scholarly journals Path computation enhancement in SDN networks

2021 ◽  
Author(s):  
Tim Huang
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Management Approach ◽  
Distributed Network ◽  
Data Center Networks ◽  
Network Nodes ◽  
Path Computation ◽  
Shortest Path Algorithms ◽  
Load Balancing Algorithm ◽  
Hybrid Sdn

Path computation is always the core topic in networking. The target of the path computation is to choose an appropriate path for the traffic flow. With the emergence of Software-defined networking (SDN), path computation moves from the distributed network nodes to a centralized controller. In this thesis, we will present a load balancing algorithm in SDN framework for popular data center networks and a fault management approach for hybrid SDN networks. The proposed load balancing algorithm computes and selects appropriate paths based on characteristics of data center networks and congestion status. In addition, a solution that supports proper operations of a hybrid SDN network will also be proposed. The evaluation shows the proposed load balancing algorithm performs better than classic shortest path algorithms. We also demonstrated that the proposed solution for hybrid SDN networks can support proper operations in complicated hybrid SDN networks.

scholarly journals Path computation enhancement in SDN networks

2021 ◽  
Author(s):  
Tim Huang
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Management Approach ◽  
Distributed Network ◽  
Data Center Networks ◽  
Network Nodes ◽  
Path Computation ◽  
Shortest Path Algorithms ◽  
Load Balancing Algorithm ◽  
Hybrid Sdn

Path computation is always the core topic in networking. The target of the path computation is to choose an appropriate path for the traffic flow. With the emergence of Software-defined networking (SDN), path computation moves from the distributed network nodes to a centralized controller. In this thesis, we will present a load balancing algorithm in SDN framework for popular data center networks and a fault management approach for hybrid SDN networks. The proposed load balancing algorithm computes and selects appropriate paths based on characteristics of data center networks and congestion status. In addition, a solution that supports proper operations of a hybrid SDN network will also be proposed. The evaluation shows the proposed load balancing algorithm performs better than classic shortest path algorithms. We also demonstrated that the proposed solution for hybrid SDN networks can support proper operations in complicated hybrid SDN networks.

Hidden Markov Model-based Load Balancing in Data Center Networks

2019 ◽  
Vol 63 (10) ◽  
pp. 1449-1462
Author(s):  
Binjie He ◽  
Dong Zhang ◽  
Chang Zhao
Keyword(s):  
Load Balancing ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Data Center ◽  
Data Centers ◽  
Hidden Markov ◽  
Path Selection ◽  
Data Center Networks ◽  
Data Flows ◽  
Load Balancing Algorithm

Abstract Modern data centers provide multiple parallel paths for end-to-end communications. Recent studies have been done on how to allocate rational paths for data flows to increase the throughput of data center networks. A centralized load balancing algorithm can improve the rationality of the path selection by using path bandwidth information. However, to ensure the accuracy of the information, current centralized load balancing algorithms monitor all the link bandwidth information in the path to determine the path bandwidth. Due to the excessive link bandwidth information monitored by the controller, however, much time is consumed, which is unacceptable for modern data centers. This paper proposes an algorithm called hidden Markov Model-based Load Balancing (HMMLB). HMMLB utilizes the hidden Markov Model (HMM) to select paths for data flows with fewer monitored links, less time cost, and approximate the same network throughput rate as a traditional centralized load balancing algorithm. To generate HMMLB, this research first turns the problem of path selection into an HMM problem. Secondly, deploying traditional centralized load balancing algorithms in the data center topology to collect training data. Finally, training the HMM with the collected data. Through simulation experiments, this paper verifies HMMLB’s effectiveness.

Load balancing with traffic isolation in data center networks

2021 ◽  
Author(s):  
Tao Zhang ◽  
Qianqiang Zhang ◽  
Yasi Lei ◽  
Shaojun Zou ◽  
Juan Huang ◽  
...  
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Data Center Networks

scholarly journals Load Balance in Data Center SDN Networks

2018 ◽  
Vol 8 (5) ◽  
pp. 3084 ◽  
Author(s):  
Tariq Emad Ali ◽  
Ameer Hussein Morad ◽  
Mohammed A. Abdala
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Network Architecture ◽  
Current Data ◽  
Traffic Load ◽  
Network Architectures ◽  
Data Center Networks ◽  
Network Resources ◽  
Cloud Network ◽  
And Storage

<span>In the last two decades, networks had been changed according to the rapid changing in its requirements.  The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations.  The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs.  Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs</span>

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