Practical Use of High-level Petri Nets

This booklet contains the proceedings of the Workshop on Practical Use of High-level Petri Nets, June 27, 2000. The workshop is part of the 21st International Conference on Application and Theory of Petri Nets organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The workshop papers are available in electronic form via the web pages: http://www.daimi.au.dk/pn2000/proceeding

A QoS model for highly variable mobile networks

Aufgabe eines reservierungsbasierten QoS-Systems ist die Garantie spezifischer Übertragungsparameter für Datenflüsse in Umgebungen mit begrenzten Ressourcen. Zu diesem Zweck muss das System verschiedene Anforderungen gegeneinander abwägen und eine Ressourcenzuteilung maximalen Wertes für die Nutzer finden. In existierenden Lösungen leidet die Ressourcenzuteilung unter eine Informationslücke: die Netzwerkschicht betrachtet einzelne Datenströme ohne Kenntnis ihrer Beziehungen in höheren Schichten. Durch diese Lücke kann es zur Zuteilung von Ressourcen an nicht nutzbare Reservierungen kommen, die auf andere, nicht aktive Ströme angewiesen sind. Dies resultiert in einer Verschwendung von Ressourcen, welche anderweitig besser zur Erbringung von Diensten genutzt werden könnten. Die vorliegende Arbeit schlägt ein QoS-System der Netzwerkschicht vor, welches Kenntnis über die existierenden Pfadbeziehungen besitzt. Diese werden als Ausdrücke der Aussagenlogik formuliert, in denen die Zustände der reservierten Pfade als Boolesche Variablen repräsentiert werden. Durch Auswertung der entsprechenden Ausdrücke kann der Optimierungsprozess verschwendete Ressourcen erkennen und vermeiden. Das Optimierungsproblem ist eine Instanz des Rucksackproblems mit Nebenbedingungen. Durch Umwandlung in ein Mixed Integer Linear Program können durch existierende Algorithmen wie Branch-and-Cut optimale Ressourcenzuteilungen in vertretbarer Zeit berechnet werden. Die vorliegenden Ergebnisse zeigen, dass die Optimierung ohne Kenntnis der Pfadbeziehungen in bestimmten Szenarien bis zu 75% der zugeteilten Ressourcen verschwendet. Eine Lösung dieses Problems erlaubt eine wesentlich effizientere Nutzung begrenzter Ressourcen und damit den Transport einer deutlich großen Zahl an Anwendungssitzungen. Zusammen mit einem netzseitigen Ressourcenmanagement, welches Reservierungen pausieren und fortsetzen kann, ist dieser Ansatz besonders für stark veränderliche Netze mit langen Übertragungsverzögerungen geeignet. Das Netz findet autonom eine optimale Ressourcenzuteilung, ohne die begrenzten Ressourcen durch zusätzliche Signalisierung zu belasten.The goal of a reservation-based QoS system is to guarantee specific transmission parameters to data flows especially in a resource-constrained environment. To do so, it has to balance different requests and find a resource allocation maximizing the overall value to its users. Traditionally there is an information gap in this optimization process: The network layer operates on individual data flows, whereas higher layers bind multiple flows together to form more complex connections. Without being aware of these relationships introduced on higher layers, the network layer may assign transmission resources to reservations, while not guaranteeing other, additionally required reservations. The result is a sub-optimal allocation, which wastes resources that could ultimately be used to better satisfy users in an already quite strained environment. This work proposes to make the network layer aware of higher-layer relationships by modeling them as propositional formulas over the resource allocation. Each reservation is represented by a Boolean variable giving its current resource assignment state. By deriving the resulting value of each propositional formula the optimization process can detect - and ultimately eliminate - wasted resources. The optimization problem is an instance of the Knapsack problem with additional Boolean constraints. By transforming it into a Mixed Integer Linear Program existing optimization algorithms like Branch-and-Cut can be used to find optimal solutions in a reasonable time frame. The results of this work indicate that, depending on the scenario, up to 75% of assigned resources may be wasted in a relation-unaware system. Alleviating this problem yields a dramatic increase of the number of admitted application sessions. Together with proactive resource management, where reservations can be suspended and resumed by the network, this approach is especially suited for highly variable, long delay networks. It is able to autonomously find the optimal resource distribution, without putting additional signaling burden on already limited resources

Service Composition for Collective Adaptive Systems

Collective adaptive systems are large-scale resource-sharing systems which adapt to the demands of their users by redistributing resources to balance load or provide alternative services where the current provision is perceived to be insufficient. Smart transport systems are a primary example where real-time location tracking systems record the location availability of assets such as cycles for hire, or fleet vehicles such as buses, trains and trams. We consider the problem of an informed user optimising his journey using a composition of services offered by different service providers

Renegotiable VBR service

In this work we address the problem of supporting the QoS requirements for applications while efficiently allocating the network resources. We analyse this problem at the source node where the traffic profile is negotiated with the network and the traffic is shaped according to the contract. We advocate VBR renegotiation as an efficient mechanism to accommodate traffic fluctuations over the burst time-scale. This is in line with the Integrated Service of the IETF with the Resource reSerVation Protocol (RSVP), where the negotiated contract may be modified periodically. In this thesis, we analyse the fundamental elements needed for solving the VBR renegotiation. A source periodically estimates the needs based on: (1) its future traffic, (2) cost objective, (3) information from the past. The issues of this estimation are twofold: future traffic prediction given a prediction, the optimal change. In the case of a CBR specification the optimisation problem is trivial. But with a VBR specification this problem is complex because of the multidimensionality of the VBR traffic descriptor and the non zero condition of the system at the times where the parameter set is changed. We, therefore, focus on the problem of finding the optimal change for sources with pre-recorded or classified traffic. The prediction of the future traffic is out of the scope of this thesis. Traditional existing models are not suitable for modelling this dynamic situation because they do not take into account the non-zero conditions at the transient moments. To address the shortfalls of the traditional approaches, a new class of shapers, the time varying leaky bucket shaper class, has been introduced and characterised by network calculus. To our knowledge, this is the first model that takes into account non-zero conditions at the transient time. This innovative result forms the basis of Renegotiable VBR Service (RVBR). The application of our RVBR mathematical model to the initial problem of supporting the applications' QoS requirements while efficiently allocating the network resources results in simple, efficient algorithms. Through simulation, we first compare RVBR service versus VBR service and versus renegotiable CBR service. We show that RVBR service provides significant advantages in terms of resource costs and resource utilisation. Then, we illustrate that when the service assumes zero conditions at the transient time, the source could potentially experience losses in the case of policing because of the mismatch between the assumed bucket and buffer level and the policed bucket and buffer level. As an example of RVBR service usage, we describe the simulation of RVBR service in a scenario where a sender transmits a MPEG2 video over a network using RSVP reservation protocol with Controlled-Load service. We also describe the implementation design of a Video on Demand application, which is the first example of an RVBR-enabled application. The simulation and experimentation results lead us to believe that RVBR service provides an adequate service (in terms of QoS guaranteed and of efficient resource allocation) to sources with pre-recorded or classified traffic

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