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

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.

Security in wireless sensor networks

A survey on FinTech

Trust is an important concept in human interactions which facilitates the formation and continued existence of functional human societies. In the first decade of the 21st century, computational trust models have been applied to solve many problems in wireless communication systems. This cross-disciplinary research has yielded many innovative solutions. In this paper, we examine the latest methods which have been proposed by researchers to manage trust and reputation in wireless communication systems. Specifically, we survey the state of the art in the application of trust models in the fields of mobile ad hoc networks (MANETs), wireless sensor networks (WSNs), and cognitive radio networks (CRNs). We classify the mainstream methods into natural categories and illustrate how they complement each other in achieving design goals. Major research directions are also outlined.

A Survey of Trust and Reputation Management Systems in Wireless Communications

Major requirements for building Smart Homes in Smart Cities based on Internet of Things technologies

Pervasive devices interacting in open and dynamic spaces with each others require a mechanism that allows them acting autonomously in a secure way and protecting their resources. Trust is fundamental to establish communication with other users, because the identity is often uncertain and on one's own does not provide trust information, for instance, could an unknown user be trustworthy? Nowadays, these devices have a so limited security support. So, we propose a simple trust management model to enhance such support, allowing them interact in ad hoc networks and peer-to-peer applications in a secure way. In this paper, our main contribution is a mathematical and a probabilistic model, as well as demonstrating the model feasibility, since it has been assessed through the prototype implementation, which has been tested in a Pocket PC.

Developing a model for trust management in pervasive devices

Cloud computing allows accessing resources across Internet transparently: requiring no expertise in, or control over the underlying infrastructure. There is an increasing interest in sharing media files with family and friends. However, UPnP or DLNA were not designed for media distribution beyond the boundaries of a local network and manage media files through web applications can be tedious. To overcome this problem, we propose Media Cloud, a middleware for Set-top boxes for classifying, searching, and delivering media inside home network and across the cloud that interoperates with UPnP and DLNA.

Media cloud: an open cloud computing middleware for content management

Consumer cloud computing paradigm has emerged as the natural evolution and integration of advances in several areas including distributed computing, service oriented architecture and consumer electronics. In this complex ecosystem, security and identity management challenges have cropped up, given their dynamism and heterogeneity. As a direct consequence, dynamic federated identity management with privacy improvements has arisen as an indispensable mechanism to enable the global scalability and usability that are required for the successful implantation of Cloud technologies. With these requirements in mind, we present an IdM architecture based on privacy and reputation extensions compliance with the SAMLv2/ID-FF standards1.

Enhancing privacy and dynamic federation in IdM for consumer cloud computing

Alice first meets Bob in an entertainment shop, then, they wish to share multimedia content, but Do they know what are trustworthy users? How do they share such information in a secure way? How do they establish the permissions? Pervasive computing environments originate this kind of scenario, users with their personal devices interacting without need of wires, by forming ad-hoc networks. Such devices considered pervasive are having increasingly faster processors, larger memories and wider communication capabilities, which allows certain autonomy for collaborating and sharing resources. So, they require a suitable access control in order to avoid unauthorised access, or disclosure/modification of relevant information; in general, to protect the data that are usually confidential and the resources. This paper presents a distributed solution for access control, making use of the autonomy and cooperation capability of the devices, since in open dynamic environments is very difficult to depend on central server. The access control is based on a pervasive trust management model from which trust degrees are dynamically obtained. We present the TrustAC reference and functional model, as well as a prototype implementation using XACML-compliant policies.

TrustAC: trust-based access control for pervasive devices

The Internet of Things will bring a scenario in which interaction between humans and devices will be critical to allow people to use, monitor or configure Internet of Things devices. Interactions in such applications are based on traditional graphical interfaces. Devices that accept interaction based on Natural Language, e.g., through voice commands, can understand basic human orders or answering questions whenever user expressions fit into a known language pattern. Some devices can understand natural language voice commands but require sophisticated voice assistants located in the cloud, which raises significant privacy concerns. Others devices which handle voice-processing locally can perform a very limited local recognition system, requiring users to be familiar with words the system can process. The purpose of this work is to diminish the complexity of Natural Language processing in the context of IoT. The solution posited in this article allows Internet of Things devices to offload Natural Language processing to a system that improves the use of Natural Language and alleviates the need to learn or remember specific words or terms intended for triggering device actions. We have evaluated the feasibility of the design with a proof-of-concept implemented in a home environment and it was tested by real users.

Andrés Marín

Papers

Developing a model for trust management in pervasive devices

Media cloud: an open cloud computing middleware for content management

Enhancing privacy and dynamic federation in IdM for consumer cloud computing

TrustAC: trust-based access control for pervasive devices

Seamless human-device interaction in the internet of things