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

Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.

Industrial Internet of Things: Challenges, Opportunities, and Directions

https://uwe-repository.worktribe.com/preview/871355/IoT5m.pdf

5G Internet of Things: A survey

algorithmics and modular computations, Theory of Codes and Cryptography (3).From an analytical 1. RE Blahut. Theory and practice of error control codes. eecs.uottawa.ca/∼yongacog/courses/coding/ (3) R.E. Blahut,Theory and Practice of Error Control Codes, Addison Wesley, 1983. QA 268. Cached. Download as a PDF 457, Theory and Practice of Error Control CodesBlahut 1984 (Show Context). Citation Context..ontinued fractions.

Theory and practice of error control codes

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives. The participating nodes in IoT networks are usually resource-constrained, which makes them luring targets for cyber attacks. In this regard, extensive efforts have been made to address the security and privacy issues in IoT networks primarily through traditional cryptographic approaches. However, the unique characteristics of IoT nodes render the existing solutions insufficient to encompass the entire security spectrum of the IoT networks. Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, can be leveraged to cope with different security problems. In this paper, we systematically review the security requirements, attack vectors, and the current security solutions for the IoT networks. We then shed light on the gaps in these security solutions that call for ML and DL approaches. Finally, we discuss in detail the existing ML and DL solutions for addressing different security problems in IoT networks. We also discuss several future research directions for ML- and DL-based IoT security.

Machine Learning in IoT Security: Current Solutions and Future Challenges

Transmitters, receivers, and coding schemes to increase data rate and decrease bit error rate of an optical data link are disclosed. Data is transmitted across the link with a less than nominal bit error rate (BER), by encoding the data using a forward error correction (FEC) code or by requesting retransmission of transmitted packets in error. Data is transmitted at a speed that introduces errors at a rate that is in excess of the nominal BER but that may be corrected using the FEC code or retransmission so that the data may be received with less than the nominal BER. The data rate is increased as the link operating speed is increased beyond the overhead required by the FEC codes or retransmission. High speed FEC encoders and decoders facilitating such transmission are disclosed.

Transmitter, receiver, and coding scheme to increase data rate and decrease bit error rate of an optical data link

Approximate Markov chains for the performance of banyan networks built with basic switches of arbitrary size containing input queues, output queues or a combination of input buffers and output queues are presented. These chains are also extended to model banyans where each link is replaced by a number of parallel links. Comparison with simulations indicates that the chains are reasonably accurate for practical network loads. It is shown that banyans built with switches containing a combination of single input buffers and output queues outperforms banyans built with switches containing only input queues or only output queues. Banyans built with larger nodes are shown to outperform banyans built with smaller nodes. It is shown that banyan-based networks with multiple links can be designed to have extremely low blocking probabilities. >

Markov chain analysis of packet-switched banyans with arbitrary switch sizes, queue sizes, link multiplicities and speedups

“Hypermeshes”: optical interconnection networks for parallel computing

Two implementations of a fiber-optic packet-switched hypercube are proposed. In the first, each directed link is implemented with a fixed wavelength laser and photodetector, and all optical transmissions are wavelength multiplexed onto one or more fibers. In the second, the electronic crosspoint matrices within the nodes are eliminated by allowing each laser to be tunable over a range of log N wavelengths. Assume that a hot potato, or deflection, routing algorithm is used; as soon as a packet is received at a node, a routing decision is made and the packet is sent out. The node attempts to send the packet towards its destination. The analysis indicates that a hypercube, hot-potato routing offers essentially optimal performance for random traffic, regardless of how large the hypercube grows, and it significantly outperforms traditional shortest-path routing with buffering and flow control. A few variations, including an algorithm which gives priority to packets closer to their destinations and one which gives priority to various classes of traffic, are also proposed and analyzed. >

An analysis of 'hot-potato' routing in a fiber optic packet switched hypercube

A reconfigurable intelligent optical backplane architecture for parallel computing
 and communications is described. The backplane consists of a large number of
 reconfigurable optical channels organized in a ring with relatively simple
 point-to-point optical interconnections between neighboring smart-pixel arrays. The
 intelligent backplane can implement (1) dynamically reconfigurable connections
 between any printed circuit boards, (2) dynamic embeddings of classical
 interconnection networks such as buses, rings, multidimensional meshes, hypercubes,
 shuffles, and crossbars, (3) multipoint switching, (4) sorting, (5) parallel-prefix
 operations, (6) pattern-matching operations, (7) snoopy caches and intelligent memory
 systems, and (8) media-access control functions. The smart-pixel arrays can be
 enhanced to include more complex functions, such as queuing and routing, as the
 technologies mature. Descriptions of the architecture and the smart-pixel arrays and
 discussions of the system cost, availability, and performance are included.

https://works.bepress.com/scott_hinton/13/download/

Ted H. Szymanski

Papers

Transmitter, receiver, and coding scheme to increase data rate and decrease bit error rate of an optical data link

Markov chain analysis of packet-switched banyans with arbitrary switch sizes, queue sizes, link multiplicities and speedups

“Hypermeshes”: optical interconnection networks for parallel computing

An analysis of 'hot-potato' routing in a fiber optic packet switched hypercube

Reconfigurable Intelligent Optical BackPlane for Parallel Computing and Communications