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A Survey on 5G Enabled Multi-Access Edge Computing for Smart Cities: Issues and Future Prospects

  • Tufail, Ali;Namoun, Abdallah;Alrehaili, Ahmed;Ali, Arshad
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.107-118
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    • 2021
  • The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

EXECUTION TIME AND POWER CONSUMPTION OPTIMIZATION in FOG COMPUTING ENVIRONMENT

  • Alghamdi, Anwar;Alzahrani, Ahmed;Thayananthan, Vijey
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.137-142
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    • 2021
  • The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

Design and Implementation of Real Time Device Monitoring and History Management System based on Multiple devices in Smart Factory (스마트팩토리에서 다중장치기반 실시간 장비 모니터링 및 이력관리 시스템 설계 및 구현)

  • Kim, Dong-Hyun;Lee, Jae-min;Kim, Jong-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.124-133
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    • 2021
  • Smart factory is a future factory that collects, analyzes, and monitors various data in real time by attaching sensors to equipment in the factory. In a smart factory, it is very important to inquire and generate the status and history of equipment in real time, and the emergence of various smart devices enables this to be performed more efficiently. This paper proposes a multi device-based system that can create, search, and delete equipment status and history in real time. The proposed system uses the Android system and the smart glass system at the same time in consideration of the special environment of the factory. The smart glass system uses a QR code for equipment recognition and provides a more efficient work environment by using a voice recognition function. We designed a system structure for real time equipment monitoring based on multi devices, and we show practicality by implementing and Android system, a smart glass system, and a web application server.

Implementation of a Sensor Network in a Welding Workplace Based on IoT for Smart Shipyards (스마트 조선소를 위한 사물인터넷 기반 용접 작업장 센서네트워크 구축)

  • Kim, Hyun Sik;Lee, Gi Seung;Kang, Seog Geun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.433-439
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    • 2021
  • In this paper, we propose a method to implement an IoT-based sensor network for each workplace of a shipyard. Here, at the most common welding workplace in shipyards, the shipbuilding blocks are used as a communication medium to transmit information such as the worker's location, welding progress, and working hour to a server using LoRa and powerline communication. To achieve the data communication, inductive couplers and hybrid modems have been manufactured and installed on wire feeders and pin jigs to establish a sensor network. As a result of field test, the proposed system shows a success rate of data transmission and a rate of successful recognition of worker's location of about 98% or more. In addition, the process management system platform can record and display the work process data generated at the field in real time. The proposed system can be a starting point for enhancing the competitiveness of Korean shipbuilding industry through the establishment of a smart shipyard.

Comparison of Home Automation System Using IPV-4 and IPV-6 Based On Mitigate Reconnaissance Attacks

  • Ali, Muhammad Shujat;Siddiq, Imran;Faisal, Abdullah;Awan, Muhammad Zubair
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.341-347
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    • 2022
  • This research is designed to help and offer hold up to complete the requirements of aged and disable in a home. The control approach and the tone approach are used to manage the house appliances. The major organize system implementation in technology of wireless to offer distant contact from a phone Internet Protocol connectivity for access and calculating strategy and appliance remotely. The planned system no need a committed server PC with value of parallel systems and offers a new communication-protocol to observe and control a house environment with more than just the switch functionality. To express the possibility and efficiency of this system, devices like as lights switches, power plugs, and motion-sensors have been included with the planned home control system and supply more security manage on the control with low electrical energy activate method. The rank of switches is corresponding in all this control system whereby all user interfaces indicate the real time existing status. This system planned to manage electrical-appliances and devices in house with reasonably low cost of design, user friendly interface, easily install and provide high security. Research community generally specified that the network "Reconnaissance Attacks" in IPv6 are usually impossible due to they will take huge challenge to carry out address scanning of 264 hosts in an IPv6 subnet."It being deployed of IPv6 shows that it definitely enhances security and undermines the probability". This research of the IPv6 addressing-strategies at present utilizes and planned a new strategy and move toward to "mitigate reconnaissance attacks".

Development of KEPCO e-IoT Standard Type oneM2M Gateway for Efficient Management of Energy Facilities (에너지 설비의 효율적 관리를 위한 한전 e-IoT 표준형 oneM2M Gateway 개발)

  • Sim, Hyun;Kim, Yo-Han
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1213-1222
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    • 2021
  • This study is a digitalization study based on ICT technology as part of the development of innovative technologies in the new energy industry as a 2050 carbon-neutral policy. It is the development of an oneM2M-based IoT server platform that can be integrated and managed in conjunction with the external interface of each energy facility. It analyzes KEPCO's e-IoT standard specifications through the Power Research Institute's 'SPIN' and develops representative standards, LWM2M and oneM gateway platforms. OneM2M secures and analyzes the recently announced standard for Release 2 instead of the existing Release 1. In addition, the e-IoT standard oneM2M platform is developed based on R2. In addition, it selects the specifications for e-IoT gateway devices that can sufficiently implement KEPCO's e-IoT standards. In addition, a technology and system for developing a high-performance gateway device that considers future scalability were proposed.

Development of a System for Field-data Collection Transmission and Monitoring based on Low Power Wide Area Network (저전력 광역통신망 기반 현장데이터 수집 전송 및 모니터링 시스템 개발)

  • Yeong-Tae, Ju;Jong-Sil, Kim;Eung-Kon, Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1105-1112
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    • 2022
  • Field data monitoring systems such as renewable energy generation and smart farm integrated control are developing from PC and server to mobile first, and various wireless communication and application services have emerged with the development of IoT technology. Low-power wide-area networks are services optimized for low-power, low-capacity, and low-speed data transmission, and data collected in the field is transmitted to designated storage servers or cloud-based data platforms, enabling data monitoring. In this paper, we implement an IoT repeater that collects field data with a single device and transmits it to a wireless carrier cloud data flat using a low-power wide-area network, and a monitoring app using it. Using this, the system configuration is simpler, the cost of deployment and operation is lower, and effective data accumulation is possible.

IoT Collaboration System Based on Edge Computing for Smart Livestock System (스마트 축사를 위한 에지 컴퓨팅 기반 IoT 협업 시스템)

  • Ahn, Chi-Hyun;Lee, Hyungtak;Chung, Kwangsue
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.258-264
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    • 2022
  • The smart farm for livestock, in which information and communication technology (ICT) is combined with livestock farm, is mostly based on the cloud computing paradigm. A cloud-based smart livestock farm has disadvantages such as increased response time, burden on cloud resource caused by the increased number of IoT sensors, traffic burden on the network, and lack of failure resilience mechanisms through collaboration with adjacent IoT devices. In this paper, with these problems in mind, we propose an IoT collaboration system based on edge computing. By using the relatively limited computing resources of the edge device to share the cloud's web server function, we aim to reduce the cloud's resources needed and improve response time to user requests. In addition, through the heartbeat-based failure recovery mechanism, IoT device failures were detected and appropriate measures were taken.

Research on Science DMZ scalability for the high performance research data networking (연구데이터의 고성능 네트워킹을 위한 Science DMZ 확장성 연구)

  • Lee, Chankyun;Jang, Minseok;Noh, Minki;Seok, Woojin
    • KNOM Review
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    • v.22 no.2
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    • pp.22-28
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    • 2019
  • A Science DeMilitarized Zone (DMZ) is an optimized network technology tailored to research data nature. The Science DMZ guarantees end-to-end network performance by forming a closed research network without redundant networking and security devices for the authorized researchers. Data Transfer Node (DTN) is an essential component for the high performance and security of the Science DMZ, since only transfer functions of research data are allowed to the DTN without any security- and performance-threatening functions such as commercial internet service. Current Science DMZ requires per-user DTN server installation which turns out a scalability limitation of the networks in terms of management overhead, entry barrier of the user, and networks-wise CAPEX. In order to relax the aforementioned scalability issues, this paper suggests a centralized DTN design where end users in a group can share the centralized DTN. We evaluate the effectiveness of the suggested sharable DTN design by comparing CAPEX against to that of current design with respect to the diverse network load and the state-of-the-art computing machine.

Development of Cloud based Data Collection and Analysis for Manufacturing (클라우드 기반의 생산설비 데이터 수집 및 분석 시스템 개발)

  • Young-Dong Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.216-221
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    • 2022
  • The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.