• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.8
• /
• pp.1654-1660
• /
• 2004

In this paper, we describes the design and implementation of LonWorks communication module for distributed intelligent control using LonWorks technology of Echelon. LonWorks communication module can be divided hardware and firmware. First, hardwares is divided into microcontroller attaching sensors and LonWorks components for working together control network and data network. Hardwares are consisted of neuron chip, microcontroller, transceiver, LONCard. Second, operating firmware is realized with neuron C using NodeBulider 3.0 development tool. Produced and implemented LonWorks communication module is pretested using LTM-10A, Gizmo 4 I/O board, parallel I/O Interface. For field test, microcontroller module part is tested by HyperTerminal, communication procedure in data network is certified by transmitting and receiving short message using LonMaker for Windows tool. Herewith, LON technology is based on network communication technique using LonWorks.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.11B
• /
• pp.707-721
• /
• 2005

Recently, there has been a dramatic increase in data traffic, driven primarily by the explosive growth of the Internet. Optical networking is believed as a key solution to keep up with the growth, thus, the most pressing issue is how to manage and control large optical networks. Currently, provisioning end-to-end connections across the transport network has involved the network operator, leading to long provisioning times in an era when customers are demanding shorter provisioning time. To address this critical issue, new control intelligence is being studied for use within optical networks to shorten provisioning time. Both the IETF and the ITU-T have been aggressively defining many aspects of a control plane for the next generation convergence transport network. Basically, they are based on the distributed control scheme. In this Paper, we suey the applicability of the centralized control scheme for the provisioning control of optical transport network to utilize its inherent advantages over the distributed control scheme. We discuss new central control architecture, and control procedure. Also, we examine the applicability of the existing IETF routing and signaling protocols to the new control concepts, and then, we propose the additional routing and signaling information elements.

• Proceedings of the KIEE Conference
• /
• 2002.11b
• /
• pp.241-243
• /
• 2002

Recently, great efforts are concentrated on the autonomous, adaptive protection schemes with advanced artificial intelligence and digital technology. It is highly required for a next generation protective system not only to detect and to clear a fault, but also to fit itself to the changing environment. In this paper it is suggested an evaluation method for the protection ability of a protective system in a distributed system. The suggested method is of bottom-up scheme, in other words, protection ability is estimated from the lowest level of parameters in each protective devices to the highest level of the whole protective system. This feature makes it possible to evaluate the protection ability either for the protective device(or a system), or for a protected system. And, in addition, it is enabled that the protectability concept can be applied in the design stage of a protective system for a distribution network. The proposed method is applied to a simple distributed network to show its effectiveness.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.2
• /
• pp.371-378
• /
• 2002

In the resent years, the term mobile agent is probably one of the most overused words in many appliable areas of distributed open systems as electronic commerce and electronic data interchange, and it has very different meanings in the area of artificial intelligence, network management, or distributed systems. However, the use of mobile agent adds significant problems, primarily in the area of EC/EDI. Therefore it is very important to control the roaming agents to keep one's privacy or property in distributed open networks. The surge in secure intranets for commercial applications provides a robust, secure environment to which trading partners can increasingly entrust their interactions to some mobile agents. In this paper, we introduce a mechanism to protect mobile agent itself from the malicious server he is visiting and also we introduce a mechanism to protect vital resources of the open systems as internet.

• International Journal of Advanced Culture Technology
• /
• v.2 no.2
• /
• pp.7-10
• /
• 2014

In order to develop smart grid communications infrastructure, a high level of interconnectivity and reliability among its nodes is required. Sensors, advanced metering devices, electrical appliances, and monitoring devices, just to mention a few, will be highly interconnected allowing for the seamless flow of data. Reliability and security in this flow of data between nodes is crucial due to the low latency and cyber-attacks resilience requirements of the Smart Grid. In particular, Artificial Intelligence techniques such as Fuzzy Logic, Bayesian Inference, Neural Networks, and other methods can be employed to enhance the security gaps in conventional IDSs. A distributed FPGA-based network with adaptive and cooperative capabilities can be used to study several security and communication aspects of the smart grid infrastructure both from the attackers and defensive point of view. In this paper, the vital issue of security in the smart grid is discussed, along with a possible approach to achieve this by employing FPGA based Radial Basis Function (RBF) network intrusion.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.12
• /
• pp.984-990
• /
• 2005

The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.

• ETRI Journal
• /
• v.45 no.5
• /
• pp.735-745
• /
• 2023

This paper surveys recent multiagent reinforcement learning and neural Myerson auction deep learning efforts to improve mobility control and resource management in autonomous ground and aerial vehicles. The multiagent reinforcement learning communication network (CommNet) was introduced to enable multiple agents to perform actions in a distributed manner to achieve shared goals by training all agents' states and actions in a single neural network. Additionally, the Myerson auction method guarantees trustworthiness among multiple agents to optimize rewards in highly dynamic systems. Our findings suggest that the integration of MARL CommNet and Myerson techniques is very much needed for improved efficiency and trustworthiness.

• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.12
• /
• pp.291-306
• /
• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Intelligence and Information Systems
• /
• v.14 no.4
• /
• pp.19-30
• /
• 2008

Semantic heterogeneity should be overcome to support automated information sharing process between information systems in ontology-based distributed environments. To do so, traditional approaches have been based on explicit mapping between ontologies from human experts of the domain. However, the manual tasks are very expensive, so that it is difficult to obtain ontology mappings between all possible pairs of information systems. Thereby, in this paper, we propose a system to make the existing mapping information sharable and exchangeable. It means that the proposed system can collect the existing mapping information and aggregate them. Consequently, we can estimate the ontology mappings in an indirect manner. In particular, this paper focuses on query propagation on the distributed networks. Once we have the indirect mapping between systems, the queries can be efficiently transformed to automatically exchange knowledge between heterogeneous information systems.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.179-188
• /
• 2018

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.