scholarly journals A simulated annealing algorithm for router nodes placement problem in Wireless Mesh Networks

2011 ◽  
Vol 19 (10) ◽  
pp. 2276-2284 ◽  
Author(s):  
Fatos Xhafa ◽  
Admir Barolli ◽  
Christian Sánchez ◽  
Leonard Barolli
Keyword(s):  
Simulated Annealing ◽  
Wireless Mesh Networks ◽  
Simulated Annealing Algorithm ◽  
Mesh Networks ◽  
Placement Problem ◽  
Wireless Mesh ◽  
Annealing Algorithm

scholarly journals Threshold Accepting Heuristic for Fair Flow Optimization in Wireless Mesh Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jarosław Hurkała ◽  
Tomasz Śliwiński
Keyword(s):  
Wireless Mesh Networks ◽  
Simulated Annealing Algorithm ◽  
Mesh Networks ◽  
Difficult Problem ◽  
Weighted Averaging ◽  
Mixed Integer ◽  
Threshold Accepting ◽  
Wireless Mesh ◽  
Annealing Algorithm ◽  
Better Than

Developing effective, fairness-preserving optimization algorithms is of considerable importance in systems which serve many users. In this paper we show the results of the threshold accepting procedure applied to extremely difficult problem of fair resource allocation in wireless mesh networks (WMN). The fairness is modeled by allowing preferences with regard to distribution of Internet traffic between network participants. As aggregation operator we utilize weighted ordered weighted averaging (WOWA). In the underlaying optimization problem, the physical medium properties cause strong interference among simultaneously operating node devices, leading to nonlinearities in the mixed-integer pricing subproblem. That is where the threshold accepting procedure is applied. We show that, the threshold accepting heuristic performs much better than the widely utilized simulated annealing algorithm.

Application of WMN-SA Simulation System for Node Placement in Wireless Mesh Networks

2014 ◽  
Vol 6 (2) ◽  
pp. 13-21 ◽  
Author(s):  
Shinji Sakamoto ◽  
Algenti Lala ◽  
Tetsuya Oda ◽  
Vladi Kolici ◽  
Leonard Barolli ◽  
...  
Keyword(s):  
Wireless Mesh Networks ◽  
Mesh Networks ◽  
Network Connectivity ◽  
Simulation System ◽  
Placement Problem ◽  
Node Placement ◽  
Wireless Mesh ◽  
User Coverage ◽  
Router Node Placement ◽  
Cost Efficient

One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. In WMNs, there are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, the authors consider the router node placement problem in WMNs. The objective is to find the optimal distribution of router nodes in order to provide the best network connectivity (the maximal number of connected routers) and coverage (maximal number of covered clients). The authors apply their proposed WMN-SA simulation system in a realistic scenario of the distribution of mesh clients considering Itoshima City, Fukuoka Prefecture, Japan. From simulation results, they found many insights that can be very important for real deployment of WMNs.

scholarly journals Performance Evaluation Considering Iterations per Phase and SA Temperature in WMN-SA System

2014 ◽  
Vol 10 (3) ◽  
pp. 321-330 ◽  
Author(s):  
Shinji Sakamoto ◽  
Elis Kulla ◽  
Tetsuya Oda ◽  
Makoto Ikeda ◽  
Leonard Barolli ◽  
...  
Keyword(s):  
Simulated Annealing Algorithm ◽  
Mesh Networks ◽  
Network Connectivity ◽  
Placement Problem ◽  
Node Placement ◽  
Wireless Mesh ◽  
Size Of Giant Component ◽  
User Coverage ◽  
Router Node Placement ◽  
Cost Efficient

One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider Simulated Annealing Algorithm (SA) temperature and Iteration per phase for the router node placement problem in WMNs. We want to find the optimal distribution of router nodes in order to provide the best network connectivity and provide the best coverage in a set of Normal distributed clients. From simulation results, we found how to optimize both the size of Giant Component and number of covered mesh clients. When the number of iterations per phase is big, the performance is better in WMN-SA System. From for SA temperature, when SA temperature is 0 and 1, the performance is almost same. When SA temperature is 2 and 3 or more, the performance decrease because there are many kick ups.

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