MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters

MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters Software-defined networking (SDN) introduces a new method in networking that by offering programmability and centralization, it can dynamically control and configure networks. In traditional networks, data plane did the whole forwarding process, but SDN decouples data plane and control plane by using programmable software controllers for deciding how to forward different flows. By implementing control plane in a software-based independent layer, the network management will become much easier and new policies can be applied to the network by changing a few lines of code. Since the resource allocation and meeting the required service-level agreement are really important in large-scale networks such as cloud datacenters, using SDN can be very useful. In these networks, one logically centralized controller cannot handle the whole network traffic and it will become network bottleneck. Therefore, multiple distributed controllers should be allocated in different regions of the network. Since the request rate of switches varies in time, by dynamic allocation of controllers, network resources will be allocated efficiently and this approach can also reduce power consumption. In this paper, we are going to propose a framework for provisioning software controllers in cloud datacenters by using metaheuristic algorithms. These algorithms can be less accurate compared to other kinds, but their main characteristics like simplicity, flexibility, derivation free, and local optimum avoidance make them a good nominee for solving controller provisioning problem and controller placement problem. Our framework improves computation time and reaches better results compared to other allocation techniques, but it is less accurate in some scenarios. Therefore, we believe metaheuristic approach can be very useful in developing new technologies for SDN in the future. The Journal of Supercomputing Springer Journals

MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters

Loading next page...
Springer US
Copyright © 2017 by Springer Science+Business Media New York
Computer Science; Programming Languages, Compilers, Interpreters; Processor Architectures; Computer Science, general
Publisher site
See Article on Publisher Site


You’re reading a free preview. Subscribe to read the entire article.

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches


Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.



billed annually
Start Free Trial

14-day Free Trial