Genetic Algorithms for Network Optimization

Kosiński, Witold; Mikolajewski, Daniel

doi:10.1109/cason.2009.19

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…Content may change prior to final publication. a randomized, search-based, global optimization algorithm frequently employed to solve network or integer complex problems [55]- [59]. Section IV-D includes a case study to assess how closely a GA solution is to the optimal solution.…”

Section: Numerical Evaluation and Discussionmentioning

confidence: 99%

Maximizing Network Reliability to 0-Day Exploits Through a Heterogeneous Node Migration Strategy

2021

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A recurrent problem currently affecting network reliability is the simultaneous exploitation of 0-day vulnerabilities shared between several node implementations across the network. When such 0-day vulnerabilities are exploited, large portions of the network may get compromised as a result. In this work, we propose a network node migration strategy to minimize the impact of 0-day attacks on network reliability. The migration method proposes replacing homogeneous node implementations with diverse alternatives to yield a heterogeneous network. The migration method allocates heterogeneous nodes within the network by minimizing the product between the average and the maximum number of network partitions, which may emerge after the simultaneous exploitation of 0-day risks on shared network resources. As we show, our migration strategy maximizes network connectivity in the event of a simultaneous 0-day attack. Our work's significant findings are the following: First, increasing the heterogeneity in node technologies reduces the attacker's ability to break down the entire network. Second, given a set of available network technologies that partially share risks, a network design implemented using several heterogeneous technologies sharing a small number of 0-day risks is more reliable than one with a small number of technologies whose 0-day risks are disjoint. Third, we observed that in a node-heterogeneous network topology, clustering nodes by technology improves network reliability.INDEX TERMS Network diversity, network reliability, 0-day vulnerabilities, connected components.

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Section: Numerical Evaluation and Discussionmentioning

confidence: 99%

Maximizing Network Reliability to 0-Day Exploits Through a Heterogeneous Node Migration Strategy

2021

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Optimization of Network paths in congested SDN using Genetic Algorithm

MAHESH

Devi

2022

ijngc

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Computer network and Communication over such networks become integral part of human life from the very beginning of twenty first century. From the very first radio communication in the beginning of 19th Century to the latest wireless and Software Defined Network (SDN) communication over the satellite and local allied computer networks, caused increase in more and more traffic over the computer network. Internet was not only provided over the copper, fiber optics cables, but rather it becomes a commercial service sector over the low earth orbit satellites across the globe. Majority of the contents flowing over such networks are either academic, research, corporate data bases like banking, finance, IT services, social media, and also specially of the entertainment industry. Every small to large organization in corporate and research and development organization faced problems of computer network congestion over the time. As the demand for more data access is required hence the congestion over the network started to increase. Every nation and individual organization have their own policy to control domestic network traffic as bandwidth is limited and commercial aspects are involved. Various algorithms have focused to regulate network, but very few algorithms exist which focuses on providing alternative paths for better network traffic management. This paper focuses on using modern Genetic Algorithms like Ants colony optimization to first identify congestions over the network and then using such insights to find alternative paths through mutation and cross over. The proposed solution was executed, and generated result comparatively proved that use of Genetic Algorithm has helped to find alternative paths more effectively over the SDN.

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Genetic Algorithms for Network Optimization

Cited by 2 publications

References 16 publications

Maximizing Network Reliability to 0-Day Exploits Through a Heterogeneous Node Migration Strategy

Maximizing Network Reliability to 0-Day Exploits Through a Heterogeneous Node Migration Strategy

Optimization of Network paths in congested SDN using Genetic Algorithm

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