Data Communications Architecture Research Articles

An Improved Pairing-Free Ciphertext Policy Framework for IoT

Internet of Things (IoT) enables devices to get connected to the internet. Once they are connected, they behave as smart devices thereby releasing sensitive data periodically. There is a necessity to preserve the confidentiality and integrity of this data during transmission in public communication channels and also permitting only legitimate users to access their data A key challenge of smart networks is to establish a secure end-to-end data communication architecture by addressing the security vulnerabilities of data users and smart devices. The objective of this research work is to create a framework encompassing Ciphertext policy Attribute-based Encryption scheme using block encryption and BLAKE hashing technique. An improved Pairing-Free-Ciphertext policy Attribute-based encryption algorithm has been developed to overcome the aforementioned challenges. Further, a comparative study has been performed between the proposed scheme and the different encryption algorithms. It is found that the proposed scheme scores well over the already existing schemes. The scheme is evaluated in terms of execution time and communication overhead. The robustness of the proposed scheme is also analyzed from the perspective of several security goals.

Large graph convolutional network training with GPU-oriented data communication architecture

Graph Convolutional Networks (GCNs) are increasingly adopted in large-scale graph-based recommender systems. Training GCN requires the minibatch generator traversing graphs and sampling the sparsely located neighboring nodes to obtain their features. Since real-world graphs often exceed the capacity of GPU memory, current GCN training systems keep the feature table in host memory and rely on the CPU to collect sparse features before sending them to the GPUs. This approach, however, puts tremendous pressure on host memory bandwidth and the CPU. This is because the CPU needs to (1) read sparse features from memory, (2) write features into memory as a dense format, and (3) transfer the features from memory to the GPUs. In this work, we propose a novel GPU-oriented data communication approach for GCN training, where GPU threads directly access sparse features in host memory through zero-copy accesses without much CPU help. By removing the CPU gathering stage, our method significantly reduces the consumption of the host resources and data access latency. We further present two important techniques to achieve high host memory access efficiency by the GPU: (1) automatic data access address alignment to maximize PCIe packet efficiency, and (2) asynchronous zero-copy access and kernel execution to fully overlap data transfer with training. We incorporate our method into PyTorch and evaluate its effectiveness using several graphs with sizes up to 111 million nodes and 1.6 billion edges. In a multi-GPU training setup, our method is 65--92% faster than the conventional data transfer method, and can even match the performance of all-in-GPU-memory training for some graphs that fit in GPU memory.

Architectural Enhancement of Network on Chip

This paper gives a new architectural design suggestion of NoC, with efficient way of communication. Firstly, to create a serial data communication architecture in competence with the existing widely used parallel form of data transmission and reception [1]. Secondly to enable simultaneous transmission and reception between more than one module at the same time. Thirdly to create the architecture that is modifiable as per the need of user. The theoretical data rate calculated was 300 MBps. The throughput we achieved after the completion is 250MBps.

Impedance Control Self-Calibration of a Collaborative Robot Using Kinematic Coupling

This paper presents a closed-loop calibration approach using impedance control. The process is managed by a data communication architecture based on open-source tools and designed for adaptability. The calibration procedure uses precision spheres and a kinematic coupling standard machine tool components, which are suitable for harsh industrial environments. As such, the required equipment is low cost (approximately group-separator = , 2000 [$]USD), robust, and is quick to set up, especially when compared to traditional calibration devices. As demonstrated through an experimental study and validated with a laser tracker, the absolute accuracy of the KUKA LBR iiwa robot was improved to a maximum error of 0 . 990 , representing a 58.4% improvement when compared to the nominal model. Further testing showed that a traditional calibration using a laser tracker only improved the maximum error by 58 μ m over the impedance control approach.

Water Quality Monitoring Using Wireless Sensor Networks

Water is essential for human survival. Although approximately 71% of the world is covered in water, only 2.5% of this is fresh water; hence, fresh water is a valuable resource that must be carefully monitored and maintained. In developing countries, 80% of people are without access to potable water. Cholera is still reported in more than 50 countries. In Africa, 75% of the drinking water comes from underground sources, which makes water monitoring an issue of key concern, as water monitoring can be used to track water quality changes over time, identify existing or emerging problems, and design effective intervention programs to remedy water pollution. It is important to have detailed knowledge of potable water quality to enable proper treatment and also prevent contamination. In this article, we review methods for water quality monitoring (WQM) from traditional manual methods to more technologically advanced methods employing wireless sensor networks (WSNs) for in situ WQM. In particular, we highlight recent developments in the sensor devices, data acquisition procedures, communication and network architectures, and power management schemes to maintain a long-lived operational WQM system. Finally, we discuss open issues that need to be addressed to further advance automatic WQM using WSNs.

A Bayesian paradigm for aircraft operational capability assessment and improved fault diagnostics

In recent years, Bayesian networks have been drawing attention of the industrial and research community especially in the field of diagnostics for the reasoning capabilities they offer under conditions of uncertainty.Given the system of interest, a Bayesian network represents a graphical model of the system itself, in which the different players are linked to each other through probabilistic and causal relations. If the model is queried with appropriate statistical techniques, the whole approach can present several advantages over other data analysis methods. Among the others: 1) the approach can provide outputs even if some entries to the model are missing, due to the above mentioned dependencies between the players of the system; 2) the approach represents an ideal environment to include prior knowledge during the building up of the model, given the causal and probabilistic semantics; 3) a Bayesian network provides the possibility to learn causal relationships and gives therefore the possibility to improve the domain knowledge.Airbus Defence and Space has been working on improving the aircraft diagnostics capabilities at component, sub-system and system level in terms of fault detection and isolation. The focus has been also to develop means for reasoning about the remaining operational and functional capabilities of the aircraft.The initial outcomes have been tested on a simulation platform featuring a Data Acquisition Processing Unit, various computing nodes, on which the different aircraft systems (like the fuel system, the hydraulic system, the actuation systems, etc…) run. The data communication architecture of the platform is based on OSA-CBM (Open System Architecture for Condition-Based Maintenance).Initial objectives of the project are: 1) to demonstrate the feasibility of integration of the concept within the above described simulation framework; 2) to develop means to allow an easy and structured translation of the system engineer knowledge in terms of a Bayesian network with associated conditional probabilities; 3) to provide a modular architecture for the concept facilitating effective coordination between the development-departments and efficient development and maintenance of the software and 4) to prove the scalability of the concept (i.e. applicability to systems of different sizes and reasoning on different levels from component to system level).The candidate systems selected for the proof of concept are the fuel and the hydraulic systems of a generic aircraft. The results obtained so far look promising with respect to the above mentioned objectives of the project.

The HAMSTER Data Communication Architecture for Unmanned Aerial, Ground and Aquatic Systems

This paper presents HAMSTER, the HeAlthy, Mobility and Security based data communication archiTEctuRe. HAMSTER is designed for Unmanned Vehicles and addresses mainly three types of communications: machine-to-machine, machine-to-infrastructure and internal machine communications. It is divided into three main versions: Flying HAMSTER (for aerial systems), Running HAMSTER (for terrestrial systems) and Swimming HAMSTER (for aquatic systems). Every version of such architecture is also equipped with Sphere and Nimble. Sphere deals with Safety & Security aspects regarding communication, components “health” and modules authentication. Nimble is aimed at increasing the overall mobility in such scenarios, strongly actuating with inherent communications of each application field. This paper details every aspect of HAMSTER and presents, as a plus at the end, two case studies: the first one consists of an evaluation of five communications schemes for internal communications in airplanes; the second one is a cryptographic evaluation of two Elliptic Curve Cryptography algorithms.

The ON-TIME real-time railway traffic management framework: A proof-of-concept using a scalable standardised data communication architecture

Automatic real-time control of traffic perturbations has recently become a central issue for many European railway infrastructure managers. The aim is to make use of mathematical algorithms to maintain the required service availability during unplanned disturbances to operations. In the literature many tools for real-time traffic control are proposed, but their effects on traffic have never been studied neither in real life nor in fully realistic simulation environments. We can mention only a few pilot tests and a unique installation in the Lötschberg Base tunnel in Switzerland, which uses a replanning framework that is generally applicable but does not consider a standard data communication format. Standardisation of railway data is instead one of the main requirements of the European Railway Traffic Management System (ERTMS) to enable traffic interoperability across different countries along the Trans-European Transport Network (TEN-T). Following this direction, this paper introduces one of the outputs of the European project ON-TIME: a framework for the automatic real-time management of railway traffic, designed for being standard and interoperable across different European railways. We make use of a web-based Service-Oriented Architecture to ensure scalability and flexibility of application. A standard railML interface is used for the input/output data of the modules, allowing immediate applicability of the framework to any network having a railML representation. A proof-of-concept is provided where the framework is tested in a closed-loop with the simulation environment HERMES for perturbed traffic scenarios on different networks in the UK, the Netherlands and Sweden. Tests are performed for two different replanning algorithms (ROMA and RECIFE) used for the automatic detection and optimised resolution of train conflicts. The two algorithms are compared on the test case in Sweden. Results show that the design of the proposed framework is effective in managing traffic perturbations and is extendible to real-life systems.

Distributed Agent-Based Computing in Material-Embedded Sensor Network Systems With the Agent-on-Chip Architecture

Distributed material-embedded systems like sensor networks integrated in sensorial materials require new data processing and communication architectures. Reliability and robustness of the entire heterogeneous environment in the presence of node, sensor, link, data processing, and communication failures must be offered, especially concerning limited service of material-embedded systems after manufacturing. In this paper, multiagent systems with state-based mobile agents are used for computing in unreliable mesh-like networks of nodes, usually consisting of a single microchip, introducing a novel design approach for reliable distributed and parallel data processing on embedded systems with static resources. An advanced high-level synthesis approach is used to map the agent behavior to multiagent systems implementable entirely on microchip-level supporting agent-on-chip (AoC) processing architectures. The agent behavior, interaction, and mobility are fully integrated on the microchip using a reconfigurable pipelined communicating process architecture implemented with finite-state machines and register-transfer logic. The agent processing architecture is related to Petri Net token processing. A reconfiguration mechanism of the agent processing system achieves some degree of agent adaptation and algorithmic selection. The agent behavior, interaction, and mobility features are modeled and specified with an activity-based agent behavior programming language. Agent interaction and communication is provided by a simple tuple-space database implemented on node level and signals providing remote inter-node level communication and interaction.

Distributed computing and reliable communication in sensor networks using multi-agent systems

There is a growing demand for robust distributed computing and systems in sensor networks. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. The focus of the application scenario lies on sensor networks and low-power, resource-aware single System-On-Chip designs, i.e., for use in sensor-equipped technical structures and materials. We propose and compare two different data processing and communication architectures for the implementation of mobile agents in sensor networks consisting of single microchip low-resource nodes. Furthermore, a reliable smart communication protocol for incomplete and irregular networks are introduced. Two case studies show the suitability of agent-based approaches for distributed computing.

Communications Architecture of the Liquid Robotics Wave Glider

This paper describes the data communications architecture for the Liquid Robotics Wave Glider and some of the motivations for the design as well as how the architecture evolved over time.

A WWW-based multimedia center for learning data communications — phase 1

The use of multimedia in education has become an important element to improve the quality of education and to reduce the cost of the educational system. In addition, the students got the benefit of learning and understanding the material better than in the conventional way. In this work, a learning package called "Data Communications Learning Center" (DCLC) has been developed and tested. The main objective of this center is to help university students and others to learn data communication concepts, architectures and operations. The center is a world wide web (www) based, and it allows any student that uses a standard modem for the Internet access to use our center. The center has been developed to be easy to use. The initial evaluation of the center examined by a few students have complemented that the center has improved their understanding to some data communication concepts which the center already supports. Although our intention is to support one topic at the first stage of this project, one can easily add other topics to the center. Any professor who is willing to put his course in the center can achieve this without any prior knowledge about the internal design of the center.

Sandia's Terminal Switching Network and Fiber Optic Loop

At Sandia National Laboratories, a data communications architecture — whose major elements include a fiber loop, technical control centers, and a terminal switching network — provides security for data communications. The optical fiber loop supplies the advantages of high bandwidth, negligible crosstalk, immunity to interference, and resistance to tapping. The technical control centers, as elements on the fiber loop, focus regional communications and simplify distribution over the loop. The terminal switching network uses the fiber loop and the control centers' distribution and control capabilities to layer management and security control onto the Sandia network. By designing data communications around this set of trusted elements, Sandia has implemented a robust, secure system without sacrificing performance or responsiveness.

Military requirements for packet-switched networks and their implications for protocol standardization

This paper outlines the nature of the military requirements for packet-switched data communications and contrasts these requirements with those of commercial, industrial and private users served by common carrier public packet-switched data networks. Current US Department of Defense policy on the use of commercial standards in defense systems is reviewed. Deficiencies in existing standards for military applications are identified and implications for the development of a suitable military data communications architecture are drawn. A strategy of military standardization is outlined which adopts commercial standards where they apply and supplements these with special military standards as needed to satisfy unique military requirements. The thesis of this paper is illustrated by a discussion of the applicability of the CCITT X.25 protocol standard to military communications.

The Throughput of Packet Broadcasting Channels

Packet broadcasting is a form of data communications architecture which can combine the features of packet switching with those of broadcast channels for data communication networks. Much of the basic theory of packet broadcasting has been presented as a byproduct in a sequence of papers with a distinctly practical emphasis. In this paper we provide a unified presentation of packet broadcasting theory. In Section II we introduce the theory of packet broadcasting data networks. In Section III we provide some theoretical results dealing with the performance of a packet broadcasting network when the users of the network have a variety of data rates. In Section IV we deal with packet broadcasting networks distributed in space, and in Section V we derive some properties of power-limited packet broadcasting channels, showing that the throughput of such channels can approach that of equivalent point-to-point channels.