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Resource-Efficient Deep Packet Inspection and Dashboard for Activity and Energy Sensing Supporting Eco-Friendly ICT Infrastructure.

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Bibliographic Details
Title: Resource-Efficient Deep Packet Inspection and Dashboard for Activity and Energy Sensing Supporting Eco-Friendly ICT Infrastructure.
Authors: Harwahyu, Ruki, Kurnia, Abdul Fikih, Suryanegara, Muhammad
Source: International Journal of Technology; 2025, Vol. 16 Issue 6, p2062-2083, 22p
Subject Terms: DEEP packet inspection (Computer security), ENERGY consumption, INTERNET security, DASHBOARDS (Management information systems), ELECTRONIC data processing, COMPUTER network monitoring, INTERNET of things, GREEN technology
Abstract: An organization typically has various enterprise apps and Internet of Things (IoT) systems. The usages of these systems are typically well reflected by the packets transmitted to the network. This paper presents a unique approach to strive for energy savings in organizations by exploiting fact observables in networks. DPI is employed to dissect passing network packets and predict their protocols. Data Plan Development Kit (DPDK) is adopted to push the hardware limit and speed up the inspection. A webbased customizable dashboard is incorporated to allow human observation according to the characteristics of the organization. Several API endpoints are provided to extend the functionalities, such as ML/AI integration. An energy-sensing model is proposed to measure the energy usage or generation by various connected systems, such as IoTs, smart ACs, and solar panel controllers. The results demonstrate that the working prototype improves processing efficiency, enabling the system to handle large volumes of data up to 10GB, achieving an average packet processing efficiency of 99.991%. The system can also accurately identify various protocols, mapping the cybersecurity risks and anomalies, with an average packet loss rate of only 0.83%. The standardized UAT confirms the system's usability, reliability, and robust security. The findings of this study are expected to provide a practical, reliable, efficient, and user-friendly network monitoring solution while contributing to the development of open-source and flexible network traffic monitoring and green technology. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:An organization typically has various enterprise apps and Internet of Things (IoT) systems. The usages of these systems are typically well reflected by the packets transmitted to the network. This paper presents a unique approach to strive for energy savings in organizations by exploiting fact observables in networks. DPI is employed to dissect passing network packets and predict their protocols. Data Plan Development Kit (DPDK) is adopted to push the hardware limit and speed up the inspection. A webbased customizable dashboard is incorporated to allow human observation according to the characteristics of the organization. Several API endpoints are provided to extend the functionalities, such as ML/AI integration. An energy-sensing model is proposed to measure the energy usage or generation by various connected systems, such as IoTs, smart ACs, and solar panel controllers. The results demonstrate that the working prototype improves processing efficiency, enabling the system to handle large volumes of data up to 10GB, achieving an average packet processing efficiency of 99.991%. The system can also accurately identify various protocols, mapping the cybersecurity risks and anomalies, with an average packet loss rate of only 0.83%. The standardized UAT confirms the system's usability, reliability, and robust security. The findings of this study are expected to provide a practical, reliable, efficient, and user-friendly network monitoring solution while contributing to the development of open-source and flexible network traffic monitoring and green technology. [ABSTRACT FROM AUTHOR]
ISSN:20869614
DOI:10.14716/ijtech.v16i6.7655