511 research outputs found

    Design of Overlay Networks for Internet Multicast - Doctoral Dissertation, August 2002

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    Multicast is an efficient transmission scheme for supporting group communication in networks. Contrasted with unicast, where multiple point-to-point connections must be used to support communications among a group of users, multicast is more efficient because each data packet is replicated in the network – at the branching points leading to distinguished destinations, thus reducing the transmission load on the data sources and traffic load on the network links. To implement multicast, networks need to incorporate new routing and forwarding mechanisms in addition to the existing are not adequately supported in the current networks. The IP multicast are not adequately supported in the current networks. The IP multicast solution has serious scaling and deployment limitations, and cannot be easily extended to provide more enhanced data services. Furthermore, and perhaps most importantly, IP multicast has ignored the economic nature of the problem, lacking incentives for service providers to deploy the service in wide area networks. Overlay multicast holds promise for the realization of large scale Internet multicast services. An overlay network is a virtual topology constructed on top of the Internet infrastructure. The concept of overlay networks enables multicast to be deployed as a service network rather than a network primitive mechanism, allowing deployment over heterogeneous networks without the need of universal network support. This dissertation addresses the network design aspects of overlay networks to provide scalable multicast services in the Internet. The resources and the network cost in the context of overlay networks are different from that in conventional networks, presenting new challenges and new problems to solve. Our design goal are the maximization of network utility and improved service quality. As the overall network design problem is extremely complex, we divide the problem into three components: the efficient management of session traffic (multicast routing), the provisioning of overlay network resources (bandwidth dimensioning) and overlay topology optimization (service placement). The combined solution provides a comprehensive procedure for planning and managing an overlay multicast network. We also consider a complementary form of overlay multicast called application-level multicast (ALMI). ALMI allows end systems to directly create an overlay multicast session among themselves. This gives applications the flexibility to communicate without relying on service provides. The tradeoff is that users do not have direct control on the topology and data paths taken by the session flows and will typically get lower quality of service due to the best effort nature of the Internet environment. ALMI is therefore suitable for sessions of small size or sessions where all members are well connected to the network. Furthermore, the ALMI framework allows us to experiment with application specific components such as data reliability, in order to identify a useful set of communication semantic for enhanced data services

    Operational Research: Methods and Applications

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    Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

    A Polyhedral Study of Mixed 0-1 Set

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    We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

    Operational research:methods and applications

    Get PDF
    Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

    LIPIcs, Volume 248, ISAAC 2022, Complete Volume

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    LIPIcs, Volume 248, ISAAC 2022, Complete Volum

    Oblivious Network Optimization and Security Modeling in Sustainable Smart Grids and Cities

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    Today\u27s interconnected world requires an inexpensive, fast, and reliable way of transferring information. There exists an increasingly important need for intelligent and adaptable routing of network flows. In the last few years, many researchers have worked toward developing versatile solutions to the problem of routing network flows in unpredictable circumstances. These attempts have evolved into a rich literature in the area of oblivious network design which typically route the network flows via a routing scheme that makes use of a spanning tree or a set of trees of the graph representation of the network. In the first chapter, we provide an introduction to network design. This introductory chapter has been designed to clarify the importance and position of oblivious routing problems in the context of network design as well as its containing field of research. Part I of this dissertation discusses the fundamental role of linked hierarchical data structures in providing the mathematical tools needed to construct rigorous versatile routing schemes and applies hierarchical routing tools to the process of constructing versatile routing schemes. Part II of this dissertation applies the routing tools generated in Part I to address real-world network optimization problems in the area of electrical power networks, clusters of micrograms, and content-centric networks. There is an increasing concern regarding the security and privacy of both physical and communication layers of smart interactive customer-driven power networks, better known as smart grids. Part III of this dissertation utilizes an advanced interdisciplinary approach to address existing security and privacy issues, proposing legitimate countermeasures for each of them from the standpoint of both computing and electrical engineering. The proposed methods are theoretically proven by mathematical tools and illustrated by real-world examples

    Robuste und großumfängliche Netzwerkoptimierung in der Logistik

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    This thesis explores possibilities and limitations of extending classical combinatorial optimization problems for network flows and network design. We propose new mathematical models for logistics networks that feature commodities with multidimensional properties, e.g. their mass and volume, to capture consolidation effects of commodities with complementing properties. We provide new theoretical insights and solution methods with immediate practical impact that we test on real-world instances from the automotive, chemical, and retail industry. The first model is for tactical transportation planning with temporal consolidation effects. We propose various heuristics and prove for our instances, that most of our solutions are within a single-digit percentage of the optimum. We also study problem variants where commodities are routed unsplittably and give hardness results for various special cases and a dynamic program that finds optimal forest solutions, which overestimate real costs. The second model is for strategic route planning under uncertainty. We provide for a robust optimization method that anticipates fluctuations of demands by minimizing worst-case costs over a restricted scenario set. We show that the adversary problem is NP-hard. To still find solutions with very good worst-case cost, we derive a carefully relaxed and simplified MILP, which solves well for large instances. It can be extended to include hub decisions leading to a robust M-median hub location problem. We find a price of robustness for our instances that is moderate for scenarios using average demand values as lower bounds. Trend based scenarios show a considerable tradeoff between historical average costs and worst case costs. Another robustness concept are incremental hub chains that provide solutions for every number of hubs to operate, such that they are robust under changes of this number. A comparison of incremental solutions with M-median solutions obtained with an LP-based search suggests that a price of being incremental is low for our instances. Finally, we investigate the problem of scheduling the maintenance of edges in a network. We focus on maintaining connectivity between two nodes over time. We show that the problem can be solved in polynomial time in arbitrary networks if preemption is allowed. If preemption is restricted to integral time points, the problem is NP-hard and for the non-preemptive case, we show strong non-approximability results.Diese Arbeit untersucht Möglichkeiten, klassische kombinatorische Optimierungsprobleme für Netzwerkflüsse und Netzwerkdesign zu erweitern. Wir stellen neue mathematische Modelle für Logistiknetzwerke vor, die mehrdimensionale Eigenschaften der Güter berücksichtigen, etwa Masse oder Volumen, um Konsolidierungseffekte von Gütern mit komplementären Eigenschaften zu nutzen. Wir erarbeiten neue theoretische Einsichten und Lösungsmethoden von praktischer Relevanz, die wir an realen Instanzen aus der Automobilindustrie, der Chemiebranche und aus dem Einzelhandel evaluieren. Für die taktische Transportplanung mit zeitlichen Konsolidierungseffekte erarbeiten wir verschiedene Heuristiken, welche für unsere Instanzen die Optimalitätslücke zu 10% schließen. Wir geben Härteresultate für verschiedene Spezialfälle mit unteilbaren Gütern an, sowie ein dynamisches Programm, welches Lösungen mit optimalen Baumkosten berechnet; eine Überschätzung der realen Kosten. Für die strategische Routenplanung unter Unsicherheit entwickeln wir eine robuste Optimierungsmethode, welche Nachfrageschwankungen antizipiert, indem Worstcase-Kosten über einer beschränkten Szenarienmenge minimiert werden. Wir zeigen, dass das Gegenspielerproblem NP-schwer ist. Um Lösungen mit guten Worstcase-Kosten zu finden, leiten wir ein sorgfältig relaxiertes MILP her. Seine natürliche Erweiterung für Hubentscheidungen führt auf ein robustes M-Median Hub Location Problem. Wir finden einen moderaten Preis der Robustheit für Szenarien, die Durchschnittsnachfragemengen als untere Intervallgrenze verwenden. Trendbasierten Szenarien zeigen einen deutlichen Tradeoff zwischen historischen Durchschnittskosten und Worstcase-Kosten. Ein weiteres Robustheitskonzept stellen inkrementale Hubketten dar, welche Lösungen für jede Anzahl an Hubstandorten angeben, sodass sie gegen Änderungen dieser Anzahl robust sind. Ein Vergleich mit entsprechenden M-Median Lösungen, die wir mit einer LP-basierten Hubsuche erhalten, zeigt einen geringen Preis der Inkrementalität bei unseren Instanzen auf. Zuletzt untersuchen wir das Problem Wartungsarbeiten an Kanten in einem Netzwerk zu planen, um Konnektivität zwischen zwei Knoten zu bewahren. Wir zeigen, dass sich das Problem polynomiell in beliebigen Netzen lösen lässt, falls Wartungsarbeiten unterbrochen werden dürfen. Falls dies nur zu ganzzahligen Zeitpunkten erlaubt ist, ist es bereits NP-schwer. Für den Fall ohne Unterbrechungen zeigen wir starke Nichtapproximierbarkeitsresultate
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