Expect the unexpected: Sub-second optimization for segment routing

In this paper, we study how to perform traffic engineering at an extremely-small time scale with segment routing, addressing a critical need for modern wide area networks. Prior work has shown that segment routing enables to better engineer traffic, thanks to its ability to program detours in forwarding paths, at scale. Two main approaches have been explored for traffic engineering with segment routing, respectively based on integer linear programming and constraint programming. However, no previous work deeply investigated how quickly those approaches can react to unexpected traffic changes and failures. We highlight limitations of existing algorithms, both in terms of required execution time and amount of path changes to be applied. Thus, we propose a new approach, based on local search and focused on the quick re-arrangement of (few) forwarding paths. We describe heuristics for sub-second recomputation of segment-routing paths that comply with requirements on the maximum link load (e.g., for congestion avoidance). Our heuristics enable a prompt answer to sudden criticalities affecting network services and business agreements. Through extensive simulations, we indeed experimentally show that our proposal significantly outperforms previous algorithms in the context of time-constrained optimization, supporting radical traffic changes in few tens of milliseconds for realistic networks

Optimal fault-tolerant placement of relay nodes in a mission critical wireless network

The operations of many critical infrastructures (e.g., airports) heavily depend on proper functioning of the radio communication network supporting operations. As a result, such a communication network is indeed a mission-critical communication network that needs adequate protection from external electromagnetic interferences. This is usually done through radiogoniometers. Basically, by using at least three suitably deployed radiogoniometers and a gateway gathering information from them, sources of electromagnetic emissions that are not supposed to be present in the monitored area can be localised. Typically, relay nodes are used to connect radiogoniometers to the gateway. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper address the problem of computing a deployment for relay nodes that minimises the relay node network cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that the above problem can be formulated as a Mixed Integer Linear Programming (MILP) as well as a Pseudo-Boolean Satisfiability (PB-SAT) optimisation problem and present experimental results com- paring the two approaches on realistic scenarios

Multi-objective model for optimizing railway infrastructure asset renewal

Trabalho inspirado num problema real da empresa Infraestruturas de Portugal, EP.A multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.info:eu-repo/semantics/publishedVersio

Iterative Resource Allocation Algorithm for EONs Based on a Linearized GN Model

Elastic optical networks (EONs) rely on efficient resource planning to meet future communication needs and avoid resource overprovisioning. Estimation of physical-layer impairments (PLIs) in EONs plays an important role in the network planning stage. Traditionally, the transmission reach (TR) and Gaussian noise (GN) models have been broadly employed in the estimation of the PLIs. However, the TR model cannot accurately estimate PLIs, whereas the GN model is incompatible with state of the art linear optimization solvers. In this paper, we propose a physical-layer estimation model based on the GN model, referred to as the conservative linearized Gaussian noise (CLGN) model. To address the routing, spectrum, and regeneration assignment problem accounting for PLIs, we introduce a link-based mixed integer linear programming formulation employing the CLGN, whose heavy computational burden is relieved by a heuristic approach referred to as the sequential iterative optimization algorithm. We show through simulation that network resources such as spectrum and regeneration nodes can be saved utilizing the CLGN model rather than the TR model. Our proposed heuristic algorithm speeds up the optimization process and provides better resource usage compared to state of the art algorithms on benchmark networks

Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results

Fixed and mobile telecom operators, enterprise network operators and cloud providers strive to face the challenging demands coming from the evolution of IP networks (e.g. huge bandwidth requirements, integration of billions of devices and millions of services in the cloud). Proposed in the early 2010s, Segment Routing (SR) architecture helps face these challenging demands, and it is currently being adopted and deployed. SR architecture is based on the concept of source routing and has interesting scalability properties, as it dramatically reduces the amount of state information to be configured in the core nodes to support complex services. SR architecture was first implemented with the MPLS dataplane and then, quite recently, with the IPv6 dataplane (SRv6). IPv6 SR architecture (SRv6) has been extended from the simple steering of packets across nodes to a general network programming approach, making it very suitable for use cases such as Service Function Chaining and Network Function Virtualization. In this paper we present a tutorial and a comprehensive survey on SR technology, analyzing standardization efforts, patents, research activities and implementation results. We start with an introduction on the motivations for Segment Routing and an overview of its evolution and standardization. Then, we provide a tutorial on Segment Routing technology, with a focus on the novel SRv6 solution. We discuss the standardization efforts and the patents providing details on the most important documents and mentioning other ongoing activities. We then thoroughly analyze research activities according to a taxonomy. We have identified 8 main categories during our analysis of the current state of play: Monitoring, Traffic Engineering, Failure Recovery, Centrally Controlled Architectures, Path Encoding, Network Programming, Performance Evaluation and Miscellaneous...Comment: SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIAL

Optimizing Integrated Arrival, Departure and Surface Operations Under Uncertainty

In airports and surrounding terminal airspaces, the integration of arrival, departure and surface scheduling and routing have the potential to improve the operations efficiency. Recent research had developed mixed-integer-linear programming algorithm-based scheduler for integrated arrival and departure operations in the presence of uncertainty. This paper extends to the surface previous research performed by the authors to integrate taxiway and runway operations. The developed algorithm is capable of computing optimal aircraft schedules and routings that reflects the integration of air and ground operations. A preliminary study case is conducted for a set of thirteen aircraft evolving in a model of the Los Angeles International airport and surrounding terminal areas. Using historical data, a representative traffic scenario is constructed and probabilistic distributions of pushback delay and arrival gate delay are obtained. To assess the benefits of optimization, a First- Come-First-Serve algorithm approach comparison is realized. Evaluation results demonstrate that the optimization can help identifying runway sequencing and schedule that reduce gate waiting time without increasing average taxi times