This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

https://publications.uni.lu/bitstream/10993/20596/1/survey_on_SDN.pdf

Software-Defined Networking: A Comprehensive Survey

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Thank you for reading principles of optics electromagnetic theory of propagation interference and diffraction of light. As you may know, people have search hundreds times for their favorite novels like this principles of optics electromagnetic theory of propagation interference and diffraction of light, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their computer.

Principles Of Optics Electromagnetic Theory Of Propagation Interference And Diffraction Of Light

Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -- with a focus on aspects such as resiliency, scalability, performance, security and dependability -- as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cyto.a.22625

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

The increasing use of wireless networks and the constant miniaturization of electrical devices has empowered the development of Wireless Body Area Networks (WBANs). In these networks various sensors are attached on clothing or on the body or even implanted under the skin. The wireless nature of the network and the wide variety of sensors offer numerous new, practical and innovative applications to improve health care and the Quality of Life. The sensors of a WBAN measure for example the heartbeat, the body temperature or record a prolonged electrocardiogram. Using a WBAN, the patient experiences a greater physical mobility and is no longer compelled to stay in the hospital. This paper offers a survey of the concept of Wireless Body Area Networks. First, we focus on some applications with special interest in patient monitoring. Then the communication in a WBAN and its positioning between the different technologies is discussed. An overview of the current research on the physical layer, existing MAC and network protocols is given. Further, cross layer and quality of service is discussed. As WBANs are placed on the human body and often transport private data, security is also considered. An overview of current and past projects is given. Finally, the open research issues and challenges are pointed out.

/pdf/a-survey-on-wireless-body-area-networks-f3nx5ii4yv.pdf

A survey on wireless body area networks

An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging design problems. However, due to the computational cost of these high fidelity simulations, the use of neural networks, kernel methods, and other surrogate modeling techniques have become indispensable. Surrogate models are compact and cheap to evaluate, and have proven very useful for tasks such as optimization, design space exploration, prototyping, and sensitivity analysis. Consequently, in many fields there is great interest in tools and techniques that facilitate the construction of such regression models, while minimizing the computational cost and maximizing model accuracy. This paper presents a mature, flexible, and adaptive machine learning toolkit for regression modeling and active learning to tackle these issues. The toolkit brings together algorithms for data fitting, model selection, sample selection (active learning), hyperparameter optimization, and distributed computing in order to empower a domain expert to efficiently generate an accurate model for the problem or data at hand.

/pdf/a-surrogate-modeling-and-adaptive-sampling-toolbox-for-4rkytqpmzi.pdf

A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design

https://biblio.ugent.be/publication/5782416/file/5782424.pdf

Trends in worldwide ICT electricity consumption from 2007 to 2012

Chapter 1: Introduction 1.1 Communications networks today 1.2 Network reliability 1.3 Different phases in a recovery process 1.4 Performance of recovery mechanisms: criteria 1.5 Classification of single-layer recovery mechanisms 1.6 Multi-layer recovery 1.7 Conclusion Chapter 2: SONET-SDH 2.1 Introduction: transmission networks 2.2 SDH and SONET Networks 2.3 Operational aspects 2.4 Ring protection 2.5 Linear Protection 2.6 Restoration 2.7 Case study 2.8 Summary 2.9 Recommended reference work and research-related topics Chapter 3: Optical Networks 3.1 Evolution of the optical network layer 3.2. The Optical Transport Network 3.3 Fault detection and propagation 3.4 Recovery in optical networks 3.5 Recovery mechanisms in ring-based optical networks 3.6 Recovery mechanisms in mesh-based optical networks 3.7 Ring-based versus mesh-based recovery schemes 3.8 Availability 3.9 Som recent trends in research 3.10 Summary Chapter 4: IP Routing 4.1 IP routing protocols 4.2 Analysis of the IP recovery cycle 4.3 Failure profile and fault detection 4.4 Dampening algorithms 4.5 FIS propagation (LSA origination and flooding) 4.6 Route computation 4.7 Temporary loops during network states changes 4.8 Load balancing 4.9 QOS guarantees during failure 4.10 Non Stop Forwarding: an example with OSPF 4.11 A case study with IS-IS 4.12 Summary 4.13 Algorithm complexity 4.14 Incremental SPF 4.15 Interaction between fast IGP convergence and NSF 4.16 Research related topics Chapter 5: MPLS Traffic Engineering 5.1 MPLS Traffic Engineering refresher 5.2. Analysis of the recovery cycle 5.3. MPLS Traffic Engineering global default restoration 5.4 MPLS Traffic engineering global path protection 5.5 MPLS Traffic Engineering local protection 5.6. Another MPLS Traffic Engineering recovery alternative 5.7. Load balancing 5.8 Comparison of global protection and local protection 5.9 Revertive versus non revertive modes 5.10 Failure profiles and fault detection 5.11 Case Studies 5.12 Standardization 5.13 Summary 5.14 RSVP signaling extensions for MPLS TE local protection 5.15 Backup path computation 5.16 Research related topics Chapter 6 Multi-Layer Networks 6.1 ASON / GMPLS networks 6.2 Generic multi-layer recovery approaches 6.3 Case studies 6.4 Conclusion 6.5 References

Piet Demeester

Papers

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

A survey on wireless body area networks

A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design

Trends in worldwide ICT electricity consumption from 2007 to 2012

Network Recovery: Protection and Restoration of Optical, SONET-SDH, IP, and MPLS