Results 51 to 60 of about 1,875 (163)
An Efficient Deadline Based Priority Job Scheduling in Mobile Cloud Computing
To improve quality of service (QoS) and optimize cost efficiency, a multi‐objective model has been proposed with shortest execution first scheduling (SEFS) for unconstrained jobs and efficient deadline and priority job scheduling (EDPS) for constrained jobs.
Muhammad Makama Mahmudur Rahman Ohee +5 more
wiley +1 more source
Improving Cloud Task Scheduling in Cloud Sim Plus using Demand-Aware VM Selection
Deep reinforcement learning and metaheuristics are becoming popular ways to study cloud task scheduling to make things like makespan and completion time better; however, these methods often require a lot of computing power and can make it harder to ...
Nagham Ajeel Sultan
doaj +1 more source
QoS Transformation in the Cloud: Advancing Service Quality Through Innovative Resource Scheduling
A new resource allocation system that may make decisions at runtime to handle the processing of applications at a VM has been presented. Independent tasks were submitted to the CloudSim simulator to test the MAPSO scheduling algorithm. The findings show that MAPSO improved a number of key aspects.
P. Tamilarasu +3 more
wiley +1 more source
The Internet of Vehicles requires high bandwidth and low latency services to unleash the potential of fully connected vehicles. Thus, the offloading proposals that successfully manage massive real-time service requests from vehicle nodes are needed.
Katja Gilly +3 more
doaj +1 more source
An analytical model of the multitap least mean squares (LMS) loop interference cancellation system was established, and the correlation function of Quadrature Phase‐Shift Keying (QPSK) signals was derived, with particular emphasis on the comparative analysis of performance differences between single‐ and dual‐LMS loop architectures.
Zhipeng Liu, Yunhao Jiang
wiley +1 more source
The rapid growth of Internet of Things (IoT) devices has posed significant security challenges, particularly in detecting anomalies and malicious behaviors in network traffic. This study presents an innovative intrusion detection system (IDS) framework that combines Gaussian noise injection and Hurst parameter calculation with a hybrid convolutional ...
Roya Morshedi +3 more
wiley +1 more source
Integrating I/Os in Cloudsim for Performance and Energy Estimation
International audienceThis article presents an extension of the IaaS Cloud simulator CloudSim. This extension takes into account the processing of i/o workload generated by virtual machines within a data center, and evaluates the overall performance and ...
Ouarnoughi, Hamza +3 more
core +1 more source
The technological advances, popularity and complexity of cloud computing systems make the need for cloud simulators evident. Cloud simulators are programs that simulate a real datacenter into your personal computer. Their main objective is evaluating the
Nawar Jawad (12930242) +2 more
core +1 more source
Task scheduling in heterogeneous cloud environment using mean grey wolf optimization algorithm
The primary objective of task scheduling involves scheduling the task on resources and minimizing the objective of the schedule. In this study, we proposed mean grey wolf optimization algorithm to enhance the system performance there by depleting the ...
Gobalakrishnan Natesan +1 more
doaj +1 more source
A Survey of Load Balancing Approaches Based on Switch Migration in Software‐Defined Networks
In this article, after discussing the load balancing of multiple controllers as one of the research challenges in this field, its solution through the switch migration is investigated. A variety of load balancing methods based on switch migration are investigated and then a comprehensive comparison is made between them.
Hamid Reza Naji, Harir Riyahi
wiley +1 more source

