Cognitive-Aware Network Virtualization Hypervisor for Efficient Resource Provisioning in Software Defined Cloud Networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIntegration of different technologies forms an integral part of modern network engineering and 5G technology deployment. Although Software Defined Networking (SDN) and Network Functions Virtualization (NFV) function well independently, integrating these two technologies present the cooperate advantages to service providers and service users. Operations of cloud computing technologies have been enhanced with the advent of SDN and NFV for efficient solutions deployment and infrastructure management in Software Defined Cloud Datacentre Networks (SDCDCN) where dynamic controllability is indispensable for elastic service provision. The provisioning of joint compute and network resources enabled by SDCN is essential to enforce reasonable Service Level Agreements (SLAs) stating the Quality of Service (QoS) while saving energy consumption and resource wastage. This thesis presents a Cognitive- Aware Network virtualization Hypervisor which was developed from merging the programmable dynamic network control attributes of SDN and the network slicing attributes of NFV to provision joint compute and network resources in SDCDCN for QoS fulfilment and energy efficiency. It focuses on the techniques for allocating Virtual Network Requests on physical hosts and switches considering SLA, QoS, and energy efficiency aspects. The thesis advances the state-of the-art with the following key contributions: A modelling and simulation environment for Software Defined Cloud Datacentre Networks abstracting functionalities and behaviours of virtual and physical network resources. The second is a novel dynamic overbooking algorithm for energy efficiency and SLA enforcement with the migration of virtual machines and network flows. Finally, a performance-aware intelligent overbooking for predicting network resource usage and performance for the next defined time interval considering multiple performance indexes

The design and evaluation of Wireless Sensor Networks for applications in industrial locations

In manufacturing industries, there exist many applications where Wireless Sensor Networks (WSN\u27s) are integrated to provide wireless solution for the automated manufacturing processes. It is well known that industrial environments characterized by extreme conditions such as high temperature, pressure, and electromagnetic (EM) interference that can affect the performance of the WSN\u27s. The key solution to overcome this performance issue is by monitoring the received Signal Strength Index (RSSI) at the received sensor of the WSN device and track frame error rate of wireless packets. ZigBee is a wireless sensor network (WSN) standard designed for specific needs of the remote monitoring sensor system. Zigbee networks can be established by three different topologies: start, hybrid, and mesh. In this research project, the interest in analyzing the characteristics of the Zigbee performance was completed using a star topology network. Three performance parameters were obtained: the RSSI signal to monitor the received wireless packets from the sending node, path-lost exponent to determine the effect of industrial environment on wireless signals, and the frame error rate to know the discontinue time. The study was in three phases and took place in two settings: The first was at the manufacturing laboratory at the University of Northern Iowa, the second and the third were at the facility of a Midwestern manufacturing company. The study aimed to provide an analytical tool to evaluate the performances of Zigbee networks in industrial environments and compare the results to show that harsh environments do affect its performance. The study also involved testing the performance of WSN. This was done by simulating input/output Line passing with digital and analog data. Packets were sent from one node and counted at the receiving side to measure the packet error rate of WSN in industrial environment. In conclusion, investigating the WSN\u27s systems performance in industrial environment provides is crucial to identify the effects of the harsh conditions. It is necessary to run similar investigation to prevent the malfunction of the manufacturing applications. Testing a simple WSN in industrial environment can be capable of predicting the performance of the network. It is also recommended to have an embedded approach to WSN applications that can self-monitor its performance

IMPROVING QoS OF VoWLAN VIA CROSS-LAYER BASED ADAPTIVE APPROACH

Voice over Internet Protocol (VoIP) is a technology that allows the transmission of voice packets over Internet Protocol (IP). Recently, the integration of VoIP and Wireless Local Area Network (WLAN), and known as Voice over WLAN (VoWLAN), has become popular driven by the mobility requirements ofusers, as well as by factor of its tangible cost effectiveness. However, WLAN network architecture was primarily designed to support the transmission of data, and not for voice traffic, which makes it lack ofproviding the stringent Quality ofService (QoS) for VoIP applications. On the other hand, WLAN operates based on IEEE 802.11 standards that support Link Adaptive (LA) technique. However, LA leads to having a network with multi-rate transmissions that causes network bandwidth variation, which hence degrades the voice quality. Therefore, it is important to develop an algorithm that would be able to overcome the negative effect of the multi-rate issue on VoIP quality. Hence, the main goal ofthis research work is to develop an agent that utilizes IP protocols by applying a Cross-Layering approach to eliminate the above-mentioned negative effect. This could be expected from the interaction between Medium Access Control (MAC) layer and Application layer, where the proposed agent adapts the voice packet size at the Application layer according to the change of MAC transmission data rate to avoid network congestion from happening. The agent also monitors the quality of conversations from the periodically generated Real Time Control Protocol (RTCP) reports. If voice quality degradation is detected, then the agent performs further rate adaptation to improve the quality. The agent performance has been evaluated by carrying out an extensive series ofsimulation using OPNET Modeler. The obtained results of different performance parameters are presented, comparing the performance ofVoWLAN that used the proposed agent to that ofthe standard network without agent. The results ofall measured quality parameters hav