ICN/NDN: Information Centric Networking is precisely that: an internet architecture that puts information at the center where it needs to be. ICN is an approach to evolve the Internet infrastructure away from a host-centric paradigm based on perpetual connectivity and the end-to-end principle, to a network architecture in which the focal point is “named information” (or content or data) per Wikipedia. ICN replaces the client-server model with a new publish-subscribe model. Evolving the network to an ICN will not only deliver much-needed efficiencies and performance improvements, but it will also align our networking architecture with perhaps the largest engine of information generation. Named Data Networking (NDN) is an entirely new architecture, but one whose design principles are derived from the successes of today’s Internet, reflecting our understanding of the strengths and limitations of the current Internet architecture, and one that can be rolled out through incremental deployment over the current operational Internet.
At HotICN2018, we have already invited most of the top ICN faculty, researchers and students worldwide as our organization members. It is definitely a great chance for ICN/NDN community people gathering together to discuss, social and exchange insights and information.
Cisco's 'Hybrid Information-Centric Networking' gets a workout at Verizon:
Last week, we noted the re-emergence of a sleeper technology, Information-Centric Networking (ICN). we've now learned that Cisco's been hard at work on it: Switchzilla has unveiled a trial implementation with Verizon. Cisco called its implementation a “hybrid ICN” implementation, based on software it acquired from long-time collaborator Xerox PARC in February.
Communicating names in ICN is the key technical challenge, and Cisco described its approach as deploying ICN “within IP”: “It preserves all features of ICN communication by encoding ICN names into IP addresses”. This approach, Cisco said in this February blog post, offers “transparent interconnection with standard IP networking equipment”, meaning users can adopt ICN without having to replace or retire network-layer devices like routers.
The carrier's veep for technology architecture and strategy Srini Kalapala was quoted as saying the test showed ICN could be deployed “with minimal existing IP infrastructure upgrades required” (Click here for the full news)
Blockchain: A blockchain, originally block chain, is a continuously growing list of records, called blocks, which are linked and secured using cryptography. Each block typically contains a cryptographic hash of the previous block, a timestamp and transaction data. By design, a blockchain is inherently resistant to modification of the data. Blockchain is the distributed trust network that the Internet always needed and never had, With blockchain, we can imagine a world in which contracts are embedded in digital code and stored in transparent, shared databases, where they are protected from deletion, tampering, and revision. Blockchain is a foundational technology: It has the potential to create new foundations for our economic and social systems, and its impact will be enormous.
At HotICN2018, we welcome researchers and engineers to submit their innovative academic papers covering various areas including distributed algorithms and systems, scalability and performance issues and mostly interested in industrial White Papers. Investors, learners and industrial solution seekers are all welcomed to attend.
Recently, the Blockchain technology has been a buzz topic with countless comments and discussion, even comes with “Midnight Sleepless Blockchain Wechat Group” and “Mutual Diss between Celebrities”, which floods into numerous onlookers with Bewilderment, anxiety, curiosity and exuberance. The concept and technology of Blockchain is deemed as complicated and mysterious to the majority, most of them is unable to recognize Bitcoin and Blockchain and figure out coin zone, chain zone and mine zone`, while the other pioneering majority take full use of the hotspot to conduct currency speculation and overseas ICO with zeal and expectation. The gradual understanding and acquaintance, along with the focus on the value and meaning of technology as well as distinct positive facet revealed in compliment articles published by mainstream media, such as, People's Daily, Xinhuanet and GMW, drives Prof. Kai Lei(General Chair of IEEE hotICN 2018) to share his feelings about Blockchain as a three-year Blockchain scholar naturally. (Click here for full artile)
Knowledge Graph (KG): In common sense, Knowledge Graph is a knowledge base integrated with the data mining/search engine for a visually appealing and intuitive graphical presentation of information related to queries. The Knowledge Graph was first known as a knowledge base used by Google and its services to enhance its search engine's results with information gathered from a variety of sources per Wikipedia. KGs come in different shapes and sizes, however they will follow a simple principle: organizing information in a structured way by explicitly describing the relations among entities. KG research is quite cutting-edge and requires large amount of interdisciplinary experts such as: Natural Language Processing, Artificial Intelligence/Deep Learning, Data Mining, Information retrieval and representation, fast parallel computing and systems, crossing disciplinary domain experience with finance, medical, social science and so on.
At HotICN2018, we invite researcher discuss how Knowledge Graph as defined are a crucial component of the future of the Web and have great potential for transformational change in data science and domain sciences. There are many various interesting problems and challenges we can discuss about: Where is the knowledge we need in Big Data? What is valuable knowledge and what is information garbage? How to extract the knowledge we need from the data structure? After obtaining knowledge, how can we express the acquired knowledge in the form of calculable form of computer? Because there are so many sources of knowledge, how can you combine knowledge from different sources? Then, in the process of computing based on knowledge, how can machines use knowledge to make rational reasoning, or make perceptual decisions or predictions?