A Novel Approach for Minimizing Response Time in IoT using Adaptive Algorithm

Hitesh Kumar Sharma ^*1, Samta Jain Goyal ², Sumit Kumar³, Abhishek Kumar⁴

^1,2,4 Amity University, Gwalior, M.P, India

³ G.N.S University, Sasaram, Bihar, India

Emails: hitesh.sharma2@s.amity.edu; sjgoyal@gwa.amity.edu; sumit170787@gmail.com; kabhishek.mcse@gmail.com

Abstract

This research offers four work and computer tool setups. The dynamic Resource Allocation Algorithm is crucial to the system.  This lets you manage changing supply. Once the PWMA knows how much work is coming up, it may divide resources and plan. The Load Balancing Algorithm (LBA) distributes work evenly to avoid over- or under-utilization and it also provides access content faster via the Adaptive Caching Algorithm (ACA). The proposed system surpasses the top alternative in several domains, such as data transmission, reaction time, energy conservation, load distribution effectiveness, and recovery time from failures. This is because the suggested solution incorporates many disparate approaches. Graphs and charts are visual representations that effectively illustrate the similarities and differences between the two methodologies. The hybrid technique is especially beneficial when the workload is unpredictable and prone to fluctuations. To do this, it instructs you on the fundamentals of efficient and adaptable computer resource management.

Keywords: Adaptive Caching; Computational Resource Management; Dynamic Resource Allocation; Load Balancing; Performance Optimization; Predictive Workload Management; Resource Utilization; System Efficiency; Workload Handling; Workload Prediction.