Optimization of Resource Scheduling and Allocation Algorithms

Rahul, Satyakam; Bhardwaj, Vinay

doi:10.1109/icps55917.2022.00034

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Rahul and Bhardwaj [19], discussed the various existing scheduling techniques such as round-robin, min-min and first come first serve (FCFS). In this work they have analyzed all the parameters utilized in the previous works and then presented a hybrid algorithm to improve the performance.…”

Section: Literature Surveymentioning

confidence: 99%

A secure framework for effective workload resource management

Nayagi,

Mohan

2024

IJEECS

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An efficient and dynamic role-based access-control (RBAC) model is presented in this work which utilizes access-control for internet of things (IoT) nodes while minimizing storage and computational overhead. Also, for the identification of the malicious packets at the gateway server, a machine learning method has been presented. In addition, a framework for data management techniques in the IoT environment is designed to ensure efficient and secure storage, management, and processing of IoT data. The results have been evaluated by using the Montage and Cybershake workload in terms of energy consumption, processing time, detection accuracy and misclassification rate. The results show that the proposed secure framework for effective workload resource management (SFE-WRM) attains better performance in comparison to the reliable and energy‐efficient route selection (REERS) and FTA-WRM method. Also, by using the security method, the proposed method provides better security to the IoT nodes during the data aggregation and processing of the workload. The ultimate aim of this work is to provide a solution for the development of a secure and efficient IoT environment that can address critical security challenges and enable the widespread adoption of IoT devices and services.

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Section: Literature Surveymentioning

confidence: 99%

A secure framework for effective workload resource management

Nayagi,

Mohan

2024

IJEECS

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“…Actual Cost = Cost of Underlined tasks + Cost of tasks which has crossed the deadline (5) Energy: Energy is calculated as the total of all instances' movement factor, time, and cost factor.…”

Section: Timementioning

confidence: 99%

(EERO) Energy-Efficient Fog Resource Optimization Model for Scientific Workflow Applications

Rahul

Bhardwaj

2023

Preprint

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Network congestion and increased latency may result from the speedy development of intelligent services and Internet of Things devices contacting cloud data centers. Fog computing meets the latency and privacy needs of operations running at the network edge by focusing on widely linked heterogeneous devices. The intricate and stringent Quality of Service limitations makes allocating resources in this paradigm challenging. We investigate workflow scheduling in fog-cloud systems to give an energy-efficient task plan within tolerable application completion times. The Energy Efficient optimization mode is presented. This paper investigated the outcomes of algorithms created by the community to address issues with energy management. The objective is to provide energy-efficient algorithms for a particular problem that minimize service compromise while reducing energy usage. The algorithms must attain a provably good performance, a crucial requirement. The goal is to find an efficient Pareto front by employing a Bayesian method with a maximum likelihood procedure for processing the fog node tasks while improving task scheduling by integrating heuristic methodologies such as PEFT and the Multi-objective genetic algorithm.

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Optimized Resource Allocation using Predictive Analysis in Virtual Environment

et al. 2023

2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)

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Optimization of Resource Scheduling and Allocation Algorithms

Cited by 3 publications

References 10 publications

A secure framework for effective workload resource management

A secure framework for effective workload resource management

(EERO) Energy-Efficient Fog Resource Optimization Model for Scientific Workflow Applications

Optimized Resource Allocation using Predictive Analysis in Virtual Environment

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