Integrating Fog Computing and IoT in Education: Campus Resource Management: Energy EffieciencyMonitoring DOI Open Access

Simbarashe Fani,

Tichaona Phillip Sumbureru

International Journal of Innovative Science and Research Technology (IJISRT), Journal Year: 2024, Volume and Issue: unknown, P. 3245 - 3249

Published: Aug. 23, 2024

The swift evolution of the Internet Things (IoT) has led to generation immense sums data that require effective processing and storage. Old cloud computing methods often struggle meet real-time low latency necessities IoT applications. To discourse these encounters, fog developed as a proficient model carries resources closer sources.  This paper presents an energy-efficient monitoring system for school campus integrates technologies improve resource management. projected contains three main components:  sensor nodes positioned across collect on energy consumption, environmental conditions, occupancy levels. Fog process locally, do analytics, make smart decisions augment usage. A cloud-based platform provides unified monitoring, reporting, long-term Key Features System Comprise: Real-time analysis consumption designs Automated control lighting, HVAC, other building systems based conditions Predictive maintenance equipment increase efficiency Centralized panel campus-wide management Secure privacy-conserving at layer summarizes 10 results related through integration IoT. work fills major gap in literature by presenting holistic combines fog-based processing, intelligent decision-making, reporting optimization educational campus. Simulations real-world deployment small- scale setting show proposed yields substantial gains savings, reduced operational costs, enhanced user comfort compared traditional approaches. study contributes new findings solutions sustainable technology adoption education sector, upon previous studies have employed

Language: Английский

Leveraging Community-based Approaches for Enhancing Resource Allocation in Fog Computing Environment DOI Open Access

Alasef M. Ghalwah,

Ghaidaa A. Al-Sultany

Engineering Technology & Applied Science Research, Journal Year: 2025, Volume and Issue: 15(1), P. 20372 - 20378

Published: Feb. 2, 2025

Efficient resource allocation in fog computing environments is essential to address the increasing demand for high-performance and adaptable network services. Traditional methods lack granular differentiation based on traffic characteristics often resulting suboptimal bandwidth utilization elevated latency. To enhance efficiency, this study applies a community-based approach leveraging Louvain algorithm dynamically cluster nodes with similar demands. By forming communities latency needs, enables targeted distribution, aligning each community optimized pathways that specific requirements. The results indicate notable performance gains, including 14% increase affecting download reduction by an average of 23% time-sensitive applications. These improvements highlight effectiveness proposed managing diverse demands, improving data flow stability, enhancing overall infrastructures. findings underscore potential support scalable, adaptable, secure management, positioning it as viable solution meet complex needs IoT other distributed systems.

Language: Английский

Citations

0
Intelligent Transportation Systems DOI

Subhakar Devendran,

P. Thanapal

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 315 - 326

Published: April 4, 2025

The rise of IoT devices and big data generation pose challenges to Intelligent Transportation Systems (ITS), particularly in remote areas. Unmanned aerial vehicles (UAVs) have shown potential enhancing computation communication, but there is a lack literature on well-developed model that combines UAVs with multi-hop, fog-cloud collaborative architecture. This work proposes an optimized multi-hop offloading architecture uses improve job resource allocation ITS. approach fog cloud computing UAV-enabled collaboration address the limitations processing large amounts time-sensitive tasks. problem formulated as mixed integer nonlinear programming (MINLP) constraints user association, UAV positioning, task offloading, allocation. proposed algorithm minimizes energy consumption, latency, optimizes prioritization across layers.

Language: Английский

Citations

0
Integrating Fog Computing and IoT in Education: Campus Resource Management: Energy EffieciencyMonitoring DOI Open Access

Simbarashe Fani,

Tichaona Phillip Sumbureru

International Journal of Innovative Science and Research Technology (IJISRT), Journal Year: 2024, Volume and Issue: unknown, P. 3245 - 3249

Published: Aug. 23, 2024

The swift evolution of the Internet Things (IoT) has led to generation immense sums data that require effective processing and storage. Old cloud computing methods often struggle meet real-time low latency necessities IoT applications. To discourse these encounters, fog developed as a proficient model carries resources closer sources.  This paper presents an energy-efficient monitoring system for school campus integrates technologies improve resource management. projected contains three main components:  sensor nodes positioned across collect on energy consumption, environmental conditions, occupancy levels. Fog process locally, do analytics, make smart decisions augment usage. A cloud-based platform provides unified monitoring, reporting, long-term Key Features System Comprise: Real-time analysis consumption designs Automated control lighting, HVAC, other building systems based conditions Predictive maintenance equipment increase efficiency Centralized panel campus-wide management Secure privacy-conserving at layer summarizes 10 results related through integration IoT. work fills major gap in literature by presenting holistic combines fog-based processing, intelligent decision-making, reporting optimization educational campus. Simulations real-world deployment small- scale setting show proposed yields substantial gains savings, reduced operational costs, enhanced user comfort compared traditional approaches. study contributes new findings solutions sustainable technology adoption education sector, upon previous studies have employed

Language: Английский

Citations

2