Year: 2024
Type: article
Abstract: With the rapid expansion of cloud computing and the pervasive growth of IoT across industries and educational sectors, the need for efficient remote data management and service orchestration has become paramount. Web services, facilitated by APIs, offer a modular approach to integrating and streamlining complex business processes. However, real-time monitoring and optimal service selection within large-scale, cloud-based repositories remain significant challenges. This study introduces the Improved Eagle Strategy (IES) hybrid model, designed to drastically reduce computation time while ensuring accurate service selection tailored to specific user requirements. Through comprehensive NetLogo simulations, the IES model demonstrates superior efficiency in service selection compared to existing methodologies. Additionally, the IES model's application through a web dashboard system highlights its capability to manage both functional and non-functional service attributes effectively. When deployed on real-time IoT devices, the IES model not only enhances computation speed but also ensures a more responsive and user-centric service environment. This research underscores the transformative potential of the IES model in optimizing cloud computing processes, particularly within the IoT ecosystem.
Source: Future Internet
DOI: 10.3390/fi16110409
Authors: Venushini Rajendran, R Kanesaraj Ramasamy
Institution: Multimedia University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,819
OpenAlex ID: W4404111815