Nature-inspired meta-heuristic algorithms for solving the load balancing problem in the software-defined network

被引:42
作者
Neghabi, Ali Akbar [1 ]
Navimipour, Nima Jafari [2 ]
Hosseinzadeh, Mehdi [1 ]
Rezaee, Ali [1 ]
机构
[1] Islamic Azad Univ, Sci & Res Branch, Dept Comp Engn, Tehran, Iran
[2] Islamic Azad Univ, Tabriz Branch, Dept Comp Engn, Tabriz, Iran
关键词
load balancing; meta-heuristic; nature-inspired; review; SDN; software-defined networks; OPTIMIZATION; OPENFLOW; SDN; SYSTEM; COLONY; PERFORMANCE; MECHANISMS; DISCOVERY; INTERNET; MUTATION;
D O I
10.1002/dac.3875
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The growth of the networks has difficult network management. Recently, a concept called software-defined network (SDN) has been proposed to address this issue, which makes network management more adaptable. Control and forwarding planes are separated in SDN. The control plane is a centralized logical controller that controls the network. The forwarding plane that consists of transfer devices is responsible for transmitting packets. Because the network resources are limited, optimizing the use of resources in the networks is an important issue. Load balancing improves the balanced distribution of loads across multiple resources in order to maximize the reliability and network resources efficiency. SDN controllers can create an optimal load balancing compared to traditional networks because they have a network global view. The load-balancing problem can be solved using many different nature-inspired meta-heuristic techniques because it has the NP-complete nature. Hence, for solving load balancing problem in SDN, nature-inspired meta-heuristic techniques are important methods. However, to the best of our knowledge, there is not a survey or systematic review on studying these matters. Accordingly, in the area of the load balancing in the SDN, this paper reviews systematically the nature-inspired meta-heuristic techniques. Also, this study demonstrates advantages and disadvantages regarded of the chosen nature-inspired meta-heuristic techniques and considers their algorithms metrics. Moreover, to apply better load balancing techniques in the future, the important challenges of these techniques have been investigated.
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页数:26
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