scholarly journals MACHINE LEARNING APPROACHES IN IMPROVING SERVICE LEVEL AGREEMENT-BASED ADMISSION CONTROL FOR A SOFTWARE-AS-A-SERVICE PROVIDER IN CLOUD

2013 ◽  
Vol 9 (10) ◽  
pp. 1283-1294 ◽  
Author(s):  
Mohana
Author(s):  
A.C. Leonard

End users have expectations regarding services and support, and the quality thereof, provided by the supplier. They compare their expectations to the received service to assess the service quality (Coye, 2004). In order to ensure that the service supplied by the service provider meets the expectations of end users, a successful service level agreement (SLA) is required. Quality SLA’s clearly define, amongst many other elements, the commitments and responsibilities of the IT service provider and end users within the service delivery processes (Larson, 1998). One method of measuring the success of SLA’s is by using service metrics with regard to the availability, reliability, serviceability, response, and user satisfaction of the SLA (Larson, 1998). Therefore, the success of the SLA depends on a clear, common understanding of the services and service quality between the service provider and end users. Furthermore commitment, trust, and cooperation between all parties is necessary to achieve success with SLA’s (Hiles, 1994). However, in this paper it is argued that all these soft issues can only form a basis when sound relationships are established and maintained between the IT service provider and end users (Leonard, 2002). This paper aims to determine how the establishment of a sound IT-end user relationship can add value to the SLA for both the IT service provider and the end users, and increase the success of SLA’s.


2020 ◽  
Vol 12 (6) ◽  
pp. 99
Author(s):  
Jiao Wang ◽  
Jay Weitzen ◽  
Oguz Bayat ◽  
Volkan Sevindik ◽  
Mingzhe Li

Network slicing allows operators to sell customized slices to various tenants at different prices. To provide better-performing and cost-efficient services, network slicing is looking to intelligent resource management approaches to be aligned to users’ activities per slice. In this article, we propose a radio access network (RAN) slicing design methodology for quality of service (QoS) provisioning, for differentiated services in a 5G network. A performance model is constructed for each service using machine learning (ML)-based approaches, optimized using interference coordination approaches, and used to facilitate service level agreement (SLA) mapping to the radio resource. The optimal bandwidth allocation is dynamically adjusted based on instantaneous network load conditions. We investigate the application of machine learning in solving the radio resource slicing problem and demonstrate the advantage of machine learning through extensive simulations. A case study is presented to demonstrate the effectiveness of the proposed radio resource slicing approach.


2020 ◽  
Vol 10 (2) ◽  
pp. 125-144
Author(s):  
Hillman Akhyar Damanik ◽  
Merry Anggraeni

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.


2021 ◽  
Author(s):  
Hiren Kumar Deva Sarma

<p>Quality of Service (QoS) is one of the most important parameters to be considered in computer networking and communication. The traditional network incorporates various quality QoS frameworks to enhance the quality of services. Due to the distributed nature of the traditional networks, providing quality of service, based on service level agreement (SLA) is a complex task for the network designers and administrators. With the advent of software defined networks (SDN), the task of ensuring QoS is expected to become feasible. Since SDN has logically centralized architecture, it may be able to provide QoS, which was otherwise extremely difficult in traditional network architectures. Emergence and popularity of machine learning (ML) and deep learning (DL) have opened up even more possibilities in the line of QoS assurance. In this article, the focus has been mainly on machine learning and deep learning based QoS aware protocols that have been developed so far for SDN. The functional areas of SDN namely traffic classification, QoS aware routing, queuing, and scheduling are considered in this survey. The article presents a systematic and comprehensive study on different ML and DL based approaches designed to improve overall QoS in SDN. Different research issues & challenges, and future research directions in the area of QoS in SDN are outlined. <b></b></p>


2020 ◽  
Vol 39 (6) ◽  
pp. 8345-8356
Author(s):  
M. Alamelu ◽  
T.S. Pradeep Kumar ◽  
V. Vijayakumar

Service Level Agreement (SLA) is an agreement between the service provider and consumer to provide the verifiable quality of services. Using the valuable metrics in SLA, a service consumer could easily evaluate the service provider. Though there are different types of SLA models are available between the consumer and provider, the proposed approach describes the Fuzzy rule base SLA agreement generation among multiple service providers. A negotiation system is designed in this work to collect the different sets of provider services. With their desired quality metrics, a common Fuzzy based SLA report is generated and compared against the existing consumer requirements. From the analysis of the common agreement report, consumers can easily evaluate the best service with the desired Impact service, cost and Quality. The main advantage of this approach is that it reduces the time consumption of a consumer. Moreover, the best service provider can be selected among multiple providers with the desired QoS parameters. At the same time, the bilateral negotiation is enhanced with the approach of multilateral negotiation to improve the searching time of consumers.


Author(s):  
G.R. Gangadharan ◽  
Lorna Uden ◽  
Paul Oude Luttighuis

Software as a Service (SaaS) has become an important pragmatic in the world of enterprise software and business services markets. SaaS supports the concept of outsourcing where business processes are offered under a service level agreement for a given price. However, sourcing SaaS may not always involve outsourcing with respect to the transfer of internal activities and resources to external service providers. Users of SaaS need to know what strategies to use when determining sourcing requirements. In this paper, the authors develop a classification for sourcing SaaS based on Kraljic's matrix and a mapping of SaaS services to the sourcing structures. Further, they evaluate the proposed sourcing models against two real world case studies.


2020 ◽  
Vol 7 (2) ◽  
pp. 194
Author(s):  
Bayu Rima Aditya ◽  
Muhammad Barja Sanjaya

The main component of the entire strategy in Service Level Management (SLM) as a service provider is shown by implementing the Service Level Agreement (SLA). The service provider has to always guarantee that SLA which is indeed determined for a customer is achieved and fulfilled. The thing causing a failure in fulfilment of SLA is the expectation of business that is categorized in high indication while SLA establishment is still in progress, so it is indicated that there is a difference of perception between business and IT paradigm. The aim of this study is to build a framework to facilitate the achievement of a balance between the expected quality for the customer as the receiver party and the service which is offered by a service provider. The methodology which is applied in this study is by using an approach of informationengineering that consists of planning the analysis of related vision, planning of the technology effect, analysis of critical success factor, analysis of problem and purpose, as well as the identification of business area. The research which is conducted has given an obvious perspective paradigm in general that an integrated information system is indeed needed into the implementation of SLM to complete the significance among the functional divisions in a company


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