scholarly journals Fixed channel assignment algorithm for multi-radio multi-channel MESH networks

2008 ◽  
Vol 8 (6) ◽  
pp. 811-828 ◽  
Author(s):  
Hamed M. K. Alazemi ◽  
A. Das ◽  
R. Vijaykumar ◽  
S. Roy
Author(s):  
Felix Juraschek ◽  
Mesut Günes ◽  
Bastian Blywis

DES-Chan is a framework for experimentally driven research on distributed channel assignment algorithms in wireless mesh networks. DES-Chan eases the development process by providing a set of common services required by distributed channel assignment algorithms. A new challenge for channel assignment algorithms are sources of external interferences. With the increasing number of wireless devices in the unlicensed radio spectrum, co-located devices that share the same radio channel may have a severe impact on the network performance. DES-Chan provides a sensing component to detect such external devices and predict their future activity. As a proof of concept, the authors present a reference implementation of a distributed greedy channel assignment algorithm. The authors evaluate its performance in the DES-Testbed, a multi-transceiver wireless mesh network with 128 nodes at the Freie Universität Berlin.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 85903-85912
Author(s):  
Junhua Xing ◽  
Qi Li ◽  
Haixin Sun ◽  
Jie Qi ◽  
Zhenggen Zhu ◽  
...  

Author(s):  
Tarik Mountassir ◽  
Bouchaib Nassereddine ◽  
Abdelkrim Haqiq ◽  
Samir Bennani

Unlike most of proposed solutions that usually consider the overall throughput as the main optimization, Channel Assignment in Wireless Mesh Networks has to ensure connectivity, minimize interference level and guarantee an acceptable throughput. This problem must be solved taking into account all the parameters that influence the output of the proposed algorithm. In this paper, the authors propose an efficient multi-objective optimization model that, simultaneously, optimizes two conflicting objective functions in order to assign channel to radio interfaces subject to connectivity, interference and bandwidth requirements. Then they use the Multi-Objective Particle Swarm Optimization Technique to resolve this problem and provide a non-dominated set of near optimal solutions.


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