Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks
Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol) dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many...
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doaj-32e0be3741ef4934bf2e67cdddecd6ef2020-11-24T22:40:54ZengElsevierEngineering Science and Technology, an International Journal2215-09862017-02-0120131032010.1016/j.jestch.2016.06.015Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networksRamanpreet Kaur0Amrit Lal Sangal1Krishan Kumar2Department of Computer Science and Engineering, National Institute of Technology, Jalandhar, Punjab, IndiaDepartment of Computer Science and Engineering, National Institute of Technology, Jalandhar, Punjab, IndiaDepartment of Computer Science and Engineering, Shaheed Bhagat Singh State Technical Campus, Ferozpur, Punjab, IndiaIntelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol) dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.http://www.sciencedirect.com/science/article/pii/S2215098616302725Overlay maintenanceNeuro-fuzzyStabilization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ramanpreet Kaur Amrit Lal Sangal Krishan Kumar |
spellingShingle |
Ramanpreet Kaur Amrit Lal Sangal Krishan Kumar Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks Engineering Science and Technology, an International Journal Overlay maintenance Neuro-fuzzy Stabilization |
author_facet |
Ramanpreet Kaur Amrit Lal Sangal Krishan Kumar |
author_sort |
Ramanpreet Kaur |
title |
Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
title_short |
Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
title_full |
Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
title_fullStr |
Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
title_full_unstemmed |
Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
title_sort |
modeling and simulation of adaptive neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks |
publisher |
Elsevier |
series |
Engineering Science and Technology, an International Journal |
issn |
2215-0986 |
publishDate |
2017-02-01 |
description |
Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol) dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach. |
topic |
Overlay maintenance Neuro-fuzzy Stabilization |
url |
http://www.sciencedirect.com/science/article/pii/S2215098616302725 |
work_keys_str_mv |
AT ramanpreetkaur modelingandsimulationofadaptiveneurofuzzybasedintelligentsystemforpredictivestabilizationinstructuredoverlaynetworks AT amritlalsangal modelingandsimulationofadaptiveneurofuzzybasedintelligentsystemforpredictivestabilizationinstructuredoverlaynetworks AT krishankumar modelingandsimulationofadaptiveneurofuzzybasedintelligentsystemforpredictivestabilizationinstructuredoverlaynetworks |
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1725702820771921920 |