Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

We survey research on self-driving cars published in the literature focusing on autonomous cars developed since the DARPA challenges, which are equipped with an autonomy system that can be categorized as SAE level 3 or higher. The architecture of the autonomy system of self-driving cars is typically organized into the perception system and the decision-making system. The perception system is generally divided into many subsystems responsible for tasks such as self-driving-car localization, static obstacles mapping, moving obstacles detection and tracking, road mapping, traffic signalization detection and recognition, among others. The decision-making system is commonly partitioned as well into many subsystems responsible for tasks such as route planning, path planning, behavior selection, motion planning, and control. In this survey, we present the typical architecture of the autonomy system of self-driving cars. We also review research on relevant methods for perception and decision making. Furthermore, we present a detailed description of the architecture of the autonomy system of the self-driving car developed at the Universidade Federal do Espirito Santo (UFES), named Intelligent Autonomous Robotics Automobile (IARA). Finally, we list prominent self-driving car research platforms developed by academia and technology companies, and reported in the media.

Self-driving cars: A survey

Fast depleting fossil fuels and the growing awareness for environmental protection have led us to the energy crisis. Hence, efforts are being made by researchers to investigate new ways to extract energy from renewable sources. ‘Microgrids’ with Distributed Generators (DG) are being implemented with renewable energy systems. Optimization methods justify the cost of investment of a microgrid by enabling economic and reliable utilization of the resources. This paper strives to bring to light the concept of Hybrid Renewable Energy Systems (HRES) and state of art application of optimization tools and techniques to microgrids, integrating renewable energies. With an extensive literature survey on HRES, a framework of diverse objectives has been outlined for which optimization approaches were applied to empower the microgrid. A review of modelling and applications of renewable energy generation and storage sources is also presented.

Optimization in microgrids with hybrid energy systems – A review

Modern cars are incorporating an increasing number of driver assist features, among which automatic lane keeping. The latter allows the car to properly position itself within the road lanes, which is also crucial for any subsequent lane departure or trajectory planning decision in fully autonomous cars. Traditional lane detection methods rely on a combination of highly-specialized, hand-crafted features and heuristics, usually followed by post-processing techniques, that are computationally expensive and prone to scalability due to road scene variations. More recent approaches leverage deep learning models, trained for pixel-wise lane segmentation, even when no markings are present in the image due to their big receptive field. Despite their advantages, these methods are limited to detecting a pre-defined, fixed number of lanes, e.g. ego-lanes, and can not cope with lane changes. In this paper, we go beyond the aforementioned limitations and propose to cast the lane detection problem as an instance segmentation problem - in which each lane forms its own instance - that can be trained end-to-end. To parametrize the segmented lane instances before fitting the lane, we further propose to apply a learned perspective transformation, conditioned on the image, in contrast to a fixed ”bird’s-eye view” transformation. By doing so, we ensure a lane fitting which is robust against road plane changes, unlike existing approaches that rely on a fixed, predefined transformation. In summary, we propose a fast lane detection algorithm, running at 50 fps, which can handle a variable number of lanes and cope with lane changes. We verify our method on the tuSimple dataset and achieve competitive results.

Towards End-to-End Lane Detection: an Instance Segmentation Approach

With the rapid proliferation of new technologies and services in the wireless domain, spectrum scarcity has become a major concern. The allocation of the Industrial, Medical and Scientific (ISM) band has enabled the explosion of new technologies (e.g. Wi-Fi) due to its licence-exempt characteristic. The widespread adoption of Wi-Fi technology, combined with the rapid penetration of smart phones running popular user services (e.g. social online networks) has overcrowded substantially the ISM band. On the other hand, according to a number of recent reports, several parts of the static allocated licensed bands are under-utilized. This has brought up the idea of the opportunistic use of these bands through the, so-called, cognitive radios and cognitive radio networks. Cognitive radios have enabled the opportunity to transmit in several licensed bands without causing harmful interference to licensed users. Along with the realization of cognitive radios, new security threats have been raised. Adversaries can exploit several vulnerabilities of this new technology and cause severe performance degradation. Security threats are mainly related to two fundamental characteristics of cognitive radios: cognitive capability, and reconfigurability. Threats related to the cognitive capability include attacks launched by adversaries that mimic primary transmitters, and transmission of false observations related to spectrum sensing. Reconfiguration can be exploited by attackers through the use of malicious code installed in cognitive radios. Furthermore, as cognitive radio networks are wireless in nature, they face all classic threats present in the conventional wireless networks. The scope of this work is to give an overview of the security threats and challenges that cognitive radios and cognitive radio networks face, along with the current state-of-the-art to detect the corresponding attacks. In addition, future challenges are addressed.

A Survey on Security Threats and Detection Techniques in Cognitive Radio Networks

This dissertation deals with a variety of topics regarding multistage interconnection networks (MINs), including routing algorithm, the rearrangeability problem and the fault-tolerance issue The 2$log\sb{2}N$- or 2($log\sb{2}N$ $-$ 1)-stage MINs are made by concatenating two $log\sb{2}N$-stage unique path networks It is shown that there exists a topological equivalence among these $2log\sb{2}N$-stage networks A class of $2log\sb{2}N$-stage networks including the concatenation of two omega networks are treated in detail, and the sufficient conditions for proper routing are discussed A general routing algorithm is developed that routes a class of symmetric networks The algorithm routes the network from center stages to outer stages at both the input and output sides simultaneously The algorithm presented is simpler and more flexible than the well-known looping algorithm, in that it can be applied adaptively according to the structure of a network It can be applied to routing the network regardless of the center stage connection patterns, ie, straight, skewed straight, simple butterfly or skewed butterfly, as long as the network is symmetric
Based on the routing algorithm, we examine the rearrangeability of the omega+omega network By proving that the $2log\sb{2}N$-stage omega+omega network is rearrangeable, we improve the best known upper bound in the number of stages in a shuffle-exchange network to $2log\sb{2}N$ In addition to the generality, it is shown that the algorithm can provide a higher degree of fault-tolerance than any other algorithms known so far We show that, with alternate ways in realizing a permutation, any single control fault can be tolerated, and show also that some double faults can be tolerated under some conditions
From the practical point of view, we also propose a fault-tolerating network called composite banyan network The $log\sb{2}N$-stage composite banyan network is composed of 3 $\times$ 3 switching elements Instead of using a complex numerical calculation to find a path, the proposed network uses a simple routing tag to find paths between any source and destination pairs It is shown that the composite banyan network is faster, more reliable and more cost-efficient than any other networks that use 3 $\times$ 3 switching elements

Some aspects of multistate interconnection networks: routing, rearrangeability and fault-tolerance

The Computer Forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. Many researches about Computer Forensics have been done so far. But those researches have focused on how to collect the forensic evidence for both analysis and proofs after receiving the intrusion or infringement reports of hosts from computer users or network administrators. In this paper, we describe how to selectively collect the forensic evidence of good quality from observable and protective hosts at the time of infringement occurrence by malicious users. By correlating the event logs of Intrusion Detection Systems(IDSes) and hosts with the configuration information of hosts periodically, we calculate the value of infringement severity that implies the real infringement possibility of the hosts. Based on this severity value, we selectively collect the evidence for proofs at the time of infringement occurrence. As a result, we show that we can minimize the information damage of the evidence for both analysis and proofs, and reduce the amount of data which are used to analyze the degree of infringement severity.

An efficient forensic evidence collection scheme of host infringement at the occurrence time

Ego-lane index-aware vehicular localisation using the DeepRoad Network for urban environments

We design a new high performance ATM switch architecture based on a distributed network with O(N) hardware complexity. Considering various performance parameters such as average hop distance, adoptability of self routing, and flexibility on the number of nodes, we choose the generalized shuffle network (GSN) as a building block for the ATM switch design. To improve the throughput of the switch, a layering strategy called weaved GSN (WGSN) is adopted in our switch design. The performance of WGSN is studied under uniform and full load conditions through analytic modeling and simulation. The analysis and simulation results show that the proposed switch has better throughput and cell loss performance when compared with other banyan-based switch architectures known so far.

Design and analysis of an ATM switch based on a distributed network: weaved GSN

To realize the high-speed intrusion detection by accommodating many regex-based signatures and the growing network link capacities, we propose a Service TimE-Aware Load balancing algorithm, which is called STEAL. This work is motivated from the observation that utilization of the many-core Network Intrusion Detection System (NIDS) is influenced by unfair computational distribution among many-core NIDS nodes. To avoid unfair computational distribution among many-core NIDS nodes, STEAL is designed to dynamically distribute the large volume of traffic among many-core NIDS nodes based on the packet service time, which is represented by the deep packet time in many-core NIDS nodes. From experiments, we show that compared to the commonly used load balancing algorithm based on arrival rate, STEAL increases the number of received packets, i.e., decreases the number of dropped packets, in many-core NIDS. Specifically, by integrating an open source NIDS, i.e. Bro, with STEAL, we show that even under the attack-dominant traffic and many signatures, STEAL can rapidly improve the performance of many-core NIDS to realize the high-speed intrusion detection.

Seung-Woo Seo

Papers

Some aspects of multistate interconnection networks: routing, rearrangeability and fault-tolerance

An efficient forensic evidence collection scheme of host infringement at the occurrence time

Ego-lane index-aware vehicular localisation using the DeepRoad Network for urban environments

Design and analysis of an ATM switch based on a distributed network: weaved GSN

STEAL: Service Time-Aware Load balancer on many-core processors for fast intrusion detection