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Utilizing Soft Computing Application for QOS and Security Optimization by Meta-Heuristic-Based Genetic Approach

Utilizing Soft Computing Application for QOS and Security Optimization by Meta-Heuristic-Based Genetic Approach

Sherin Zafar
Copyright: © 2017 |Pages: 11
ISBN13: 9781522521549|ISBN10: 1522521542|EISBN13: 9781522521556
DOI: 10.4018/978-1-5225-2154-9.ch010
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MLA

Zafar, Sherin. "Utilizing Soft Computing Application for QOS and Security Optimization by Meta-Heuristic-Based Genetic Approach." Detecting and Mitigating Robotic Cyber Security Risks, edited by Raghavendra Kumar, et al., IGI Global, 2017, pp. 148-158. https://doi.org/10.4018/978-1-5225-2154-9.ch010

APA

Zafar, S. (2017). Utilizing Soft Computing Application for QOS and Security Optimization by Meta-Heuristic-Based Genetic Approach. In R. Kumar, P. Pattnaik, & P. Pandey (Eds.), Detecting and Mitigating Robotic Cyber Security Risks (pp. 148-158). IGI Global. https://doi.org/10.4018/978-1-5225-2154-9.ch010

Chicago

Zafar, Sherin. "Utilizing Soft Computing Application for QOS and Security Optimization by Meta-Heuristic-Based Genetic Approach." In Detecting and Mitigating Robotic Cyber Security Risks, edited by Raghavendra Kumar, Prasant Kumar Pattnaik, and Priyanka Pandey, 148-158. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2154-9.ch010

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Abstract

In cloud computing network, due to high node mobility, routing is regarded as one of the most challenging task. Some of the traditional protocols developed for cloud networks, wireless network and cyber world use dynamic optimization for QOS accomplishment using some of the optimality criterions like shortest distance, minimal bandwidth usage and minimum delay and constraints like limited power and limited capability of wireless links. GA (Genetic Algorithm) based approach is utilized in this chapter for QOS design based secured routing protocol, where GA is used for finding the most optimal (fittest route) hence improving QOS leading to an optimized secured routing protocol. GA based approach which is discussed in this chapter, selecting the fittest route leads to optimization of QOS based performance parameters like average packet delivery ratio, average drop rate etc. Simulation results shown in the chapter also validate the approach.

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