Outline

  • Abstract
  • Keywords
  • 1. Introduction
  • 2. Background and Relatedwork
  • 2.1. Minimizing Deployment Cost
  • 2.2. Minimizing Latency
  • 3. Mathematical Model for Sdn Multi-Controller
  • 4. Latency-Aware, Cost-Aware Controller Placement Problem
  • 4.1. Problem Formulation
  • 4.2. System Utilization
  • 4.3. Salp Swarm Algorithm (ssa)
  • 4.4. Chaotic Salp Swarm Algorithm (cssa)
  • 4.5. Chaotic Maps
  • 4.6. Cssa for Optimal Number of Controllers and Optimal Allocations
  • 5. Performance Evaluation
  • 5.1. 1. Simulation Setup
  • 5.2. 2. Simulation Results
  • 5.3. 3. System Comparison
  • 6. Conclusion
  • Appendix A.
  • References

رئوس مطالب

  • چکیده
  • کلیدواژه ها
  • 1. مقدمه
  • 2. پیشینه و کارهای مرتبط
  • 1. 2. به حداقل رساندن هزینه های استقرار
  • 2.2. به حداقل رساندن تاخیر
  • 3. مدل ریاضی شبکه چندکنترل کننده ای SDN
  • 4. مسئله استقرار کنترل کننده آگاه از هزینه و تاخیر
  • 1. 4. فرمولاسیون مسئله
  • 2. 4. بهره برداری از سیستم
  • 3. 4. الگوریتم ازدحام سالپ (SSA)
  • 4. 4. الگوریتم ازدحام سالپ مبتنی بر آشوب (CSSA)
  • 5. 4. نگاشت های آشوب
  • 6. 4. CSSA برای تعداد بهینه کنترل کننده ها و تخصیص های بهینه
  • 6. نتیجه گیری
  • ضمیمه A
  • منابع

Abstract

Software-defined networking (SDN) is a novel network paradigm that enables flexible management for networks. However, with the increase in network capacity, a single controller of SDN has many limitations on both performance and scalability. Distributed multi-controller deployment is a promising method to satisfy fault tolerant and scalability. There are still open research issues related to controllers placement, and the optimal number of deployed controllers. In this paper, a dynamic optimization algorithm that is based on the Salp Swarm Optimization Algorithm (SSOA) is developed with the introduction of chaotic maps for enhancing the optimizer’s performance. The algorithm dynamically evaluates the optimum number of controllers and the optimal connections between switches and controllers in large scale SDN networks. In order to evaluate the proposed algorithm, several experiments were conducted and implemented in various scenarios. Moreover, the algorithm was compared to the linear and meta-heuristic algorithms. Simulation results show that the proposed algorithm outperforms meta-heuristic algorithms and a game theory based algorithm in terms of execution time and reliability.

Keywords: - - - - -

Conclusions

This work introduces the latency and cost aware controller placement problem. The problem is defined and a meta-heuristic algorithm is presented to solve the problem for the optimum solution. The algorithm is a chaotic SSA that is developed to get the optimal number of controllers and also the optimum allocations of switches to controllers, that minimize the latency and the deployment cost. The introduction of chaotic maps improves the optimizer performance and prevents the local optima. The algorithm is tested for various real topologies extracted from the zoo topology. The effect of variation of different network parameters on the performance is checked. Simulation results validate the proposed work and a comparison with other meta-heuristic algorithms and a game theory based algorithm is presented.

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