Thesis (M. Sc.)--Carleton University, 2008. / Includes bibliographical references (p. 81-83). Also available in electronic format on the Internet.

Orientadores: Edson Luiz Ursini, Paulo Sérgio Martins Pedro / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-24T15:16:37Z (GMT). No. of bitstreams: 1 Santos_VlademirFazio_M.pdf: 4330659 bytes, checksum: a576d09102c26740d57f44a9686c5b76 (MD5) Previous issue date: 2014 / Resumo: Iniciativas industriais para finalizar a produção de multi-commodities embaladas sem formar estoque requerem inovação tecnológica constante. Atuam sincronizadamente com o múltiplo carregamento simultâneo diretamente em caminhões. Para isso desenvolvemos um modelo de simulação por eventos discretos e apresentamos seu modelo analítico de tráfego validado com Redes de Filas de Jackson e pela Lei de Conservação de Little. Descrevemos os limites do intervalo de variação de tempos máximos e médios de permanência de multi-commodities em sistemas de tempo real para três servidores paralelos. Esse sistema opera com mudanças dinâmicas de diferentes políticas de escalonamento. Um resultado é a confirmação do compromisso entre tempos máximos e médios independentemente de intensidade de tráfego e de políticas de escalonamento a que o modelo seja submetido. Outro é a identificação de uma faixa de relativa estabilidade operacional fora de regiões críticas. Assim, contribuímos com os princípios de um método que pode ser adotado como apoio às decisões de planejamento em ambientes industriais complexos submetidos a filas em tempo real / Abstract: The industrial initiatives for the production finalization of packed multi-commodities without forming stock require constant technological innovation. They operate a synchronous process to simultaneous multi-loading straightly into trucks. Regarding to this we developed a discrete event simulation model and present its traffic analytical model validated with the theory of Jackson Queueing Networks and the Little's Conservation Law. We describe the limits for the range of multi-commodities throuput-times and maximum waiting time in real-time systems with three parallel servers. This system operates with dynamical changes of different scheduling policies. A reached result is the confirmation of the average and maximum times mutual commitment despite of traffic intensity and scheduling policies that the model is submitted to. Another is the identification of a range of relative operational stability out of critical regions. As a contribution we offer the principles of a method that can be used to planning decision support in complex industrial environments subject to real-time queues / Mestrado / Tecnologia e Inovação / Mestre em Tecnologia

The thesis proposes a method for teaching computer simulation. The method involves the use of a large-scale real-life project which had been carried out by the author on a consultancy basis. This project has been developed into a teaching package which is intended for a wide spectrum of students, thus little knowledge of mathematics is assumed. This method has been found to be the most successful one by the author in over twenty years of experience with different types of students and this particular package has been tried successfully with a group of students in Hong Kong. The.real system and the relevant problems involved are first described and considered. From this an extremely simplified version is then extracted. Solution methods are considered and the usefulness of simulation demonstrated. The tools required for a simulation are then introduced, the simulation language used being GPSS which is considered by the author to be the most appropriate on the basis of ease of learning and future usefulness. In a series of steps realistic complications are added to this simple system while in parallel the required extra elements of the simulation language are introduced building up to the final simulation of the real system by the students who will by then have a thorough grasp of GPSS. They will also have had the experience of developing a full-scale simulation model. At this stage the students will be in a position to apply their knowledge and experience to problems in other fields and the author hopes that the lecturer will be motivated to develop similar projects for teaching in other areas.

One of causes of increased latency service over the whole IMS network can be unbalanced SIP (Session Initiation Protocol) signalling traffic through CSCF (Call Session Control Function). This thesis is devoted to the proposal of weight-based load balancing algorithm which can be used for the S-CSCF assignment performed by I-CSCF during the initial registration procedure of subscribers over the IMS architecture. The designed mechanism is implemented and evaluated in the mathematical model of IMS subsystem based on single servers with FIFO queues with the unlimited capacity in the numerical computing environment - Matlab. Two test-cases with different performance conditions of available S-CSCFs are described. The influence of measured latency affected by performance of other nodes (e.g. P-CSCF, I-CSCF, HSS, etc.) is minimized. Each of simulated test-cases is measured with various service times of SCSCFs and inter-arrival times. The obtained results of designed algorithm are compared with well-known selection algorithm – the round-robin algorithm. It is shown that new selection mechanism improved the service latency of whole IMS network. The possible weakness of the designed weight-based algorithm is sensitivity to traffic model over the modelled IMS architecture.

Cognitive radio networks (CRN) have been tipped as one of the most promising paradigms for next generation wireless communication, due primarily to its huge promise of mitigating the spectrum scarcity challenge. To help achieve this promise, CRN develop mechanisms that permit spectrum spaces to be allocated to, and used by more than one user, either simultaneously or opportunistically, under certain preconditions. However, because of various limitations associated with CRN, spectrum and other resources available for use in CRN are usually very scarce. Developing appropriate models that can efficiently utilise the scarce resources in a manner that is fair, among its numerous and diverse users, is required in order to achieve the utmost for CRN. 'Resource allocation (RA) in CRN' describes how such models can be developed and analysed. In developing appropriate RA models for CRN, factors that can limit the realisation of optimal solutions have to be identified and addressed; otherwise, the promised improvement in spectrum/resource utilisation would be seriously undermined. In this thesis, by a careful examination of relevant literature, the most critical limitations to RA optimisation in CRN are identified and studied, and appropriate solution models that address such limitations are investigated and proffered. One such problem, identified as a potential limitation to achieving optimality in its RA solutions, is the problem of heterogeneity in CRN. Although it is indeed the more realistic consideration, introducing heterogeneity into RA in CRN exacerbates the complex nature of RA problems. In the study, three broad classifications of heterogeneity, applicable to CRN, are identified; heterogeneous networks, channels and users. RA models that incorporate these heterogeneous considerations are then developed and analysed. By studying their structures, the complex RA problems are smartly reformulated as integer linear programming problems and solved using classical optimisation. This smart move makes it possible to achieve optimality in the RA solutions for heterogeneous CRN. Another serious limitation to achieving optimality in RA for CRN is the strictness in the level of permissible interference to the primary users (PUs) due to the activities of the secondary users (SUs). To mitigate this problem, the concept of cooperative diversity is investigated and employed. In the cooperative model, the SUs, by assisting each other in relaying their data, reduce their level of interference to PUs significantly, thus achieving greater results in the RA solutions. Furthermore, an iterative-based heuristic is developed that solves the RA optimisation problem timeously and efficiently, thereby minimising network complexity. Although results obtained from the heuristic are only suboptimal, the gains in terms of reduction in computations and time make the idea worthwhile, especially when considering large networks. The final problem identified and addressed is the limiting effect of long waiting time (delay) on the RA and overall productivity of CRN. To address this problem, queueing theory is investigated and employed. The queueing model developed and analysed helps to improve both the blocking probability as well as the system throughput, thus achieving significant improvement in the RA solutions for CRN. Since RA is an essential pivot on which the CRN's productivity revolves, this thesis, by providing viable solutions to the most debilitating problems in RA for CRN, stands out as an indispensable contribution to helping CRN realise its much-proclaimed promises. / Thesis (PhD)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / PhD / Unrestricted

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第23326号 / 情博第762号 / 新制||情||130(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 大木 英司, 教授 守倉 正博, 教授 岡部 寿男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

<p>Queueing systems are everywhere: in transportation networks, service centers, communication systems, clinics, manufacturing systems, etc. In this dissertation, we contribute to the theory of queueing in two aspects. In the first part, we dilate the interplay between retrials and strategic arrival behavior in single-class queueing networks. Specifically, we study a variation of the ‘Network Concert Queueing Game,’ wherein a fixed but large number of strategic users arrive at a network of queues where they can be routed to other queues in the network following a fixed routing matrix, or potentially fedback to the end of the queue they arrive at. Working in a non-atomic setting, we prove the existence of Nash equilibrium arrival and routing profiles in three simple, but non-trivial, network topologies/architectures. In two of them, we also prove the uniqueness of the equilibrium. Our results prove that Nash equilibrium decisions on when to arrive and which queue to join in a network are substantially impacted by routing, inducing ‘herding’ behavior under certain conditions on the network architecture. Our theory raises important design implications for capacity-sharing in systems with strategic users, such as ride-sharing and crowdsourcing platforms.</p> <p><br></p> <p>In the second part, we develop a new method of data-driven model calibration or estimation for queueing models. Statistical and theoretical analyses of traffic traces show that the doubly stochastic Poisson processes are appropriate models of high intensity traffic arriving at an array of service systems. On the other hand, the statistical estimation of the underlying latent stochastic intensity process driving the traffic model involves a rather complicated nonlinear filtering problem. In this thesis we use deep neural networks to ‘parameterize’ the path measures induced by the stochastic intensity process, and solve this nonlinear filtering problem by maximizing a tight surrogate objective called the evidence lower bound (ELBO). This framework is flexible in the sense that we can also estimate other stochastic processes (e.g., the queue length process) and their related parameters (e.g., the service time distribution). We demonstrate the effectiveness of our results through extensive simulations. We also provide approximation guarantees for the estimation/calibration problem. Working with the Markov chain induced by the Euler-Maruyama discretization of the latent diffusion, we show that (1) there exists a sequence of approximate data generating distributions that converges to the “ground truth” distribution in total variation distance; (2) the variational gap is strictly positive for the optimal solution to the ELBO. Extending to the non-Markov setting, we identify the variational gap minimizing approximate posterior for an arbitrary (known) posterior and further, prove a lower bound on the optimal ELBO. Recent theoretical results on optimizing the ELBO for related (but ultimately different) models show that when the data generating distribution equals the ground truth distribution and the variational gap is zero, the probability measures that achieve these conditions also maximize the ELBO. Our results show that this may not be true in all problem settings.</p>

No description available.

Peer-to-peer swarming, as used by BitTorrent, is one of the de facto solutions for content dissemination in today’s Internet. By leveraging resources provided by users, peer-to-peer swarming is a simple, scalable and efficient mechanism for content distribution. Although peer-to-peer swarming has been widely studied for a decade, prior work has focused on the dissemination of one commodity (a single file). This thesis focuses on the multi-commodity case. We have discovered through measurements that a vast number of publishers currently disseminate multiple files in a single swarm (bundle). The first contribution of this thesis is a model for content availability. We use the model to show that, when publishers are intermittent, bundling K files increases content availability exponentially as function of K. When there is a stable publisher, we consider content availability among peers (excluding the publisher). Our second contribution is the estimate of the dependency of peers on the stable publisher, which is useful for provisioning purposes as well as in deciding how to bundle. To this goal, we propose a new metric, swarm self-sustainability, and present a model that yields swarm self-sustainability as a function of the file size, popularity and service capacity of peers. Then, we investigate reciprocity and the use of barter that occurs among peers. As our third contribution, we prove that the loss of efficiency due to the download of unrequested content to enforce direct reciprocity, as opposed to indirect reciprocity, is at most two in a class of networks without relays. Finally, we study algorithmic and economic problems faced by enterprises who leverage swarming systems and who control prices and bundling strategies. As our fourth contribution, we present two formulations of the optimal bundling problem, and prove that one is NP hard whereas the other is solvable by a greedy strategy. From an economic standpoint, we present conditions for the existence and uniqueness of an equilibrium between publishers and peers.

Decomposition methods based on the hierarchical partitioning of the state space of queueing network models offer powerful evaluation tools for the performance analysis of computer systems and communication networks. These methods being conventionally implemented capture the exact solution of separable queueing network models but their credibility differs when applied to general queueing networks. This thesis provides a universal information theoretic framework for the implementation of hierarchical decomposition schemes, based on the principle of minimum relative entropy given fully decomposable subset and aggregate utilization, mean queue length and flow-balance constraints. This principle is used, in conjuction with asymptotic connections to infinite capacity queues, to derive new closed form approximations for the conditional and marginal state probabilities of general queueing network models. The minimum relative entropy solutions are implemented iteratively at each decomposition level involving the generalized exponential (GE) distributional model in approximating the general service and asymptotic flow processes in the network. It is shown that the minimum relative entropy joint state probability, subject to mean queue length and flow-balance constraints, is identical to the exact product-form solution obtained as if the network was separable. An investigation into the effect of different couplings of the resource units on the relative accuracy of the approximation is carried out, based on an extensive experimentation. The credibility of the method is demonstrated with some illustrative examples involving first-come-first-served general queueing networks with single and multiple servers and favourable comparisons against exact solutions and other approximations are made.