Data Mining Practical Machine Learning Tools and Techniques

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

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A Break in the Clouds: Towards a Cloud Definition

Network virtualization is recognized as an enabling technology for the future Internet. It aims to overcome the resistance of the current Internet to architectural change. Application of this technology relies on algorithms that can instantiate virtualized networks on a substrate infrastructure, optimizing the layout for service-relevant metrics. This class of algorithms is commonly known as "Virtual Network Embedding (VNE)" algorithms. This paper presents a survey of current research in the VNE area. Based upon a novel classification scheme for VNE algorithms a taxonomy of current approaches to the VNE problem is provided and opportunities for further research are discussed.

Virtual Network Embedding: A Survey

Network anomaly detection is an important and dynamic research area. Many network intrusion detection methods and systems (NIDS) have been proposed in the literature. In this paper, we provide a structured and comprehensive overview of various facets of network anomaly detection so that a researcher can become quickly familiar with every aspect of network anomaly detection. We present attacks normally encountered by network intrusion detection systems. We categorize existing network anomaly detection methods and systems based on the underlying computational techniques used. Within this framework, we briefly describe and compare a large number of network anomaly detection methods and systems. In addition, we also discuss tools that can be used by network defenders and datasets that researchers in network anomaly detection can use. We also highlight research directions in network anomaly detection.

Network Anomaly Detection: Methods, Systems and Tools

Cloud outages, no matter how long, are responsible for large financial losses. Cloud providers look for solutions that provide high availability even in failure cases. Redundancy has been often used as an alternative; however it has a cost, and depending on the redundancy model, we can have different levels of availability. Beyond that, adding more resources also means adding more complexity and more point of failures. In this paper, we propose a risk-based model for estimating the availability of a redundancy setup. In order to analyze our model, we conduct Monte Carlo simulations and results show that for all models, the number of applications we deploy in a Cloud environment impacts on its availability.

Risk-based model for availability estimation of SAF redundancy models

The Internet of Things (IoT) has emerged as one of the prominent concepts in academic discourse in recent times reflecting a wider trend by industry to connect physical objects to the Internet and to each other. The IoT is already generating an unprecedented volume of data in greater varieties and higher velocities. Making sense of such data is an emerging and significant challenge. Infographics are visual representations that provide a visual space for end users to compare and analyze data, information, and knowledge in a more efficient form than traditional forms. The nature of loT requires a continuum modification in how end users see information to achieve such efficiency gains. Conceptualizing and implementing Infographics in an loT system can thus require significant planning and development for both data scientists, graphic designers and developers resulting in both costs in terms of time and effort. To address this problem, this paper presents SiMoNa, a domain-specific modeling language (DSML) to create, connect, interact, and build interactive infographic presentations for loT systems efficiently based on the model-driven develonment (MDD) naradiam.

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SiMoNa: A Proof-of-concept Domain Specific Modeling Language for IoT Infographics

Due to the growth of Cloud Computing, the supporting infrastructure has become more complex, and the centralized solutions suffer resource management difficulties due to the large scale and the dynamicity of the scenario. Consequently, distributed solutions have been proposed in the literature and the self-organizing ones have attracted particular interest due to their robustness and adaptability characteristics. Techniques, such as bio-inspired computing, multi-agent systems, and evolutionary techniques are used to manage resources. The main goal of this paper is to present a start study about how self-organizing solutions are applied in resource management of Cloud providers, as well as to highlight the main research challenges in this area.

Self-organizing strategies for resource management in Cloud Computing: State-of-the-art and challenges

Knowing available energy in each part of a wireless sensor networks (WSN) is undoubtedly essential information. A simple approach to achieve this would be for sensor nodes to periodically report to the sink node on their available energy. This approach is expensive however in terms of energy consumption. In this work we apply several sampling techniques for obtaining such information in WSNs. The results show our samples are representative and the energy map may be satisfactorily built using information from a single subgroup of nodes hence leading to important energy savings.

Sampling energy consumption in wireless sensor networks

Recently, peer-to-peer (P2P) streaming applications have drawn attention to both users and research community. The P2P approach for IPTV has the appealing feature of providing TV-like quality content distribution service (for both on-demand and live TV), which has been attracting a large number of users from across the globe. However, there is very little understanding about their network architecture and resource consumption. This work aims at having an in-depth understanding of Joost, a video-on-demand P2P system for distributing TV content, created by Skype and Kazaa founders. Results show that Joost relies on UDP for content delivery with an asymmetric bandwidth consumption of until 750 Kbps (download) and 480 Kbps (upload). We also evaluated the Joost control plane, which is mainly based on TCP. Along with other P2P IPTV technologies, such systems could have a great impact on network bandwidth utilization, even more than P2P file transfer ones.

Djamel Sadok

Papers

Risk-based model for availability estimation of SAF redundancy models

SiMoNa: A Proof-of-concept Domain Specific Modeling Language for IoT Infographics

Self-organizing strategies for resource management in Cloud Computing: State-of-the-art and challenges

Sampling energy consumption in wireless sensor networks

A step towards understanding Joost IPTV