EDMA-RM: An Event-Driven and Mobility-Aware Resource Management Framework for Green IoT-Edge-Fog-Cloud Networks

被引:1
作者
Kumar, Rohit [1 ]
Agrawal, Neha [2 ]
机构
[1] SNU Chennai, CSE Dept, Chengalpattu 603105, Tamil Nadu, India
[2] Indian Inst Informat Technol Sri City, CSE Grp, Chittoor 517646, Andhra Pradesh, India
关键词
Resource management; Internet of Things; Edge computing; Cloud computing; Sensors; Task analysis; Delays; edge computing; fog computing; green network; Internet of Things (IoT); load balancing; multiconstrained optimization; INTERNET;
D O I
10.1109/JSEN.2024.3404470
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Inefficient management of Internet of Things (IoT) network traffic poses the risk of load imbalance and unauthorized access, resulting in a notable decline in network performance. This challenge can be effectively addressed by improving the network performance through the edge and fog computing implementation. The primary objective is to offload certain computing tasks to the network edge and fog layers, thereby facilitating effective network maintenance and well distribution of the overall network load. Additionally, leveraging cloud services can further refine this process, fostering green networking by optimizing resource utilization through efficient layered resource management. Despite existing literature exploring load balancing and access control in IoT, a comprehensive event-based resource management solution that addresses mobility issues in IoT-Edge-Fog-Cloud networks is notably scarce. In response, this work proposes the development of an event-driven and mobility-aware resource management (EDMA-RM) framework tailored for green IoT-Edge-Fog-Cloud networks. The framework is evaluated through multiple test cases, including non-LBRM (NLBRM), load-balanced resource management (LBRM), role-based access control (RBAC)-LBRM, and EDMA-RM, considering performance indicators such as CPU usage, memory usage, delay, and jitter. The assessment reveals notable improvement rates for EDMA-RM in comparison to alternative techniques, with average enhancement percentages of 13.84% for CPU, 12.40% for memory, 10.18% for delay, and 21.23% for jitter. These outcomes highlight the efficacy of the proposed EDMA-RM approach.
引用
收藏
页码:23004 / 23012
页数:9
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