The next generation internet initiative

Digital transformation is pushing all market sectors to level up their digital capabilities to better serve customers and improve the user experience. The European Commission launched in 2016 the Next Generation Internet (NGI) initiative as part of the DSM strategy. NGI includes a number of different – but always interrelated – emerging technologies in the following focus areas: artificial intelligence and autonomous machines, blockchains and distributed ledgers, big data, Internet of Things, 5G, cybersecurity and privacy technologies, cloud and edge computing, and open data. As for cooperation in the field of Information and Communications Technology, Europe and the United States should seek a joint framework to expand efforts in new emerging technologies, while preserving common principles around a comprehensive EU–US digital economy dialogue. The NGI Initiative is an important opportunity to radically rethink the way the Internet works today, and more human-focused narratives are needed more than ever

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

An Optimal Algorithm For Mutual Exclusion In . . .

An algorithm is proposed that creates mutual exclu-sion in a computer network whose nodes communicate only by messages and do not share memory. The algo-rithm sends only 2*(N- 1) messages, where N is the number of nodes in the network per critical section invocation. This number of messages i at a minimum if parallel, distributed, symmetric control is used; hence, the algorithm is optimal in this respect. The time needed to achieve mutual exclusion is also minimal under some general assumptions. As in Lamport's "bakery algorithm, " unbounded se-quence numbers are used to provide first-come first-served priority into the critical section. It is shown that the number can be contained in a fixed amount of memory by storing it as the residue of a modulus. The number of messages required to implement he exclusion can be reduced by using sequential node-by-node processing, by using broadcast message techniques, or by sending infor-mation through timing channels. The "readers and writers " problem is solved by a simple modification of the algorithm and the modifications necessary to make the algorithm robust are described. Key Words and Phrases: concurrent programming, critical section, distributed algorithm, mutual exclusion

Editor An Optimal Algorithm for Mutual Exclusion in Computer Networks

An algorithm is proposed that creates mutual exclu-sion in a computer network whose nodes communicate only by messages and do not share memory. The algo-rithm sends only 2*(N- 1) messages, where N is the number of nodes in the network per critical section invocation. This number of messages is at a minimum if parallel, distributed, symmetric control is used; hence, the algorithm is optimal in this respect. The time needed to achieve mutual exclusion is also minimal under some general assumptions. As in Lamport's "bakery algorithm, " unbounded se-quence numbers are used to provide first-come first-served priority into the critical section. It is shown that the number can be contained in a fixed amount of memory by storing it as the residue of a modulus. The number of messages required to implement the exclusion can be reduced by using sequential node-by-node processing, by using broadcast message techniques, or by sending infor-mation through timing channels. The "readers and writers " problem is solved by a simple modification of the algorithm and the modifications necessary to make the algorithm robust are described. Key Words and Phrases: concurrent programming, critical section, distributed algorithm, mutual exclusion

Oral History Project - Mid-Level Networks Discussion (November 28, 2007)

Panelists discuss the creation of campus networks and the subsequent development of regional mid-level networks as university supercomputers began to become interconnected with each otherhttp://deepblue.lib.umich.edu/bitstream/2027.42/96223/1/NSFNET-Mid-Levels.m4