Recent Trends in Software-Defined Networking: A Bibliometric Review

Software-Defined Networking is referred to as the next big thing in the field of networking. Legacy networks contain various components such as switches, routers, etc. with a variety of complex protocols. A network administrator is responsible for configuring all these various components. Apart from complex network management, network security is also a persistent issue in the field of networking. SDN promises simplicity in network management while also dramatically improving the security of networks. This paper gives an analysis of the current trends in in SDN as well as Security challenges with SDN. A bibliometric review on SDN has also been outlined in this paper. We have also mentioned some of the challenges posed by the SDN architecture and also some of the solutions to combat the

QoS - Aware content oriented flow routing in optical computer network

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis, one of the most important issues in the field of networks communication is tackled and addressed. This issue is represented by QoS, where the increasing demand on highquality applications together with the fast increase in the rates of Internet users have led to massive traffic being transmitted on the Internet. This thesis proposes new ideas to manage the flow of this huge traffic in a manner that contributes in improving the communication QoS. This can be achieved by replacing the conventional application-insensitive routing schemes by others which take into account the type of applications when making the routing decision. As a first contribution, the effect on the potential development in the quality of experience on the loading of Basra optical network has been investigated. Furthermore, the traffic due to each application was dealt with in different ways according to their delay and loss sensitivities. Load rate distributions over the various links due to the different applications were deployed to investigate the places of possible congestions in the network and the dominant applications that cause such congestions. In addition, OpenFlow and Optica Burst Switching (OBS) techniques were used to provide a wider range of network controllability and management. A centralised routing protocol that takes into account the available bandwidth, delay, and security as three important QoS parameters, when forwarding traffics of different types, was proposed and implemented using OMNeT++ networks simulator. As a novel idea, security has been incorporated in our QoS requirements by incorporating Oyster Optics Technology (OOT) to secure some of the optical links aiming to supply the network with some secure paths for those applications that have high privacy requirements. A particular type of traffic is to be routed according to the importance of these three QoS parameters for such a traffic type. The link utilisation, end to end delays and securities due to the different applications were recorded to prove the feasibility of our proposed system. In order to decrease the amount of traffic overhead, the same QoS constraints were implemented on a distributed Ant colony based routing. The traditional Ant routing protocol was improved by adopting the idea of Red-Green-Blue (RGB) pheromones routing to incorporate these QoS constraints. Improvements of 11% load balancing, and 9% security for private data was achieved compared to the conventional Ant routing techniques. In addition, this Ant based routing was utilised to propose an improved solution for the routing and wavelength assignment problem in the WDM optical computer networks

The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures

Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment

Improving Pan-African research and education networks through traffic engineering: A LISP/SDN approach

The UbuntuNet Alliance, a consortium of National Research and Education Networks (NRENs) runs an exclusive data network for education and research in east and southern Africa. Despite a high degree of route redundancy in the Alliance's topology, a large portion of Internet traffic between the NRENs is circuitously routed through Europe. This thesis proposes a performance-based strategy for dynamic ranking of inter-NREN paths to reduce latencies. The thesis makes two contributions: firstly, mapping Africa's inter-NREN topology and quantifying the extent and impact of circuitous routing; and, secondly, a dynamic traffic engineering scheme based on Software Defined Networking (SDN), Locator/Identifier Separation Protocol (LISP) and Reinforcement Learning. To quantify the extent and impact of circuitous routing among Africa's NRENs, active topology discovery was conducted. Traceroute results showed that up to 75% of traffic from African sources to African NRENs went through inter-continental routes and experienced much higher latencies than that of traffic routed within Africa. An efficient mechanism for topology discovery was implemented by incorporating prior knowledge of overlapping paths to minimize redundancy during measurements. Evaluation of the network probing mechanism showed a 47% reduction in packets required to complete measurements. An interactive geospatial topology visualization tool was designed to evaluate how NREN stakeholders could identify routes between NRENs. Usability evaluation showed that users were able to identify routes with an accuracy level of 68%. NRENs are faced with at least three problems to optimize traffic engineering, namely: how to discover alternate end-to-end paths; how to measure and monitor performance of different paths; and how to reconfigure alternate end-to-end paths. This work designed and evaluated a traffic engineering mechanism for dynamic discovery and configuration of alternate inter-NREN paths using SDN, LISP and Reinforcement Learning. A LISP/SDN based traffic engineering mechanism was designed to enable NRENs to dynamically rank alternate gateways. Emulation-based evaluation of the mechanism showed that dynamic path ranking was able to achieve 20% lower latencies compared to the default static path selection. SDN and Reinforcement Learning were used to enable dynamic packet forwarding in a multipath environment, through hop-by-hop ranking of alternate links based on latency and available bandwidth. The solution achieved minimum latencies with significant increases in aggregate throughput compared to static single path packet forwarding. Overall, this thesis provides evidence that integration of LISP, SDN and Reinforcement Learning, as well as ranking and dynamic configuration of paths could help Africa's NRENs to minimise latencies and to achieve better throughputs

Conserve and Protect Resources in Software-Defined Networking via the Traffic Engineering Approach

Software Defined Networking (SDN) is revolutionizing the architecture and operation of computer networks and promises a more agile and cost-efficient network management. SDN centralizes the network control logic and separates the control plane from the data plane, thus enabling flexible management of networks. A network based on SDN consists of a data plane and a control plane. To assist management of devices and data flows, a network also has an independent monitoring plane. These coexisting network planes have various types of resources, such as bandwidth utilized to transmit monitoring data, energy spent to power data forwarding devices and computational resources to control a network. Unwise management, even abusive utilization of these resources lead to the degradation of the network performance and increase the Operating Expenditure (Opex) of the network owner. Conserving and protecting limited network resources is thus among the key requirements for efficient networking. However, the heterogeneity of the network hardware and network traffic workloads expands the configuration space of SDN, making it a challenging task to operate a network efficiently. Furthermore, the existing approaches usually lack the capability to automatically adapt network configurations to handle network dynamics and diverse optimization requirements. Addtionally, a centralized SDN controller has to run in a protected environment against certain attacks. This thesis builds upon the centralized management capability of SDN, and uses cross-layer network optimizations to perform joint traffic engineering, e.g., routing, hardware and software configurations. The overall goal is to overcome the management complexities in conserving and protecting resources in multiple functional planes in SDN when facing network heterogeneities and system dynamics. This thesis presents four contributions: (1) resource-efficient network monitoring, (2) resource-efficient data forwarding, (3) using self-adaptive algorithms to improve network resource efficiency, and (4) mitigating abusive usage of resources for network controlling. The first contribution of this thesis is a resource-efficient network monitoring solution. In this thesis, we consider one specific type of virtual network management function: flow packet inspection. This type of the network monitoring application requires to duplicate packets of target flows and send them to packet monitors for in-depth analysis. To avoid the competition for resources between the original data and duplicated data, the network operators can transmit the data flows through physically (e.g., different communication mediums) or virtually (e.g., distinguished network slices) separated channels having different resource consumption properties. We propose the REMO solution, namely Resource Efficient distributed Monitoring, to reduce the overall network resource consumption incurred by both types of data, via jointly considering the locations of the packet monitors, the selection of devices forking the data packets, and flow path scheduling strategies. In the second contribution of this thesis, we investigate the resource efficiency problem in hybrid, server-centric data center networks equipped with both traditional wired connections (e.g., InfiniBand or Ethernet) and advanced high-data-rate wireless links (e.g., directional 60GHz wireless technology). The configuration space of hybrid SDN equipped with both wired and wireless communication technologies is massively large due to the complexity brought by the device heterogeneity. To tackle this problem, we present the ECAS framework to reduce the power consumption and maintain the network performance. The approaches based on the optimization models and heuristic algorithms are considered as the traditional way to reduce the operation and facility resource consumption in SDN. These approaches are either difficult to directly solve or specific for a particular problem space. As the third contribution of this thesis, we investigates the approach of using Deep Reinforcement Learning (DRL) to improve the adaptivity of the management modules for network resource and data flow scheduling. The goal of the DRL agent in the SDN network is to reduce the power consumption of SDN networks without severely degrading the network performance. The fourth contribution of this thesis is a protection mechanism based upon flow rate limiting to mitigate abusive usage of the SDN control plane resource. Due to the centralized architecture of SDN and its handling mechanism for new data flows, the network controller can be the failure point due to the crafted cyber-attacks, especially the Control-Plane- Saturation (CPS) attack. We proposes an In-Network Flow mAnagement Scheme (INFAS) to effectively reduce the generation of malicious control packets depending on the parameters configured for the proposed mitigation algorithm. In summary, the contributions of this thesis address various unique challenges to construct resource-efficient and secure SDN. This is achieved by designing and implementing novel and intelligent models and algorithms to configure networks and perform network traffic engineering, in the protected centralized network controller

DESIGN OF RELIABLE AND SUSTAINABLE WIRELESS SENSOR NETWORKS: CHALLENGES, PROTOCOLS AND CASE STUDIES

Integrated with the function of sensing, processing, and wireless communication, wireless sensors are attracting strong interest for a variety of monitoring and control applications. Wireless sensor networks (WSNs) have been deployed for industrial and remote monitoring purposes. As energy shortage is a worldwide problem, more attention has been placed on incorporating energy harvesting devices in WSNs. The main objective of this research is to systematically study the design principles and technical approaches to address three key challenges in designing reliable and sustainable WSNs; namely, communication reliability, operation with extremely low and dynamic power sources, and multi-tier network architecture. Mathematical throughput models, sustainable WSN communication strategies, and multi-tier network architecture are studied in this research to address these challenges, leading to protocols for reliable communication, energy-efficient operation, and network planning for specific application requirements. To account for realistic operating conditions, the study has implemented three distinct WSN testbeds: a WSN attached to the high-speed rotating spindle of a turning lathe, a WSN powered by a microbial fuel cell based energy harvesting system, and a WSN with a multi-tier network architecture. With each testbed, models and protocols are extracted, verified and analyzed. Extensive research has studied low power WSNs and energy harvesting capabilities. Despite these efforts, some important questions have not been well understood. This dissertation addresses the following three dimensions of the challenge. First, for reliable communication protocol design, mathematical throughput or energy efficiency estimation models are essential, yet have not been investigated accounting for specific application environment characteristics and requirements. Second, for WSNs with energy harvesting power sources, most current networking protocols do not work efficiently with the systems considered in this dissertation, such as those powered by extremely low and dynamic energy sources. Third, for multi-tier wireless network system design, routing protocols that are adaptive to real-world network conditions have not been studied. This dissertation focuses on these questions and explores experimentally derived mathematical models for designing protocols to meet specific application requirements. The main contributions of this research are 1) for industrial wireless sensor systems with fast-changing but repetitive mobile conditions, understand the performance and optimal choice of reliable wireless sensor data transmission methods, 2) for ultra-low energy harvesting wireless sensor devices, design an energy neutral communication protocol, and 3) for distributed rural wireless sensor systems, understand the efficiency of realistic routing in a multi-tier wireless network. Altogether, knowledge derived from study of the systems, models, and protocols in this work fuels the establishment of a useful framework for designing future WSNs

Threat Landscape and Good Practice Guide for Software Defined Networks/5G

5G represents the next major phase of mobile telecommunication systems and network architectures beyond the current 4G standards, aiming at extreme broadband and ultra-robust, low latency connectivity, to enable the programmable connectivity for the Internet of Everything2. Despite the significant debate on the technical specifications and the technological maturity of 5G, which are under discussion in various fora3, 5G is expected to affect positively and significantly several industry sectors ranging from ICT to industry sectors such as car and other manufacturing, health and agriculture in the period up to and beyond 2020. 5G will be driven by the influence of software on network functions, known as Software Defined Networking (SDN) and Network Function Virtualization (NFV). The key concept that underpins SDN is the logical centralization of network control functions by decoupling the control and packet forwarding functionality of the network. NFV complements this vision through the virtualization of these functionalities based on recent advances in general server and enterprise IT virtualization. Considering the technological maturity of the technologies that 5G can leverage on, SDN is the one that is moving faster from development to production. To realize the business potential of SDN/5G, a number of technical issues related to the design and operation of Software Defined Networks need to be addressed. Amongst them, SDN/5G security is one of the key issues, that needs to be addressed comprehensively in order to avoid missing the business opportunities arising from SDN/5G. In this report, we review threats and potential compromises related to the security of SDN/5G networks. More specifically, this report contains a review of the emerging threat landscape of 5G networks with particular focus on Software Defined Networking. It also considers security of NFV and radio network access. To provide a comprehensive account of the emerging threat SDN/5G landscape, this report has identified related network assets and the security threats, challenges and risks arising for these assets. Driven by the identified threats and risks, this report has also reviewed and identified existing security mechanisms and good practices for SDN/5G/NFV, and based on these it has analysed gaps and provided technical, policy and organizational recommendations for proactively enhancing the security of SDN/5G