Modelling and Performance Analysis of OpenFlow Switches in Software-Defined Networking

<p>Software-Defined-Networking (SDN) simplifies the configuration complexity in the computer communication network by decoupling the control plane from the data plane in a switch. In SDN, the switch has the data plane only and is configured by the logically centralised controller which simplifies the forwarding of packets in the network. However, an SDN switch is sensitive to delay and loss of packets which significantly affects the network performance. This thesis uses queueing theory to conduct modelling and performance analysis of OpenFlow-based SDN switches. OpenFlow is the de-facto protocol for communication between an SDN switch and the controller. Using queueing theory, three aspects of packet processing in an SDN switch are explored. First, the existing research has primarily modelled the output buffer of an SDN switch using two buffer sharing mechanisms: the single shared buffer and the priority buffer. However, the effect of buffer dimensioning in these buffer sharing mechanisms has not been investigated. Buffer dimensioning helps in determining the minimum buffer capacity for a desired loss probability. The research in this thesis shows that the use of priority buffer in an SDN switch reduces the time to update flow tables than the shared buffer but at the cost of a higher buffer capacity. Second, much of the existing research has not investigated the impact of internal buffering of data packets whereby a fraction of a data packet header is sent to the controller instead of an entire data packet. To investigate the impact of internal buffering, the queueing model for an SDN switch with the internal buffer is developed. The investigation shows that at the time of congestion, the internal buffer in an SDN switch improves the network performance with lower delay and lower packet loss. Finally, existing research has focused on a software switch in SDN and very little research has studied the performance of a hardware switch. To characterise the performance of SDN-based hardware and software switches and identify the tradeoffs between them, a unified queueing model has been developed. The unified queueing model is an analytical tool for network engineers to predict delay and packet loss in their SDN deployments. The analysis shows the benefits of a hardware switch over a software switch. These benefits are lower delay and lower packet loss. However, the increasing involvement of the controller reduces the benefit of using a hardware switch, i.e. forwarding packets at the line speed rate. This research guides network designers and analysts in the selection of the shared or buffer model for an SDN switch for their desired Quality of Service (QoS). Furthermore, the developed queueing model for an SDN switch with the internal buffer studies the impact of internal buffering in an SDN switch. Finally, the unified queueing model helps in the selection of a software or hardware switch in SDN.</p>

Modelling and Performance Analysis of OpenFlow Switches in Software-Defined Networking

<p>Software-Defined-Networking (SDN) simplifies the configuration complexity in the computer communication network by decoupling the control plane from the data plane in a switch. In SDN, the switch has the data plane only and is configured by the logically centralised controller which simplifies the forwarding of packets in the network. However, an SDN switch is sensitive to delay and loss of packets which significantly affects the network performance. This thesis uses queueing theory to conduct modelling and performance analysis of OpenFlow-based SDN switches. OpenFlow is the de-facto protocol for communication between an SDN switch and the controller. Using queueing theory, three aspects of packet processing in an SDN switch are explored. First, the existing research has primarily modelled the output buffer of an SDN switch using two buffer sharing mechanisms: the single shared buffer and the priority buffer. However, the effect of buffer dimensioning in these buffer sharing mechanisms has not been investigated. Buffer dimensioning helps in determining the minimum buffer capacity for a desired loss probability. The research in this thesis shows that the use of priority buffer in an SDN switch reduces the time to update flow tables than the shared buffer but at the cost of a higher buffer capacity. Second, much of the existing research has not investigated the impact of internal buffering of data packets whereby a fraction of a data packet header is sent to the controller instead of an entire data packet. To investigate the impact of internal buffering, the queueing model for an SDN switch with the internal buffer is developed. The investigation shows that at the time of congestion, the internal buffer in an SDN switch improves the network performance with lower delay and lower packet loss. Finally, existing research has focused on a software switch in SDN and very little research has studied the performance of a hardware switch. To characterise the performance of SDN-based hardware and software switches and identify the tradeoffs between them, a unified queueing model has been developed. The unified queueing model is an analytical tool for network engineers to predict delay and packet loss in their SDN deployments. The analysis shows the benefits of a hardware switch over a software switch. These benefits are lower delay and lower packet loss. However, the increasing involvement of the controller reduces the benefit of using a hardware switch, i.e. forwarding packets at the line speed rate. This research guides network designers and analysts in the selection of the shared or buffer model for an SDN switch for their desired Quality of Service (QoS). Furthermore, the developed queueing model for an SDN switch with the internal buffer studies the impact of internal buffering in an SDN switch. Finally, the unified queueing model helps in the selection of a software or hardware switch in SDN.</p>

hQChain_Leveraging towards Blockchain and Queueing Model for Secure Smart Connected Health

Blockchain facilitates a broad spectrum of applications such as transaction of cryptocurrency, catering to financial services, designing and constructing smart cities and so on. It has astounding benefits including accountability, consistency and decentralization. Smart healthcare can be exemplified as utilizing propitious electronic technology safeguarded with blockchain for superior diagnosis of the disorders, improvised and cost-effective treatment of the patients, and enhanced quality of lives. Since, blockchain in smart healthcare architecture hosts substantial amount of patient data queueing models play a pivotal role to efficiently process the data. In this paper, it highlights the concepts of blockchain, then delve into the smart healthcare architecture and then deal with the several queueing models that already exist. It proposes the model i.e. hQChain which is inculcating M1,b/Mb/1 queueing model into blockchain based smart healthcare architecture. It offers a queuing mathematical and analytical model to analyze and study the performance measurement of hQChain model.

hQChain

Blockchain facilitates a broad spectrum of applications such as transaction of cryptocurrency, catering to financial services, designing and constructing smart cities and so on. It has astounding benefits including accountability, consistency and decentralization. Smart healthcare can be exemplified as utilizing propitious electronic technology safeguarded with blockchain for superior diagnosis of the disorders, improvised and cost-effective treatment of the patients, and enhanced quality of lives. Since, blockchain in smart healthcare architecture hosts substantial amount of patient data queueing models play a pivotal role to efficiently process the data. In this paper, it highlights the concepts of blockchain, then delve into the smart healthcare architecture and then deal with the several queueing models that already exist. It proposes the model i.e. hQChain which is inculcating M1,b/Mb/1 queueing model into blockchain based smart healthcare architecture. It offers a queuing mathematical and analytical model to analyze and study the performance measurement of hQChain model.

Customer-Server Population Dynamics in Heavy Traffic

We study a many-server queueing model with server vacations, where the population size dynamics of servers and customers are coupled: a server may leave for vacation only when no customers await, and the capacity available to customers is directly affected by the number of servers on vacation. We focus on scaling regimes in which server dynamics and queue dynamics fluctuate at matching time scales so that their limiting dynamics are coupled. Specifically, we argue that interesting coupled dynamics occur in (a) the Halfin–Whitt regime, (b) the nondegenerate slowdown regime, and (c) the intermediate near Halfin–Whitt regime, whereas the dynamics asymptotically decouple in the other heavy-traffic regimes. We characterize the limiting dynamics, which are different for each scaling regime. We consider relevant respective performance measures for regimes (a) and (b)—namely, the probability of wait and the slowdown. Although closed-form formulas for these performance measures have been derived for models that do not accommodate server vacations, it is difficult to obtain closed-form formulas for these performance measures in the setting with server vacations. Instead, we propose formulas that approximate these performance measures and depend on the steady-state mean number of available servers and previously derived formulas for models without server vacations. We test the accuracy of these formulas numerically.