There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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

Matrix Factorization Techniques for Recommender Systems

Device-to-device (D2D) communications was initially proposed in cellular networks as a new paradigm for enhancing network performance. The emergence of new applications such as content distribution and location-aware advertisement introduced new user cases for D2D communications in cellular networks. The initial studies showed that D2D communications has advantages such as increased spectral efficiency and reduced communication delay. However, this communication mode introduces complications in terms of interference control overhead and protocols that are still open research problems. The feasibility of D2D communications in Long-Term Evolution Advanced is being studied by academia, industry, and standardization bodies. To date, there are more than 100 papers available on D2D communications in cellular networks, but there is no survey on this field. In this paper, we provide a taxonomy based on the D2D communicating spectrum and review the available literature extensively under the proposed taxonomy. Moreover, we provide new insights into the over-explored and under-explored areas that lead us to identify open research problems of D2D communications in cellular networks.

https://eprints.networks.imdea.org/id/document/2488

A Survey on Device-to-Device Communication in Cellular Networks

Device-to-Device (D2D) communication was initially proposed in cellular networks as a new paradigm to enhance network performance. The emergence of new applications such as content distribution and location-aware advertisement introduced new use-cases for D2D communications in cellular networks. The initial studies showed that D2D communication has advantages such as increased spectral efficiency and reduced communication delay. However, this communication mode introduces complications in terms of interference control overhead and protocols that are still open research problems. The feasibility of D2D communications in LTE-A is being studied by academia, industry, and the standardization bodies. To date, there are more than 100 papers available on D2D communications in cellular networks and, there is no survey on this field. In this article, we provide a taxonomy based on the D2D communicating spectrum and review the available literature extensively under the proposed taxonomy. Moreover, we provide new insights to the over-explored and under-explored areas which lead us to identify open research problems of D2D communication in cellular networks.

Low-Complexity ICI Cancellation Based on BEM for OFDM Systems over Doubly Selective Channels

When data is released or shared among different organizations, some sensitive or confidential information may be subject to be exposed by using data mining tools. Thus, a question arises: how can we protect sensitive knowledge while allowing other parties to extract the knowledge behind the shared data. In this paper, we address the problem of privacy preserving in association rule mining from the perspective of multi-objective optimization. A sensitive rule can be hidden by adding items into the dataset to make the support of the antecedent part of the sensitive rule increase and accordingly the confidence of the sensitive rule decrease. The evolutionary multi-objective optimization (EMO) algorithm is utilized to find suitable transactions (or tuples) to be modified so as the side effects to be minimized. Experiments on real datasets demonstrated the effectiveness of the proposed method.

Use EMO to protect sensitive knowledge in association rule mining by adding items

Moving target defense (MTD) is a new defensive mechanism developed in power systems to thwart false data injection attacks (FDIAs). However, since the MTD works by perturbing the branch parameters with the distributed flexible ac transmission system (D-FACTS), it might cause additional infrastructure and operation costs and affect the system dynamics. This is a complicated problem because it is closely related to which branches should be perturbed and how much they are changed. In this article, we analyze the essentials of MTD and construct an effective and low-cost MTD. To begin with, we provide a sufficient and necessary condition for MTD to protect a bus from being affected by the intended FDIA. Based on this result, we propose a new metric to quantify the protection level of MTD and an efficient algorithm to minimize the number of required D-FACTS devices for protecting a specific set of buses. To reduce the operation cost, we develop two strategies to make the increasing operation cost zero for activating the MTD. Furthermore, we analyze the impact of MTD on the system dynamics with a special emphasize on small signal stability. Finally, we conduct extensive simulations to validate our findings with the test cases of power systems in MATPOWER.

Security Enhancement of Power System State Estimation With an Effective and Low-Cost Moving Target Defense

With the rapid development of crowdsourcing platforms that aggregate the intelligence of Internet workers, crowdsourcing has been widely utilized to address problems that require human cognitive abilities. Considering great dynamics of worker arrival and departure, it is of vital importance to design a task assignment scheme to adaptively select the most beneficial tasks for the available workers. In this paper, in order to make the most efficient utilization of the worker labor and balance the accuracy of answers and the overall latency, we a) develop a parameter estimation model that assists in estimating worker expertise, question easiness and answer confidence; b) propose a \textit{quality-assured synchronized task assignment scheme} that executes in batches and maximizes the number of potentially completed questions (MCQ) within each batch. We prove that MCQ problem is NP-hard and present two greedy approximation solutions to address the problem. The effectiveness and efficiency of the approximation solutions are further evaluated through extensive experiments on synthetic and real datasets. The experimental results show that the accuracy and the overall latency of the MCQ approaches outperform the existing online task assignment algorithms in the synchronized task assignment scenario.

Quality-Assured Synchronized Task Assignment in Crowdsourcing

In this paper, we present and analyze an interference avoidance scheme for OFDM cognitive radio systems From an active suppression point of view, it effectively prevents the negative effect of intercarrier interference that a cognitive radio may inflict on primary transmission due to frequency offset At the same time, it ensures bandwidth efficiency of secondary transmission Based on the least square error criterion, it is robust to frequency offset estimation error and has a low computational complexity Furthermore, its generalized form and algorithm can simply adapt to different frequency offsets and be extended to multiple users' case Simulation results show the enhanced performance of our proposed scheme, which greatly reduces the interference power in comparison with the passive tone null scheme

Peng Cheng

Papers

Low-Complexity ICI Cancellation Based on BEM for OFDM Systems over Doubly Selective Channels

Use EMO to protect sensitive knowledge in association rule mining by adding items

Security Enhancement of Power System State Estimation With an Effective and Low-Cost Moving Target Defense

Quality-Assured Synchronized Task Assignment in Crowdsourcing

An Interference Avoidance Scheme for OFDM Cognitive Radio Systems