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An Introduction to MultiAgent Systems.

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

Information Theory and Reliable Communication

‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Single-user multi-antenna technologies are well upported in current standard specifications like LTE Release 8/9. Further development of the specification (LTE-Advanced) is expected to conform to the requirements for IMT-Advanced systems. One of the key enabling features of LTE-Advanced to meet IMT-Advanced downlink performance requirements is multi-user MIMO, where a transmitter serves multiple users simultaneously on the same frequency resource, primarily relying on spatial separation. In general, multi-user MIMO is beneficial for improving average user spectral efficiency. However, cell edge user spectral efficiency may be reduced if multi-user MIMO is used exclusively, due to residual inter-user interference arising from practical multi-user beamforming and reduced transmit power allocated to each user. Therefore, it should be possible to configure the UE-specific transmission mode to support dynamic switching between single-user MIMO and multi-user MIMO to balance the cell edge user spectral efficiency as well as the average cell user spectral efficiency. In this article, we study various aspects of multi-user MIMO including design philosophy, multi-user precoding, and control signaling. The associated feedback schemes, including those that facilitate dynamic switching, are discussed. Performance evaluation is conducted to demonstrate the gain of dynamically switched single-user and multiuser MIMO as opposed to traditional single-user MIMO.

Downlink MIMO in LTE-advanced: SU-MIMO vs. MU-MIMO

Mobile network operators (MNOs) are in the process of overlaying their conventional macro cellular networks with shorter range cells such as outdoor pico cells. The resultant increase in network complexity creates substantial overhead in terms of operating expenses, time, and labor for their planning and management. Artificial intelligence (AI) offers the potential for MNOs to operate their networks in a more organic and cost-efficient manner. We argue that deploying AI in fifth generation (5G) and beyond will require surmounting significant technical barriers in terms of robustness, performance, and complexity. We outline future research directions, identify top five challenges, and present a possible roadmap to realize the vision of AI-enabled cellular networks for Beyond- 5G and sixth generation (6G) networks.

Artificial Intelligence-Enabled Cellular Networks: A Critical Path to Beyond-5G and 6G

The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors, such as environmental monitoring, mobile-health systems, intelligent transportation systems, and so on. The information and communication technology sector is experiencing a significant growth in data traffic, driven by the widespread usage of smartphones, tablets, and video streaming, along with the significant growth of sensors deployments that are anticipated in the near future. It is expected to outstandingly increase the growth rate of raw sensed data. In this paper, we present the CPS taxonomy via providing a broad overview of data collection, storage, access, processing, and analysis. Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects. Furthermore, CPS requires cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that are continuously being generated in the network. Thus, we also provide an overview of the different security solutions proposed for CPS big data storage, access, and analytics. We also discuss big data meeting green challenges in the contexts of CPS.

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Wireless systems offer a unique mixture of connectivity, flexibility, and freedom. It is therefore not surprising that wireless technology is being embraced with increasing vigor. For real-time applications, user satisfaction is closely linked to quantities such as queue length, packet loss probability, and delay. System performance is therefore related to, not only Shannon capacity, but also quality of service (QoS) requirements. This work studies the problem of resource allocation in the context of stringent QoS constraints. The joint impact of spectral bandwidth, power, and code rate is considered. Analytical expressions for the probability of buffer overflow, its associated exponential decay rate, and the effective capacity are obtained. Fundamental performance limits for Markov wireless channel models are identified. It is found that, even with an unlimited power and spectral bandwidth budget, only a finite arrival rate can be supported for a QoS constraint defined in terms of exponential decay rate

Resource Allocation and Quality of Service Evaluation for Wireless Communication Systems Using Fluid Models

Cyber-physical systems (CPS) help create new services and applications by revolutionising our world in different fields through their tight interactions and automated decisions. This is especially true with the ongoing increase in the number of physical things (sensors, actuators, smartphones, tablets, and so on) along with the explosive increase in the usage of online networking services and applications. Future fifth generation (5G) cellular networks will facilitate the enabling of CPS communications over current network infrastructure through different technologies such as device-to-device (D2D) communications. In this study, the authors discuss about the main challenges that cellular providers will face as the massive number of CPS devices attempt to access the cellular spectrum. A case study is presented on how to ease the spectrum access of these devices through D2D spatial spectrum sensing. Furthermore, the authors discuss about protecting these D2D links from eavesdropping, since security is becoming a critical aspect in the cyber-physical space, especially with the large amount of traffic that is constantly flowing through the network.

Lingjia Liu

Papers

Downlink MIMO in LTE-advanced: SU-MIMO vs. MU-MIMO

Artificial Intelligence-Enabled Cellular Networks: A Critical Path to Beyond-5G and 6G

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Resource Allocation and Quality of Service Evaluation for Wireless Communication Systems Using Fluid Models

Enabling cyber-physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber-security