Overcoming Bandwidth Fluctuations in Hybrid Networks with QoS-Aware Adaptive Routing

With an escalating reliance on sensor-driven scientific endeavors in challenging terrains, the significance of robust hybrid networks, formed by a combination of wireless and wired links, is more noticeable than ever. These networks serve as essential channels for data streaming to centralized data centers, but their efficiency is often degraded by bandwidth fluctuations and network congestion. Especially in bandwidth-sensitive hybrid networks, these issues present demanding challenges to Quality of Service (QoS). Traditional network management solutions fail to provide an adaptive response to these dynamic challenges, thereby underscoring the need for innovative solutions. This thesis introduces a novel approach leveraging the concept of Software-Defined Networking (SDN) to establish a dynamic, congestion-aware routing mechanism. This proposed mechanism stands out by comprising a unique strategy of using bandwidth-based measurements, which help accurately detect and localize network congestion. Unlike traditional methodologies that rely on rigid route management, our approach demonstrates dynamic data flow route adjustment. Experimental data indicate promising outcomes with clear improvements in network utilization and application performance. Furthermore, the proposed algorithm exhibits remarkable scalability, providing quick route-finding solutions for various data flows, without impacting system performance. Thus, this thesis contributes to the ongoing discourse on enhancing hybrid network efficiency in challenging conditions, setting the stage for future explorations in this area

Evaluation of virtual routing appliances as routers virtual environment

A virtual routing appliance is a system for the rapid, automated management and employment of virtual networks. Virtual routing appliances utilize virtual machines to enable virtual infrastructure, and they have been used commonly in order to implement experimental networks and devoted subnets over a virtual network. Existing research in this area such as cluster-based virtual routers, and Xen routers require the use of physical resources to establish connectivity and to guarantee efficient resource utilization. The virtual routing appliance uses dynamic routing protocols such as RIP, and OSPF to forward traffic between different subnets and manage IP packets at the IP layer. The virtual routing appliance permits rapidly deployable virtual infrastructure, which is helpful for installing isolated infrastructure for restricted purposes, and which is also vital to the deployment of both network and application services. This research is a self-sufficient initiative to evaluate the feasibility of setting up virtual routing appliances in a virtual environment. A virtual routing appliance can convey about substantial cost benefits to organizations, especially educational institutions with limited use of physical resources

Automated System to Debug Under-performing Network Flows in Wide Area Networks

Locating the cause of performance losses in large high performance Wide Area Networks (WAN) is an extremely challenging problem. This is because WANs comprise several distributed sub-networks (Autonomous Networks), with their own independent network monitoring systems. Each individual monitoring system has limited or no access to network devices outside its own network. Moreover, conventional network monitoring systems are designed only to provide information about the health of individual network devices, and do not provide sufficient information to monitor endto- end performance – thus, adding severe overhead on debugging end-toend performance issues. In this thesis, an automated tool is designed that requires no special access to network devices and no special software installations on the network devices or end hosts. The system detects performance losses and locates the most likely problem nodes (routers/links) in the network. A key component of this system is the novel hybrid network monitoring/data collection system. The monitoring/data collection sub-system is designed to obtain the best of both active and passive monitoring techniques. Then, pattern analysis algorithms are designed. They locate the causes of performance loss using the data collected from above sub-system. This system is being tested on the GLORIAD (Global Ring Network for Advanced Application Development) network. One of the future goals is to in tegrate this system into the GLORIAD’s network monitoring tool set, to provide end-to-end network monitoring and problem mitigation capabilities

Distributed control of reconfigurable mobile network agents for resource coordination

Includes abstract.Includes bibliographical references.Considering the tremendous growth of internet applications and network resource federation proposed towards future open access network (FOAN), the need to analyze the robustness of the classical signalling mechanisms across multiple network operators cannot be over-emphasized. It is envisaged, there will be additional challenges in meeting the bandwidth requirements and network management...The first objective of this project is to describe the networking environment based on the support for heterogeneity of network components..

Statistical analysis of network traffic for anomaly detection and quality of service provisioning

Network-wide traffic analysis and monitoring in large-scale networks is a challenging and expensive task. In this thesis work we have proposed to analyze the traffic of a large-scale IP network from aggregated traffic measurements, reducing measurement overheads and simplifying implementation issues. We have provided contributions in three different networking fields related to network-wide traffic analysis and monitoring in large-scale IP networks. The first contribution regards Traffic Matrix (TM) modeling and estimation, where we have proposed new statistical models and new estimation methods to analyze the Origin-Destination (OD) flows of a large-scale TM from easily available link traffic measurements. The second contribution regards the detection and localization of volume anomalies in the TM, where we have introduced novel methods with solid optimality properties that outperform current well-known techniques for network-wide anomaly detection proposed so far in the literature. The last contribution regards the optimization of the routing configuration in large-scale IP networks, particularly when the traffic is highly variable and difficult to predict. Using the notions of Robust Routing Optimization we have proposed new approaches for Quality of Service provisioning under highly variable and uncertain traffic scenarios. In order to provide strong evidence on the relevance of our contributions, all the methods proposed in this thesis work were validated using real traffic data from different operational networks. Additionally, their performance was compared against well-known works in each field, showing outperforming results in most cases. Taking together the ensemble of developed TM models, the optimal network-wide anomaly detection and localization methods, and the routing optimization algorithms, this thesis work offers a complete solution for network operators to efficiently monitor large-scale IP networks from aggregated traffic measurements and to provide accurate QoS-based performance, even in the event of volume traffic anomalie

Aspects of proactive traffic engineering in IP networks

To deliver a reliable communication service over the Internet it is essential for the network operator to manage the traffic situation in the network. The traffic situation is controlled by the routing function which determines what path traffic follows from source to destination. Current practices for setting routing parameters in IP networks are designed to be simple to manage. This can lead to congestion in parts of the network while other parts of the network are far from fully utilized. In this thesis we explore issues related to optimization of the routing function to balance load in the network and efficiently deliver a reliable communication service to the users. The optimization takes into account not only the traffic situation under normal operational conditions, but also traffic situations that appear under a wide variety of circumstances deviating from the nominal case. In order to balance load in the network knowledge of the traffic situations is needed. Consequently, in this thesis we investigate methods for efficient derivation of the traffic situation. The derivation is based on estimation of traffic demands from link load measurements. The advantage of using link load measurements is that they are easily obtained and consist of a limited amount of data that need to be processed. We evaluate and demonstrate how estimation based on link counts gives the operator a fast and accurate description of the traffic demands. For the evaluation we have access to a unique data set of complete traffic demands from an operational IP backbone. However, to honor service level agreements at all times the variability of the traffic needs to be accounted for in the load balancing. In addition, optimization techniques are often sensitive to errors and variations in input data. Hence, when an optimized routing setting is subjected to real traffic demands in the network, performance often deviate from what can be anticipated from the optimization. Thus, we identify and model different traffic uncertainties and describe how the routing setting can be optimized, not only for a nominal case, but for a wide range of different traffic situations that might appear in the network. Our results can be applied in MPLS enabled networks as well as in networks using link state routing protocols such as the widely used OSPF and IS-IS protocols. Only minor changes may be needed in current networks to implement our algorithms. The contributions of this thesis is that we: demonstrate that it is possible to estimate the traffic matrix with acceptable precision, and we develop methods and models for common traffic uncertainties to account for these uncertainties in the optimization of the routing configuration. In addition, we identify important properties in the structure of the traffic to successfully balance uncertain and varying traffic demands