A survey of the machine interference problem

This paper surveys the research published on the machine interference problem since the 1985 review by Stecke & Aronson. After introducing the basic model, we discuss the literature along several dimensions. We then note how research has evolved since the 1985 review, including a trend towards the modelling of stochastic (rather than deterministic) systems and the corresponding use of more advanced queuing methods for analysis. We conclude with some suggestions for areas holding particular promise for future studies.Natural Sciences and Engineering Research Council (NSERC) Discovery Grant 238294-200

Asymptotic waiting time analysis of finite source M/GI/1 retrial queueing systems with conflicts and unreliable server

The goal of the present paper is to analyze the steady-state distribution of the waiting time in a finite source M/G/1 retrial queueing system where conflicts may happen and the server is unreliable. An asymptotic method is used when the number of source N tends to infinity, the arrival intensity from the sources, the intensity of repeated calls tend to zero, while service intensity, breakdown intensity, recovery intensity are fixed. It is proved that the limiting steady-state probability distribution of the number of transitions/retrials of a customer into the orbit is geometric, and the waiting time of a customer is generalized exponentially distributed. The average total service time of a customer is also determined. Our new contribution to this topic is the inclusion of breakdown and recovery of the server. Prelimit distributions obtained by means of stochastic simulation are compared to the asymptotic ones and several numerical examples illustrate the power of the proposed asymptotic approach

Queueing System with Potential for Recruiting Secondary Servers

In this paper, we consider a single server queueing system in which the arrivals occur according to a Markovian arrival process (MAP). The served customers may be recruited (or opted from those customers’ point of view) to act as secondary servers to provide services to the waiting customers. Such customers who are recruited to be servers are referred to as secondary servers. The service times of the main as well as that of the secondary servers are assumed to be exponentially distributed possibly with different parameters. Assuming that at most there can only be one secondary server at any given time and that the secondary server will leave after serving its assigned group of customers, the model is studied as a QBD-type queue. However, one can also study this model as a G I/M/1-type queue. The model is analyzed in steady state, and a few illustrative numerical examples are presented

Topology and congestion invariant in global internet-scale networks

PhDInfrastructures like telecommunication systems, power transmission grids and the Internet are complex networks that are vulnerable to catastrophic failure. A common mechanism behind this kind of failure is avalanche-like breakdown of the network's components. If a component fails due to overload, its load will be redistributed, causing other components to overload and fail. This failure can propagate throughout the entire network. From studies of catastrophic failures in di erent technological networks, the consensus is that the occurrence of a catastrophe is due to the interaction between the connectivity and the dynamical behaviour of the networks' elements. The research in this thesis focuses particularly on packet-oriented networks. In these networks the tra c (dynamics) and the topology (connectivity) are coupled by the routing mechanisms. The interactions between the network's topology and its tra c are complex as they depend on many parameters, e.g. Quality of Service, congestion management (queuing), link bandwidth, link delay, and types of tra c. It is not straightforward to predict whether a network will fail catastrophically or not. Furthermore, even if considering a very simpli ed version of packet networks, there are still fundamental questions about catastrophic behaviour that have not been studied, such as: will a network become unstable and fail catastrophically as its size increases; do catastrophic networks have speci c connectivity properties? One of the main di culties when studying these questions is that, in general, we do not know in advance if a network is going to fail catastrophically. In this thesis we study how to build catastrophic 5 networks. The motivation behind the research is that once we have constructed networks that will fail catastrophically then we can study its behaviour before the catastrophe occurs, for example the dynamical behaviour of the nodes before an imminent catastrophe. Our theoretical and algorithmic approach is based on the observation that for many simple networks there is a topology-tra c invariant for the onset of congestion. We have extended this approach to consider cascading congestion. We have developed two methods to construct catastrophes. The main results in this thesis are that there is a family of catastrophic networks that have a scale invariant; hence at the break point it is possible to predict the behaviour of large networks by studying a much smaller network. The results also suggest that if the tra c on a network increases exponentially, then there is a maximum size that a network can have, after that the network will always fail catastrophically. To verify if catastrophic networks built using our algorithmic approach can re ect real situations, we evaluated the performance of a small catastrophic network. By building the scenario using open source network simulation software OMNet++, we were able to simulate a router network using the Open Shortest Path First routing protocol and carrying User Datagram Protocol tra c. Our results show that this kind of networks can collapse as a cascade of failures. Furthermore, recently the failure of Google Mail routers [1] con rms this kind of catastrophic failure does occur in real situations

A reputation framework for behavioural history: developing and sharing reputations from behavioural history of network clients

The open architecture of the Internet has enabled its massive growth and success by facilitating easy connectivity between hosts. At the same time, the Internet has also opened itself up to abuse, e.g. arising out of unsolicited communication, both intentional and unintentional. It remains an open question as to how best servers should protect themselves from malicious clients whilst offering good service to innocent clients. There has been research on behavioural profiling and reputation of clients, mostly at the network level and also for email as an application, to detect malicious clients. However, this area continues to pose open research challenges. This thesis is motivated by the need for a generalised framework capable of aiding efficient detection of malicious clients while being able to reward clients with behaviour profiles conforming to the acceptable use and other relevant policies. The main contribution of this thesis is a novel, generalised, context-aware, policy independent, privacy preserving framework for developing and sharing client reputation based on behavioural history. The framework, augmenting existing protocols, allows fitting in of policies at various stages, thus keeping itself open and flexible to implementation. Locally recorded behavioural history of clients with known identities are translated to client reputations, which are then shared globally. The reputations enable privacy for clients by not exposing the details of their behaviour during interactions with the servers. The local and globally shared reputations facilitate servers in selecting service levels, including restricting access to malicious clients. We present results and analyses of simulations, with synthetic data and some proposed example policies, of client-server interactions and of attacks on our model. Suggestions presented for possible future extensions are drawn from our experiences with simulation

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES

Market-oriented micro virtual power prosumers operations in distribution system operator framework

As the European Union is on track to meet its 2020 energy targets on raising the share of renewable energy and increasing the efficiency in the energy consumption, considerable attention has been given to the integration of distributed energy resources (DERs) into the restructured distribution system. This thesis proposes market-oriented operations of micro virtual power prosumers (J.lVPPs) in the distribution system operator framework, in which the J.lVPPs evolve from home-oriented energy management systems to price-taking prosumers and to price-making prosumers. Considering the diversity of the DERs installed in the residential sector, a configurable J.l VPP is proposed first to deliver multiple energy services using a fuzzy logic-based generic algorithm. By responding to the retail price dynamics and applying load control, the J.lVPP achieves considerable electricity bill savings, active utilisation of energy storage system and fast return on investment. As the J.lVPPs enter the distribution system market, they are modelled as price-takers in a two-settlement market first and a chance-constrained formulation is proposed to derive the bidding strategies. The obtained strategy demonstrates its ability to bring the J.l VPP maximum profit based on different composition of DERs and to maintain adequate supply capacity to meet the demand considering the volatile renewable generation and load forecast. Given the non-cooperative nature of the actual market, the J.l VPPs are transformed into price-makers and their market behaviours are studied in the context of electricity market equilibrium models. The resulted equilibrium problems with equilibrium constraints (EPEC) are presented and solved using a novel application of coevolutionary approach. Compared with the roles of home-oriented energy management systems and price-taking prosumers, the J.lVPPs as price­ making prosumers have an improved utilisation rate of the installed DER capacity and a guaranteed profit from participating in the distribution system market

Market-oriented micro virtual power prosumers operations in distribution system operator framework

As the European Union is on track to meet its 2020 energy targets on raising the share of renewable energy and increasing the efficiency in the energy consumption, considerable attention has been given to the integration of distributed energy resources (DERs) into the restructured distribution system. This thesis proposes market-oriented operations of micro virtual power prosumers (J.lVPPs) in the distribution system operator framework, in which the J.lVPPs evolve from home-oriented energy management systems to price-taking prosumers and to price-making prosumers. Considering the diversity of the DERs installed in the residential sector, a configurable J.l VPP is proposed first to deliver multiple energy services using a fuzzy logic-based generic algorithm. By responding to the retail price dynamics and applying load control, the J.lVPP achieves considerable electricity bill savings, active utilisation of energy storage system and fast return on investment. As the J.lVPPs enter the distribution system market, they are modelled as price-takers in a two-settlement market first and a chance-constrained formulation is proposed to derive the bidding strategies. The obtained strategy demonstrates its ability to bring the J.l VPP maximum profit based on different composition of DERs and to maintain adequate supply capacity to meet the demand considering the volatile renewable generation and load forecast. Given the non-cooperative nature of the actual market, the J.l VPPs are transformed into price-makers and their market behaviours are studied in the context of electricity market equilibrium models. The resulted equilibrium problems with equilibrium constraints (EPEC) are presented and solved using a novel application of coevolutionary approach. Compared with the roles of home-oriented energy management systems and price-taking prosumers, the J.lVPPs as price­ making prosumers have an improved utilisation rate of the installed DER capacity and a guaranteed profit from participating in the distribution system market