A dandelion-encoded evolutionary algorithm for the delay-constrained capacitated minimum spanning tree problem

This paper proposes an evolutionary algorithm with Dandelion-encoding to tackle the Delay-Constrained Capacitated Minimum Spanning Tree (DC-CMST) problem. This problem has been recently proposed, and consists of finding several broadcast trees from a source node, jointly considering traffic and delay constraints in trees. A version of the problem in which the source node is also included in the optimization process is considered as well in the paper. The Dandelion code used in the proposed evolutionary algorithm has been recently proposed as an effective way of encoding trees in evolutionary algorithms. Good properties of locality has been reported on this encoding, which makes it very effective to solve problems in which the solutions can be expressed in form of trees. In the paper we describe the main characteristics of the algorithm, the implementation of the Dandelion-encoding to tackled the DC-CMST problem and a modification needed to include the source node in the optimization. In the experimental section of this article we compare the results obtained by our evolutionary with that of a recently proposed heuristic for the DC-CMST. the Least Cost (LC) algorithm. We show that our Dandelion-encoded evolutionary algorithm is able to obtain better results that the LC in all the instances tackled. (C) 2008 Elsevier B.V. All rights reserved

A Microeconomics-Based Fuzzy QoS Unicast Routing Scheme in NGI

Abstract. Due to the difficulty on exact measurement and expression of NGI (Next-Generation Internet) network status, the necessary QoS routing information is fuzzy. With the gradual commercialization of network operation, paying for network usage calls for QoS pricing and accounting. In this paper, a microeconomics-based fuzzy QoS unicast routing scheme is proposed, consisting of three phases: edge evaluation, game analysis, and route selection. It attempts to make both network provider and user utilities maximized along the found route, with not only the user QoS requirements satisfied but also the Pareto-optimum under the Nash equilibrium on their utilities achieved

QOS routing source routing problems and solutions

The notion of Quality-of-Service has been proposed to capture qualitatively or quantitatively defined performance contracts between the service provider and the user applications. Integrated network services are designed to support Quality-of-Service (QoS). One of the primary goals for the integrated network services is to find the paths that satisfy given QoS requirements, namely QoS routing. The challenging issue in this area is to route packets subjected to multiple uncorrelated constraints because the problem is inherently NP-complete. This thesis studies the source routing heuristic approaches that bring the time complexity down to the polynomial-time for the multi-constrained path (MCP) problem. A new source routing framework (SRDE) is further proposed to tackle this problem. The theoretical analysis and simulation results demonstrate that the proposed framework is capable of integrating existing source routing algorithms, resulting in better performance in terms of the time complexity and success ratio

Optimized resource distribution for interactive TV applications

This paper proposes a novel resource optimization scheme for cloud-based interactive television applications that are increasingly believed to be the future of television broadcasting and media consumption, in general. The varying distribution of groups of users and the need for on-the-fly media processing inherent to this type of application necessitates a mechanism to efficiently allocate the resources at both a content and network level. A heuristic solution is proposed in order to (a) generate end-to-end delay bound multicast trees for individual groups of users and (b) co-locate multiple multicast trees, such that a minimum group quality metric can be satisfied. The performance of the proposed heuristic solution is evaluated in terms of the serving probability (i.e., the resource utilization efficiency) and execution time of the resource allocation decision making process. It is shown that improvements in the serving probability of up to 50%, in comparison with existing resource allocation schemes, and several orders of magnitude reduction of the execution time, in comparison to the linear programming approach to solving the optimization problem, can be achieved

Secure and robust multi-constrained QoS aware routing algorithm for VANETs

Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In Vehicular Ad hoc Networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the Ant Colony Optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented Evolving Graph (VoEG) model to perform plausibility checks on the exchanged routing control messages among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service

Computing Delay-Constrained Least-Cost Paths for Segment Routing is Easier Than You Think

With the growth of demands for quasi-instantaneous communication services such as real-time video streaming, cloud gaming, and industry 4.0 applications, multi-constraint Traffic Engineering (TE) becomes increasingly important. While legacy TE management planes have proven laborious to deploy, Segment Routing (SR) drastically eases the deployment of TE paths and thus became the most appropriate technology for many operators. The flexibility of SR sparked demands in ways to compute more elaborate paths. In particular, there exists a clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC) for real-time applications requiring both low delay and high bandwidth routes. However, most current DCLC solutions are heuristics not specifically tailored for SR. In this work, we leverage both inherent limitations in the accuracy of delay measurements and an operational constraint added by SR. We include these characteristics in the design of BEST2COP, an exact but efficient ECMP-aware algorithm that natively solves DCLC in SR domains. Through an extensive performance evaluation, we first show that BEST2COP scales well even in large random networks. In real networks having up to thousands of destinations, our algorithm returns all DCLC solutions encoded as SR paths in way less than a second

Вибір методу підвищення відмово стійкості програмно- конфігуруємої (SDN) мережі

Об’єкт дослідження: програмно-конфігуруємі мережі. Предмет дослідження: способи забезпечення надійності в програмно- конфігуруємих мережах. Мета дипломної роботи: вибрати методи забезпечення надійності (вімовостікості) SDN мережі для архітектурних рішень та на прикладному рівні. У першому розділі описано і проаналізовано технологію SDN. Наведено детальний опис методів резервування на прикладному рівні та розглянуто посилення надійності з точки зору фізичної реалізації. Сформульовано завдання для дипломної роботи. У спеціальній частині проведено аналіз впливу резервування на SDN мережу, проведено аналіз існуючих структур архітектури рівня контролю, математично визначена середній час відгуку контролера, запропоновано модифікований спосіб структуризації рівня управління SDN, розглянуто потенційні алгоритми забезпечення відновлення мережі. В економічному розділі визначено розмір капітальних та експлуатаційних витрат для побудови проектованної мережі

A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

A constrained steiner tree approach for reconstructions of multicast trees.

Sun Tong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 77-81).Abstracts in English and Chinese.Chinese Abstract --- p.IAbstract --- p.IIAcknowledgements --- p.IIIList of Contents --- p.IVList of Figures --- p.VIIChapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Multicast Routing Problem --- p.1Chapter 1.2 --- Constrained multicast routing problem and SSRA algorithm --- p.4Chapter 1.3 --- Thesis organization --- p.7Chapter Chapter 2 --- Constrained Multicast Routing Algorithms --- p.8Chapter 2.1 --- Steiner tree heuristic --- p.8Chapter 2.1.1 --- Shortest Paths Heuristic --- p.9Chapter 2.1.2 --- Distance Network Heuristic --- p.10Chapter 2.2 --- Review of existing constrained multicast routing algorithms --- p.10Chapter 2.2.1 --- Static group member --- p.10Chapter 2.2.2 --- Dynamic group member --- p.14Chapter 2.2.2.1 --- Non-rearrangeable --- p.15Chapter 2.2.2.2 --- Rearrangeable --- p.23Chapter Chapter 3 --- Small Scale Rearrangement Algorithm for Multicast Routing --- p.32Chapter 3.1 --- Problem formulation --- p.32Chapter 3.1.1 --- Network Model --- p.32Chapter 3.1.2 --- Problem Specification --- p.33Chapter 3.1.3 --- Definitions and Notations --- p.36Chapter 3.2 --- Local Checking Scheme (LCS) --- p.37Chapter 3.3 --- Small Scale Rearrangement Algorithm (SSRA) for Multicast Routing --- p.41Chapter 3.3.1 --- Static group membership --- p.42Chapter 3.3.2 --- Dynamic group membership --- p.43Chapter 3.3.2.1 --- Node addition --- p.44Chapter 3.3.2.2 --- Node removal --- p.44Chapter 3.3.2.3 --- General steps --- p.45Chapter 3.3.2.4 --- Example --- p.47Chapter Chapter 4 --- Analysis --- p.50Chapter Chapter 5 --- Simulations --- p.54Chapter 5.1 --- Simulation Model --- p.54Chapter 5.2 --- Simulation Parameters Parameter Default Value/Generating Method --- p.56Chapter 5.3 --- Performance Metrics --- p.58Chapter 5.4 --- Discussion of Results --- p.59Chapter 5.4.1 --- Group 1: static group membership --- p.59Chapter 5.4.2 --- Group 2: dynamic group membership --- p.63Chapter 5.4.3 --- Comparison --- p.69Chapter 5.5 --- Implementation Issue --- p.73Chapter Chapter 6 --- Conclusion --- p.75Reference --- p.7