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
相关论文
共 26 条
[1]   Dynamic load balancing assisted optimized access control mechanism for Edge-Fog-Cloud network in Internet of Things environment [J].
Agrawal, Neha .
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (21)
[2]   Defense Mechanisms Against DDoS Attacks in a Cloud Computing Environment: State-of-the-Art and Research Challenges [J].
Agrawal, Neha ;
Tapaswi, Shashikala .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (04) :3769-3795
[3]  
Chen S., 2017, IEEE INTERNET COMPUT, V21, P4, DOI DOI 10.1109/MIC.2017.39
[4]   Energy-Optimal Dynamic Computation Offloading for Industrial IoT in Fog Computing [J].
Chen, Siguang ;
Zheng, Yimin ;
Lu, Weifeng ;
Varadarajan, Vijayakumar ;
Wang, Kun .
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2020, 4 (02) :566-576
[5]   A Matching Theory Framework for Tasks Offloading in Fog Computing for IoT Systems [J].
Chiti, Francesco ;
Fantacci, Romano ;
Picano, Benedetta .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (06) :5089-5096
[6]   Location of Fog Nodes for Reduction of Energy Consumption of End-User Devices [J].
da Silva, Rodrigo A. C. ;
da Fonseca, Nelson L. S. .
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2020, 4 (02) :593-605
[7]   Towards Workload Balancing in Fog Computing Empowered IoT [J].
Fan, Qiang ;
Ansari, Nirwan .
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2020, 7 (01) :253-262
[8]   Mobi-IoST: Mobility-Aware Cloud-Fog-Edge-IoT Collaborative Framework for Time-Critical Applications [J].
Ghosh, Shreya ;
Mukherjee, Anwesha ;
Ghosh, Soumya K. ;
Buyya, Rajkumar .
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2020, 7 (04) :2271-2285
[9]   Internet of Things (IoT): A vision, architectural elements, and future directions [J].
Gubbi, Jayavardhana ;
Buyya, Rajkumar ;
Marusic, Slaven ;
Palaniswami, Marimuthu .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2013, 29 (07) :1645-1660
[10]   Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds [J].
Guo, Xijuan ;
Liu, Liqing ;
Chang, Zheng ;
Ristaniemi, Tapani .
WIRELESS NETWORKS, 2018, 24 (01) :79-88