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.
A SURVEY ON REDUCING ENERGY SPRAWL IN CLOUD COMPUTINGaciijournal
Cloud computing is the cluster of autonomic computing, grid computing and utility computing. Cloud
providers are there to rescue their customers from the problem of dynamism. The providers focus on
resource sharing and in improving the performance. Energy consumption is the major factor to degrade the
performance. Reducing energy sprawl will bloom the performance. This paper delineates the different
techniques involved in scheduling the workload of the servers in order to minimize the energy sprawl.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud computing requires many tasks to be executed by the provided resources to achieve good performance, shortest response time and high utilization of resources. To achieve these challenges there is a need to develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to optimize energy consumption. This study accomplished with all the existing techniques mainly focus on reducing energy consumption.
A survey to harness an efficient energy in cloud computingijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud computing requires many tasks to be executed by the provided resources to achieve good performance, shortest response time and high utilization of resources. To achieve these challenges there is a need to develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to
optimize energy consumption. This study accomplished with all the existing techniques mainly focus on reducing energy consumption.
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 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.
Optimization of energy consumption in cloud computing datacenters IJECEIAES
Cloud computing has emerged as a practical paradigm for providing IT resources, infrastructure and services. This has led to the establishment of datacenters that have substantial energy demands for their operation. This work investigates the optimization of energy consumption in cloud datacenter using energy efficient allocation of tasks to resources. The work seeks to develop formal optimization models that minimize the energy consumption of computational resources and evaluates the use of existing optimization solvers in testing these models. Integer linear programming (ILP) techniques are used to model the scheduling problem. The objective is to minimize the total power consumed by the active and idle cores of the servers’ CPUs while meeting a set of constraints. Next, we use these models to carry out a detailed performance comparison between a selected set of Generic ILP and 0-1 Boolean satisfiability based solvers in solving the ILP formulations. Simulation results indicate that in some cases the developed models have saved up to 38% in energy consumption when compared to common techniques such as round robin. Furthermore, results also showed that generic ILP solvers had superior performance when compared to SAT-based ILP solvers especially as the number of tasks and resources grow in size.
A survey on energy efficient with task consolidation in the virtualized cloud...eSAT Journals
Abstract Cloud computing is a new model of computing that is widely used in today’s industry, organizations and society in information technology service delivery as a utility. It enables organizations to reduce operational expenditure and capital expenditure. However, cloud computing with underutilized resources still consumes an unacceptable amount of energy than fully utilized resource. Many techniques for optimizing energy consumption in virtualized cloud have been proposed. This paper surveys different energy efficient models with task consolidation in the virtualized cloud computing environment. Keywords: Cloud computing, Virtualization, Task consolidation, Energy consumption, Virtual machine
A survey on energy efficient with task consolidation in the virtualized cloud...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A SURVEY ON REDUCING ENERGY SPRAWL IN CLOUD COMPUTINGaciijournal
Cloud computing is the cluster of autonomic computing, grid computing and utility computing. Cloud
providers are there to rescue their customers from the problem of dynamism. The providers focus on
resource sharing and in improving the performance. Energy consumption is the major factor to degrade the
performance. Reducing energy sprawl will bloom the performance. This paper delineates the different
techniques involved in scheduling the workload of the servers in order to minimize the energy sprawl.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud computing requires many tasks to be executed by the provided resources to achieve good performance, shortest response time and high utilization of resources. To achieve these challenges there is a need to develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to optimize energy consumption. This study accomplished with all the existing techniques mainly focus on reducing energy consumption.
A survey to harness an efficient energy in cloud computingijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud computing requires many tasks to be executed by the provided resources to achieve good performance, shortest response time and high utilization of resources. To achieve these challenges there is a need to develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to
optimize energy consumption. This study accomplished with all the existing techniques mainly focus on reducing energy consumption.
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 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.
Optimization of energy consumption in cloud computing datacenters IJECEIAES
Cloud computing has emerged as a practical paradigm for providing IT resources, infrastructure and services. This has led to the establishment of datacenters that have substantial energy demands for their operation. This work investigates the optimization of energy consumption in cloud datacenter using energy efficient allocation of tasks to resources. The work seeks to develop formal optimization models that minimize the energy consumption of computational resources and evaluates the use of existing optimization solvers in testing these models. Integer linear programming (ILP) techniques are used to model the scheduling problem. The objective is to minimize the total power consumed by the active and idle cores of the servers’ CPUs while meeting a set of constraints. Next, we use these models to carry out a detailed performance comparison between a selected set of Generic ILP and 0-1 Boolean satisfiability based solvers in solving the ILP formulations. Simulation results indicate that in some cases the developed models have saved up to 38% in energy consumption when compared to common techniques such as round robin. Furthermore, results also showed that generic ILP solvers had superior performance when compared to SAT-based ILP solvers especially as the number of tasks and resources grow in size.
A survey on energy efficient with task consolidation in the virtualized cloud...eSAT Journals
Abstract Cloud computing is a new model of computing that is widely used in today’s industry, organizations and society in information technology service delivery as a utility. It enables organizations to reduce operational expenditure and capital expenditure. However, cloud computing with underutilized resources still consumes an unacceptable amount of energy than fully utilized resource. Many techniques for optimizing energy consumption in virtualized cloud have been proposed. This paper surveys different energy efficient models with task consolidation in the virtualized cloud computing environment. Keywords: Cloud computing, Virtualization, Task consolidation, Energy consumption, Virtual machine
A survey on energy efficient with task consolidation in the virtualized cloud...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The document proposes an Earthquake Disaster Based Resource Scheduling (EDBRS) framework for efficiently allocating cloud computing resources during earthquake disasters. The framework aims to minimize execution costs and times of cloud workloads by prioritizing urgent workloads related to emergency response. It models the resource scheduling problem and considers factors like workload deadlines, resource speeds and costs. The framework also presents algorithms for optimally assigning equal-length and variable-length workloads across multiple public and private cloud resources to balance performance and cost. The goal is to efficiently allocate cloud resources to disaster response zones based on urgency to reduce loss of life during earthquakes.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...ijccsa
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
KEYWORDS
Energy Consumption, Virtual Machine Placement, Harmony Search Algorithm, Server Consolidati
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract
Life time of Wireless device Networks (WSNs) has perpetually been a important issue and has received enlarged attention within the
recent years. Typically wireless device nodes area unit equipped with low power batteries that area unit impossible to recharge.
Wireless device networks ought to have enough energy to satisfy the specified necessities of applications. during this paper, we have a
tendency to propose Energy economical Routing and Fault node Replacement (EERFNR) formula to extend the lifespan of wireless
device network, cut back information loss and conjointly cut back device node replacement value. Transmission drawback and device
node loading drawback is solved by adding many relay nodes and composition device node’s routing mistreatment stratified Gradient
Diffusion. The device node will save backup nodes to cut back the energy for re-looking the route once the device node routing is
broken. Genetic formula can calculate the device nodes to exchange, apply the foremost on the market routing methods to replace the
fewest device nodes.
Keywords: Genetic algorithmic rule, stratified gradient diffusion, grade diffusion, wireless device networks
Energy efficient task scheduling algorithms for cloud data centerseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
IRJET- An Energy-Saving Task Scheduling Strategy based on Vacation Queuing & ...IRJET Journal
This document summarizes a research paper that proposes an energy-saving task scheduling strategy for cloud computing based on vacation queuing and optimization of resources. The proposed approach aims to minimize energy consumption, reduce processing time, and increase the number of sleeping nodes to make the system more efficient. It introduces a task scheduling algorithm that assigns tasks to computing nodes based on their properties using a load balancer. Simulation results show the proposed algorithm reduces energy consumption while meeting task performance compared to the vacation queuing algorithm. The document discusses related work on energy optimization techniques, presents the proposed approach, and analyzes results showing improvements in energy usage, time, and idle nodes.
This document summarizes and compares various scheduling algorithms used in cloud computing environments. It begins with an introduction to cloud computing and the need for scheduling algorithms in cloud environments. It then describes several existing scheduling algorithms, including compromised-time-cost scheduling, particle swarm optimization-based heuristic, improved cost-based algorithm, resource-aware scheduling, innovative transaction intensive cost-constraint scheduling, scalable heterogeneous earliest-finish-time algorithm, and multiple QoS constrained scheduling strategy of multi-workflows. These algorithms aim to optimize metrics such as execution time, cost, deadline, load balancing, and quality of service. The document concludes by comparing the different scheduling strategies.
Cost-Efficient Task Scheduling with Ant Colony Algorithm for Executing Large ...Editor IJCATR
This document summarizes a research paper that proposes an optimized ant colony optimization (ACO) algorithm for task scheduling in cloud computing. The goal is to minimize makespan and cost while improving fairness and load balancing. The ACO algorithm is adapted to prioritize and fairly allocate tasks to machines based on their performance. Simulations show the proposed ACO algorithm reduces makespan by 80% compared to Berger and greedy algorithms. It also increases processor utilization and balances loads across machines better than the other algorithms. The researchers conclude the optimized ACO approach improves resource usage and user satisfaction for task scheduling in cloud computing.
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.
This document discusses energy efficiency in cloud computing. It notes that cloud computing has led to large data centers with significant energy usage and carbon footprints. The resource allocation problem in cloud computing is treated as a linear programming problem aimed at minimizing energy consumption. Several heuristic algorithms are adopted and analyzed for resource allocation using an expected time to compute task model to develop green cloud computing solutions that reduce costs and environmental impacts.
An optimized scientific workflow scheduling in cloud computingDIGVIJAY SHINDE
The document discusses optimizing scientific workflow scheduling in cloud computing. It begins with definitions of workflow and cloud computing. Workflow is a group of repeatable dependent tasks, while cloud computing provides applications and hardware resources over the Internet. There are three cloud service models: SaaS, PaaS, and IaaS. The document explores how to efficiently schedule workflows in the cloud to reduce makespan, cost, and energy consumption. It reviews different scheduling algorithms like FCFS, genetic algorithms, and discusses optimizing objectives like time and cost. The document provides a literature review comparing various workflow scheduling methods and algorithms. It concludes with discussing open issues and directions for future work in optimizing workflow scheduling for cloud computing.
A Survey on Reducing Energy Sprawl In Cloud Computingaciijournal
Cloud computing is the cluster of autonomic computing, grid computing and utility computing. Cloud
providers are there to rescue their customers from the problem of dynamism. The providers focus on
resource sharing and in improving the performance. Energy consumption is the major factor to degrade the
performance. Reducing energy sprawl will bloom the performance. This paper delineates the different
techniques involved in scheduling the workload of the servers in order to minimize the energy sprawl.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
This document summarizes various techniques for improving energy efficiency in cloud computing. It begins with an introduction to energy consumption problems in cloud computing such as energy sprawl and increased electricity costs. It then reviews 10 existing energy efficient models including workload consolidation, virtual machine power metering, renewable energy-aware migration, and energy-aware scheduling. Each model is evaluated based on the hardware/datasets used, tools, and parameters analyzed. The document concludes that while cloud computing can be more energy efficient, further technological solutions and enhanced frameworks are still needed to achieve optimal energy efficiency.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud
computing requires many tasks to be executed by the provided resources to achieve good performance,
shortest response time and high utilization of resources. To achieve these challenges there is a need to
develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to
optimize energy consumption. This study accomplished with all the existing techniques mainly focus on
reducing energy consumption
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.
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.
Intelligent task processing using mobile edge computing: processing time opti...IAESIJAI
The fast-paced development of the internet of things led to the increase of computing resource services that could provide a fast response time, which is an unsatisfied feature when using cloud infrastructures due to network latency. Therefore, mobile edge computing became an emerging model by extending computation and storage resources to the network edge, to meet the demands of delay-sensitive and heavy computing applications. Computation offloading is the main feature that makes Edge computing surpass the existing cloud-based technologies to break limitations such as computing capabilities, battery resources, and storage availability, it enhances the durability and performance of mobile devices by offloading local intensive computation tasks to edge servers. However, the optimal solution is not always guaranteed by offloading computation, there-fore, the offloading decision is a crucial step depending on many parameters that should be taken in consideration. In this paper, we use a simulator to compare a two tier edge orchestrator architecture with the results obtained by implementing a system model that aims to minimize a task’s processing time constrained by time delay and the limited device’s computational resource and usage based on a modified version.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...neirew J
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
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.
A load balancing strategy for reducing data loss risk on cloud using remodif...IJECEIAES
This document summarizes a research paper that proposes a load balancing strategy called the re-modified throttled algorithm (RMTA) to reduce the risk of data loss on cloud computing. The RMTA aims to address limitations in previous algorithms by considering both the availability and capacity of virtual machines (VMs) during load distribution and migration processes. It maintains two index tables to track available and unavailable VMs. When a new request arrives, the RMTA load balancer selects a VM that has sufficient available storage and bandwidth to handle the request size without risk of data overflow. This is intended to minimize data loss or hampering during migration. The performance of the RMTA is evaluated through simulation and analysis on the CloudAnalyst tool.
Intelligent Workload Management in Virtualized Cloud EnvironmentIJTET Journal
Abstract— Cloud computing is a rising high performance computing environment with a huge scale, heterogeneous collection of self-sufficient systems and elastic computational design. To develop the overall performance of cloud computing, through the deadline constraint, a task scheduling replica is traditional for falling the system power utilization of cloud computing and recovering the yield of service providers. To improve the overall act of cloud environment, with the deadline constraint, a task scheduling model is conventional for reducing the system performance time of cloud computing and improving the profit of service providers. In favor of scheduling replica, a solving technique based on multi-objective genetic algorithm (MO-GA) is considered and the study is determined on programming rules, intersect operators, mixture operators and the scheme of arrangement of Pareto solutions. The model is designed based on open source cloud computing simulation platform CloudSim, to obtainable scheduling algorithms, the result shows that the proposed algorithm can obtain an enhanced solution, thus balancing the load for the concert of multiple objects.
The document proposes an Earthquake Disaster Based Resource Scheduling (EDBRS) framework for efficiently allocating cloud computing resources during earthquake disasters. The framework aims to minimize execution costs and times of cloud workloads by prioritizing urgent workloads related to emergency response. It models the resource scheduling problem and considers factors like workload deadlines, resource speeds and costs. The framework also presents algorithms for optimally assigning equal-length and variable-length workloads across multiple public and private cloud resources to balance performance and cost. The goal is to efficiently allocate cloud resources to disaster response zones based on urgency to reduce loss of life during earthquakes.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...ijccsa
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
KEYWORDS
Energy Consumption, Virtual Machine Placement, Harmony Search Algorithm, Server Consolidati
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract
Life time of Wireless device Networks (WSNs) has perpetually been a important issue and has received enlarged attention within the
recent years. Typically wireless device nodes area unit equipped with low power batteries that area unit impossible to recharge.
Wireless device networks ought to have enough energy to satisfy the specified necessities of applications. during this paper, we have a
tendency to propose Energy economical Routing and Fault node Replacement (EERFNR) formula to extend the lifespan of wireless
device network, cut back information loss and conjointly cut back device node replacement value. Transmission drawback and device
node loading drawback is solved by adding many relay nodes and composition device node’s routing mistreatment stratified Gradient
Diffusion. The device node will save backup nodes to cut back the energy for re-looking the route once the device node routing is
broken. Genetic formula can calculate the device nodes to exchange, apply the foremost on the market routing methods to replace the
fewest device nodes.
Keywords: Genetic algorithmic rule, stratified gradient diffusion, grade diffusion, wireless device networks
Energy efficient task scheduling algorithms for cloud data centerseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
IRJET- An Energy-Saving Task Scheduling Strategy based on Vacation Queuing & ...IRJET Journal
This document summarizes a research paper that proposes an energy-saving task scheduling strategy for cloud computing based on vacation queuing and optimization of resources. The proposed approach aims to minimize energy consumption, reduce processing time, and increase the number of sleeping nodes to make the system more efficient. It introduces a task scheduling algorithm that assigns tasks to computing nodes based on their properties using a load balancer. Simulation results show the proposed algorithm reduces energy consumption while meeting task performance compared to the vacation queuing algorithm. The document discusses related work on energy optimization techniques, presents the proposed approach, and analyzes results showing improvements in energy usage, time, and idle nodes.
This document summarizes and compares various scheduling algorithms used in cloud computing environments. It begins with an introduction to cloud computing and the need for scheduling algorithms in cloud environments. It then describes several existing scheduling algorithms, including compromised-time-cost scheduling, particle swarm optimization-based heuristic, improved cost-based algorithm, resource-aware scheduling, innovative transaction intensive cost-constraint scheduling, scalable heterogeneous earliest-finish-time algorithm, and multiple QoS constrained scheduling strategy of multi-workflows. These algorithms aim to optimize metrics such as execution time, cost, deadline, load balancing, and quality of service. The document concludes by comparing the different scheduling strategies.
Cost-Efficient Task Scheduling with Ant Colony Algorithm for Executing Large ...Editor IJCATR
This document summarizes a research paper that proposes an optimized ant colony optimization (ACO) algorithm for task scheduling in cloud computing. The goal is to minimize makespan and cost while improving fairness and load balancing. The ACO algorithm is adapted to prioritize and fairly allocate tasks to machines based on their performance. Simulations show the proposed ACO algorithm reduces makespan by 80% compared to Berger and greedy algorithms. It also increases processor utilization and balances loads across machines better than the other algorithms. The researchers conclude the optimized ACO approach improves resource usage and user satisfaction for task scheduling in cloud computing.
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.
This document discusses energy efficiency in cloud computing. It notes that cloud computing has led to large data centers with significant energy usage and carbon footprints. The resource allocation problem in cloud computing is treated as a linear programming problem aimed at minimizing energy consumption. Several heuristic algorithms are adopted and analyzed for resource allocation using an expected time to compute task model to develop green cloud computing solutions that reduce costs and environmental impacts.
An optimized scientific workflow scheduling in cloud computingDIGVIJAY SHINDE
The document discusses optimizing scientific workflow scheduling in cloud computing. It begins with definitions of workflow and cloud computing. Workflow is a group of repeatable dependent tasks, while cloud computing provides applications and hardware resources over the Internet. There are three cloud service models: SaaS, PaaS, and IaaS. The document explores how to efficiently schedule workflows in the cloud to reduce makespan, cost, and energy consumption. It reviews different scheduling algorithms like FCFS, genetic algorithms, and discusses optimizing objectives like time and cost. The document provides a literature review comparing various workflow scheduling methods and algorithms. It concludes with discussing open issues and directions for future work in optimizing workflow scheduling for cloud computing.
A Survey on Reducing Energy Sprawl In Cloud Computingaciijournal
Cloud computing is the cluster of autonomic computing, grid computing and utility computing. Cloud
providers are there to rescue their customers from the problem of dynamism. The providers focus on
resource sharing and in improving the performance. Energy consumption is the major factor to degrade the
performance. Reducing energy sprawl will bloom the performance. This paper delineates the different
techniques involved in scheduling the workload of the servers in order to minimize the energy sprawl.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
This document summarizes various techniques for improving energy efficiency in cloud computing. It begins with an introduction to energy consumption problems in cloud computing such as energy sprawl and increased electricity costs. It then reviews 10 existing energy efficient models including workload consolidation, virtual machine power metering, renewable energy-aware migration, and energy-aware scheduling. Each model is evaluated based on the hardware/datasets used, tools, and parameters analyzed. The document concludes that while cloud computing can be more energy efficient, further technological solutions and enhanced frameworks are still needed to achieve optimal energy efficiency.
A SURVEY: TO HARNESS AN EFFICIENT ENERGY IN CLOUD COMPUTINGijujournal
Cloud computing affords huge potential for dynamism, flexibility and cost-effective IT operations. Cloud
computing requires many tasks to be executed by the provided resources to achieve good performance,
shortest response time and high utilization of resources. To achieve these challenges there is a need to
develop a new energy aware scheduling algorithm that outperform appropriate allocation map of task to
optimize energy consumption. This study accomplished with all the existing techniques mainly focus on
reducing energy consumption
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.
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.
Intelligent task processing using mobile edge computing: processing time opti...IAESIJAI
The fast-paced development of the internet of things led to the increase of computing resource services that could provide a fast response time, which is an unsatisfied feature when using cloud infrastructures due to network latency. Therefore, mobile edge computing became an emerging model by extending computation and storage resources to the network edge, to meet the demands of delay-sensitive and heavy computing applications. Computation offloading is the main feature that makes Edge computing surpass the existing cloud-based technologies to break limitations such as computing capabilities, battery resources, and storage availability, it enhances the durability and performance of mobile devices by offloading local intensive computation tasks to edge servers. However, the optimal solution is not always guaranteed by offloading computation, there-fore, the offloading decision is a crucial step depending on many parameters that should be taken in consideration. In this paper, we use a simulator to compare a two tier edge orchestrator architecture with the results obtained by implementing a system model that aims to minimize a task’s processing time constrained by time delay and the limited device’s computational resource and usage based on a modified version.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...neirew J
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
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.
A load balancing strategy for reducing data loss risk on cloud using remodif...IJECEIAES
This document summarizes a research paper that proposes a load balancing strategy called the re-modified throttled algorithm (RMTA) to reduce the risk of data loss on cloud computing. The RMTA aims to address limitations in previous algorithms by considering both the availability and capacity of virtual machines (VMs) during load distribution and migration processes. It maintains two index tables to track available and unavailable VMs. When a new request arrives, the RMTA load balancer selects a VM that has sufficient available storage and bandwidth to handle the request size without risk of data overflow. This is intended to minimize data loss or hampering during migration. The performance of the RMTA is evaluated through simulation and analysis on the CloudAnalyst tool.
Intelligent Workload Management in Virtualized Cloud EnvironmentIJTET Journal
Abstract— Cloud computing is a rising high performance computing environment with a huge scale, heterogeneous collection of self-sufficient systems and elastic computational design. To develop the overall performance of cloud computing, through the deadline constraint, a task scheduling replica is traditional for falling the system power utilization of cloud computing and recovering the yield of service providers. To improve the overall act of cloud environment, with the deadline constraint, a task scheduling model is conventional for reducing the system performance time of cloud computing and improving the profit of service providers. In favor of scheduling replica, a solving technique based on multi-objective genetic algorithm (MO-GA) is considered and the study is determined on programming rules, intersect operators, mixture operators and the scheme of arrangement of Pareto solutions. The model is designed based on open source cloud computing simulation platform CloudSim, to obtainable scheduling algorithms, the result shows that the proposed algorithm can obtain an enhanced solution, thus balancing the load for the concert of multiple objects.
PROPOSED LOAD BALANCING ALGORITHM TO REDUCE RESPONSE TIME AND PROCESSING TIME...IJCNCJournal
Cloud computing is a new technology that brings new challenges to all organizations around the world.
Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As
for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development
of the scale and number of applications, this access is often threatened by overload. Therefore, this paper
our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud
computing to improve performance for end-user. We have simulated the proposed algorithm with the
CloudAnalyts simulation tool and this algorithm has improved response times and processing time of the
cloud data center.
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.
LOAD BALANCING ALGORITHM ON CLOUD COMPUTING FOR OPTIMIZE RESPONE TIMEijccsa
To improve the performance of cloud computing, there are many parameters and issues that we should consider, including resource allocation, resource responsiveness, connectivity to resources, unused resources exploration, corresponding resource mapping and planning for resource. The planning for the use of resources can be based on many kinds of parameters, and the service response time is one of them.
The users can easily figure out the response time of their requests, and it becomes one of the important QoSs. When we discover and explore more on this, response time can provide solutions for the distribution, the load balancing of resources with better efficiency. This is one of the most promising
research directions for improving the cloud technology. Therefore, this paper proposes a load balancing algorithm based on response time of requests on cloud with the name APRA (ARIMA Prediction of Response Time Algorithm), the main idea is to use ARIMA algorithms to predict the coming response time, thus giving a better way of effectively resolving resource allocation with threshold value. The experiment
result outcomes are potential and valuable for load balancing with predicted response time, it shows that prediction is a great direction for load balancing.
Scheduling Divisible Jobs to Optimize the Computation and Energy Costsinventionjournals
ABSTRACT : The important challenge in cloud computing environment is to design a scheduling strategy to handle jobs, and to process them in a heterogeneous environment with shared data centers. In this paper, we attempt to investigate a new analytical framework model that enables an existing private cloud data-center for scheduling jobs and minimizing the overall computation and energy cost together. Our model is based on Divisible Load Theory (DLT) model to derive closed-form solution for the load fractions to be assigned to each machines considering computation and energy cost. Our analysis also attempts to schedule the jobs such a way that cloud provider can gain maximum benefit for his service and Quality of Service (QoS) requirement user’s job. Finally, we quantify the performance of the strategies via rigorous simulation studies.
Resource-efficient workload task scheduling for cloud-assisted internet of th...IJECEIAES
One of the most challenging tasks in the internet of things-cloud-based environment is the resource allocation for the tasks. The cloud provides various resources such as virtual machines, computational cores, networks, and other resources for the execution of the various tasks of the internet of things (IoT). Moreover, some methods are used for executing IoT tasks using an optimal resource management system but these methods are not efficient. Hence, in this research, we present a resource-efficient workload task scheduling (RWTS) model for a cloud-assisted IoT environment to execute the IoT task which utilizes few numbers of resources to bring a good tradeoff, achieve high performance using fewer resources of the cloud, compute the number of resources required for the execution of the IoT task such as bandwidth and computational core. Furthermore, this model mainly focuses to reduce energy consumption and also provides a task scheduling model to schedule the IoT tasks in an IoT-cloud-based environment. The experimentation has been done using the Montage workflow and the results have been obtained in terms of execution time, power sum, average power, and energy consumption. When compared with the existing model, the RWTS model performs better when the size of the tasks is increased.
This document summarizes a research paper on developing an efficient and dynamic resource allocation mechanism for cloud infrastructure services based on genetic algorithms. The mechanism aims to reduce energy utilization and latency by exactly matching resource requirements to virtual machine capacities while tolerating variations in available infrastructure and workload requirements. It proposes classifying workloads and machines based on their heterogeneities and allocating tasks in a way that diversifies machine usage to reduce risks from potential attackers. The genetic algorithm-based approach is compared to other scheduling methods and experimental results demonstrate its effectiveness in lowering power consumption and delay. Future work could account for machines with capacities exceeding available resources and optimize allocation based on predicted capacities.
Task scheduling is an important aspect to improve the utilization of resources in the Cloud Computing. This paper proposes a Divide and Conquer based approach for heterogeneous earliest finish time algorithm. The proposed system works in two phases. In the first phase it assigns the ranks to the incoming tasks with respect to size of it. In the second phase, we properly assign and manage the task to the virtual machine with the consideration of ideal time of respective virtual machine. This helps to get more effective resource utilization in Cloud Computing. The experimental results using Cybershake Scientific Workflow shows that the proposed Divide and Conquer HEFT performs better than HEFT in terms of task's finish time and response time. The result obtained by experimentally demonstrate that the proposed DCHEFT performance superiorly.
The cloud environment offers an appropriate location for the implementation of huge range of scientific applications. However, in the existing workflows the major dispute is to assign the assets to the tasks in a well-organized way so, that it acquires less finishing time and load on every virtual machines will be impartial. To overcome this problem, GA_ MINMIN has been proposed that combines the features of GA and MINMIN scheduling algorithms. This algorithm is fundamentally a three-layer structure where GA is connected on the main level and hereditary calculation was performed for distributing belonging in an advanced way. At second level, the execution request of the assignments was resolved based on their size. This would be finished with the assistance of MIN-MIN. At third level, all the virtual machines have been running in parallel so that task response time will get decreased with more advanced outcomes. The proposed algorithm has been executed on the simulation environment.
An advanced ensemble load balancing approach for fog computing applicationsIJECEIAES
Fog computing has emerged as a viable concept for expanding the capabilities of cloud computing to the periphery of the network allowing for efficient data processing and analysis from internet of things (IoT) devices. Load balancing is essential in fog computing because it ensures optimal resource utilization and performance among distributed fog nodes. This paper proposed an ensemble-based load-balancing approach for fog computing environments. An advanced ensemble load balancing approach (AELBA) uses real-time monitoring and analysis of fog node metrics, such as resource utilization, network congestion, and service response times, to facilitate effective load distribution. Based on the ensemble's collective decision-making, these metrics are fed into a centralized load-balancing controller, which dynamically adjusts the load distribution across fog nodes. Performance of the proposed ensemble load-balancing approach is evaluated and compared it to traditional load-balancing techniques in fog using extensive simulation experiments. The results demonstrate that our ensemble-based approach outperforms individual load-balancing algorithms regarding response time, resource utilization, and scalability. It adapts to dynamic fog environments, providing efficient load balancing even under varying workload conditions.
Similar to IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUD (20)
NEW ONTOLOGY RETRIEVAL IMAGE METHOD IN 5K COREL IMAGESijcax
This document summarizes a research paper that proposes a new ontology-based method for automatic image retrieval and annotation using 5,000 images from the Corel dataset. The method combines global and regional visual features with contextual relationships defined in an ontology. It creates a new ontology based on WordNet to semantically relate tags and reduce gaps between low-level features and high-level concepts. Experimental results show the proposed method increases annotation accuracy compared to other methods.
THE STUDY OF CUCKOO OPTIMIZATION ALGORITHM FOR PRODUCTION PLANNING PROBLEMijcax
Constrained Nonlinear programming problems are hard problems, and one of the most widely used and
common problems for production planning problem to optimize. In this study, one of the mathematical
models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is
efficient method to solve continues non linear problem. Moreover, mentioned models of production
planning solved with Genetic algorithm and Lingo software and the results will compared. The Cuckoo
Algorithm is suitable choice for optimization in convergence of solution
COMPARATIVE ANALYSIS OF ROUTING PROTOCOLS IN MOBILE AD HOC NETWORKSijcax
This document compares the performance of five routing protocols (AODV, DSR, DSDV, OLSR, DYMO) in mobile ad hoc networks through simulations. It summarizes each protocol and discusses the simulation setup. The protocols are categorized as reactive, proactive, or hybrid. Key performance metrics like packet delivery ratio, end-to-end delay, and routing load are evaluated under varying pause times using the NS-2 simulator. The analysis seeks to determine the best operational conditions for each protocol in mobile ad hoc networks.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school
students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and
science were studied and compared. The purpose of this research is to predict the academic major of high
school students using Bayesian networks. The effective factors have been used in academic major selection
for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on
each other, discretization data and processing them was performed by GeNIe. The proper course would be
advised for students to continue their education.
A Multi Criteria Decision Making Based Approach for Semantic Image Annotation ijcax
Automatic image annotation has emerged as an important research topic due to its potential application on
both image understanding and web image search. This paper presents a model, which integrates visual
topics and regional contexts to automatic image annotation. Regional contexts model the relationship
between the regions, while visual topics provide the global distribution of topics over an image. Previous
image annotation methods neglected the relationship between the regions in an image, while these regions
are exactly explanation of the image semantics, therefore considering the relationship between them are
helpful to annotate the images. Regional contexts and visual topics are learned by PLSA (Probability
Latent Semantic Analysis) from the training data. The proposed model incorporates these two types of
information by MCDM (Multi Criteria Decision Making) approach based on WSM (Weighted Sum
Method). Experiments conducted on the 5k Corel dataset demonstrate the effectiveness of the proposed
model.
On Fuzzy Soft Multi Set and Its Application in Information Systems ijcax
Research on information and communication technologies have been developed rapidly since it can be
applied easily to several areas like computer science, medical science, economics, environments,
engineering, among other. Applications of soft set theory, especially in information systems have been
found paramount importance. Recently, Mukherjee and Das defined some new operations in fuzzy soft
multi set theory and show that the De-Morgan’s type of results hold in fuzzy soft multi set theory with
respect to these newly defined operations. In this paper, we extend their work and study some more basic
properties of their defined operations. Also, we define some basic supporting tools in information system
also application of fuzzy soft multi sets in information system are presented and discussed. Here we define
the notion of fuzzy multi-valued information system in fuzzy soft multi set theory and show that every fuzzy
soft multi set is a fuzzy multi valued information system.
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
SPAM FILTERING SECURITY EVALUATION FRAMEWORK USING SVM, LR AND MILR ijcax
The Pattern classification system classifies the pattern into feature space within a boundary. In case
adversarial applications use, for example Spam Filtering, the Network Intrusion Detection System (NIDS),
Biometric Authentication, the pattern classification systems are used. Spam filtering is an adversary
application in which data can be employed by humans to attenuate perspective operations. To appraise the
security issue related Spam Filtering voluminous machine learning systems. We presented a framework for
the experimental evaluation of the classifier security in an adversarial environments, that combines and
constructs on the arms race and security by design, Adversary modelling and Data distribution under
attack. Furthermore, we presented a SVM, LR and MILR classifier for classification to categorize email as
legitimate (ham) or spam emails on the basis of thee text samples.
Visually impaired people face many problems in their day to day lives. Among them, outdoor navigation is
one of the major concerns. The existing solutions based on Wireless Sensor Networks(WSN) and Global
Positioning System (GPS) track ZigBee units or RFID (Radio Frequency Identification) tags fixed on the
navigation system. The issues pertaining to these solutions are as follows: (1) It is suitable only when the
visually impaired person is commuting in a familiar environment; (2) The device provides only a one way
communication; (3) Most of these instruments are heavy and sometimes costly. Preferable solution would
be to make a system which is easy to carry and cheap.
The objective of this paper is to break down the technological barriers, and to propose a system by
developing an Android App which would help a visually impaired person while traveling via the public
transport system like Bus. The proposed system uses an inbuilt feature of smart phone such as GPS
location tracker to track the location of the user and Text to Speech converter. The system also integrates
Google Speech to Text converter for capturing the voice input and converts them to text. This system
recommends the requirement of installing a GPS module in buses for real time tracking. With minor
modification, this App can also help older people for independent navigation.
INTELLIGENT AGENT FOR PUBLICATION AND SUBSCRIPTION PATTERN ANALYSIS OF NEWS W...ijcax
The rapid growth of Internet has revolutionized online news reporting. Many users tend to use online news
websites to obtain news information. When considering Sri Lanka, there are numerous news websites,
which are subscribed on a daily basis. With the rise in this number of news websites, the Sri Lankan
authorities of media face the issue of lacking a proper methodology or a tool which is capable of tracking
and regulating publications made by different disseminators of news.
This paper proposes a News Agent toolbox which periodically extracts news articles and associated
comments with the aid of a concept called Mapping Rules; to classify them into Personalized Categories
defined in terms of keywords based Category Profiles. The proposed tool also analyzes comments made by
the readers with the aid of simple statistical techniques to discover the most popular news articles and
fluctuations in popularity of news stories.
ADVANCED E-VOTING APPLICATION USING ANDROID PLATFORMijcax
The advancement in the mobile devices, wireless and web technologies given rise to the new application
that will make the voting process very easy and efficient. The E-voting promises the possibility of
convenient, easy and safe way to capture and count the votes in an election[1]. This research project
provides the specification and requirements for E-Voting using an Android platform. The e-voting means
the voting process in election by using electronic device. The android platform is used to develop an evoting application. At first, an introduction about the system is presented. Sections II and III describe all
the concepts (survey, design and implementation) that would be used in this work. Finally, the proposed evoting system will be presented. This technology helps the user to cast the vote without visiting the polling
booth. The application follows proper authentication measures in order to avoid fraud voters using the
system. Once the voting session is completed the results can be available within a fraction of seconds. All
the candidates vote count is encrypted and stored in the database in order to avoid any attacks and
disclosure of results by third person other than the administrator. Once the session is completed the admin
can decrypt the vote count and publish results and can complete the voting process.
The design of silicon chips in every semiconductor industry involves the testing of these chips with other
components on the board. The platform developed acts as power on vehicle for the silicon chips. This
Printed Circuit Board design that serves as a validation platform is foundational to the semiconductor
industry.
The manual/repetitive design activities that accompany the development of this board must be minimized to
achieve high quality, improve design efficiency, and eliminate human-errors. One of the time consuming
tasks in the board design is the Trace Length matching. The paper aims to reduce the length matching time
by automating it using SKILL scripts.
RESEARCH TRENDS İN EDUCATIONAL TECHNOLOGY İN TURKEY: 2010-2018 YEAR THESIS AN...ijcax
The purpose of this research is the analysis using meta-analysis of studies in the field of Educational
Technology in Turkey and in the field is to demonstrate how to get to that trend. For this purpose, a total of
263 studies were analyzed including 98 theses and 165 articles published between 2010-2018. Purpose
sampling method was used when selecting publications. In the research, while selecting articles and theses;
Turkey addressed; YOK Tez Tarama Database, Journal of Hacettepe University Faculty of Education,
Educational Sciences : Theory & Practice Journal, Education and Science Journal, Elementary Education
Online Journal, The Turkish Online Journal of Education and The Turkish Online Journal of Educational
Technology used in journals. Publications have been reviewed under 11 criteria. Index, year of
publication, research scope, method, education level, sample, number of samples, data collection methods,
analysis techniques, and research tendency, research topics in Educational Technology Research in Turkey
has revealed. The data is interpreted based on percentage and frequency and the results are shown using
the table.
RESEARCH TRENDS İN EDUCATIONAL TECHNOLOGY İN TURKEY: 2010-2018 YEAR THESIS AN...ijcax
The purpose of this research is the analysis using meta-analysis of studies in the field of Educational
Technology in Turkey and in the field is to demonstrate how to get to that trend. For this purpose, a total of
263 studies were analyzed including 98 theses and 165 articles published between 2010-2018. Purpose
sampling method was used when selecting publications. In the research, while selecting articles and theses;
Turkey addressed; YOK Tez Tarama Database, Journal of Hacettepe University Faculty of Education,
Educational Sciences : Theory & Practice Journal, Education and Science Journal, Elementary Education
Online Journal, The Turkish Online Journal of Education and The Turkish Online Journal of Educational
Technology used in journals. Publications have been reviewed under 11 criteria. Index, year of
publication, research scope, method, education level, sample, number of samples, data collection methods,
analysis techniques, and research tendency, research topics in Educational Technology Research in Turkey
has revealed. The data is interpreted based on percentage and frequency and the results are shown using
the table
IMPACT OF APPLYING INTERNATIONAL QUALITY STANDARDS ON MEDICAL EQUIPMENT IN SA...ijcax
This document summarizes a study on the impact of applying international quality standards on medical equipment in Saudi Arabia. A questionnaire was distributed to 300 healthcare professionals in public and private hospitals to collect data. The results showed that around 80% of respondents strongly agreed that international standards like ISO have significantly improved safety, testing and calibration of medical devices, use of consistent terminology, and compatibility/interoperability. Adopting global quality standards appears to have reduced risks associated with medical equipment and enhanced patient safety in Saudi Arabia according to the healthcare workers surveyed.
SPAM FILTERING SECURITY EVALUATION FRAMEWORK USING SVM, LR AND MILR ijcax
The Pattern classification system classifies the pattern into feature space within a boundary. In case adversarial applications use, for example Spam Filtering, the Network Intrusion Detection System (NIDS), Biometric Authentication, the pattern classification systems are used. Spam filtering is an adversary
application in which data can be employed by humans to attenuate perspective operations. To appraise the
security issue related Spam Filtering voluminous machine learning systems. We presented a framework for the experimental evaluation of the classifier security in an adversarial environments, that combines and constructs on the arms race and security by design, Adversary modelling and Data distribution under
attack. Furthermore, we presented a SVM, LR and MILR classifier for classification to categorize email as legitimate (ham) or spam emails on the basis of thee text samples
Developing Product Configurator Tool Using CADs’ API with the help of Paramet...ijcax
Order placingis a crucial phase of lifecycle of a Mass-customizable product and seeks improvement in
Mechanical industry. ‘Product Configurator’ is a good solution to bring in data transparency and speed
up the process. Configuration tools arebeing used on a very small scale,reasons being lack of awareness
and dearer costs of existing tools. In this research work a product configurator is developedfor
Hydraulic Actuator (HA).This method uses Applicable Programing Interface (API) of a CAD tool coupled
with Visual Basics (VB) and MS Excel.Itis a standaloneapplication of VB and its integration into web
portal can be the future scope. The final aim was to reduce time delay at CRM phase,bring more
transparency in the ordering system and to establish a method which, small and medium scale enterprises
canafford. Trails on the tool developed generated Part-Assembly drawings, BOM and JT files in
moments.
DESIGN AND DEVELOPMENT OF CUSTOM CHANGE MANAGEMENT WORKFLOW TEMPLATES AND HAN...ijcax
A large no. of automobile companies finding a convinient way to manage design changes with the use of
various PLM techniques. Change in any product is something that should occur on timely basis to match
up with customer requirement and cost reduction. The change made in the vehicle designs directly affects
various concerned agencies. Automobile Vehicle structures contains thousands of parts and if there is any
change is occurring in child parts then it becomes important to track that impacted part, propose a solution
on that part and release a new assembly structure with feasible changes such that all efforts need to be
done for cost reduction.
Visually impaired people face many problems in their day to day lives. Among them, outdoor navigation is
one of the major concerns. The existing solutions based on Wireless Sensor Networks(WSN) and Global
Positioning System (GPS) track ZigBee units or RFID (Radio Frequency Identification) tags fixed on the
navigation system. The issues pertaining to these solutions are as follows: (1) It is suitable only when the
visually impaired person is commuting in a familiar environment; (2) The device provides only a one way
communication; (3) Most of these instruments are heavy and sometimes costly. Preferable solution would
be to make a system which is easy to carry and cheap.
The objective of this paper is to break down the technological barriers, and to propose a system by
developing an Android App which would help a visually impaired person while traveling via the public
transport system like Bus. The proposed system uses an inbuilt feature of smart phone such as GPS
location tracker to track the location of the user and Text to Speech converter. The system also integrates
Google Speech to Text converter for capturing the voice input and converts them to text. This system
recommends the requirement of installing a GPS module in buses for real time tracking. With minor
modification, this App can also help older people for independent navigation.
TEACHER’S ATTITUDE TOWARDS UTILISING FUTURE GADGETS IN EDUCATION ijcax
Today’s era is an era of modernization and globalization. Everything is happening at a very fast rate
whether it is politics, societal reforms, commercialization, transportation, or educational innovations. In
every few second, technology grows either in the form of arrival of the new devices/gadgets with millions of
apps and these latest technological objects may be in the form of hardware/software devices. We are the
educationists, teachers, students and stakeholders of present Indian educational system. These
gadgets/devices are partly being used by us or most of them are still unaware of these innovative
technologies due to the mass media or economical factor. So, there is a need to improvise ourselves
towards utilizing the future gadgets in order to explore the educational uses, barriers and preparatoryneeds of these available devices for educational purposes. This paper aims to study the opinion of the
teacher-educators about the usage of future gadgets in higher education. It will also contribute towards
establishing the list of latest technological devices, and how it can enhances the process of teachinglearning system.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
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Date: May 29, 2024
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IMPROVING REAL TIME TASK AND HARNESSING ENERGY USING CSBTS IN VIRTUALIZED CLOUD
1. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
DOI:10.5121/ijcax.2016.3101 1
IMPROVING REAL TIME TASK AND HARNESSING
ENERGY USING CSBTS IN VIRTUALIZED CLOUD
Malathi.P
1
, Arumugam.S
2
1
M.E.Scholar, Department of Computer Science & Engineering, Nandha Engineering
College, Erode-638052, Tamil Nadu, India
2
Professor, Department of Computer Science & Engineering, Nandha Engineering
College, Erode-638052, Tamil Nadu, India
ABSTRACT
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.
KEYWORDS
Cloud computing, Energy consumption, Virtualization, real time tasks, cluster scoring based task
scheduling.
1. INTRODUCTION
Cloud computing that works for the problem of dynamism. Dynamism is the demand keeps on
changing. Sharing resource is another advantage that helps the cloud providers to attain optimum
utilization of resources. The virtualization technique is to scale up and scale down the resources
according to the user demands in figure1.
Cloud computing provides packaged services. It provides that large scale data centers cuddled
with the cloud services, which results in consuming enormous energy with huge cost [15]. There
is a need for the cloud providers to build and manage for the low cost [12].several techniques
have been attempted to minimize the energy consumption such as virtual machine consolidation
and dynamic server provisioning [19].there were many techniques for the software problem and
the latest development for the hardware solutions are DVFS, power capping [12].renewable
energy aware service migration is mainly used to migrate services throughout the geographical
locations [8].IAAS-clouds that fully nucleus with the virtualization [10].
2. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
2
Figure 1 Virtualization Model
The real time tasks are executed in a timely deterministic manner and scalable [15]. It is
consider to serve real-time application is to be processed without buffering delays. The time
required for processing is measured in seconds.
A key feature of a real time task is the amount of time it takes to accept and complete
a task. A hard real-time task has less jitter than a soft real-time task. A real task that can
customarily meet a deadline is a soft real-time task, but if it can meet a
deadline deterministically it is a hard real-time task.
Objectives:
To establish an enabling scheduling architecture for rolling-horizon optimization with
vertical scheduling operation.
Dynamically adjust the virtual machines to save the energy.
Cluster score values are recalculated even during the task is partially completed.
Storage capacity of cluster resources is considered for the evaluation.
Multiple a, b and c values are calculated for each sub task and then the cluster assignment
is effective than existing system.
Replication method assists in faster task completion.
Contribution: The extensive contributions of this paper are as follows:
We proposed a cluster scoring based task scheduling scheme by rolling-horizon
(RH) optimization, and we deployed an enabling scheduling architecture for
rolling-horizon optimization with vertical scaling.
We established some policies for VMs‘ creation, migration and cancellation in
order to save the energy.
We put forward a cluster scoring based task scheduling for real-time independent
tasks in a cloud.
The remaining paper is organized as follows: Section 2 presents overview, Section 3 presents the
related work, and Section 4 presents proposed work, section 5 conclusions and future work.
3. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
3
2. OVERVIEW
2.1 Energy –wear and tear
The catastrophic in cloud is energy sprawl. This is because of two reasons. Work overload and
improper scheduling [5, 10] is the major factor and next is due to the increment in monetary cost
of electricity [13]. The manual failure will be overcome by using virtualization and monitoring
[12]. Second problem would be resolved by harnessing the renewable energy [9]. The two
bulldoze in energy consumption problem are shown in Figure 2
Figure2. Bulldoze in energy consumption
2.1.1 Task Scheduling
The essential for cloud computing is task scheduling. Based on various parameters the task is to
be scheduled. It is used to finish the task on time and is responsible to improve flexibility in cloud
and reliability of systems in cloud. The tasks are uncertain, so scheduling is deployed to
overcome the uncertainty [15].
2.1.2 Virtualization
Virtualization technology which enables the creation, migration and cancellation of virtual
machines [5].when the task needs excess space, low and over utilization of resources leads to
migration. Virtualization enables the load balancing, consolidation, and hot spot mitigation [4]. It
allocates data center resources dynamically based on user needs and optimizing number of
servers to support green computing.
2.2 Real Time Tasks
Many applications are deployed in clouds with real time nature [15].real time tasks are not only
depends on the correctness it takes time instant on account. Missing deadlines will leads to the
severe consequences. The project work considers the real time tasks. The real time tasks are much
more important than the energy consumption problem.
energy
consumption
software
level
hardware
level
4. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
4
3. RELATED WORK
3.1. Workload Consolidation
Srikantaiah et al. [22] have brought up the relationship between energy consumption and
resource. In a same while the act of workload consolidation were evaluated. According to the
Pareto frontier algorithm, the authors combined the tasks and balance energy consumption by
computing optimal points. Profiling step uses an energy aware resource allocation mechanism. It
resolves the bin packing and quadratic assignment problems.
3.2. Virtual Machine Power Metering
ChonglinGu et al. [12] used virtual machine power metering to measure the power consumption
of data centers. Virtual power metering has a following three steps such as information collection,
modelling, and estimation. Power meter is composed with internal and external meter. It has two
methods such as white box method and black box method. The black box method is in trend. The
virtual machine service billing, power budgeting, power saving scheduling is measured by the
power meter.
3.3. Energy Conservation Techniques
MehiarDabbaghet al. [22] have analysed power management techniques that reveal the
virtualization technology is used to save energy. The author considered the workload prediction,
virtual machine placement and workload consolidation. The unused physical machines are used
to save energy by Workload prediction. The overload problem is taken into account and resolved
by the virtual machine placement and workload consolidation .It achieves the green computing.
Energy savings can be obtained by turning number of servers into lower power state.
3.4. Virtual Machine Scheduling
Dong Jiankang et al. [20] virtual machine scheduling has the combo of vm placement and vm
migration. Virtual machine placement is to place the machine to finish the job on time .virtual
machine migration is to move the machines according to the workload. Algorithm is implemented
by c++.Compared to random algorithm the energy consumption is low. It considers the
parameters for evaluation are total communication traffic and maximum link utilization.
3.5. Renewable energy – aware migration
UttamMandalet al. [8] has deployed the virtual machine migration renewable energy aware cloud
service to adjust energy demand using resource allocation technique. Renewable energy is used in
the place of non renewable energy. By using the renewable energy reduces the carbon foot print
and greenhouse gas emission. It has an ability to replace the 40-50%0f brown energy by green
energy.
3.6. Tasks Oriented Energy-Aware Scheduling
Xiaomin Zhu et al. [15] have analyzed EARH algorithm. Algorithm employs energy aware
scheduling integrated with rolling horizon optimization policy. The real time controller and
5. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
5
virtual machine controller are composed in rolling horizon to hold new task along with the
waiting task. Resource scale up and scale down are taken into account by the algorithm. It was
implemented by cloudsim toolkit. The results indicate that improved the scheduling quality and it
conserves the energy.
3.7. Ant Colony System
FahimehFarahnakian et al. [19] used dynamic consolidation of virtual machines and live
migration. The virtual machine consolidation is based on the ant colony system. It have the
artificial ants to migrate the virtual machines. It have global and local agent. Consolidating virtual
machine into reduced number of physical machine by Global agent. The physical machine status
is detected by the Local agent. Cloudsim toolkit is used for implementation. The energy
consumption is reduced up to 53.4% by this technique.
3.8. Dynamic Resource Allocation
Zhen Xiao et al. [4] explained virtualization technology. Due to excess space capacity, hot spot
and load imbalance which migrates the machine. Virtualization enables the load balancing,
consolidation, and hot spot mitigation [4]. It allocates data center resources dynamically based on
user needs and optimizing number of servers to support green computing. The uneven utilization
of server is measured by the SKEWNESSS algorithm. Algorithm is simulated by trace driven
simulation. It achieves green computing.
3.9. Energy-Aware Scheduling
Li Hongyou et al. [6] have proposed the workload aware consolidation technique. Algorithm
focused to investigate the problem of consolidating heterogeneous workloads and it tries to
execute all virtual machines with fewer amounts of physical machines. When the machine is
under loaded it turnoff the unused physical servers. It focuses on the multi-dimensional resources.
Live migration algorithm to migrate the machines dynamically. cloudsim tool kit for simulation.
3.10. Energy-Aware Task Consolidation
Ching-Hsien Hsu et al. [11] have proposed a technique which minimizes energy consumption is
energy-aware task consolidation (ETC) technique. It restricts CPU use below a specified peak
threshold. The major work of ETC is Task consolidation. The task migration is considered as
network latency by energy cost model. For evaluation ETC is compared with the MAXUTIL.
MAXUTIL is aspires to maximize cloud computing resources and is greedy algorithm. The
simulation result shows that 17% improvement.
4. PROPOSED WORK
The proposed system which is illustrated in Figure 3 shows how the jobs are assigned to the
cluster of resources. Jobs can be divided into n number of jobs based on the data and computation
intensive. The task scheduler allocates the job by computing ATP, ACP to the cluster. If there is a
need for storage capacity and bandwidth in high rate to assign the job it divides into subtasks. The
cluster of resources includes CPU Available, Computation power (CP), CPU Speed, Load and
Memory Available.
6. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
6
Figure3. Work of the algorithm
Step 1: Cluster Details
In this module, the cluster id is given with ATP (Average Transmission Power) and ACP
(Average Computing Power) and CS (Cluster Score) value set to zero. The details are saved in
‗Cluster‘ table.
Step 2: Resource Collection
In this module, collecting the resource id, Resource Name, IPAddress, CPU MHz, CPU MHz
available, Load Percent, CP (available computing power) and Storage Capacity. The details are
saved in ‗Resources‘ table.
Step 3: Assign Cluster to Resource
In this module, the cluster id is fetched from ‗Clusters‘ table and resource id is retrieved from
‗Resource‘ table. The ‗Clusters_Resources‘ table hold the selected ids.
Step 4: Add Job
In this module, the job id, name, required RAM in MHz, required hard disk storage in MB, CPU
MHz and network bandwidth is keyed in and saved into ‗Jobs‘ table.
Step 5: Cluster Score Calculation for Data Intensive and Computation Intensive Strategy
In this module, the clustering score is calculated based on the following formula.
CSi =a. ATPi+ b. ACPi
7. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
7
Where,
CSi =cluster score which is computed by using the average transmission power and
average computing power.
a and b are the weightage value of ATP and ACP
Bandwidth_availablei,j is the available bandwidth between clusters
ACPi means the average available CPU power cluster i is provided for the job
ACP= {(CPU_speedk is the CPU speed of resource k in cluster i +
loadk is the current load of the resource k in cluster i,) /
n is the number of resources in cluster i}
CPk indicates the available computing power of resource k.
The transmission power and the computing power of a resource direct focus on the performance
of task execution. Task scheduling considers the two parameters for evaluation. Large bandwidth
in the resources of the same cluster on that time we have to consider the different bandwidth.
To adjust the score, Local update and global update are used. The task is to be obtained from the
user and it will be sub divided according to data intensive and computation intensive. Next is to
compute the ACP, ATP and CS. the task is allocated to high cluster score. After completing the
task the information server sends the alert to the user and recomputes the cluster score.
Step 6 Cluster Score Calculation with Storage Capacity
In addition with existing formula, the storage capacity is also calculated like Average
Transmission Power and so sum of a and b is 1. All other calculations are used in same scenario
as above module. The job is split into tasks with a and b values for each sub task. So one cluster
is assigned for one task and others cluster for other tasks. Likewise jobs are considered as replica
units and so more clusters are assigned for each task.
5. CONCLUSION AND FUTUREWORK
The proposed strategy to implement a cluster scoring method to schedule jobs in grid
environment. CSBTS selects the feasible resource to execute a job according to the status of
resources. Local and global update rules are applied to get the latest status of each resource. Local
update rule updates the status of the resource and select the cluster to execute the job and the Job
Scheduler uses the latest information to assign the next job. Global update gives the final
completion of tasks. The Job Scheduler supplies the latest information of all resources and
clusters such that the Job Scheduler can select the feasible resource for the next job.
Virtualization technology is to switch off the idle machines. Finally the project aims to reduce the
completion time and to harness an efficient energy. The future work is to implement this concept
in real time.
8. International Journal of Computer-Aided Technologies (IJCAx) Vol.3, No.1, January 2016
8
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