Distributed computing system with dual independent communications paths between computers and employing split tokens

This is a distributed computing system providing flexible fault tolerance; ease of software design and concurrency specification; and dynamic balance of the loads. The system comprises a plurality of computers each having a first input/output interface and a second input/output interface for interfacing to communications networks each second input/output interface including a bypass for bypassing the associated computer. A global communications network interconnects the first input/output interfaces for providing each computer the ability to broadcast messages simultaneously to the remainder of the computers. A meshwork communications network interconnects the second input/output interfaces providing each computer with the ability to establish a communications link with another of the computers bypassing the remainder of computers. Each computer is controlled by a resident copy of a common operating system. Communications between respective ones of computers is by means of split tokens each having a moving first portion which is sent from computer to computer and a resident second portion which is disposed in the memory of at least one of computer and wherein the location of the second portion is part of the first portion. The split tokens represent both functions to be executed by the computers and data to be employed in the execution of the functions. The first input/output interfaces each include logic for detecting a collision between messages and for terminating the broadcasting of a message whereby collisions between messages are detected and avoided

The Legacy of the Federal Communications Commission’s Computer Inquiries

The FCC and the computer industry have learned much in the 35 years since the agency first began to regulate computer networks. Safeguards were imposed on common carriers for the benefit of the networks. This Article examines the so-called Computer Inquiries and how they have repeatedly re-examined and redefined the nature of the regulatory treatment of computer networks over communications networks. The Author reviews Computer I, in which the FCC first attempted to divide the world technologically between computers that ran communications networks ( pure communications ) and computers at the end of telephone lines with which people interacted ( pure data processing ). In Computer II, the FCC reclassified the computer world on the basis of the services provided-basic or enhanced. The FCC\u27s third and final attack on the issue, Computer III, retained the conceptual framework, but redetermined how the policy objectives would be implemented. The Author concludes that the actions taken by the FCC may not have invented the Internet, but they certainly contributed to its success

The Legacy of the Federal Communications Commission’s Computer Inquiries

The FCC and the computer industry have learned much in the 35 years since the agency first began to regulate computer networks. Safeguards were imposed on common carriers for the benefit of the networks. This Article examines the so-called Computer Inquiries and how they have repeatedly re-examined and redefined the nature of the regulatory treatment of computer networks over communications networks. The Author reviews Computer I, in which the FCC first attempted to divide the world technologically between computers that ran communications networks ( pure communications ) and computers at the end of telephone lines with which people interacted ( pure data processing ). In Computer II, the FCC reclassified the computer world on the basis of the services provided-basic or enhanced. The FCC\u27s third and final attack on the issue, Computer III, retained the conceptual framework, but redetermined how the policy objectives would be implemented. The Author concludes that the actions taken by the FCC may not have invented the Internet, but they certainly contributed to its success

Delayed commutation in quantum computer networks

In the same way that classical computer networks connect and enhance the capabilities of classical computers, quantum networks can combine the advantages of quantum information and communications. We propose a non-classical network element, a delayed commutation switch, that can solve the problem of switching time in packet switching networks. With the help of some local ancillary qubits and superdense codes we can route the information after part of it has left the network node.Comment: 4 pages. 4 figures. Preliminar versio

DNET: A communications facility for distributed heterogeneous computing

This document describes DNET, a heterogeneous data communications networking facility. DNET allows programs operating on hosts on dissimilar networks to communicate with one another without concern for computer hardware, network protocol, or operating system differences. The overall DNET network is defined as the collection of host machines/networks on which the DNET software is operating. Each underlying network is considered a DNET 'domain'. Data communications service is provided between any two processes on any two hosts on any of the networks (domains) that may be reached via DNET. DNET provides protocol transparent, reliable, streaming data transmission between hosts (restricted, initially to DECnet and TCP/IP networks). DNET also provides variable length datagram service with optional return receipts

Telecommunications media for the delivery of educational programming

The technical characteristics of various telecommunications media are examined for incorporation into educational networks. FM radio, AM radio, and VHF and UHF television are considered along with computer-aided instruction. The application of iteration networks to library systems, and microform technology are discussed. The basic principles of the communications theory are outlined, and the operation of the PLATO 4 random access system is described

Geometric deep learning: going beyond Euclidean data

Many scientific fields study data with an underlying structure that is a non-Euclidean space. Some examples include social networks in computational social sciences, sensor networks in communications, functional networks in brain imaging, regulatory networks in genetics, and meshed surfaces in computer graphics. In many applications, such geometric data are large and complex (in the case of social networks, on the scale of billions), and are natural targets for machine learning techniques. In particular, we would like to use deep neural networks, which have recently proven to be powerful tools for a broad range of problems from computer vision, natural language processing, and audio analysis. However, these tools have been most successful on data with an underlying Euclidean or grid-like structure, and in cases where the invariances of these structures are built into networks used to model them. Geometric deep learning is an umbrella term for emerging techniques attempting to generalize (structured) deep neural models to non-Euclidean domains such as graphs and manifolds. The purpose of this paper is to overview different examples of geometric deep learning problems and present available solutions, key difficulties, applications, and future research directions in this nascent field