scholarly journals An Efficient Network Resource Management in SDN for Cloud Services

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1556
Author(s):  
Myunghoon Jeon ◽  
Namgi Kim ◽  
Yehoon Jang ◽  
Byoung-Dai Lee
Keyword(s):  
Cloud Services ◽  
Computing Technology ◽  
Network Efficiency ◽  
Network Resources ◽  
Network Resource ◽  
Service Flow ◽  
Network Utilization ◽  
Network Resource Management ◽  
Flow Information

With the recent advancements in cloud computing technology, the number of cloud-based services has been gradually increasing. Symmetrically, users are asking for quality of experience (QoE) to be maintained or improved. To do this, it has become necessary to manage network resources more efficiently inside the cloud. Many theoretical studies for improving the users’ QoE have been proposed. However, there are few practical solutions due to the lack of symmetry between implementation and theoretical researches. Hence, in this study, we propose a ranking table-based network resource allocation method that dynamically allocates network resources per service flow based on flow information periodically collected from a software defined network (SDN). It dynamically identifies the size of the data transmission for each service flow on the SDN and differentially allocates network resources to each service flow based on this size. As a result, it maintains the maximum QoE for the user by increasing the network utilization. The experimental results show that the proposed method achieves 29.4% higher network efficiency than the general Open Shortest Path First (OSPF) method on average.

A Discovery Technology Based on Distributed Resource Management Domain

2015 ◽  
Vol 713-715 ◽  
pp. 2195-2198
Author(s):  
Jun Li Mao ◽  
Xiang Luo ◽  
Xiao Zhen Wang ◽  
Chao Hong Yang
Keyword(s):  
Resource Management ◽  
Resource Selection ◽  
Resource Discovery ◽  
Network Resources ◽  
Network Resource ◽  
Management Domain ◽  
Network Resource Management ◽  
Long Time ◽  
Resource Organization ◽  
Resource Description

Resource discovery is the key of network resource management, which includes multiple aspects, such as resource description, resource organization, and resource discovery and resource selection. For a long time, communication network resourcehas been lack of unified and standardized description, causing users difficult to precisely find related resources in demand. This paper presents a distributed resource query methods based on management domain, including distributed resource query architecture, the basic process of resource discovery, update method,query methods and so on. The method of network resources makes use of collaborative queries to realize network resource discovery according to need.

Cloud-Based Service Delivery Architecture with Service-Populating and Mobility-Aware Mechanisms

2014 ◽  
pp. 183-199
Author(s):  
Fragkiskos Sardis ◽  
Glenford Mapp ◽  
Jonathan Loo
Keyword(s):  
Service Delivery ◽  
Mobile Devices ◽  
Cloud Services ◽  
Network Resources ◽  
Internet Backbone ◽  
High Bandwidth ◽  
Processing And Storage ◽  
Cloud Technologies ◽  
And Storage

Advances in Mobile and Cloud technologies have redefined the way we perceive and use computers. Mobile devices now rely on Cloud technology for storage and applications. Furthermore, recent advances in network technology ensure that mobile devices in the future will have high-bandwidth connectivity at all times. This drives the incentive of doing all the processing and storage in the Cloud and using mobile devices to access the services. In this chapter, the authors argue that always-on connectivity along with increased demand of Cloud services will contest the Internet backbone and create problems in the management of Cloud resources. Client mobility is also a factor that should be taken into account when providing Cloud services to mobile devices. The authors therefore propose a new service delivery architecture that takes into account client mobility as well as the distance between clients and services in order to manage Cloud and network resources more efficiently and provide a better Quality of Experience for the user.

scholarly journals Artificial Intelligence Control Logic in Next-Generation Programmable Networks

2021 ◽  
Vol 11 (19) ◽  
pp. 9163
Author(s):  
Mateusz Żotkiewicz ◽  
Wiktor Szałyga ◽  
Jaroslaw Domaszewicz ◽  
Andrzej Bąk ◽  
Zbigniew Kopertowski ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bandwidth Allocation ◽  
Network Performance ◽  
Next Generation ◽  
Control Logic ◽  
Network Resources ◽  
Network Resource ◽  
Programmable Networks ◽  
Network Utilization ◽  
Effective Network

The new generation of programmable networks allow mechanisms to be deployed for the efficient control of dynamic bandwidth allocation and ensure Quality of Service (QoS) in terms of Key Performance Indicators (KPIs) for delay or loss sensitive Internet of Things (IoT) services. To achieve flexible, dynamic and automated network resource management in Software-Defined Networking (SDN), Artificial Intelligence (AI) algorithms can provide an effective solution. In the paper, we propose the solution for network resources allocation, where the AI algorithm is responsible for controlling intent-based routing in SDN. The paper focuses on the problem of optimal switching of intents between two designated paths using the Deep-Q-Learning approach based on an artificial neural network. The proposed algorithm is the main novelty of this paper. The Developed Networked Application Emulation System (NAPES) allows the AI solution to be tested with different patterns to evaluate the performance of the proposed solution. The AI algorithm was trained to maximize the total throughput in the network and effective network utilization. The results presented confirm the validity of applied AI approach to the problem of improving network performance in next-generation networks and the usefulness of the NAPES traffic generator for efficient economical and technical deployment in IoT networking systems evaluation.

scholarly journals JSSTR: A Joint Server Selection and Traffic Routing Algorithm for the Software-Defined Data Center

2018 ◽  
Vol 8 (9) ◽  
pp. 1478 ◽  
Author(s):  
Yunhe Cui ◽  
Lianshan Yan ◽  
Qing Qian ◽  
Huanlai Xing ◽  
Saifei Li
Keyword(s):  
Load Balancing ◽  
Routing Algorithm ◽  
Network Efficiency ◽  
Network Resources ◽  
Server Selection ◽  
Traffic Routing ◽  
Network Load ◽  
Network Utilization ◽  
Shuffle Frog Leaping Algorithm ◽  
The Impact

Server load balancing technology makes services highly functional by distributing the incoming user requests to different servers. Thus, it plays a key role in data centers. However, most of the current server load balancing schemes are designed without considering the impact on the network. More specifically, when using these schemes, the server selection and routing path calculation are usually executed sequentially, which may result in inefficient use of network resources or even cause some issues in the network. As an emerging architecture, Software-Defined Networking (SDN) provides new solutions to overcome these shortcomings. Therefore, taking advantages of SDN, this paper proposes a Joint Server Selection and Traffic Routing algorithm (JSSTR) based on improving the Shuffle Frog Leaping Algorithm (SFLA) to achieve high network utilization, network load balancing and server load balancing. Evaluation results validate that the proposed algorithm can significantly improve network efficiency and balance the network load and server load.

Location-Based Network Resource Management

2011 ◽  
pp. 865-888 ◽  
Author(s):  
Ioannis Priggouris ◽  
Evangelos Zervas ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Quality Of Service ◽  
Resource Management ◽  
Mobile Communications ◽  
Mobile Network ◽  
Direct Consequence ◽  
Research Area ◽  
Network Resource ◽  
Network Resource Management ◽  
Near Future

The vision that wireless technology in the near future will provide mobile users with at least similar multimedia services as those available to the fixed hosts is quite established today. Towards this direction, extensive research efforts are underway to guarantee Quality-of-service (QoS) in mobile environments. An important factor that affects the provisioning of resources in such environments is the variability of the environment itself. From the user’s perspective, this variability is a direct consequence of the user’s movement and, at any given time, a function of his position. Exploiting the user’s location to optimally manage and provision the resources of the mobile network is likely to enhance both the capacity of the network and the offered quality of service. In this chapter, we aim to provide a general introduction to the emerging research area of mobile communications, which is generally known as location-based network resource management.

scholarly journals qCon: QoS-Aware Network Resource Management for Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3444 ◽  
Author(s):  
Cheol-Ho Hong ◽  
Kyungwoon Lee ◽  
Minkoo Kang ◽  
Chuck Yoo
Keyword(s):  
Resource Management ◽  
Network Performance ◽  
Fog Computing ◽  
Raspberry Pi ◽  
Small Data ◽  
Network Resources ◽  
Network Resource ◽  
Network Bandwidth ◽  
Computing Paradigm ◽  
Network Resource Management

Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board.

Adaptive Handoff Algorithm for Efficient Network Resource Utilization in Mobile Internet Environments

2003 ◽  
Vol 04 (03) ◽  
pp. 361-375
Author(s):  
Satoshi Ohzahata ◽  
Shigetomo Kimura ◽  
Yoshihiko Ebihara
Keyword(s):  
Mobile Ip ◽  
Base Station ◽  
Mobile Internet ◽  
Mobile Nodes ◽  
Network Resources ◽  
Simulation Experiments ◽  
Network Resource ◽  
Decision Mechanism ◽  
Blocking Rate ◽  
Network Utilization

In this paper, we propose an adaptive handoff algorithm based on the "threshold-with-hysteresis." In general, such handoff algorithms are proposed to improve their handoff decision mechanism for only one user. Our algorithm aims to provide efficient network utilization and effect for all users. The proposed method dynamically changes the timing of handoff by the number of calls in the base station (BS). In our algorithm, when a BS has quite many calls, each MN tends to easily go out from the cell. On the other hand, in case that the BS is less crowded, every MN tries to keep the current connection as long as possible. From above control, the network resource is efficiently used, because our proposed method works as if the network resources are traded among the adjacent BSs. To implement our algorithm in Mobile IP, we also propose a system architecture with QoS mechanism. To realize the handoff decision based on the mobile nodes, the periodical agent advertisements in Mobile IP include information of the congestion status at the BS for our algorithm. The simulation experiments show that our proposed algorithm improves the average handoff blocking rate without decreasing throughput of the entire networks.

Location-Based Network Resource Management

2011 ◽  
pp. 139-164 ◽  
Author(s):  
Ioannis Priggouris ◽  
Evangelos Zervas ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Quality Of Service ◽  
Resource Management ◽  
Mobile Communications ◽  
Mobile Network ◽  
Direct Consequence ◽  
Research Area ◽  
Network Resource ◽  
Network Resource Management ◽  
Near Future

The vision that wireless technology in the near future will provide mobile users with at least similar multimedia services as those available to the fixed hosts is quite established today. Towards this direction, extensive research efforts are underway to guarantee Quality-of-service (QoS) in mobile environments. An important factor that affects the provisioning of resources in such environments is the variability of the environment itself. From the user’s perspective, this variability is a direct consequence of the user’s movement and, at any given time, a function of his position. Exploiting the user’s location to optimally manage and provision the resources of the mobile network is likely to enhance both the capacity of the network and the offered quality of service. In this chapter, we aim to provide a general introduction to the emerging research area of mobile communications, which is generally known as location-based network resource management.

Terms of use of “edutainment” and “cloud technologies” in professional art education

2018 ◽  
pp. 132-133
Author(s):  
V. Lymarenko
Keyword(s):  
Art Education ◽  
Technological Development ◽  
Educational Process ◽  
Cloud Services ◽  
Practical Significance ◽  
Network Resources ◽  
Modern Computer ◽  
Information Products ◽  
Network Technologies ◽  
Cloud Technologies

Trends in technology lead to an increasing of their role in the development of humanity. Exactly “cloud technologies”, which are the basis for the technological development of the information society now, also they play the role of the leading tool of informatization of education, especially united with “edutainment”.During the development and implementation of software and network technologies in professional artistic education, the following issues remain unsolved: the provision of modern computer equipment and software, technical support for the stable work of information products, and the provision of selective authorized access for students to specific network resources. The methodology based on “cloud calculates” technology provides an opportunity to overcome these difficulties. And the last, but not at least, students may be attracted to the most promising areas of the development of modern information products.Actuality, practical significance, and insufficient development of these problems caused the choice of the topic of our research: “Terms of use of “edutainment” and “cloud technologies” in professional artistic education “.The aim of the research is to determine the conditions of the use of “edutainment” and “cloud technologies” in the preparation of future teachers of musical art.Methods of research: analysis of psychological and pedagogical literature in order to determine the state of development of the problem; synthesis, comparison, generalization for justifying the concepts of “edutainment” and “cloud technologies” and methods of their use in the educational process.This article deals with issues of the use of edutainment technologies and “cloud technologies”. It is offered conditions of using edutainment and “cloud technologies” in post-nonclassical professional art education on the example of subject “Musical Art”. Actual “cloud” services are analyzed and examples of their integration to educational process of professional art establishments are proposed.

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