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

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges

In studying the performance of coded communications over memoryless channels (with or without fading), the results are given as upper bounds on the average bit error probability (BEP). In principle, there are three different approaches to arriving at these bounds, all of which employ obtaining the so-called pairwise error probability , or the probability of choosing one symbol sequence over another for a given pair of possible transmitted symbol sequences, followed by a weighted summation over all pairwise events. In this chapter, we will focus on the results obtained from the third approach since these provide the tightest upper bounds on the true performance. The first emphasis will be placed on evaluating the pairwise error probability with and without CSI, following which we shall discuss how the results of these evaluations can be used via the transfer bound approach to evaluate average BEP of coded modulation transmitted over the fading channel.

Coded Communication over Fading Channels

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

A Wireless Sensor Network (WSN) is composed of distributed sensors with limited processing capabilities and energy restrictions. These unique attributes pose new challenges amongst which prolonging the WSN lifetime is one of the most important. Challenges are often tackled by a code-and-fix process that relies on low-level hardware and software information.Recently, the need of abstracting an implementation view into an architectural design is getting more realized. A clear separation of concerns is needed since hardware and software aspects are locked and tied down to specific types of nodes, hampering the possibility of reuse across projects and organizations. This means that exploiting the right level of abstraction, and keeping explicit (and separated) software and hardware architectural details will surely ease developers' job.In this paper we propose a modeling framework that allows developers to model separately the software architecture of the WSN, the low-level hardware specification of the WSN nodes and the physical environment where nodes are deployed in. The framework can use these models to generate executable code for analysis purposes. In this paper we focus on energy consumption analysis.

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A model-driven engineering framework for architecting and analysing wireless sensor networks

In recent years, there has been a huge trend towards running network intensive applications, such as Internet servers and Cloud-based service in virtual environment, where multiple virtual machines (VMs) running on the same machine share the machine's physical and network resources. In such environment, the virtual machine monitor (VMM) virtualizes the machine's resources in terms of CPU, memory, storage, network and I/O devices to allow multiple operating systems running in different VMs to operate and access the network concurrently. A key feature of virtualization is live migration (LM) that allows transfer of virtual machine from one physical server to another without interrupting the services running in virtual machine. Live migration facilitates workload balancing, fault tolerance, online system maintenance, consolidation of virtual machines etc. However, live migration is still in an early stage of implementation and its security is yet to be evaluated. The security concern of live migration is a major factor for its adoption by the IT industry. Therefore, this paper uses the X.805 security standard to investigate attacks on live virtual machine migration. The analysis highlights the main source of threats and suggests approaches to tackle them. The paper also surveys and compares different proposals in the literature to secure the live migration.

Secure Live Virtual Machines Migration: Issues and Solutions

Cooperative applications for VANETs will require seamless communication between vehicle to infrastructure and vehicle to vehicle. IEEE 802.11p has been developed to facilitate this effort. However, in order to have seamless communication for these applications, it is necessary to look at handover as vehicles move between roadside units. Traditional models of handover used in normal mobile environments are unable to cope with the high velocity of the vehicle and the relatively small area of coverage with regard to vehicular environments. The Y-Comm framework has yielded techniques to calculate the time before vertical handover and the network dwell time for any given network topology. Furthermore, by knowing these two parameters, it is also possible to improve channel allocation and resource management in network infrastructure such as base stations, relays, and so on. In this article we explain our overall approach by describing the VANET Testbed and show that in vehicular environments it is necessary to consider a new handover model that is based on a probabilistic rather than a fixed coverage approach. Finally, we show a new performance model for proactive handover, which is then compared with traditional approaches. Introdu

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Enabling seamless V2I communications: toward developing cooperative automotive applications in VANET systems

The aim of this study is to investigate the relationship between no mobile phobia (nomophobia) which is defined as a modern fear of being unable to communicate through the mobile phone, and Fear of Missing Out (FOMO) which is known to be related with the problematic relationship with Social Networking Sites (SNSs), and play a critical role in the increased use of Social Networking Sites (SNS). The data were collected from a convenient sample of 538 university students via Nomophobia (NMP-Q) and FOMO Scales, The results show that a positive moderate level of relationship was found between Nomophobia and FOMO levels. The findings showed that FOMO level of university students predicts 41% of the total variance at the Nomophobia level. That is, when FOMO level increases, students’ nomophobia level can be predicted from data depicting the increase.

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Relationship between nomophobia and fear of missing out among Turkish university students

This paper investigates double-threshold-based energy detector for cooperative spectrum sensing mechanisms in cognitive wireless radio networks. We first propose a hybrid double-threshold-based energy detector (HDTED) to improve the sensing performance at secondary users (SUs) by exploiting both the local binary/energy decisions and global binary decisions feedback from the fusion center (FC). Significantly, we derive closed-form expressions and bounds for the probabilities of missed detection and false alarm considering a practical scenario where all channel links suffer from Rayleigh fading and background noise. The derived expressions not only show the improved performance achieved with the HDTED scheme but also enable us to analyze the impacts of the number of the SUs and the fading channels on the cooperative spectrum sensing performance. Furthermore, based on the derived bounds, we propose an optimal SU selection algorithm for forwarding the local decisions to the FC, which helps reduce the number of forwarding bits for a lower-complexity signaling. Finally, numerical results are provided to demonstrate the validity of the analytical findings.

/pdf/a-hybrid-double-threshold-based-cooperative-spectrum-sensing-3am8tal20y.pdf

Orhan Gemikonakli

Papers

A model-driven engineering framework for architecting and analysing wireless sensor networks

Secure Live Virtual Machines Migration: Issues and Solutions

Enabling seamless V2I communications: toward developing cooperative automotive applications in VANET systems

Relationship between nomophobia and fear of missing out among Turkish university students

A Hybrid Double-Threshold Based Cooperative Spectrum Sensing over Fading Channels