Resilient network dimensioning for optical grid/clouds using relocation

In this paper we address the problem of dimensioning infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We will provide an overview of our work in this area, and in particular focus on how to design the resulting grid/cloud to be resilient against network link and/or server site failures. To this end, we will exploit relocation: under failure conditions, a request may be sent to an alternate destination than the one under failure-free conditions. We will provide a comprehensive overview of related work in this area, and focus in some detail on our own most recent work. The latter comprises a case study where traffic has a known origin, but we assume a degree of freedom as to where its end up being processed, which is typically the case for e. g., grid applications of the bag-of-tasks (BoT) type or for providing cloud services. In particular, we will provide in this paper a new integer linear programming (ILP) formulation to solve the resilient grid/cloud dimensioning problem using failure-dependent backup routes. Our algorithm will simultaneously decide on server and network capacity. We find that in the anycast routing problem we address, the benefit of using failure-dependent (FD) rerouting is limited compared to failure-independent (FID) backup routing. We confirm our earlier findings in terms of network capacity savings achieved by relocation compared to not exploiting relocation (order of 6-10% in the current case studies)

Network recovery after massive failures

This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large scale disruption. We give a formulation of the problem as an MILP and show that it is NP-hard. We propose a polynomial time heuristic, called Iterative Split and Prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared to several greedy approaches ISP performs better in terms of number of repaired components, and does not result in any demand loss. It performs very close to the optimal when the demand is low with respect to the supply network capacities, thanks to the ability of the algorithm to maximize sharing of repaired resources

Self-healing and SDN: bridging the gap

Achieving high programmability has become an essential aim of network research due to the ever-increasing internet traffic. Software-Defined Network (SDN) is an emerging architecture aimed to address this need. However, maintaining accurate knowledge of the network after a failure is one of the largest challenges in the SDN. Motivated by this reality, this paper focuses on the use of self-healing properties to boost the SDN robustness. This approach, unlike traditional schemes, is not based on proactively configuring multiple (and memory-intensive) backup paths in each switch or performing a reactive and time-consuming routing computation at the controller level. Instead, the control paths are quickly recovered by local switch actions and subsequently optimized by global controller knowledge. Obtained results show that the proposed approach recovers the control topology effectively in terms of time and message load over a wide range of generated networks. Consequently, scalability issues of traditional fault recovery strategies are avoided.Postprint (published version

Congestion removal in the next generation internet

The ongoing development of new and demanding Internet applications requires the Internet to deliver better service levels that are significantly better than the best effort service that the Internet currently provides and was built for. These improved service levels include guaranteed delays, jitter and bandwidth. Through extensive research into Quality of Service and Differentiated Service (DiffServ) it has become possible to provide guaranteed services, however this turns out to be inadequate without the application of Traffic Engineering methodologies and principles. Traffic Engineering is an integral part of network operation. Its major goal is to deliver the best performance from an existing service provider's network resources and, at the same time, to enhance a customers' view of network performance. In this thesis, several different traffic engineering methods for optimising the operation of native IP and IP networks employing MPLS are proposed. A feature of these new methods is their fast run times and this opens the way to making them suitable for application in an online traffic engineering environment. For native IP networks running shortest path based routing protocols, we show that an LP-based optimisation based on the well known multi-commodity flow problem can be effective in removing network congestion. Having realised that Internet service providers are now moving towards migrating their networks to the use of MPLS, we have also formulated optimisation methods to traffic engineer MPLS networks by selecting suitable routing paths and utilising the feature of explicit routing contained in MPLS. Although MPLS is capable of delivering traffic engineering across different classes of traffic, network operators still prefer to rely on the proven and simple IP based routing protocols for best effort traffic and only use MPLS to route traffic requiring special forwarding treatment. Based on this fact, we propose a method that optimises the routing patterns applicable to different classes of traffic based on their bandwidth requirements. A traffic engineering comparison study that evaluates the performance of a neural network-based method for MPLS networks and LP-based weight setting approach for shortest path based networks has been performed using a well-known open source network simulator, called ns2. The comparative evaluation is based upon the packet loss probability. The final chapter of the thesis describes the software development of a network management application called OptiFlow which integrates techniques described in earlier chapters including the LP-based weight setting optimisation methodology; it also uses traffic matrix estimation techniques that are required as input to the weight setting models that have been devised. The motivation for developing OptiFlow was to provide a prototype set of tools that meet the congestion management needs of networking industries (ISPs and telecommunications companies - telcos)

QoS Restoration using a Disjoint Path Group in ATM Networks

Abstract A QoS restoration scheme for VP-based ATM network is proposed and its related characteristics are evaluated. The proposed scheme is a state-independent restoration scheme using a disjoint path group. A VP assignment and capacity planning problem using disjoint path group are formulated. When a failure occurs, failed working VPs are switched to protection paths with the same QoS level using a simple and fast restoration algorithm. The simulated restoration characteristics of the proposed algorithm are presented. A scheme of excess capacity assignment to protection path for dynamic traffic demands is also presented and analyzed

A comparative study of single-layer and multi-layer traffic engineering approaches on transparent optical networks

This paper comparatively studies single-layer and multi-layer traffic engineering strategies on an IP/MPLS/WDM network. These strategies are evaluated and compared in two different scenarios. In the first scenario, the strategies make use of statistical information on the traffic patterns. In the second scenario, the traffic engineering decisions are based on the instantaneous traffic information only. The performance and benefits of both approaches are discussed based on simulations considering both throughput and network resource usage. © 2007 IEEE