Evaluation of Controller Capacity in Software-Defined-Network with Batch Flow Requests

The development of SDN gives a new paradigm to networking by flow-based OpenFlow architecture, which decouples the control plane from the data plane. The controller manages the switches in the network, and the central issue in this network architecture is a controller manage how many switches. This paper investigates the controller capacity regarding the flow requests to the switches forwarded from the controller in batches and models the queueing system as Mx/M/1. We present the expressions in explicit form and derive the performance measures of the controller, such as the probability distribution of the system, cumulative distribution system, mean length of the system, the waiting time of the flow requests in the system, and utilization of the controller. These measures help the service providers to make the system model depending on the number of flow requests that arrive at the controller from the switches in an idle condition.

Publication Details

Journal
Nanotechnology Perceptions
Published
2024-10-24
DOI
https://doi.org/10.62441/nano-ntp.v20i6.30
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluation of Controller Capacity in Software-Defined-Network with Batch Flow Requests

Nanotechnology Perceptions
Software-Defined Networks and 5G
article

Evaluation of Controller Capacity in Software-Defined-Network with Batch Flow Requests

article en

Abstract

The development of SDN gives a new paradigm to networking by flow-based OpenFlow architecture, which decouples the control plane from the data plane. The controller manages the switches in the network, and the central issue in this network architecture is a controller manage how many switches. This paper investigates the controller capacity regarding the flow requests to the switches forwarded from the controller in batches and models the queueing system as Mx/M/1. We present the expressions in explicit form and derive the performance measures of the controller, such as the probability distribution of the system, cumulative distribution system, mean length of the system, the waiting time of the flow requests in the system, and utilization of the controller. These measures help the service providers to make the system model depending on the number of flow requests that arrive at the controller from the switches in an idle condition.

Nanotechnology PerceptionsVol. 20(6)
Openalex Percentile: Top 78%
Software-Defined Networks and 5G
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