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- Title
An Efficient Hybrid Computing Environment to Develop a Confidential and Authenticated IoT Service Model.
- Authors
Ram, R. Saravana; Kumar, M. Vinoth; Ramamoorthy, S.; Balaji, B. Saravana; Kumar, T. Rajesh
- Abstract
The applications and scope of the Internet of Things (IoT) goes on increasing when cloud computing combines with IoT. Cloud enriches the capacity of IoT in various sectors such as Home Automation, Healthcare, Industrial IoT, etc. One of the major challenges in construction of today's smart environment is to ensure the confidentiality and authentication in data transmission of the environment. Many existing systems attempted to provide a secure IoT environment but failed to ensure the efficiency in its security. Due to this problem, the capability of IoT and Cloud comes down and suffers to produce an optimal environment. In this regard, an optimal hybrid computing model containing cloud and edge computing has been proposed to develop a confidence assessment system to ensure the security in a IoT environment. The proposed model is an amalgamation of confidence assessment system and utility pattern of dynamic load balancing in cloud and edge computing. The effective design of the edge network and edge policy minimizes the resource utilization and improves the capability of the confidence assessment system. In the proposed system, the utility factor pattern is embedded in cloud and utility syntax pattern is embedded in the edge policy to enhance the applications of IoT and Cloud services. The edge network helps the edge policy in embedding the utility syntax pattern based on confidence assessment system. The proposed model has been compared with various existing models and results in producing an optimal secure IoT environment.
- Subjects
INTERNET of things; EDGE computing; DYNAMIC loads; CLOUD computing; DYNAMIC balance (Mechanics); DATA transmission systems
- Publication
Wireless Personal Communications, 2021, Vol 117, Issue 4, p2903
- ISSN
0929-6212
- Publication type
Article
- DOI
10.1007/s11277-020-07056-0