The document discusses optimizing task scheduling in mobile cloud computing using the particle swarm optimization algorithm. It proposes using PSO to develop a task scheduling optimization model that reduces task transmission time, execution time, and costs. PSO is a dynamic scheduling algorithm that could help speed up task execution and decrease costs compared to other algorithms. The document reviews background on task scheduling and cloud computing and analyzes related work on using algorithms like genetic algorithms and ant colony optimization for task scheduling.
IRJET- Scheduling of Independent Tasks over Virtual Machines on Computati...IRJET Journal
This document discusses scheduling independent tasks over virtual machines in a cloud computing environment. It compares the performance of four scheduling algorithms: First Come First Serve (FCFS), Shortest Job First (SJF), Round Robin, and Particle Swarm Optimization (PSO). The algorithms are tested on virtual machines with 1, 2, and 4 CPU cores. PSO consistently achieves the shortest makespan (task completion time). While FCFS, SJF, and Round Robin perform similarly on single-core and dual-core VMs, Round Robin's performance degrades on quad-core VMs likely due to core collision issues. Overall, PSO schedules tasks most efficiently across all virtual machine configurations.
An Optimized-Throttled Algorithm for Distributing Load in Cloud ComputingIRJET Journal
This document proposes an optimized-throttled algorithm for distributing load in cloud computing. It summarizes existing load balancing algorithms like round robin and throttled, and then describes the proposed optimized-throttled algorithm in more detail. The algorithm prioritizes distributing load to minimize virtual machine overload and underload. It is evaluated through simulation and is shown to improve response times and processing times compared to round robin and throttled algorithms.
A Review: Metaheuristic Technique in Cloud ComputingIRJET Journal
This document reviews various meta-heuristic techniques that have been applied to problems in cloud computing, such as task scheduling, load balancing, ant colony optimization (ACO), particle swarm optimization (PSO), and gravitational search algorithm (GSA). It first provides background on cloud computing and defines common cloud computing concepts. It then surveys literature applying meta-heuristics like ACO, GA, PSO, and GSA to solve problems related to load balancing and scheduling in cloud environments. The document concludes that meta-heuristic techniques are effective for optimizing resource utilization and management in cloud computing systems.
Cloud Computing Task Scheduling Algorithm Based on Modified Genetic AlgorithmIRJET Journal
This document presents a cloud computing task scheduling algorithm based on a modified genetic algorithm. It begins with an abstract discussing scalable cloud computing and the need for efficient task scheduling and virtual machine allocation. It then discusses the problem of existing scheduling algorithms having high overhead and slow convergence. The proposed methodology uses a heuristic-based prediction model with a logistic normal distribution technique to improve data transmission prediction. Simulation results show the proposed approach has better throughput and computation time than existing algorithms for different data packet sizes. The conclusion discusses overcoming drawbacks of earlier algorithms and future work focusing on algorithms with better tradeoffs between performance characteristics.
IRJET- Time and Resource Efficient Task Scheduling in Cloud Computing Environ...IRJET Journal
This document summarizes a research paper that proposes a Task Based Allocation (TBA) algorithm to efficiently schedule tasks in a cloud computing environment. The algorithm aims to minimize makespan (completion time of all tasks) and maximize resource utilization. It first generates an Expected Time to Complete (ETC) matrix that estimates the time each task will take on different virtual machines. It then sorts tasks by length and allocates each task to the VM that minimizes its completion time, updating the VM wait times. The algorithm is evaluated using CloudSim simulation and is shown to reduce makespan, execution time and costs compared to random and first-come, first-served scheduling approaches.
Scheduling of Heterogeneous Tasks in Cloud Computing using Multi Queue (MQ) A...IRJET Journal
This document proposes a Multi Queue (MQ) task scheduling algorithm for heterogeneous tasks in cloud computing. It aims to improve upon the Round Robin and Weighted Round Robin algorithms by overcoming their drawbacks. The MQ algorithm splits tasks and resources into separate queues based on size/length and speed. Small tasks are scheduled on slower resources and large tasks on faster resources. The document compares the performance of MQ to Round Robin and Weighted Round Robin algorithms based on makespan, average resource utilization, and load balancing level using CloudSim simulations. The results show that MQ scheduling performs better than the other algorithms in most cases in terms of these metrics.
An Enhanced Throttled Load Balancing Approach for Cloud EnvironmentIRJET Journal
The document proposes an enhanced throttled load balancing approach for cloud environments. It discusses existing load balancing techniques like round robin, weighted round robin, and throttled approaches. It identifies that existing throttled approaches can lead to overloading as they do not consider task size when assigning tasks to virtual machines. The proposed approach aims to improve performance for cloud users by enhancing the basic throttled mapping approach to better distribute tasks among resources. The approach is evaluated using the CloudAnalyst simulator and results show it performs better than original techniques.
Energy-Efficient Task Scheduling in Cloud EnvironmentIRJET Journal
1. The document discusses developing an energy-efficient task scheduling approach for cloud data centers using deep reinforcement learning.
2. It aims to minimize computational costs and cooling costs by optimizing task assignment to servers based on factors like temperature, CPU, and memory.
3. The proposed approach uses a greedy algorithm to schedule tasks to servers maintaining the lowest temperature, thus reducing energy consumption and improving data center performance.
IRJET- Scheduling of Independent Tasks over Virtual Machines on Computati...IRJET Journal
This document discusses scheduling independent tasks over virtual machines in a cloud computing environment. It compares the performance of four scheduling algorithms: First Come First Serve (FCFS), Shortest Job First (SJF), Round Robin, and Particle Swarm Optimization (PSO). The algorithms are tested on virtual machines with 1, 2, and 4 CPU cores. PSO consistently achieves the shortest makespan (task completion time). While FCFS, SJF, and Round Robin perform similarly on single-core and dual-core VMs, Round Robin's performance degrades on quad-core VMs likely due to core collision issues. Overall, PSO schedules tasks most efficiently across all virtual machine configurations.
An Optimized-Throttled Algorithm for Distributing Load in Cloud ComputingIRJET Journal
This document proposes an optimized-throttled algorithm for distributing load in cloud computing. It summarizes existing load balancing algorithms like round robin and throttled, and then describes the proposed optimized-throttled algorithm in more detail. The algorithm prioritizes distributing load to minimize virtual machine overload and underload. It is evaluated through simulation and is shown to improve response times and processing times compared to round robin and throttled algorithms.
A Review: Metaheuristic Technique in Cloud ComputingIRJET Journal
This document reviews various meta-heuristic techniques that have been applied to problems in cloud computing, such as task scheduling, load balancing, ant colony optimization (ACO), particle swarm optimization (PSO), and gravitational search algorithm (GSA). It first provides background on cloud computing and defines common cloud computing concepts. It then surveys literature applying meta-heuristics like ACO, GA, PSO, and GSA to solve problems related to load balancing and scheduling in cloud environments. The document concludes that meta-heuristic techniques are effective for optimizing resource utilization and management in cloud computing systems.
Cloud Computing Task Scheduling Algorithm Based on Modified Genetic AlgorithmIRJET Journal
This document presents a cloud computing task scheduling algorithm based on a modified genetic algorithm. It begins with an abstract discussing scalable cloud computing and the need for efficient task scheduling and virtual machine allocation. It then discusses the problem of existing scheduling algorithms having high overhead and slow convergence. The proposed methodology uses a heuristic-based prediction model with a logistic normal distribution technique to improve data transmission prediction. Simulation results show the proposed approach has better throughput and computation time than existing algorithms for different data packet sizes. The conclusion discusses overcoming drawbacks of earlier algorithms and future work focusing on algorithms with better tradeoffs between performance characteristics.
IRJET- Time and Resource Efficient Task Scheduling in Cloud Computing Environ...IRJET Journal
This document summarizes a research paper that proposes a Task Based Allocation (TBA) algorithm to efficiently schedule tasks in a cloud computing environment. The algorithm aims to minimize makespan (completion time of all tasks) and maximize resource utilization. It first generates an Expected Time to Complete (ETC) matrix that estimates the time each task will take on different virtual machines. It then sorts tasks by length and allocates each task to the VM that minimizes its completion time, updating the VM wait times. The algorithm is evaluated using CloudSim simulation and is shown to reduce makespan, execution time and costs compared to random and first-come, first-served scheduling approaches.
Scheduling of Heterogeneous Tasks in Cloud Computing using Multi Queue (MQ) A...IRJET Journal
This document proposes a Multi Queue (MQ) task scheduling algorithm for heterogeneous tasks in cloud computing. It aims to improve upon the Round Robin and Weighted Round Robin algorithms by overcoming their drawbacks. The MQ algorithm splits tasks and resources into separate queues based on size/length and speed. Small tasks are scheduled on slower resources and large tasks on faster resources. The document compares the performance of MQ to Round Robin and Weighted Round Robin algorithms based on makespan, average resource utilization, and load balancing level using CloudSim simulations. The results show that MQ scheduling performs better than the other algorithms in most cases in terms of these metrics.
An Enhanced Throttled Load Balancing Approach for Cloud EnvironmentIRJET Journal
The document proposes an enhanced throttled load balancing approach for cloud environments. It discusses existing load balancing techniques like round robin, weighted round robin, and throttled approaches. It identifies that existing throttled approaches can lead to overloading as they do not consider task size when assigning tasks to virtual machines. The proposed approach aims to improve performance for cloud users by enhancing the basic throttled mapping approach to better distribute tasks among resources. The approach is evaluated using the CloudAnalyst simulator and results show it performs better than original techniques.
Energy-Efficient Task Scheduling in Cloud EnvironmentIRJET Journal
1. The document discusses developing an energy-efficient task scheduling approach for cloud data centers using deep reinforcement learning.
2. It aims to minimize computational costs and cooling costs by optimizing task assignment to servers based on factors like temperature, CPU, and memory.
3. The proposed approach uses a greedy algorithm to schedule tasks to servers maintaining the lowest temperature, thus reducing energy consumption and improving data center performance.
This document discusses load balancing in cloud computing. It begins with an introduction to cloud computing and discusses how load balancing can improve user satisfaction and resource utilization by evenly distributing tasks across resources. It then describes different types of load balancing algorithms like round robin, equally spread current execution, min-min, and max-min algorithms. It also covers dynamic load balancing approaches like ant colony optimization and honeybee foraging behavior algorithms. The document concludes by comparing various load balancing algorithms based on metrics like throughput, fault tolerance, response time, overhead, and scalability. Load balancing is important for cloud computing to efficiently allocate dynamic workloads across nodes and improve performance.
A Survey on Task Scheduling and Load Balanced Algorithms in Cloud ComputingIRJET Journal
This document summarizes a survey on task scheduling and load balancing algorithms in cloud computing. It begins with an abstract discussing cloud computing and the importance of dynamic provisioning and load balancing. It then discusses load balancing concepts and challenges, including overhead, performance, scalability, response time, and single points of failure. Common load balancing algorithms for cloud computing are also summarized, including Max-Min and Min-Min scheduling algorithms. The goals of load balancing and how it is implemented in cloud architectures is also briefly addressed.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
This document reviews scheduling techniques in cloud computing. It discusses key concepts like virtualization and different scheduling algorithms. The review surveys various scheduling algorithms for tasks, workflows, real-time applications and energy optimization. It analyzes algorithms for load balancing, fault tolerance and resource utilization to improve performance metrics like makespan, cost and energy consumption. The document concludes that effective scheduling is important in cloud computing to provide on-demand services and complete tasks accurately and on time.
A Review on Scheduling in Cloud Computingijujournal
This document reviews scheduling techniques in cloud computing. It discusses key concepts like virtualization and different scheduling algorithms. The review surveys various scheduling algorithms for tasks, workflows, real-time applications and energy efficiency. It analyzes algorithms based on parameters like makespan, cost, energy consumption and concludes many algorithms can improve resource utilization and performance while reducing energy costs.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document presents a cluster scoring based task scheduling (CSBTS) algorithm for improving real-time task completion and harnessing energy in virtualized cloud environments. The CSBTS aims to decrease task completion time by calculating cluster score values based on available transmission power and computing power. It also establishes policies for dynamically creating, migrating, and cancelling virtual machines to reduce energy consumption while meeting real-time requirements. The algorithm considers data and computation intensive jobs and divides them into subtasks to assign to clusters based on their updated scores. The goal is to optimize scheduling of real-time tasks and energy savings.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document describes a Cluster Scoring Based Task Scheduling (CSBTS) algorithm for scheduling real-time tasks in a virtualized cloud environment. The algorithm aims to decrease task completion times and save energy by dynamically adjusting VM creation, migration and cancellation. It proposes calculating a cluster score based on average transmission power and computing power to assign tasks. The cluster with the highest score is selected. Local and global updates are used to adjust scores based on latest resource status. The approach considers storage capacity and splits jobs into subtasks assigned across multiple clusters to improve performance and energy efficiency.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document presents a cluster scoring based task scheduling (CSBTS) algorithm for improving real-time task completion and harnessing energy in virtualized cloud environments. The CSBTS aims to decrease task completion time by calculating cluster score values based on available transmission power and computing power. It also establishes policies for dynamically creating, migrating, and cancelling virtual machines to meet real-time requirements while saving energy. The algorithm considers data and computation intensive jobs and assigns them to clusters based on their scores. It further divides jobs into subtasks based on storage capacity to improve scheduling. The proposed strategy aims to reduce completion time and efficiently utilize energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage based on needs. This is because of the virtualization technology. The scheduling objectives are to improve the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
Providing a multi-objective scheduling tasks by Using PSO algorithm for cost ...Editor IJCATR
This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management in cloud computing. This means that
any migration costs due to supply failure consider as a one objective and each task is a little particle and recognize by use of the
appropriate fitness schedule function (how the particles arrangement) that cost at least amount of total expense. In addition to, the weight
is granted to the each expenditure that reflects the importance of cost. The data which is used to simulate proposed method are series of
academic and research data that are prepared from the Internet and MATLAB software is used for simulation. We simulate two issues,
in the first issue, consider four task by four vehicles and divide tasks. In the second issue, make the issue more complicated and consider
six tasks by four vehicles. We write PSO's output for each two issues of various iterations. Finally, the particles dispersion and as well
as the output of the cost function were computed for each pa
IRJET- Advance Approach for Load Balancing in Cloud Computing using (HMSO) Hy...IRJET Journal
This document proposes a new hybrid multi-swarm optimization (HMSO) algorithm for load balancing in cloud computing. It aims to minimize response time and costs while improving resource utilization and customer satisfaction. The HMSO algorithm uses multi-level particle swarm optimization to find an optimal resource allocation solution. Simulation results show that the proposed HMSO technique reduces response time and datacenter costs compared to other algorithms. It also achieves a more balanced load distribution across resources.
A hybrid approach for scheduling applications in cloud computing environment IJECEIAES
Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.
This document proposes a new task scheduling algorithm called Dynamic Heterogeneous Shortest Job First (DHSJF) for heterogeneous cloud computing systems. DHSJF aims to improve performance metrics like reduced makespan and low energy consumption by considering the heterogeneity of resources and workloads. It discusses existing scheduling algorithms like Round Robin, First Come First Serve and their limitations. The proposed DHSJF algorithm prioritizes tasks with the shortest estimated completion time to optimize resource utilization and improve overall performance of the cloud computing system. Simulation results show that DHSJF provides better results for metrics like average waiting time and turnaround time as compared to Round Robin and First Come First Serve scheduling algorithms.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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This document discusses load balancing in cloud computing. It begins with an introduction to cloud computing and discusses how load balancing can improve user satisfaction and resource utilization by evenly distributing tasks across resources. It then describes different types of load balancing algorithms like round robin, equally spread current execution, min-min, and max-min algorithms. It also covers dynamic load balancing approaches like ant colony optimization and honeybee foraging behavior algorithms. The document concludes by comparing various load balancing algorithms based on metrics like throughput, fault tolerance, response time, overhead, and scalability. Load balancing is important for cloud computing to efficiently allocate dynamic workloads across nodes and improve performance.
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This document summarizes a survey on task scheduling and load balancing algorithms in cloud computing. It begins with an abstract discussing cloud computing and the importance of dynamic provisioning and load balancing. It then discusses load balancing concepts and challenges, including overhead, performance, scalability, response time, and single points of failure. Common load balancing algorithms for cloud computing are also summarized, including Max-Min and Min-Min scheduling algorithms. The goals of load balancing and how it is implemented in cloud architectures is also briefly addressed.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
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This document reviews scheduling techniques in cloud computing. It discusses key concepts like virtualization and different scheduling algorithms. The review surveys various scheduling algorithms for tasks, workflows, real-time applications and energy optimization. It analyzes algorithms for load balancing, fault tolerance and resource utilization to improve performance metrics like makespan, cost and energy consumption. The document concludes that effective scheduling is important in cloud computing to provide on-demand services and complete tasks accurately and on time.
A Review on Scheduling in Cloud Computingijujournal
This document reviews scheduling techniques in cloud computing. It discusses key concepts like virtualization and different scheduling algorithms. The review surveys various scheduling algorithms for tasks, workflows, real-time applications and energy efficiency. It analyzes algorithms based on parameters like makespan, cost, energy consumption and concludes many algorithms can improve resource utilization and performance while reducing energy costs.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document presents a cluster scoring based task scheduling (CSBTS) algorithm for improving real-time task completion and harnessing energy in virtualized cloud environments. The CSBTS aims to decrease task completion time by calculating cluster score values based on available transmission power and computing power. It also establishes policies for dynamically creating, migrating, and cancelling virtual machines to reduce energy consumption while meeting real-time requirements. The algorithm considers data and computation intensive jobs and divides them into subtasks to assign to clusters based on their updated scores. The goal is to optimize scheduling of real-time tasks and energy savings.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document describes a Cluster Scoring Based Task Scheduling (CSBTS) algorithm for scheduling real-time tasks in a virtualized cloud environment. The algorithm aims to decrease task completion times and save energy by dynamically adjusting VM creation, migration and cancellation. It proposes calculating a cluster score based on average transmission power and computing power to assign tasks. The cluster with the highest score is selected. Local and global updates are used to adjust scores based on latest resource status. The approach considers storage capacity and splits jobs into subtasks assigned across multiple clusters to improve performance and energy efficiency.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
The document presents a cluster scoring based task scheduling (CSBTS) algorithm for improving real-time task completion and harnessing energy in virtualized cloud environments. The CSBTS aims to decrease task completion time by calculating cluster score values based on available transmission power and computing power. It also establishes policies for dynamically creating, migrating, and cancelling virtual machines to meet real-time requirements while saving energy. The algorithm considers data and computation intensive jobs and assigns them to clusters based on their scores. It further divides jobs into subtasks based on storage capacity to improve scheduling. The proposed strategy aims to reduce completion time and efficiently utilize energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage based on needs. This is because of the virtualization technology. The scheduling objectives are to improve the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically adjust the scale of cloud in a while meets the real-time requirements and to save energy.
IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUDijcax
Cloud computing provides the facility for the business customers to scale up and down their resource usage
based on needs. This is because of the virtualization technology. The scheduling objectives are to improve
the system’s schedule ability for the real-time tasks and to save energy. To achieve the objectives, we
employed the virtualization technique and rolling-horizon optimization with vertical scheduling operation.
The project considers Cluster Scoring Based Task Scheduling (CSBTS) algorithm which aims to decrease
task’s completion time and the policies for VM’s creation, migration and cancellation are to dynamically
adjust the scale of cloud in a while meets the real-time requirements and to save energy.
Providing a multi-objective scheduling tasks by Using PSO algorithm for cost ...Editor IJCATR
This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management in cloud computing. This means that
any migration costs due to supply failure consider as a one objective and each task is a little particle and recognize by use of the
appropriate fitness schedule function (how the particles arrangement) that cost at least amount of total expense. In addition to, the weight
is granted to the each expenditure that reflects the importance of cost. The data which is used to simulate proposed method are series of
academic and research data that are prepared from the Internet and MATLAB software is used for simulation. We simulate two issues,
in the first issue, consider four task by four vehicles and divide tasks. In the second issue, make the issue more complicated and consider
six tasks by four vehicles. We write PSO's output for each two issues of various iterations. Finally, the particles dispersion and as well
as the output of the cost function were computed for each pa
IRJET- Advance Approach for Load Balancing in Cloud Computing using (HMSO) Hy...IRJET Journal
This document proposes a new hybrid multi-swarm optimization (HMSO) algorithm for load balancing in cloud computing. It aims to minimize response time and costs while improving resource utilization and customer satisfaction. The HMSO algorithm uses multi-level particle swarm optimization to find an optimal resource allocation solution. Simulation results show that the proposed HMSO technique reduces response time and datacenter costs compared to other algorithms. It also achieves a more balanced load distribution across resources.
A hybrid approach for scheduling applications in cloud computing environment IJECEIAES
Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.
This document proposes a new task scheduling algorithm called Dynamic Heterogeneous Shortest Job First (DHSJF) for heterogeneous cloud computing systems. DHSJF aims to improve performance metrics like reduced makespan and low energy consumption by considering the heterogeneity of resources and workloads. It discusses existing scheduling algorithms like Round Robin, First Come First Serve and their limitations. The proposed DHSJF algorithm prioritizes tasks with the shortest estimated completion time to optimize resource utilization and improve overall performance of the cloud computing system. Simulation results show that DHSJF provides better results for metrics like average waiting time and turnaround time as compared to Round Robin and First Come First Serve scheduling algorithms.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Similar to Optimizing Task Scheduling in Mobile Cloud Computing Using Particle Swarm Optimization (PSO) Algorithm (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024