http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers.



Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others.



The material is organized according to the system model-first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference.



The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms-to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.


Table of Contents

1 Introduction 
2 Modelling I; Synchronous Network Model 
3 Leader Election in a Synchronous Ring 
4 Algorithms in General Synchronous Networks 
5 Distributed Consensus with Link Failures 
6 Distributed Consensus with Process Failures 
7 More Consensus Problems 
8 Modelling II: Asynchronous System Model 
9 Modelling III: Asynchronous Shared Memory Model 
10 Mutual Exclusion 
11 Resource Allocation 
12 Consensus 
13 Atomic Objects 
14 Modelling IV: Asynchronous Network Model 
15 Basic Asynchronous Network Algorithms 
16 Synchronizers 
17 Shared Memory versus Networks 
18 Logical Time 
19 Global Snapshots and Stable Properties 
20 Network Resource Allocation 
21 Asynchronous Networks with Process Failures 
22 Data Link Protocols 
23 Partially Synchronous System Models 
24 Mutual Exclusion with Partial Synchrony 
25 Consensus with Partial Synchrony

Distributed algorithms

Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of radio-frequency identification (RFID), and wireless, mobile, and sensor devices. A wide range of industrial IoT applications have been developed and deployed in recent years. In an effort to understand the development of IoT in industries, this paper reviews the current research of IoT, key enabling technologies, major IoT applications in industries, and identifies research trends and challenges. A main contribution of this review paper is that it summarizes the current state-of-the-art IoT in industries systematically.

Internet of Things in Industries: A Survey

It has been next to impossible in the past months not to come across the term ‘‘Internet of Things’’ (IoT) one way or another. Especially the past year has seen a tremendous surge of interest in the Internet of Things. Consortia have been formed to define frameworks and standards for the IoT. Companies have started to introduce numerous IoTbased products and services. And a number of IoT-related acquisitions have been making the headlines, including, e.g., the prominent takeover of Nest by Google for $3.2 billion and the subsequent acquisitions of Dropcam by Nest and of SmartThings by Samsung. Politicians as well as practitioners increasingly acknowledge the Internet of Things as a real business opportunity, and estimates currently suggest that the IoT could grow into a market worth $7.1 trillion by 2020 (IDC 2014). While the term Internet of Things is now more and more broadly used, there is no common definition or understanding today of what the IoT actually encompasses. The origins of the term date back more than 15 years and have been attributed to the work of the Auto-ID Labs at the Massachusetts Institute of Technology (MIT) on networked radio-frequency identification (RFID) infrastructures (Atzori et al. 2010; Mattern and Floerkemeier 2010). Since then, visions for the Internet of Things have been further developed and extended beyond the scope of RFID technologies. The International Telecommunication Union (ITU) for instance now defines the Internet of Things as ‘‘a global infrastructure for the Information Society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies’’ (ITU 2012). At the same time, a multitude of alternative definitions has been proposed. Some of these definitions exhibit an emphasis on the things which become connected in the IoT. Other definitions focus on Internet-related aspects of the IoT, such as Internet protocols and network technology. And a third type centers on semantic challenges in the IoT relating to, e.g., the storage, search and organization of large volumes of information (Atzori et al. 2010). The fields of application for IoT technologies are as numerous as they are diverse, as IoT solutions are increasingly extending to virtually all areas of everyday. The most prominent areas of application include, e.g., the smart industry, where the development of intelligent production systems and connected production sites is often discussed under the heading of Industry 4.0. In the smart home or building area, intelligent thermostats and security systems are receiving a lot of attention, while smart energy applications focus on smart electricity, gas and water meters. Smart transport solutions include, e.g., vehicle fleet tracking and mobile ticketing, while in the smart health area, topics such as patients’ surveillance and chronic disease management are being addressed. And in the context of Accepted after one revision by Prof. Dr. Sinz.

/pdf/internet-of-things-technology-and-value-added-24gs2175e1.pdf

Internet of Things - Technology and Value Added

In the recent past, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics. As a consequence, it is becoming increasingly difficult to discuss typical requirements regarding hardware issues and software support. This is particularly problematic in a multidisciplinary research area such as wireless sensor networks, where close collaboration between users, application domain experts, hardware designers, and software developers is needed to implement efficient systems. In this article we discuss the consequences of this fact with regard to the design space of wireless sensor networks by considering its various dimensions. We justify our view by demonstrating that specific existing applications occupy different points in the design space.

/pdf/the-design-space-of-wireless-sensor-networks-2lr8ozcx58.pdf

The design space of wireless sensor networks

A distributed system can be characterized by the fact that the global state is distributed and that a common time base does not exist. However, the notion of time is an important concept in every day life of our decentralized \real world" and helps to solve problems like getting a consistent population census or determining the potential causality between events. We argue that a linearly ordered structure of time is not (always) adequate for distributed systems and propose a generalized non-standard model of time which consists of vectors of clocks. These clock-vectors are partially ordered and form a lattice. By using timestamps and a simple clock update mechanism the structure of causality is represented in an isomorphic way. The new model of time has a close analogy to Minkowski's relativistic spacetime and leads among others to an interesting characterization of the global state problem. Finally, we present a new algorithm to compute a consistent global snapshot of a distributed system where messages may be received out of order.

/pdf/virtual-time-and-global-states-of-distributed-systems-ary50qiv6y.pdf

Virtual Time and Global States of Distributed Systems

This paper discusses the vision, the challenges, possible usage scenarios and technological building blocks of the "Internet of Things". In particular, we consider RFID and other important technological developments such as IP stacks and web servers for smart everyday objects. The paper concludes with a discussion of social and governance issues that are likely to arise as the vision of the Internet of Things becomes a reality.

From the internet of computers to the internet of things

Ubiquitous computing is associated with a vision of everything being connected to everything. However, for successful applications to emerge, it will not be the quantity but the quality and usefulness of connections that will matter. Our concern is how qualitative relations and more selective connections can be established between smart artefacts, and how users can retain control over artefact interconnection. We propose context proximity for selective artefact communication, using the context of artefacts for matchmaking. We further suggest to empower users with simple but effective means to impose the same context on a number of artefacts. To prove our point we have implemented Smart-Its Friends, small embedded devices that become connected when a user holds them together and shakes them.

/pdf/smart-its-friends-a-technique-for-users-to-easily-establish-eyvmvt0xa0.pdf

Smart-Its Friends: A Technique for Users to Easily Establish Connections between Smart Artefacts

Creating networks of “smart things” found in the physical world (e.g., with RFID, wireless sensor and actuator networks, embedded devices) on a large scale has become the goal of a variety of recent research activities. Rather than exposing real-world data and functionality through vertical system designs, we propose to make them an integral part of the Web. As a result, smart things become easier to build upon. In such an architecture, popular Web technologies (e.g., HTML, JavaScript, Ajax, PHP, Ruby) can be used to build applications involving smart things, and users can leverage well-known Web mechanisms (e.g., browsing, searching, bookmarking, caching, linking) to interact with and share these devices. In this chapter, we describe the Web of Things (WoT) architecture and best practices based on the RESTful principles that have already contributed to the popular success, scalability, and evolvability of the Web. We discuss several prototypes using these principles, which connect environmental sensor nodes, energy monitoring systems, and RFID-tagged objects to the Web. We also show how Web-enabled smart things can be used in lightweight ad-hoc applications, called “physical Mashups”, and discuss some of the remaining challenges towards the global World Wide Web of Things.

/pdf/from-the-internet-of-things-to-the-web-of-things-resource-4fhj0tezpx.pdf

Friedemann Mattern

Papers

The design space of wireless sensor networks

Virtual Time and Global States of Distributed Systems

From the internet of computers to the internet of things

Smart-Its Friends: A Technique for Users to Easily Establish Connections between Smart Artefacts

From the Internet of Things to the Web of Things: Resource-oriented Architecture and Best Practices