possibility of SLA violations. We also have implemented an adaptive system for allocating cloud IT resources based on SLA violations and detection. We have defined two main components of SLA-PRAA i.e., (a) Handler and (b) Accounting and Billing Manager. We have also described the function of both components through algorithms. The experimental results validate the performance of our proposed method in comparison with state-of-the-art cloud SLA policies.

SLA-Aware Protocol Design for Energy-Efficient OLT Transmitter in TWDM-EPON

Environmental and economic concerns promote research on designing energy-efficient Time and Wavelength Division Multiplexed Ethernet Passive Optical Network (TWDM-EPON). TWDM-EPON allows achieving energy efficiency at the Optical Line Terminal (OLT) along with Optical Network Units (ONUs). All existing protocols for energy efficient TWDM-EPON have primarily been designed for saving energy at the OLT receivers. In this paper, we propose a method for saving energy at the OLT transmitter in TWDM-EPON while satisfying the service level agreements (SLAs) of corresponding downstream traffic. This includes a proposal for a heuristic algorithm that exploits some specific features of downstream scheduling in TWDM-EPON. Through extensive simulations, we demonstrate that the proposed method provides a significant improvement in energy efficiency in comparison with existing DBA protocols (up to ~ 45%). Moreover, we analyse a theoretical lower bound of the probability of delay bound violation (SLA parameter) and through simulations, we have demonstrated that delay bound violation probability of our proposed protocol is close to this lower bound.

Service‐Level Agreement with Dynamic Inventory Policy: The Effect of the Performance Review Period and the Incentive Structure

ABSTRACTPerformance measures are often outlined in the section of the service‐level agreement (SLA) of the contract between a supplier and a retailer. They are monitored periodically, and penalty and/or bonus payments are imposed in each performance review period, according to the SLA clauses. Previous studies have mostly considered a static inventory policy in analyzing SLAs. However, in practice, the supplier may have an opportunity to adjust the stock level in each inventory review period, according to the observed performance. This study analyzes the dynamic stocking decision for a supplier facing an SLA where the supplier sells a single product to the retailer. The ready rate is used to measure the performance in an SLA. To this end, models for both lump‐sum and linear penalty/bonus structures are developed, and the optimal stocking decisions for a strategic supplier are calculated using the stochastic dynamic programming approach. The results are then compared with the optimal static inventory policy, and new insights are derived to efficiently design an inventory system for the suppliers that are subject to service‐level incentives. In addition, we investigate the impact of SLA parameters—such as the length of the performance review period and incentive structures—on a supplier's performance, with the probability of meeting or exceeding the target service levels and the supplier's cost. We also consider the impact of demand distribution and inventory holding costs. Results show that under lump‐sum incentives, a longer performance review period benefits both the supplier and the buyer, given that the average ready rate increases with less variability as the length of the performance review period increases, leading to decrements in the supplier's total costs. In this scenario, there is a higher chance of gaining bonuses/avoiding penalties for a strategic supplier who adopts a dynamic inventory policy. On the other hand, under linear incentives, the impact of the performance review period on the supplier's cost and the performance measure (i.e., ready rate) is complicated and depends on the magnitude of the holding cost and the bonus and/or penalty structure of the contract. Under this scheme, the performance of a static inventory policy is highly dependent on the holding cost because a high holding cost may lead to failure to meet the contract requirements in terms of the service level.

A Load Balancing Algorithm for the Data Centres to Optimize Cloud Computing Applications

Despite the many past research conducted in the Cloud Computing field, some challenges still exist related to workload balancing in cloud-based applications and specifically in the Infrastructure as service (IaaS) cloud model. Efficient allocation of tasks is a crucial process in cloud computing due to the restricted number of resources/virtual machines. IaaS is one of the models of this technology that handles the backend where servers, data centers, and virtual machines are managed. Cloud Service Providers should ensure high service delivery performance in such models, avoiding situations such as hosts being overloaded or underloaded as this will result in higher execution time or machine failure, etc. Task Scheduling highly contributes to load balancing, and scheduling tasks much adheres to the requirements of the Service Level Agreement (SLA), a document offered by cloud developers to users. Important SLA parameters such as Deadline are addressed in the LB algorithm. The proposed algorithm is aimed to optimize resources and improve Load Balancing in view of the Quality of Service (QoS) task parameters, the priority of VMs, and resource allocation. The proposed LB algorithm addresses the stated issues and the current research gap based on the literature's findings. Results showed that the proposed LB algorithm results in an average of 78% resource utilization compared to the existing Dynamic LBA algorithm. It also achieves good performance in terms of less Execution time and Makespan.

Implementation Scheme SLA and Network Availability Mechanism for Customer Service Provider

Increasingly complex network heterogeneity and network monitoring tasks become the management concentration of a large distributed production infrastructure with various business services requiring a centralized control monitoring system, with increasing network size, heterogeneity and complexity. The network monitoring and management solutions available are not only expensive but also difficult to use, configure and maintain. Manually routing pins to the wrong device on a large complex network is very complicated and time-consuming for Service Provider (SP). Thus, it is necessary to have an automatic system that immediately reports to the network Service Provider (SP) monitoring system regarding the type of error or alert, Network Availability and Service Level Agreement (SLA). This research presents the modeling design and implementation of Network Availability and SLA network systems for Service Provider (SP) organizations, by being based on open-source programming tools (Zabbix System) and intelligently integrating to monitor network devices, especially to get Network Availability and SLA parameters and values on a customer or customer. Monitoring Customers devices in the network in the form of a module alert parameter that will be applied so that it is seen and can be said to be a universal Plug & Play technology concept (UPnP). Monitoring system developed will provide value and quality of service (qos) output parameters in the form of measuring and taking test value parameters Network Availability and SLA modeling, which will produce an accurate Service Level Agreement (SLA) value parameter test, and become a reference for an agreement between a service provider and a customer. As a guarantee or link availability for the services provided by Service Provide (SP) to customers. With the SLA value fulfilled at 99.9% with a 99.5% agreement, Network availability is met with a percentage of 98.89% and Down time with a percentage of only 1% of the agreement 2%, and the latency value of the terrestrial transmission media obtained is 2 ms, from the 8 ms agreement and the obtained VSAT transmission media is 500-600 ms from the agreement latency value is 700 ms.

A regression tree predictive model for virtual machine startup time in IaaS clouds

Cloud computing provides effective ways to rapidly provision computing resources over the Internet. For a better management of resource provisioning, the system requires to predict service-level agreements (SLAs) such as virtual machine (VM) startup times under various conditions of computing resources. The VM startup time is an important SLA parameter, which can impact other SLA parameters such as service initiation time and VM scale out times. By predicting VM startup times, Cloud providers can improve Cloud users’ expectations. Various quality of service (QoS) parameters have been considered in different resource allocation frameworks. Also, there are several efforts addressing QoS prediction in cloud environments. However, little research has considered VM startup time as a QoS parameter. In this paper, we propose a regression tree model for predicting average, minimum, and maximum VM startup times. To test the efficiency of our model, we implemented the model in an OpenStack test environment. The test results show that our model predicts VM startup times with an average accuracy of 91.81%.

Formulating monitoring strategy based on multiple SLA parameters for multi-tenant service-based systems

The widely used service-based systems (SBSs) are composed of individual services and delivered to multiple tenants. When runtime anomalies occurred, the violation rate of service level agreement (SLA) can increase remarkably. Therefore, service monitoring is crucial for meeting the tenant's quality of service (QoS) requirements. However, monitoring each service constantly wastes resources. In this paper, we propose a monitoring strategy based on multiple SLA parameters for multi-tenant SBSs (MMTS). The criticality of a service is evaluated to the importance of each service in a SBS based on QoS and tenants, tenants are ranked by multiple SLA parameters. Afterwards, monitoring benefit, resource cost, and system overload are weighed to formulate a cost-effective monitoring strategy. Finally, MMTS is evaluated with comprehensive experiments under multiple QoS dimensions and the results have shown that MMTS can outperform other six algorithms in the SLA violation rate and the cost-effectiveness of service monitoring.

Pro-Active and Pre-Emptive Intelligent Network Management Strategies in Internet of Things

Whenever a user browses the internet, the content he sends or receives takes the form a Protocol Data Unit as packets according to the OSI (Open Systems Interconnection) layers. These packets travel from the source to the destination through the path chosen by the routing protocols as OSPF (Open Shortest Path First) and BGP (Border Gateway Protocol). OSPF is used for interior routing within an AS (Autonomous System) and BGP is used for exterior routing between two external AS. Some customers are dual-homed where they have connections to two AS with one as the primary and the other one as secondary. Such diversed enormous traffic generated by the end users and the Internet Service Providers (ISP) have to be efficiently managed and monitored for the purpose of billing, security, QoS (Quality of Service) and SLA(Service Level Agreement) parameters. Hence the existing routing algorithms need to provide intelligent routing. The Simple Network Management Protocol (SNMP) generates the corresponding packets called SNMP traps. These specific packets are exchanged between the server and the appropriate interfaces of the routers when they are being polled. This polling technique generates a utilization graph which indicates the incoming and outgoing traffic at the core layer, distribution layer and access layer. The last mile traffic also has to be examined for checking the the bandwidth utilization. The traditional SNMP also has to incorporate the machine learning technique. This paper focuses on implementing intelligent network management in an Internet of Things environment.

Real-Time and Proactive SLA Renegotiation for a Cloud-Based System

Cloud-based systems involve the management and control on the level of delivered service, which is crucial in order to maintain service continuity and customers’ trust for the service provided. Predefined service level agreement (SLA) is normally used as the main element in managing the cloud-based system. However, such SLA basically cannot be adjusted during operations. Current studies on SLA adjustment are mainly focused on modifying the agreement before commencing operations. The cloud environment is, however, dynamic and requires occasional review of the SLA parameters to manage expectations. Thus, to maintain service continuity that is acceptable to all parties, SLA adjustment is necessary during service operations. This paper presents a real-time and proactive SLA renegotiation model to support the dynamic nature of cloud-based systems. Renegotiation is shown for four different scenarios based on parameter weightage. In order to achieve real-time decision, a multi-offer generation approach is used. A novel mechanism to detect and predict service violation is proposed to ensure proactive renegotiation. Simulation is performed to verify the model. In the simulation, the model is found to be effective as it is able to generate multi-offers in a single renegotiation round and reduce the impact of service violations during service operations.

Service Agreement Trifecta: Backup Resources, Price and Penalty in the Availability-Aware Cloud

Service Level Agreements (SLA) for cloud services entail complex trade-offs between interrelated variables such as price, penalty, and service availability (uptime) guarantee, with resource management strategies affecting fulfillment of the SLA. In this study, we address three key components of the SLA-based cloud resource management and pricing problem, from the service-provider’s perspective: (1) availability-aware backup resource provisioning; (2) price-penalty schedule determination; and (3) penalty-deferred pricing over two periods. Using the convexity of the provider’s expected total cost over the number of backup resources, we present a dichotomous search algorithm to derive the total cost minimizing number of backup resources for a given level of SLA-specified service availability guarantee. Next, we derive closed-form solutions for the lower bound of the feasible price range, yielding a schedule of breakeven price-penalty combinations, which establishes the baseline required in the economic modeling of the service contracts and related negotiation processes, and may also elicit client preference information. We then model a two-period pricing problem specifically designed to incentivize penalty deferrals in the event of an SLA violation. Detailed experimental studies of the proposed models have been carried out using real-world datacenter log data. The computational study validates the convexity of the probability density function of SLA violations over the number of backup resources. The results demonstrate significant interaction effects between the SLA parameters (price, penalty rate, and provisioning cost) and the backup resource provisioning decisions made by the provider, leading to key practical managerial implications for SLA design and resource deployment in the availability-aware cloud. The online appendix is available at https://doi.org/10.1287/isre.2017.0755 .

A review and analysis of service level agreements and chargebacks in the retail industry

Purpose The purpose of this paper is to examine service level agreements (SLAs) in the retail industry and uses empirical data to draw conclusions on the relationships between SLA parameters and retailer financial performance. Design/methodology/approach Based on prior SLA theories, hypotheses about the impacts of SLA confidentiality, choice of chargeback mechanisms and chargeback penalty on retailer inventory turnover are tested. Findings Retailer inventory turnover could vary by the level of SLA confidentiality, and the variation of retailer inventory turnovers could be explained by chargeback penalty. Research limitations/implications The research findings may not be readily applicable to SLAs outside of the retail industry. Also, most conclusions were drawn from publicly available SLAs. Practical implications The significant relationships between SLA parameters and retailer inventory turnover imply that a retailer could improve its financial performance by leveraging its SLA design. Originality/value Not only does this study contribute to the understanding of retail SLA design in practice, but it also extends prior theories by investigating the implications of SLA design on the retailer inventory turnover.

An Innovative SLA-Based Service Monitoring Framework in Cloud

Cloud computing encompasses powerful technology to perform complex computing for large applications. It provides access to various resources from any location with reduced Information Communication Technology overhead, enabling availability and scalability of resources based on consumer needs. Therefore, it has brought a paradigm shift in the way computing services are delivered. However, due to its increasing usage and rising expectations from cloud service provisioning, providing optimal and effective service is becoming an arduous task for service providers. Thus, maintaining quality of service (QoS) through regular monitoring is the utmost priority for the service provider. The key ingredient of managing QoS is a service level agreement (SLA). SLAs form a basis of measuring service quality. The cloud can be leveraged for provisioning e-Learning services to serve millions of users. The e-Learning service providers can enter into a contract with available cloud providers, which is transparent to the learners. Hence, it is critical to focus on the SLAs that need to be formulated and managed by the service providers for consumers of their e-Learning services. The objective of this paper is to propose SLA-based e-Learning service framework. This paper also identifies SLA parameters and related metrics to measure SLAs relevant to the provisioning of the proposed e-Learning service. It also proposes an innovative e-Learning service monitoring framework for managing QoS. This paper further evaluates the effectiveness of the proposed framework by provisioning of e-Learning service on Google App Engine cloud platform. It also presents experimental analysis using response graph in order to monitor associated SLAs in the proposed framework.

Service Level Agreements for Smart Healthcare in Cloud

With the advancement of Cloud computing, the adoption of cloud service in various industries is fast increasing. This is evident in the healthcare domain where the adoption is on the rise recently. However, the research contribution in this domain has been limited to certain functions. While cloud can increase availability, reachability of services, it is critical to design the healthcare service before provisioning. Besides, it is important to formulate Service Level Agreements (SLAs) to ensure that consumers can get guaranteed service from the service provider. The objective of this paper is to design the cloud based smart services for patient diagnostics. This research specifically defines service architecture for patients, physicians and diagnostic centers. In order to measure the proposed services, metrics of each SLA parameter is described with its functional and non-functional requirements. This paper also explains a case study implementation of a basic patient service using Google App Engine.

Energy Portfolio Optimization of Data Centers

Data centers have diverse options to procure electricity. However, the current literature on exploiting these options is very fractured. Specifically, it is still not clear how utilizing one energy option may affect selecting other energy options. To address this open problem, we propose a unified energy portfolio optimization framework that takes into consideration a broad range of energy choices for data centers. Despite the complexity and nonlinearity of the original models, the proposed analysis boils down to solving tractable linear mixed-integer stochastic programs. Using experimental electricity market and Internet workload data, various insightful numerical observations are reported. It is shown that the key to link different energy options with different short- and long-term profit characteristics is to conduct risk management at different time horizons. Also, there is a direct relationship between data centers’ service-level agreement parameters and their ability to exploit certain energy options. The use of on-site storage and the deployment of geographical workload distribution can particularly help data centers in utilizing high-risk energy choices, such as offering ancillary services or participating in wholesale electricity markets.

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.

A Systematic Review of Service Level Management in the Cloud

Cloud computing make it possible to flexibly procure, scale, and release computational resources on demand in response to workload changes. Stakeholders in business and academia are increasingly exploring cloud deployment options for their critical applications. One open problem is that service level agreements (SLAs) in the cloud ecosystem are yet to mature to a state where critical applications can be reliably deployed in clouds. This article systematically surveys the landscape of SLA-based cloud research to understand the state of the art and identify open problems. The survey is particularly aimed at the resource allocation phase of the SLA life cycle while highlighting implications on other phases. Results indicate that (i) minimal number of SLA parameters are accounted for in most studies; (ii) heuristics, policies, and optimisation are the most commonly used techniques for resource allocation; and (iii) the monitor-analysis-plan-execute (MAPE) architecture style is predominant in autonomic cloud systems. The results contribute to the fundamentals of engineering cloud SLA and their autonomic management, motivating further research and industrial-oriented solutions.

A comprehensive analysis of QoS-based routing mechanisms over shared mesh protected optical infrastructures

The paper describes a literature overview of the main building blocks of service level agreement based architectures over priority-aware shared mesh optical networks. The standardized protocols and existing algorithms for path attributes and service level agreement parameters negotiation are studied in this paper and shortcomings of each are identified. A thorough study of the priority-aware, service level agreement based, and risk-aware mechanisms including the existing mechanisms, the advantages and disadvantages, and the remedy for the shortcomings is provided. The mathematical models for availability analysis of different routing mechanisms, protection schemes, and network resources are discussed. Different routing strategies and wavelength assignment approaches are studied as well. The paper tries to show how the quality of service based routing mechanisms can provide service providers better network performance in addition to the higher revenue.

Renegotiation in Service Level Agreement Management for a Cloud-Based System

Managing Service Level Agreement (SLA) within a cloud-based system is important to maintain service continuity and improve trust due to cloud flexibility and scalability. We conduct a general review on cloud-based systems to understand how service continuity and trust are addressed in cloud SLA management. The review shows that SLA renegotiation is necessary to improve trust and maintain service continuity; however, research on SLA renegotiation is limited. Of the two key approaches in renegotiation, namely bargaining-based negotiation and offer generation--based negotiation, the latter approach is the most promising due to its ability to generate optimized multiple-offer SLA parameters within one round during renegotiation.

Analysis on Existing Basic Slas and Green Slas to Define New Sustainable Green SLA

Nowadays, most of the IT (Information Technology) and ICT (Information and Communication Technology) industries are practicing sustainability under green computing hoods. Users/Customers are also moving towards a new sustainable society. Therefore, while getting or providing different services from different ICT vendors, Service Level Agreement (SLA) becomes very important for both the service providers/vendors and users/customers. There are many ways to inform users/customers about various services with its inherent execution functionalities and even non-functional/Quality of Service (QoS) aspects through SLAs. However, these basic SLAs actually do not cover eco-efficient green issues or ethical issues for actual sustainable development. That is why green SLA (GSLA) should come into play. GSLA is a formal agreement incorporating all the traditional/basic commitments as well as respecting the ecological, economical and ethical aspects of sustainability. This research would survey on different basic SLA parameters for various services in ICT industries. At the same time, this survey would focus on finding the gaps and incorporating basic SLA parameters with existing green computing issues and ethical issues for different services in various computing domains. This research defines future GSLA in relationship with ICT product life and three pillars of sustainability. The proposed definition and overall survey could help different service providers/vendors to define their future GSLA as well as business strategies for this new transitional sustainable society.

SLA for E-Learning System Based on Cloud Computing

The Service Level Agreement (SLA) becomes an important issue especially over the Cloud Computing and online services that based on the ‘pay-as-you-use’ fashion. Establishing the Service level agreements (SLAs), which can be defined as a negotiation between the service provider and the user, is needed for many types of current applications as the E-Learning systems. The work in this paper presents an idea of optimizing the SLA parameters to serve any E-Learning system over the Cloud Computing platform, with defining the negotiation process, the suitable frame work, and the sequence diagram to accommodate the E-Learning systems.