scholarly journals Supporting Quality of Experience based on Service Level Agreement for Heterogeneous Networks

2016 ◽  
Vol 21 (7) ◽  
pp. 17-22
Author(s):  
Moon-Ho Lee ◽  
Jong-Chan Lee
Keyword(s):  
Heterogeneous Networks ◽  
Quality Of Experience ◽  
Service Level Agreement ◽  
Service Level

scholarly journals 5G/B5G Service Classification Using Supervised Learning

2021 ◽  
Vol 11 (11) ◽  
pp. 4942
Author(s):  
Jorge E. Preciado-Velasco ◽  
Joan D. Gonzalez-Franco ◽  
Caridad E. Anias-Calderon ◽  
Juan I. Nieto-Hipolito ◽  
Raul Rivera-Rodriguez
Keyword(s):  
Supervised Learning ◽  
Quality Of Experience ◽  
Service Providers ◽  
Matthews Correlation Coefficient ◽  
Service Level Agreement ◽  
Service Level ◽  
5G Networks ◽  
Distribution Of Resources

The classification of services in 5G/B5G (Beyond 5G) networks has become important for telecommunications service providers, who face the challenge of simultaneously offering a better Quality of Service (QoS) in their networks and a better Quality of Experience (QoE) to users. Service classification allows 5G service providers to accurately select the network slices for each service, thereby improving the QoS of the network and the QoE perceived by users, and ensuring compliance with the Service Level Agreement (SLA). Some projects have developed systems for classifying these services based on the Key Performance Indicators (KPIs) that characterize the different services. However, Key Quality Indicators (KQIs) are also significant in 5G networks, although these are generally not considered. We propose a service classifier that uses a Machine Learning (ML) approach based on Supervised Learning (SL) to improve classification and to support a better distribution of resources and traffic over 5G/B5G based networks. We carry out simulations of our proposed scheme using different SL algorithms, first with KPIs alone and then incorporating KQIs and show that the latter achieves better prediction, with an accuracy of 97% and a Matthews correlation coefficient of 96.6% with a Random Forest classifier.

A Novel QoS Aware Shortest Path Algorithm for VSDN

2017 ◽  
Vol 6 (1) ◽  
pp. 1-14
Author(s):  
Amandeep Kaur Sandhu ◽  
Jyoteesh Malhotra
Keyword(s):  
Energy Consumption ◽  
Shortest Path ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Software Defined Networks ◽  
Shortest Path Algorithm ◽  
Internet Service ◽  
Decrease Energy Consumption

This article describes how a rapid increase in usage of internet has emerged from last few years. This high usage of internet has occurred due to increase in popularity of multimedia applications. However, there is no guarantee of Quality of Service to the users. To fulfill the desired requirements, Internet Service Providers (ISPs) establish a service level agreement (SLA) with clients including specific parameters like bandwidth, reliability, cost, power consumption, etc. ISPs make maximum SLAs and decrease energy consumption to raise their profit. As a result, users do not get the desired services for which they pay. Virtual Software Defined Networks are flexible and manageable networks which can be used to achieve these goals. This article presents shortest path algorithm which improves the matrices like energy consumption, bandwidth usage, successful allocation of nodes in the network using VSDN approach. The results show a 40% increase in the performance of proposed algorithms with a respect to existing algorithms.

scholarly journals Service Level Agreement (SLA) in Utility Computing Systems

2012 ◽  
pp. 1-25 ◽  
Author(s):  
Linlin Wu ◽  
Rajkumar Buyya
Keyword(s):  
Service Level Agreement ◽  
Service Level ◽  
Future Research ◽  
Fundamental Issue ◽  
Utility Computing ◽  
Computing Systems ◽  
Comprehensive Survey ◽  
Autonomy Management ◽  
State Of Art

In recent years, extensive research has been conducted in the area of Service Level Agreement (SLA) for utility computing systems. An SLA is a formal contract used to guarantee that consumers’ service quality expectation can be achieved. In utility computing systems, the level of customer satisfaction is crucial, making SLAs significantly important in these environments. Fundamental issue is the management of SLAs, including SLA autonomy management or trade off among multiple Quality of Service (QoS) parameters. Many SLA languages and frameworks have been developed as solutions; however, there is no overall classification for these extensive works. Therefore, the aim of this chapter is to present a comprehensive survey of how SLAs are created, managed and used in utility computing environment. We discuss existing use cases from Grid and Cloud computing systems to identify the level of SLA realization in state-of-art systems and emerging challenges for future research.

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

2012 ◽  
Vol 2 (3) ◽  
pp. 86-97
Author(s):  
Veena Goswami ◽  
Sudhansu Shekhar Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Finite Buffer ◽  
Web Browser ◽  
Computing Paradigm ◽  
Computing Services ◽  
Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

scholarly journals Service Level Agreement Violation Preventive Task Scheduling for Quality of Service Delivery in Cloud Computing Environment

2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Delivery ◽  
Task Scheduling ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment

Dynamic Management of Resources in Cloud Computing

2020 ◽  
Vol 8 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Level Agreement ◽  
Service Level ◽  
Poor Quality ◽  
Migration Time ◽  
Load Imbalance ◽  
Management Of Resources ◽  
And Migration

It has already been proven that VMs are over-utilized in the initial stages and are underutilized in the later stages. Due to the random utilization of the CPU, resources are sometimes heavily loaded whereas other resources are idle. Load imbalance causes service level agreement (SLA) violations resulting in poor quality of service (QoS) aided by the imperfect management of resources. An effective load balancing mechanism helps to achieve balanced utilization, which maximizes the throughput, availability, and reliability and reduces the response and migration time. The proposed algorithm can effectively minimize the response and the migration time and maximize reliability, and throughput. This research also helps to understand the load balancing policies and analysis of other research works.

TRADE-OFF BASED NEGOTIATION OF TRAFFIC CONDITIONING AND SERVICE LEVEL AGREEMENTS IN DIFFSERV NETWORKS

2005 ◽  
Vol 06 (03) ◽  
pp. 179-192
Author(s):  
MARCO COMUZZI ◽  
CHIARA FRANCALANCI ◽  
PAOLO GIACOMAZZI
Keyword(s):  
Service Level Agreement ◽  
Service Level ◽  
Negotiation Process ◽  
Strong Impact ◽  
Negotiation Model ◽  
Trade Off ◽  
Mathematical Formalization ◽  
Traffic Conditioning ◽  
Negotiation Problem

The paper faces the problem of the runtime negotiation on the Traffic Conditioning Agreement and Service Level Agreement in IP Differentiated Services networks. A first contribution of the paper with respect to previous literature is to propose a multi-attribute description of QoS targets and traffic profile. A second contribution of this work is to provide a mathematical formalization of the negotiation problem suitable for automated negotiation. The model is tested through simulation to a) verify the convergence of the negotiation process, which is critical to ensure that negotiation can be performed automatically and b) analyze the agreement solutions that are reached by negotiation parties for different values of quality of service and price parameters. With this paper's negotiation model, the primary goal of negotiating parties is to maintain the value of their utility function constant by searching a trade-off between QoS and price. However, the willingness to cooperate of the negotiating parties has a strong impact on the agreement value of negotiation parameters.

scholarly journals A Survey on Machine Learning and Deep Learning based Quality of Service aware Protocols for Software Defined Networks

2021 ◽  
Author(s):  
Hiren Kumar Deva Sarma
Keyword(s):  
Machine Learning ◽  
Quality Of Service ◽  
Deep Learning ◽  
Service Level Agreement ◽  
Service Level ◽  
Future Research ◽  
Traffic Classification ◽  
Software Defined Networks ◽  
Research Issues

<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>

Sign in / Sign up

Export Citation Format

Share Document