Prepare to Succeed with the Internet of Things
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Iot Mag April May 2017.Qxp Layout 1
IoT Now: ISSN 2397-2793 APRIL/MAY 2017 • VOLUME 7 • ISSUE 2 TALKING HEADS Aeris CTO explains why IoT needs and deserves to have security by design INSIDE: The Enterprise Buyer's Guide – Which IoT Platform 2017 SECURE IoT SMART ENERGY INDUSTRIAL IoT TRANSPORT IoT GLOBAL NETWORK How to address the New efficiency for living, The new interconnected Connections for a Log on at growing threat. See our working and playing. manufacturing environment. moving industry. www.iotglobalnetwork.com Analyst Report at See our Analyst Report at See our Analyst Report at Read our exclusive Analyst to discover our new portal for www.iot-now.com www.iot-now.com www.iot-now.com Report inside this issue products, services and insight PLUS: 18 PAGE TRANSPORT INSIGHT REPORT: Unlimit CEO says IoT success in India means focusing on the long tail • HMS Industrial Networks on why it's time to skip the scary stories and focus on what's needed to secure manufacturing IoT • Geolocation in the Port of Barcelona with Actility • AT&T on why IoT platforms must address organisations’ different needs for functionality• Inside Digicel's deployment of Stream Technologies' IoT-X platform with added Starhome Mach technologies in 33 M2M markets • How Vodafone connectivity helps precision manufacturer ensure maximum uptime for machines • News at www.iot-now.com Get to market faster with IoT services 7RƫQGRXWPRUHQRNLDFRPLRW CONTENTS IoT NOW 10 ANALYST 27 TALKING HEADS REPORT 16 50 SECURITY IoT PLATFORMS INTERVIEW TO WATCH IN THIS ISSUE 20 CASE STUDY 58 COMPANY PROFILE Inside Actility, -
Openfog Reference Architecture for Fog Computing
OpenFog Reference Architecture for Fog Computing Produced by the OpenFog Consortium Architecture Working Group www.OpenFogConsortium.org February 2017 1 OPFRA001.020817 © OpenFog Consortium. All rights reserved. Use of this Document Copyright © 2017 OpenFog Consortium. All rights reserved. Published in the USA. Published February 2017. This is an OpenFog Consortium document and is to be used in accordance with the terms and conditions set forth below. The information contained in this document is subject to change without notice. The information in this publication was developed under the OpenFog Consortium Intellectual Property Rights policy and is provided as is. OpenFog Consortium makes no representations or warranties of any kind with respect to the information in this publication, and specifically disclaims implied warranties of fitness for a particular purpose. This document contains content that is protected by copyright. Copying or distributing the content from this document without permission is prohibited. OpenFog Consortium and the OpenFog Consortium logo are registered trademarks of OpenFog Consortium in the United States and other countries. All other trademarks used herein are the property of their respective owners. Acknowledgements The OpenFog Reference Architecture is the product of the OpenFog Architecture Workgroup, co-chaired by Charles Byers (Cisco) and Robert Swanson (Intel). It represents the collaborative work of the global membership of the OpenFog Consortium. We wish to thank these organizations for contributing -
Intelligent Edge Categories
2 TABLE OF CONTENTS © Copyright 2019 Daniel Sexton TABLE OF CONTENTS A TABLE OF CONTENTS Audience ...................................................................................................................................................... 1 Author’s Note ................................................................................................................................................ 2 Executive Summary ....................................................................................................................................... 5 Building An Intelligent Edge Strategy ............................................................................................................. 7 Edge Project Types .................................................................................................................................... 7 The Early Adopter’s Problem ....................................................................................................................... 9 Considering Life Cycles ........................................................................................................................... 9 The Strategy Box ..................................................................................................................................... 11 Intro to The Intelligent Edge........................................................................................................................ 13 What is The Edge? .................................................................................................................................. -
The Second ACM/IEEE Symposium on Edge Computing October 12-14, 2017, San Jose, CA, USA
SEC 2017 The Second ACM/IEEE Symposium on Edge Computing October 12-14, 2017, San Jose, CA, USA http://acm-ieee-sec.org/2017/ “Edge computing” is new paradigm in which the resources of a small data center are placed at the edge of the Internet, in close proximity to mobile devices, sensors, end users, and the emerging Internet of Things. Terms such as “cloudlets,” “micro data centers,” and “fog” have been used in the literature to refer to these small, edge- located data centers. They all represent counterpoints to the theme of consolidation and massive data centers that has dominated discourse in cloud computing. New challenges and opportunities arise as the consolidation of cloud computing meets the dispersion of edge computing. Building upon the success of inaugural SEC, the organizing committee is delighted to invite you to Symposium on Edge Computing 2017, to be held in San Jose, California. General Chair Steering Committee Junshan Zhang, Arizona State University Victor Bahl, Microsoft Research Program Chairs Flavio Bonomi, IoXWorks Mung Chiang, Princeton University Rong Chang, IBM Research Bruce Maggs, Akamai/Duke University Dejan Milojicic, HP Labs Program Committee Michael Rabinovich, Case Western Reserve Eric Anderson, NIST University Rajesh Balan, Singapore Management University Weisong Shi, Wayne State University (chair) Bharath Balasubramanian, AT&T Labs Research Tao Zhang, Cisco Suman Banerjee, University of Wisconsin-Madison Local Arrangement Chair Songqing Chen, George Mason University Jerry Gao, San Jose State University Mung Chiang, Princeton University Romit Roy Choudhury, University of Illinois at Urbana- Finance and Registration Chair Champaign Qun Li, College of William & Mary Landon Cox, Duke University Sponsorship Chair Eduardo Cuervo, Microsoft Research Rong Chang, IBM Fred Douglis, Dell EMC Publicity Chairs Schahram Dustdar, TU Wien Schahram Dustdar, TU Wien, Austria Robert J. -
Broader Impacts
Maria Gorlatova, Princeton University: Broader Impacts BROADER IMPACTS Maria Gorlatova [email protected] Associate Research Scholar Princeton University My contributions and plans related to broader impacts fall under the categories of involvement in initiatives related to diversity and inclusion, ongoing and planned industry engagements, and plans to transform organizational practices with the developments in the Internet of Things. Diversity and Inclusion Initiatives I actively promote diversity and inclusion in my research group and within the broader scientific and technical communities, contributing to and leading multiple related initiatives. Aspects of my contributions to diversity have been recognized with a Google Anita Borg USA Fellowship, which is awarded yearly to only 25 students across all levels of studies and across all computing-related disciplines nation-wide, based on academic performance, leadership, and impact on the community of women in technology. I am contributing to and leading initiatives that create strong wide-reaching support networks between the members of under-represented groups. For instance, I was an invited participant in the MIT Rising Stars in EECS event that created a network of top graduate and post-doctoral women in Electrical Engineering and Computer Science. I also participated in the Google Graduate Researchers of Diverse Backgrounds CS Forum, which brought together graduate students of diverse backgrounds from different parts of United States and Canada. I am also currently serving on the board of the field-specific Networking Networking Women (N2 Women) organization that develops and strengthens the community of female researchers in communications and computer networking. Near-term I will lead the development of networks between the members of under-represented groups who work in my core research areas, Internet of Things and fog and edge computing. -
RESEARCH NOTE the Aragon Research Tech Spectrum
Digital Workplace Service RESEARCH NOTE Number: 2017-7 March 1, 2017 Topic: Digital Business Platforms Issue: Who are the vendors that are battling to lead the Digital Business Platform revolution? Author: Jim Sinur The Aragon Research Tech Spectrum™ for Digital Business Platforms, 2017: Accelerating Digital Benefits Summary: Digital Business Platforms (DBPs) consist of managing digital processes, applications, and transactions in a mostly electronic manner and do so by leveraging the latest or emerging digital technologies. We evaluate 23 key providers who are leading the charge in the DBP market. TABLE OF CONTENTS Introduction .................................................................................................................................. 2 Why DBPs? ............................................................................................................................... 2 Key Trends ................................................................................................................................ 3 DBP Market Overview & Key Aspects ...................................................................................... 6 ™ Aragon Research Tech Spectrum Overview .............................................................................. 8 Dimensions of Analysis ............................................................................................................. 9 Inclusion and Exclusion Criteria ............................................................................................... -
Demystifying Internet of Things Security Successful Iot Device/Edge and Platform Security Deployment — Sunil Cheruvu Anil Kumar Ned Smith David M
Demystifying Internet of Things Security Successful IoT Device/Edge and Platform Security Deployment — Sunil Cheruvu Anil Kumar Ned Smith David M. Wheeler Demystifying Internet of Things Security Successful IoT Device/Edge and Platform Security Deployment Sunil Cheruvu Anil Kumar Ned Smith David M. Wheeler Demystifying Internet of Things Security: Successful IoT Device/Edge and Platform Security Deployment Sunil Cheruvu Anil Kumar Chandler, AZ, USA Chandler, AZ, USA Ned Smith David M. Wheeler Beaverton, OR, USA Gilbert, AZ, USA ISBN-13 (pbk): 978-1-4842-2895-1 ISBN-13 (electronic): 978-1-4842-2896-8 https://doi.org/10.1007/978-1-4842-2896-8 Copyright © 2020 by The Editor(s) (if applicable) and The Author(s) This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. -
Fog Computing the Scenario
Università degli Studi di Roma “Tor Vergata” Dipartimento di Ingegneria Civile e Ingegneria Informatica Fog Computing Corso di Sistemi e Architetture per Big Data A.A. 2016/17 Valeria Cardellini The scenario • Connected devices are creating data at an exponentially growing rate, which will drive performance and network congestion challenges at the edge of infrastructure • Performance, security, bandwidth, reliability, and many other concerns that make cloud- only solutions impractical for many use cases Valeria Cardellini - SABD 2016/17 1 A possible solution • Move information processing and intelligence at the logical edge of the networks (“the cloud close to the ground”): many micro data centers located at the network edge Valeria Cardellini - SABD 2016/17 2 Fog Computing definitions • “Fog Computing is a highly virtualized platform that provides compute, storage, and networking services between end devices and traditional Cloud Computing Data Centers, typically, but not exclusively located at the edge of network.” (Bonomi et al., 2012) • “A horizontal, system-level architecture that distributes computing, storage, control and networking functions closer to the users along a cloud-to-thing continuum.” (OpenFog consortium, 2017) Valeria Cardellini - SABD 2016/17 3 What Fog is • An extension of the traditional cloud-based computing model where implementations of the architecture can reside in multiple layers of a networks’ topology • Preserves all the benefits of Cloud computing – Including containerization, virtualization, orchestration, -
Edge and Fog Computing - Convergence of Solutions?
Edge and fog computing - convergence of solutions? Eugen Borcoci University POLITEHNICA Bucharest (UPB) [email protected] ComputationWorld 2018 Conference February 18, 2018, Barcelona Edge and fog computing - convergence of solutions? Acknowledgement 1.This overview is compiled and structured, based on several public documents belonging to different authors and groups, on Cloud/Fog, IoT, Multi-access Mobile Edge Computing, SDN, NFV, 4G/5G networking, etc.: conferences material, studies, research papers, standards, projects, overviews, tutorials, etc. (see specific references in the text and Reference list). 2. Given the extension of the topics, this presentation is a high level overview only. ComputationWorld 2018 Conference February 18, 2018, Barcelona Slide 2 Edge and fog computing - convergence of solutions? Motivation of this talk Facts: Novel services, applications and communication paradigms based on Internet technologies Internet of Things (IoT)- including industry and agriculture, Smart cities, M2M, Vehicular communications, Content/media oriented communications, Social networks, Big data applications, etc. • “Internet of Everything” (IoE) Supporting technologies ( used in cooperative mode) Cloud Computing (CC) Edge oriented computing • Multi-access/Mobile Edge Computing (MEC) • Fog Computing (FC/EC) • Cloudlets, .. Auxiliary technologies Virtualization techniques Software Defined Networks (SDN) Network Function Virtualization (NFV) ComputationWorld 2018 Conference February 18, 2018, Barcelona Slide 3 Edge and -
The Standard Issue 1, 2018 (PDF)
THE STANDARD News From ETSI . Issue 1, 2018 ETSI creates City Digital Profile group on Smart Cities Cities to procure interoperable smart solutions for their citizens ETSI has created a new Industry cities and on a large scale. Smart objectives and reducing the overall cost Specification Group “City Digital Profile” services are intended to improve the of deployment. (ISG CDP). It will help accelerate the overall quality of living in the city delivery of integrated citizen services and make them attractive to citizens, Continued on page 2 > and provide a technology road map investors, business, innovators, visitors for city leaders who will benefit from and tourists. standardized solutions from their Releasing suppliers. The City Digital Profile ISG will enable cities to procure smart solutions the Flow In providing this technology framework with confidence that those solutions and clear roadmap for technology will be extendable, configurable and investment and deployment, interoperable with similar services market confidence levels in the city from other cities and providers. infrastructure investments should City administrators will therefore increase and in addition this will give deliver advanced services to their cities the possibility to replicate those citizens, whilst respecting essential solutions across domains, between environmental factors, sustainability First 5G New Radio Specifications approved Data protection and 3GPP has approved the first 5G he presented details of the group’s privacy in a data- specifications: the non-standalone approval of the Non-standalone 5G driven economy 5G New Radio specifications were NR specifications and also outlined approved on 20 December 2017. how RAN will now turn towards the Come to our ETSI Balazs Bertenyi, RAN Chair called completion of the first phase of 5G it “an impressive achievement in a radio, Release 15, by June 2018. -
Edge Computing in Asia- Pacific, 2018 Rising Demand for Iot Deployments Driving the Adoption of Edge Computing Solutions
Frost Perspective on Edge Computing in Asia- Pacific, 2018 Rising demand for IoT deployments driving the adoption of edge computing solutions Global Digital Transformation Team at Frost & Sullivan November 2018 Table of Contents Overview 3 Adoption Analysis 8 Ecosystem Analysis 21 Last Word 40 Source: Frost & Sullivan 9AC2-72 2 2 Overview Defining Edge Computing The term edge computing refers to computing that pushes intelligence, data processing, analytics, and communication capabilities down to where the data originate, that is, at network gateways or directly at the endpoints. The aim is to reduce latency, ensure highly efficient networks operation as well as service delivery and offer an improved user experience. By extending computing closer to the data source, edge computing enables latency sensitive computing, offers greater business agility through better control and faster insights, lowers operating expenses, and results in more efficient network bandwidth support. Key Characteristics . On premises . Proximity . Real time . Wide geo-distribution Core Networks Endpoint Distributed Network Devices Gateways Centralized (Data Cloud Sources) Source: Frost & Sullivan 9AC2-72 4 Comparison – Edge versus Cloud Edge Computing Cloud Computing Target User Internet of Things (IoT) devices and enterprise users Enterprise application users Distinguishing characteristics are its proximity to end Distinguishing characteristics are virtualization, Data users and dense geographical distributions. It is based accessibility, flexibility and scalability. All of your Characteristic on the principle of isolation of user data that live on the data is not “physically” close to you. All data is edge. centralized within one or more data centers. Services are hosted in virtual servers, over the Services are hosted at the network edge or end internet and not your hard drive. -
Knowledge Integration in Smart Factories
Entry Knowledge Integration in Smart Factories Johannes Zenkert * , Christian Weber , Mareike Dornhöfer , Hasan Abu-Rasheed and Madjid Fathi Department of Electrical Engineering and Computer Science, Institute of Knowledge Based Systems and Knowledge Management, University of Siegen, 57076 Siegen, Germany; [email protected] (C.W.); [email protected] (M.D.); [email protected] (H.A.-R.); [email protected] (M.F.) * Correspondence: [email protected] Definition: Knowledge integration is well explained by the human–organization–technology (HOT) approach known from knowledge management. This approach contains the horizontal and vertical in- teraction and communication between employees, human-to-machine, but also machine-to-machine. Different organizational structures and processes are supported with the help of appropriate tech- nologies and suitable data processing and integration techniques. In a Smart Factory, manufacturing systems act largely autonomously on the basis of continuously collected data. The technical design concerns the networking of machines, their connectivity and the interaction between human and machine as well as machine-to-machine. Within a Smart Factory, machines can be considered as intelligent manufacturing systems. Such manufacturing systems can autonomously adapt to events through the ability to intelligently analyze data and act as adaptive manufacturing systems that consider changes in production, the supply chain and customer requirements. Inter-connected physical devices, sensors, actuators, and controllers form the building block of the Smart Factory, which is called the Internet of Things (IoT). IoT uses different data processing solutions, such as Citation: Zenkert, J.; Weber, C.; cloud computing, fog computing, or edge computing, to fuse and process data.