5 research outputs found
Scalable Load Balancing Scheme for Distributed Controllers in Software Defined Data Centers
International audienc
Multi-Agent Deep Reinforcement Learning for Request Dispatching in Distributed-Controller Software-Defined Networking
Recently, distributed controller architectures have been quickly gaining
popularity in Software-Defined Networking (SDN). However, the use of
distributed controllers introduces a new and important Request Dispatching (RD)
problem with the goal for every SDN switch to properly dispatch their requests
among all controllers so as to optimize network performance. This goal can be
fulfilled by designing an RD policy to guide distribution of requests at each
switch. In this paper, we propose a Multi-Agent Deep Reinforcement Learning
(MA-DRL) approach to automatically design RD policies with high adaptability
and performance. This is achieved through a new problem formulation in the form
of a Multi-Agent Markov Decision Process (MA-MDP), a new adaptive RD policy
design and a new MA-DRL algorithm called MA-PPO. Extensive simulation studies
show that our MA-DRL technique can effectively train RD policies to
significantly outperform man-made policies, model-based policies, as well as RD
policies learned via single-agent DRL algorithms
Load Balancing Mechanisms in the Software Defined Networks: A Systematic and Comprehensive Review of the Literature
With the expansion of the network and increasing their users, as well as emerging new technologies, such as cloud computing and big data, managing traditional networks is difficult. Therefore, it is necessary to change the traditional network architecture. Lately, to address this issue, a notion named software-defined network (SDN) has been proposed, which makes network management more conformable. Due to limited network resources and to meet the requirements of quality of service, one of the points that must be considered is load balancing issue that serves to distribute data traffic among multiple resources in order to maximize the efficiency and reliability of network resources. Load balancing is established based on the local information of the network in the conventional network. Hence, it is not very precise. However, SDN controllers have a global view of the network and can produce more optimized load balances. Although load balancing mechanisms are important in the SDN, to the best of our knowledge, there exists no precise and systematic review or survey on investigating these issues. Hence, this paper reviews the load balancing mechanisms which have been used in the SDN systematically based on two categories, deterministic and non-deterministic. Also, this paper represents benefits and some weakness regarded of the selected load balancing algorithms and investigates the metrics of their algorithms. In addition, the important challenges of these algorithms have been reviewed, so better load balancing techniques can be applied by the researchers in the future. © 2018 IEEE