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Advanced IT-Based Future Sustainable Computing

Author

Listed:
  • Jong Hyuk Park

    (Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea)

  • Han-Chieh Chao

    (College of Electrical Engineering & Computer Science, National Ilan University, Yilan City, Yilan County 260, Taiwan)

Abstract

Future Sustainability Computing (FSC) is a novel research topic that deals with algorithms, procedures, and applications of information technologies for abundant life. In this Special Issue, we cover novel research and applications within the scope of sustainability computing dealing with hardware/software technologies, especially for frameworks and architectures. For example, topics include dynamic group management in Internet of Things (IoT); real-time video surveillance; security threats in Software Defined Network (SDN); real-time indoor Air-Quality level indicator; effectiveness of information systems security; load-balancing for inter-sensor convergence; neighbor discovery in sensor networks; transmission algorithm with Quality of Service (QoS) consideration; analysis of the relationship between Intrusion Detection System (IDS) alerts and darknet are included.

Suggested Citation

  • Jong Hyuk Park & Han-Chieh Chao, 2017. "Advanced IT-Based Future Sustainable Computing," Sustainability, MDPI, vol. 9(5), pages 1-4, May.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:5:p:757-:d:97652
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    References listed on IDEAS

    as
    1. Myeonggil Choi, 2016. "Leadership of Information Security Manager on the Effectiveness of Information Systems Security for Secure Sustainable Computing," Sustainability, MDPI, vol. 8(7), pages 1-21, July.
    2. Jungsuk Song & Younsu Lee & Jang-Won Choi & Joon-Min Gil & Jaekyung Han & Sang-Soo Choi, 2017. "Practical In-Depth Analysis of IDS Alerts for Tracing and Identifying Potential Attackers on Darknet," Sustainability, MDPI, vol. 9(2), pages 1-18, February.
    3. Yunsick Sung, 2016. "RSSI-Based Distance Estimation Framework Using a Kalman Filter for Sustainable Indoor Computing Environments," Sustainability, MDPI, vol. 8(11), pages 1-9, November.
    4. Hyungjoo Kim & Jungho Kang, 2016. "Dynamic Group Management Scheme for Sustainable and Secure Information Sensing in IoT," Sustainability, MDPI, vol. 8(10), pages 1-14, October.
    5. Sangil Choi & Gangman Yi, 2016. "Asymmetric Block Design-Based Neighbor Discovery Protocol in Sensor Networks," Sustainability, MDPI, vol. 8(5), pages 1-11, April.
    6. Hyun-Woo Kim & Jong Hyuk Park & Young-Sik Jeong, 2016. "Sustainable Load-Balancing Scheme for Inter-Sensor Convergence Processing of Routing Cooperation Topology," Sustainability, MDPI, vol. 8(5), pages 1-10, May.
    7. Yunsick Sung & Pradip Kumar Sharma & Erik Miranda Lopez & Jong Hyuk Park, 2016. "FS-OpenSecurity: A Taxonomic Modeling of Security Threats in SDN for Future Sustainable Computing," Sustainability, MDPI, vol. 8(9), pages 1-26, September.
    8. Jaejin Jang & Im Y. Jung, 2016. "Sustainable and Practical Firmware Upgrade for Wireless Access Point Using Password-Based Authentication," Sustainability, MDPI, vol. 8(9), pages 1-17, August.
    9. Jaewoon Lee & Dongho Kim & Han-Young Ryoo & Byeong-Seok Shin, 2016. "Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life," Sustainability, MDPI, vol. 8(5), pages 1-16, May.
    10. Sang-Hyong Kim & Kwan-Jong Yoo & Yoojae Won, 2017. "Transmission Algorithm with QoS Considerations for a Sustainable MPEG Streaming Service," Sustainability, MDPI, vol. 9(3), pages 1-13, March.
    11. Wei Song & Yifei Tian & Simon Fong & Kyungeun Cho & Wei Wang & Weiqiang Zhang, 2016. "GPU-Accelerated Foreground Segmentation and Labeling for Real-Time Video Surveillance," Sustainability, MDPI, vol. 8(10), pages 1-20, September.
    12. Jungho Kang & Kwang-Il Hwang, 2016. "A Comprehensive Real-Time Indoor Air-Quality Level Indicator," Sustainability, MDPI, vol. 8(9), pages 1-15, September.
    13. Xingquan Cai & Yufeng Gao & Mengxuan Li & Wei Song, 2016. "Infrared Human Posture Recognition Method for Monitoring in Smart Homes Based on Hidden Markov Model," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
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