Title : 
Co-existence of Evolutionary Mixed-Bias Scheduling with Quiescence and IEEE 802.11 DCF for Wireless Mesh Networks
         
        
            Author : 
Ernst, Jason B. ; Brown, Joseph Alexander
         
        
            Author_Institution : 
Sch. of Comput. Sci., Univ. of Guelph, Guelph, ON, Canada
         
        
        
        
        
        
            Abstract : 
The evolutionary programming mixed bias scheduling has been shown to provide significantly reduced end-to-end delay while maintaining comparable packet delivery ratio when evaluated using simulation experiments compared to the current IEEE 802.11 DCF standard. In this paper, proposed is an enhanced MB-EP algorithm which includes a new quiescent state called MB-EP-Q. This new approach is evaluated using network simulation with respect to throughput and delay. The new approach was found to have similar performance to the existing MB-EP approach. Furthermore to demonstrate that the MB-EP-Q approach can co-exist with existing IEEE 802.11 DCF mechanisms another experiment is performed where a portion of the routers are running the MB-EP-Q algorithm while the rest run IEEE 802.11 DCF. The results show an improvement in performance even when a small proportion of the nodes are running the MB-EP-Q algorithm. This result is important since it shows that the MB-EP approaches can be applied to existing deployments gradually and with lower cost than other competing approaches which may require the entire network infrastructure to be modified.
         
        
            Keywords : 
evolutionary computation; scheduling; telecommunication standards; wireless LAN; wireless mesh networks; IEEE 802.11 DCF standard; MB-EP-Q algorithm; distributed coordination function; end-to-end delay; evolutionary mixed-bias scheduling; evolutionary programming; network simulation; quiescent state; wireless mesh networks; Delay; IEEE 802.11 Standards; Logic gates; Predictive models; Programming; Scheduling; Wireless mesh networks; IEEE 802.11 DCF; co-existence; evolutionary algorithms; evolutionary programming; feedback; mixed bias; parameter computation; scheduling; wireless mesh network;
         
        
        
        
            Conference_Titel : 
Advanced Information Networking and Applications Workshops (WAINA), 2012 26th International Conference on
         
        
            Conference_Location : 
Fukuoka
         
        
            Print_ISBN : 
978-1-4673-0867-0
         
        
        
            DOI : 
10.1109/WAINA.2012.215