Cloud Computing is an emerging technology in the area of parallel and distributed computing. Clouds consist of a collection of virtualized resources, which include both computational and storage facilities that can be provisioned on demand, depending on the users' needs. Job scheduling is one of the major activities performed in all the computing environments. Cloud computing is one the upcoming latest technology which is developing drastically. To efficiently increase the working of cloud computing environments, job scheduling is one the tasks performed in order to gain maximum profit. In this paper we proposed a new scheduling algorithm based on priority and that priority is based on ratio of job and resource. To calculate priority of job we use analytical hierarchy process. In this paper we also compare result with other algorithm like First come first serve and round robin algorithms.
A survey of various scheduling algorithm in cloud computing environmenteSAT 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.
GROUPING BASED JOB SCHEDULING ALGORITHM USING PRIORITY QUEUE AND HYBRID ALGOR...ijgca
This document describes a proposed grouping based job scheduling algorithm for grid computing that aims to maximize resource utilization and minimize job processing times. It discusses related work on job scheduling algorithms and then presents the steps of the proposed algorithm. The algorithm uses shortest job first, first-in first-out, and round robin scheduling to process jobs in groups. The algorithm is evaluated experimentally in MATLAB and shown to reduce total job processing time compared to using only first-in first-out scheduling. Graphs demonstrate the processing time improvements achieved by the combined scheduling approach.
This document proposes a new task scheduling algorithm called Dynamic Heterogeneous Shortest Job First (DHSJF) for heterogeneous cloud computing systems. DHSJF aims to improve performance metrics like reduced makespan and low energy consumption by considering the heterogeneity of resources and workloads. It discusses existing scheduling algorithms like Round Robin, First Come First Serve and their limitations. The proposed DHSJF algorithm prioritizes tasks with the shortest estimated completion time to optimize resource utilization and improve overall performance of the cloud computing system. Simulation results show that DHSJF provides better results for metrics like average waiting time and turnaround time as compared to Round Robin and First Come First Serve scheduling algorithms.
This document proposes a fair scheduling algorithm with dynamic load balancing for grid computing. It begins by introducing grid computing and the need for efficient load balancing algorithms to distribute tasks. It then describes dynamic load balancing approaches, including information, triggering, resource type, location, and selection policies. The proposed algorithm uses a fair scheduling approach that assigns tasks to processors based on their estimated fair completion times to ensure tasks receive equal shares of computing resources. It also includes a dynamic load balancing component that migrates tasks between processors to maintain balanced loads across all resources. Simulation results demonstrated the algorithm achieved balanced loads across processors and reduced overall task completion times.
Service Request Scheduling in Cloud Computing using Meta-Heuristic Technique:...IRJET Journal
This document discusses using the Teaching Learning Based Optimization (TLBO) meta-heuristic technique for service request scheduling between users and cloud service providers. TLBO is a nature-inspired algorithm that mimics the teacher-student learning process. It is compared to other meta-heuristic algorithms like Genetic Algorithm. The key steps of TLBO involve initializing a population, evaluating fitness, selecting the best solution as teacher, and updating the population through teacher and learner phases until termination criteria is met. The document proposes using number of users and virtual machines as parameters for TLBO scheduling in cloud computing. MATLAB simulation results show the initial and final iterations converging to an optimal scheduling solution.
The document discusses using a genetic algorithm to schedule tasks in a cloud computing environment. It aims to minimize task execution time and reduce computational costs compared to the traditional Round Robin scheduling algorithm. The proposed genetic algorithm mimics natural selection and genetics to evolve optimal task schedules. It was tested using the CloudSim simulation toolkit and results showed the genetic algorithm provided better performance than Round Robin scheduling.
A novel scheduling algorithm for cloud computing environmentSouvik Pal
The document describes a proposed genetic algorithm-based scheduling approach for cloud computing environments. It aims to minimize waiting time and queue length. The algorithm first permutes task burst times and finds minimum waiting times using FCFS and genetic algorithms. It then applies a queuing model to the sequences with minimum waiting time from each approach. Experimental results on 4 sample tasks show the genetic algorithm reduces waiting time compared to FCFS. The genetic operators of selection, crossover and mutation are applied to evolve optimal task scheduling sequences.
Scheduling Algorithm Based Simulator for Resource Allocation Task in Cloud Co...IRJET Journal
This document proposes a scheduling algorithm for allocating resources in cloud computing based on the Project Evaluation and Review Technique (PERT). It aims to address issues like starvation of lower priority tasks. The algorithm models task allocation as a directed acyclic graph and uses PERT to schedule critical and non-critical tasks, prioritizing higher priority tasks. The algorithm is evaluated against other scheduling methods and shows improvements in reducing completion time and optimizing resource allocation for all tasks.
A survey of various scheduling algorithm in cloud computing environmenteSAT 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.
GROUPING BASED JOB SCHEDULING ALGORITHM USING PRIORITY QUEUE AND HYBRID ALGOR...ijgca
This document describes a proposed grouping based job scheduling algorithm for grid computing that aims to maximize resource utilization and minimize job processing times. It discusses related work on job scheduling algorithms and then presents the steps of the proposed algorithm. The algorithm uses shortest job first, first-in first-out, and round robin scheduling to process jobs in groups. The algorithm is evaluated experimentally in MATLAB and shown to reduce total job processing time compared to using only first-in first-out scheduling. Graphs demonstrate the processing time improvements achieved by the combined scheduling approach.
This document proposes a new task scheduling algorithm called Dynamic Heterogeneous Shortest Job First (DHSJF) for heterogeneous cloud computing systems. DHSJF aims to improve performance metrics like reduced makespan and low energy consumption by considering the heterogeneity of resources and workloads. It discusses existing scheduling algorithms like Round Robin, First Come First Serve and their limitations. The proposed DHSJF algorithm prioritizes tasks with the shortest estimated completion time to optimize resource utilization and improve overall performance of the cloud computing system. Simulation results show that DHSJF provides better results for metrics like average waiting time and turnaround time as compared to Round Robin and First Come First Serve scheduling algorithms.
This document proposes a fair scheduling algorithm with dynamic load balancing for grid computing. It begins by introducing grid computing and the need for efficient load balancing algorithms to distribute tasks. It then describes dynamic load balancing approaches, including information, triggering, resource type, location, and selection policies. The proposed algorithm uses a fair scheduling approach that assigns tasks to processors based on their estimated fair completion times to ensure tasks receive equal shares of computing resources. It also includes a dynamic load balancing component that migrates tasks between processors to maintain balanced loads across all resources. Simulation results demonstrated the algorithm achieved balanced loads across processors and reduced overall task completion times.
Service Request Scheduling in Cloud Computing using Meta-Heuristic Technique:...IRJET Journal
This document discusses using the Teaching Learning Based Optimization (TLBO) meta-heuristic technique for service request scheduling between users and cloud service providers. TLBO is a nature-inspired algorithm that mimics the teacher-student learning process. It is compared to other meta-heuristic algorithms like Genetic Algorithm. The key steps of TLBO involve initializing a population, evaluating fitness, selecting the best solution as teacher, and updating the population through teacher and learner phases until termination criteria is met. The document proposes using number of users and virtual machines as parameters for TLBO scheduling in cloud computing. MATLAB simulation results show the initial and final iterations converging to an optimal scheduling solution.
The document discusses using a genetic algorithm to schedule tasks in a cloud computing environment. It aims to minimize task execution time and reduce computational costs compared to the traditional Round Robin scheduling algorithm. The proposed genetic algorithm mimics natural selection and genetics to evolve optimal task schedules. It was tested using the CloudSim simulation toolkit and results showed the genetic algorithm provided better performance than Round Robin scheduling.
A novel scheduling algorithm for cloud computing environmentSouvik Pal
The document describes a proposed genetic algorithm-based scheduling approach for cloud computing environments. It aims to minimize waiting time and queue length. The algorithm first permutes task burst times and finds minimum waiting times using FCFS and genetic algorithms. It then applies a queuing model to the sequences with minimum waiting time from each approach. Experimental results on 4 sample tasks show the genetic algorithm reduces waiting time compared to FCFS. The genetic operators of selection, crossover and mutation are applied to evolve optimal task scheduling sequences.
Scheduling Algorithm Based Simulator for Resource Allocation Task in Cloud Co...IRJET Journal
This document proposes a scheduling algorithm for allocating resources in cloud computing based on the Project Evaluation and Review Technique (PERT). It aims to address issues like starvation of lower priority tasks. The algorithm models task allocation as a directed acyclic graph and uses PERT to schedule critical and non-critical tasks, prioritizing higher priority tasks. The algorithm is evaluated against other scheduling methods and shows improvements in reducing completion time and optimizing resource allocation for all tasks.
An enhanced adaptive scoring job scheduling algorithm with replication strate...eSAT Publishing House
This document describes an enhanced adaptive scoring job scheduling algorithm with replication strategy for grid environments. The algorithm aims to improve upon an existing adaptive scoring job scheduling algorithm by identifying whether jobs are data-intensive or computation-intensive. It then divides large jobs into subtasks, replicates the subtasks, and allocates the replicas to clusters based on a computed cluster score in order to improve resource utilization and job completion times. The algorithm is evaluated through simulation using the GridSim toolkit.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This document proposes a genetic algorithm called Workflow Scheduling for Public Cloud Using Genetic Algorithm (WSGA) to optimize the cost of executing workflows in the public cloud. It discusses how genetic algorithms can be applied to the workflow scheduling problem to generate optimal schedules. The WSGA represents potential scheduling solutions as chromosomes, uses a fitness function to evaluate scheduling costs, and applies genetic operators like selection, crossover and mutation to evolve new schedules over multiple iterations. The goal is to minimize total execution cost while meeting workflow dependencies and deadline constraints. An experimental setup is described and the WSGA approach is claimed to reduce costs more than other heuristic scheduling algorithms for communication-intensive workflows.
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.
Task Scheduling using Hybrid Algorithm in Cloud Computing Environmentsiosrjce
The document summarizes a proposed hybrid task scheduling algorithm called PSOCS that combines particle swarm optimization (PSO) and cuckoo search (CS) for scheduling tasks in cloud computing environments. The PSOCS algorithm aims to minimize task completion time (makespan) and improve resource utilization. It was tested in a simulation using CloudSim and showed reductions in makespan and increases in utilization compared to PSO and random scheduling algorithms.
Cloud computing Review over various scheduling algorithmsIJEEE
Cloud computing has taken an importantposition in the field of research as well as in thegovernment organisations. Cloud computing uses virtualnetwork technology to provide computer resources tothe end users as well as to the customer’s. Due tocomplex computing environment the use of high logicsand task scheduler algorithms are increase which resultsin costly operation of cloud network. Researchers areattempting to build such kind of job scheduling algorithms that are compatible and applicable in cloud computing environment.In this paper, we review research work which is recently proposed by researchers on the base of energy saving scheduling techniques. We also studying various scheduling algorithms and issues related to them in cloud computing.
Genetic Algorithm for task scheduling in Cloud Computing EnvironmentSwapnil Shahade
This document proposes a modified genetic algorithm to schedule tasks in cloud computing environments. It begins with an introduction and background on cloud computing and task scheduling. It then describes the standard genetic algorithm approach and introduces the modified genetic algorithm which uses Longest Cloudlet to Fastest Processor and Smallest Cloudlet to Fastest Processor scheduling algorithms to generate the initial population. The implementation and results show that the modified genetic algorithm reduces makespan and cost compared to the standard genetic algorithm.
Task Scheduling using Tabu Search algorithm in Cloud Computing Environment us...AzarulIkhwan
1. The document proposes using Tabu Search algorithm for task scheduling in cloud computing environments using CloudSim simulator. It aims to maximize throughput and minimize turnaround time compared to traditional algorithms like FCFS.
2. The methodology section describes how CloudSim simulator works and the components involved in task scheduling. It also provides an overview of how the Tabu Search algorithm guides the search process to avoid getting stuck at local optima.
3. The expected result is that Tabu Search algorithm will provide higher throughput and lower turnaround times for cloud tasks compared to FCFS, as Tabu Search is designed to escape local optima and find better solutions.
A HYPER-HEURISTIC METHOD FOR SCHEDULING THEJOBS IN CLOUD ENVIRONMENTieijjournal
The document proposes a hyper-heuristic method for scheduling jobs in a cloud environment. It combines two low-level heuristics - Ant Colony Optimization and Particle Swarm Optimization - and uses two operators, intensification and diversity revealing, to select the heuristics. It also uses a conditional revealing operator to identify job failures while allocating resources. The hyper-heuristic aims to achieve better results than individual heuristics in terms of lower makespan time.
A Survey of Job Scheduling Algorithms Whit Hierarchical Structure to Load Ba...Editor IJCATR
Due to the advances in human civilization, problems in science and engineering are becoming more complicated than ever
before. To solve these complicated problems, grid computing becomes a popular tool. a grid environment collects, integrates, and uses
heterogeneous or homogeneous resources scattered around the globe by a high-speed network. Scheduling problems are at the heart of
any Grid-like computational system. a good scheduling algorithm can assign jobs to resources efficiently and can balance the system
load. in this paper we survey three algorithms for grid scheduling and compare benefit and disadvantages of their based on makespan.
This document discusses scheduling in cloud computing. It proposes a priority-based scheduling protocol to improve resource utilization, server performance, and minimize makespan. The protocol assigns priorities to jobs, allocates jobs to processors based on completion time, and processes jobs in parallel queues to efficiently schedule jobs in cloud computing. Future work includes analyzing time complexity and completion times through simulation to validate the protocol's efficiency.
Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
This document summarizes a research paper that proposes a new algorithm called KD-Tree approach for efficient virtual machine (VM) allocation in cloud computing environments. The algorithm aims to minimize the response time for allocating VMs to user requests. It does this by adopting a KD-Tree data structure to index physical host machines, allowing the scheduler to quickly find the host that can accommodate a new VM request with the minimum latency in O(Log n) time. The proposed approach is evaluated through simulations using the CloudSim toolkit and is shown to outperform an existing linear scheduling strategy (LSTR) algorithm in terms of reducing VM allocation times.
Optimized Assignment of Independent Task for Improving Resources Performance ...ijgca
Grid computing has emerged from category of distributed and parallel computing where the
heterogeneous resources from different network are used simultaneously to solve a particular problem that
need huge amount of resources. Potential of Grid computing depends on my issues such as security of
resources, heterogeneity of resources, fault tolerance & resource discovery and job scheduling. Scheduling
is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing
resources and is an NP-complete problem. To achieve the promising potential of grid computing, an
effective and efficient job scheduling algorithm is proposed, which will optimized two important criteria to
improve the performance of resources i.e. makespan time & resource utilization. With this, we have
classified various tasks scheduling heuristic in grid on the basis of their characteristics.
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.
Comparative Analysis of Various Grid Based Scheduling Algorithmsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Inteligent multicriteria model load blancing in cloude computingpihu2244
This document proposes an intelligent multi-criteria model for load balancing in cloud environments. It aims to maximize cloud system performance by considering three parameters (available bandwidth, processing speed, and number of parallel elements) using Analytical Hierarchy Process (AHP) for decision making. The algorithm generates a cloud simulation using CloudSim, obtains parameter values, and makes load balancing decisions with AHP. This approach seeks to minimize decision making and improve performance over using single parameters. The model and algorithm are explained through figures and pseudocode. References on load balancing, cloud computing, and AHP are also provided.
This document provides an overview and reference for the control functions and I/O capabilities of the Advanced Process Manager (APM) used in Honeywell's TotalPlant solution. It describes common functions like alarming, point types including analog inputs and outputs, digital points, and serial interfaces. It also covers more advanced control functions like regulatory PV points, logic points, process module data points, digital composite points, and regulatory control points. The document is intended as a reference for engineers designing and implementing control strategies with APM systems.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
This document summarizes a study of CEO succession events among the largest 100 U.S. corporations between 2005-2015. The study analyzed executives who were passed over for the CEO role ("succession losers") and their subsequent careers. It found that 74% of passed over executives left their companies, with 30% eventually becoming CEOs elsewhere. However, companies led by succession losers saw average stock price declines of 13% over 3 years, compared to gains for companies whose CEO selections remained unchanged. The findings suggest that boards generally identify the most qualified CEO candidates, though differences between internal and external hires complicate comparisons.
The impact of innovation on travel and tourism industries (World Travel Marke...Brian Solis
From the impact of Pokemon Go on Silicon Valley to artificial intelligence, futurist Brian Solis talks to Mathew Parsons of World Travel Market about the future of travel, tourism and hospitality.
We’re all trying to find that idea or spark that will turn a good project into a great project. Creativity plays a huge role in the outcome of our work. Harnessing the power of collaboration and open source, we can make great strides towards excellence. Not just for designers, this talk can be applicable to many different roles – even development. In this talk, Seasoned Creative Director Sara Cannon is going to share some secrets about creative methodology, collaboration, and the strong role that open source can play in our work.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
An enhanced adaptive scoring job scheduling algorithm with replication strate...eSAT Publishing House
This document describes an enhanced adaptive scoring job scheduling algorithm with replication strategy for grid environments. The algorithm aims to improve upon an existing adaptive scoring job scheduling algorithm by identifying whether jobs are data-intensive or computation-intensive. It then divides large jobs into subtasks, replicates the subtasks, and allocates the replicas to clusters based on a computed cluster score in order to improve resource utilization and job completion times. The algorithm is evaluated through simulation using the GridSim toolkit.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This document proposes a genetic algorithm called Workflow Scheduling for Public Cloud Using Genetic Algorithm (WSGA) to optimize the cost of executing workflows in the public cloud. It discusses how genetic algorithms can be applied to the workflow scheduling problem to generate optimal schedules. The WSGA represents potential scheduling solutions as chromosomes, uses a fitness function to evaluate scheduling costs, and applies genetic operators like selection, crossover and mutation to evolve new schedules over multiple iterations. The goal is to minimize total execution cost while meeting workflow dependencies and deadline constraints. An experimental setup is described and the WSGA approach is claimed to reduce costs more than other heuristic scheduling algorithms for communication-intensive workflows.
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.
Task Scheduling using Hybrid Algorithm in Cloud Computing Environmentsiosrjce
The document summarizes a proposed hybrid task scheduling algorithm called PSOCS that combines particle swarm optimization (PSO) and cuckoo search (CS) for scheduling tasks in cloud computing environments. The PSOCS algorithm aims to minimize task completion time (makespan) and improve resource utilization. It was tested in a simulation using CloudSim and showed reductions in makespan and increases in utilization compared to PSO and random scheduling algorithms.
Cloud computing Review over various scheduling algorithmsIJEEE
Cloud computing has taken an importantposition in the field of research as well as in thegovernment organisations. Cloud computing uses virtualnetwork technology to provide computer resources tothe end users as well as to the customer’s. Due tocomplex computing environment the use of high logicsand task scheduler algorithms are increase which resultsin costly operation of cloud network. Researchers areattempting to build such kind of job scheduling algorithms that are compatible and applicable in cloud computing environment.In this paper, we review research work which is recently proposed by researchers on the base of energy saving scheduling techniques. We also studying various scheduling algorithms and issues related to them in cloud computing.
Genetic Algorithm for task scheduling in Cloud Computing EnvironmentSwapnil Shahade
This document proposes a modified genetic algorithm to schedule tasks in cloud computing environments. It begins with an introduction and background on cloud computing and task scheduling. It then describes the standard genetic algorithm approach and introduces the modified genetic algorithm which uses Longest Cloudlet to Fastest Processor and Smallest Cloudlet to Fastest Processor scheduling algorithms to generate the initial population. The implementation and results show that the modified genetic algorithm reduces makespan and cost compared to the standard genetic algorithm.
Task Scheduling using Tabu Search algorithm in Cloud Computing Environment us...AzarulIkhwan
1. The document proposes using Tabu Search algorithm for task scheduling in cloud computing environments using CloudSim simulator. It aims to maximize throughput and minimize turnaround time compared to traditional algorithms like FCFS.
2. The methodology section describes how CloudSim simulator works and the components involved in task scheduling. It also provides an overview of how the Tabu Search algorithm guides the search process to avoid getting stuck at local optima.
3. The expected result is that Tabu Search algorithm will provide higher throughput and lower turnaround times for cloud tasks compared to FCFS, as Tabu Search is designed to escape local optima and find better solutions.
A HYPER-HEURISTIC METHOD FOR SCHEDULING THEJOBS IN CLOUD ENVIRONMENTieijjournal
The document proposes a hyper-heuristic method for scheduling jobs in a cloud environment. It combines two low-level heuristics - Ant Colony Optimization and Particle Swarm Optimization - and uses two operators, intensification and diversity revealing, to select the heuristics. It also uses a conditional revealing operator to identify job failures while allocating resources. The hyper-heuristic aims to achieve better results than individual heuristics in terms of lower makespan time.
A Survey of Job Scheduling Algorithms Whit Hierarchical Structure to Load Ba...Editor IJCATR
Due to the advances in human civilization, problems in science and engineering are becoming more complicated than ever
before. To solve these complicated problems, grid computing becomes a popular tool. a grid environment collects, integrates, and uses
heterogeneous or homogeneous resources scattered around the globe by a high-speed network. Scheduling problems are at the heart of
any Grid-like computational system. a good scheduling algorithm can assign jobs to resources efficiently and can balance the system
load. in this paper we survey three algorithms for grid scheduling and compare benefit and disadvantages of their based on makespan.
This document discusses scheduling in cloud computing. It proposes a priority-based scheduling protocol to improve resource utilization, server performance, and minimize makespan. The protocol assigns priorities to jobs, allocates jobs to processors based on completion time, and processes jobs in parallel queues to efficiently schedule jobs in cloud computing. Future work includes analyzing time complexity and completion times through simulation to validate the protocol's efficiency.
Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
This document summarizes a research paper that proposes a new algorithm called KD-Tree approach for efficient virtual machine (VM) allocation in cloud computing environments. The algorithm aims to minimize the response time for allocating VMs to user requests. It does this by adopting a KD-Tree data structure to index physical host machines, allowing the scheduler to quickly find the host that can accommodate a new VM request with the minimum latency in O(Log n) time. The proposed approach is evaluated through simulations using the CloudSim toolkit and is shown to outperform an existing linear scheduling strategy (LSTR) algorithm in terms of reducing VM allocation times.
Optimized Assignment of Independent Task for Improving Resources Performance ...ijgca
Grid computing has emerged from category of distributed and parallel computing where the
heterogeneous resources from different network are used simultaneously to solve a particular problem that
need huge amount of resources. Potential of Grid computing depends on my issues such as security of
resources, heterogeneity of resources, fault tolerance & resource discovery and job scheduling. Scheduling
is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing
resources and is an NP-complete problem. To achieve the promising potential of grid computing, an
effective and efficient job scheduling algorithm is proposed, which will optimized two important criteria to
improve the performance of resources i.e. makespan time & resource utilization. With this, we have
classified various tasks scheduling heuristic in grid on the basis of their characteristics.
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.
Comparative Analysis of Various Grid Based Scheduling Algorithmsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Inteligent multicriteria model load blancing in cloude computingpihu2244
This document proposes an intelligent multi-criteria model for load balancing in cloud environments. It aims to maximize cloud system performance by considering three parameters (available bandwidth, processing speed, and number of parallel elements) using Analytical Hierarchy Process (AHP) for decision making. The algorithm generates a cloud simulation using CloudSim, obtains parameter values, and makes load balancing decisions with AHP. This approach seeks to minimize decision making and improve performance over using single parameters. The model and algorithm are explained through figures and pseudocode. References on load balancing, cloud computing, and AHP are also provided.
This document provides an overview and reference for the control functions and I/O capabilities of the Advanced Process Manager (APM) used in Honeywell's TotalPlant solution. It describes common functions like alarming, point types including analog inputs and outputs, digital points, and serial interfaces. It also covers more advanced control functions like regulatory PV points, logic points, process module data points, digital composite points, and regulatory control points. The document is intended as a reference for engineers designing and implementing control strategies with APM systems.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
This document summarizes a study of CEO succession events among the largest 100 U.S. corporations between 2005-2015. The study analyzed executives who were passed over for the CEO role ("succession losers") and their subsequent careers. It found that 74% of passed over executives left their companies, with 30% eventually becoming CEOs elsewhere. However, companies led by succession losers saw average stock price declines of 13% over 3 years, compared to gains for companies whose CEO selections remained unchanged. The findings suggest that boards generally identify the most qualified CEO candidates, though differences between internal and external hires complicate comparisons.
The impact of innovation on travel and tourism industries (World Travel Marke...Brian Solis
From the impact of Pokemon Go on Silicon Valley to artificial intelligence, futurist Brian Solis talks to Mathew Parsons of World Travel Market about the future of travel, tourism and hospitality.
We’re all trying to find that idea or spark that will turn a good project into a great project. Creativity plays a huge role in the outcome of our work. Harnessing the power of collaboration and open source, we can make great strides towards excellence. Not just for designers, this talk can be applicable to many different roles – even development. In this talk, Seasoned Creative Director Sara Cannon is going to share some secrets about creative methodology, collaboration, and the strong role that open source can play in our work.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
1) The document discusses the opportunity for technology to improve organizational efficiency and transition economies into a "smart and clean world."
2) It argues that aggregate efficiency has stalled at around 22% for 30 years due to limitations of the Second Industrial Revolution, but that digitizing transport, energy, and communication through technologies like blockchain can help manage resources and increase efficiency.
3) Technologies like precision agriculture, cloud computing, robotics, and autonomous vehicles may allow for "dematerialization" and do more with fewer physical resources through effects like reduced waste and need for transportation/logistics infrastructure.
A survey of various scheduling algorithm in cloud computing environmenteSAT Journals
Abstract Cloud computing is known as a provider of dynamic services using very large scalable and virtualized resources over the Internet. Due to novelty of cloud computing field, there is no many standard task scheduling algorithm used in cloud environment. Especially that in cloud, there is a high communication cost that prevents well known task schedulers to be applied in large scale distributed environment. Today, researchers attempt to build job scheduling algorithms that are compatible and applicable in Cloud Computing environment Job scheduling is most important task in cloud computing environment because user have to pay for resources used based upon time. Hence efficient utilization of resources must be important and for that scheduling plays a vital role to get maximum benefit from the resources. In this paper we are studying various scheduling algorithm and issues related to them in cloud computing. Index Terms: cloud computing, scheduling, algorithm
DYNAMIC TASK SCHEDULING BASED ON BURST TIME REQUIREMENT FOR CLOUD ENVIRONMENTIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
Dynamic Task Scheduling based on Burst Time Requirement for Cloud EnvironmentIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
GROUPING BASED JOB SCHEDULING ALGORITHM USING PRIORITY QUEUE AND HYBRID ALGOR...ijgca
Grid computing enlarge with computing platform which is collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organization to form a distributed high performance computing infrastructure. Grid computing solves the complex computing
problems amongst multiple machines. Grid computing solves the large scale computational demands in a high performance computing environment. The main emphasis in the grid computing is given to the resource management and the job scheduler .The goal of the job scheduler is to maximize the resource utilization and minimize the processing time of the jobs. Existing approaches of Grid scheduling doesn’t give much emphasis on the performance of a Grid scheduler in processing time parameter. Schedulers allocate resources to the jobs to be executed using the First come First serve algorithm. In this paper, we have provided an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First in First out, Round robin. The job scheduling system is responsible to select best suitable machines in a grid for user jobs. The management and scheduling system generates job schedules for each machine in the grid by taking static restrictions and dynamic parameters of jobs and machines
into consideration. The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs. Queues can be optimized by using various scheduling algorithms depending upon the performance criteria to be improved e.g. response
time, throughput. The work has been done in MATLAB using the parallel computing toolbox.
Time and Reliability Optimization Bat Algorithm for Scheduling Workflow in CloudIRJET Journal
This document describes using a meta-heuristic optimization algorithm called the Bat Algorithm (BA) to schedule workflows in cloud computing environments. The BA is applied to optimize a multi-objective function that minimizes workflow execution time and maximizes reliability while keeping costs within a user-specified budget. The BA is compared to a basic randomized evolutionary algorithm (BREA) that uses greedy approaches. Experimental results show the BA performs better by finding schedules that have lower execution times and higher reliability within the given budget constraints. The BA is well-suited for this problem because it can efficiently search large solution spaces and automatically focus on optimal regions like other metaheuristics.
This document summarizes a research paper that proposes a hybrid task scheduling algorithm for cloud computing environments called PSOCS. PSOCS combines the Particle Swarm Optimization (PSO) algorithm and Cuckoo Search (CS) algorithm to optimize task scheduling and minimize completion time while increasing resource utilization. The paper describes PSO and CS algorithms individually, then defines the proposed PSOCS algorithm. It evaluates PSOCS using a simulation and finds it reduces makespan and increases utilization compared to PSO and random allocation algorithms.
This document provides an overview of scheduling mechanisms in cloud computing. It discusses task scheduling, gang scheduling based on performance and cost evaluation, and resource scheduling. For task scheduling, it describes classifying tasks based on quality of service parameters and MapReduce level scheduling. It then explains two gang scheduling algorithms - Adaptive First Come First Serve (AFCFS) and Largest Job First Serve (LJFS) - and how they are used to evaluate performance and cost. Finally, it briefly discusses resource scheduling and factors that affect scheduling mechanisms in cloud computing like efficiency, fairness, costs, and communication patterns.
Effective and Efficient Job Scheduling in Grid ComputingAditya Kokadwar
The integration of remote and diverse resources and the increasing computational needs of Grand Challenges problems combined with the faster growth of the internet and communication technologies leads to the development of global computational grids. Grid computing is a prevailing technology, which unites underutilized resources in order to support sharing of resources and services distributed across numerous administrative region. An efficient and effective scheduling system is essentially required in order to achieve the promising capacity of grids. The main goal of scheduling is to maximize the resource utilization and minimize processing time and cost of the jobs. In this research, the objective is to prioritize the jobs based on execution cost and then allocate the resources with minimum cost by merging it with conventional job grouping strategy to provide the solution for better and more efficient job scheduling which is beneficial to both user and resource broker. The proposed scheduling approach in grid computing employs a dynamic cost-based job scheduling algorithm for making an efficient mapping of a job to available resources in the grid. It also improves communication to computation ratio (CCR) and utilization of available resources by grouping the user jobs before resource allocation.
A HYPER-HEURISTIC METHOD FOR SCHEDULING THEJOBS IN CLOUD ENVIRONMENTieijjournal1
Currently cloud computing has turned into a promising technology and has become a great key for
satisfying a flexible service oriented , online provision and storage of computing resources and user’s
information in lesser expense with dynamism framework on pay per use basis.In this technology Job
Scheduling Problem is acritical issue. For well-organizedmanaging and handling resources,
administrations, scheduling plays a vital role. This paper shares out the improved Hyper- Heuristic
Scheduling Approach to schedule resources, by taking account of computation time and makespan with two
detection operators. Operators are used to select the low-level heuristics automatically. Conditional
Revealing Algorithm (CRA)idea is applied for finding the job failures while allocating the resources. We
believe that proposed hyper-heuristic achieve better results than other individual heuristics
This document describes an improved Max-Min scheduling algorithm that considers additional constraints beyond just completion time. The improved algorithm calculates a proportional fairness score for each job/task based on its size, completion time, payload storage rate, and RAM requirements. It then sorts the jobs based on these scores to prioritize jobs with the highest scores, addressing limitations of the traditional Max-Min algorithm that only considers completion time. The algorithm is evaluated using a simulator with scientific workflows and workloads. Results show the improved algorithm efficiently schedules jobs while accounting for multiple constraints.
Optimized Assignment of Independent Task for Improving Resources Performance ...Ricardo014
Grid computing has emerged from category of distributed and parallel computing where the heterogeneous resources from different network are used simultaneously to solve a particular problem that need huge amount of
resources. Potential of Grid computing depends on my issues such as security of resources, heterogeneity of resources, fault tolerance & resource discovery and job scheduling. Scheduling is one of the core steps to
efficiently exploit the capabilities of heterogeneous distributed computing resources and is an NP-complete problem. To achieve the promising potential of grid computing, an effective and efficient job scheduling algorithm is
proposed, which will optimized two important criteria to improve the performance of resources i.e. makespan time & resource utilization. With this, we have classified various tasks scheduling heuristic in grid on the basis of
their characteristics.
Optimized Assignment of Independent Task for Improving Resources Performance ...ijgca
Grid computing has emerged from category of distributed and parallel computing where the heterogeneous resources from different network are used simultaneously to solve a particular problem that need huge amount of resources. Potential of Grid computing depends on my issues such as security of resources, heterogeneity of resources, fault tolerance & resource discovery and job scheduling. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing resources and is an NP-complete problem. To achieve the promising potential of grid computing, an effective and efficient job scheduling algorithm is proposed, which will optimized two important criteria to improve the performance of resources i.e. makespan time & resource utilization. With this, we have classified various tasks scheduling heuristic in grid on the basis of their characteristics.
In the era of big data, even though we have large infrastructure, storage data varies in size,
formats, variety, volume and several platforms such as hadoop, cloud since we have problem associated
with an application how to process the data which is varying in size and format. Data varying in
application and resources available during run time is called dynamic workflow. Using large
infrastructure and huge amount of resources for the analysis of data is time consuming and waste of
resources, it’s better to use scheduling algorithm to analyse the given data set, for efficient execution of
data set without time consuming and evaluate which scheduling algorithm is best and suitable for the
given data set. We evaluate with different data set understand which is the most suitable algorithm for
analysis of data being efficient execution of data set and store the data after analysis
This document provides a comparative analysis of various grid-based scheduling algorithms. It discusses six different algorithms: Min-Min, Sufferage, Heterogeneous Earliest Finish Time (HEFT), Critical Path-On-a-Processor (CPOP), Reliability Aware Scheduling Algorithm with Duplication of HDC System (RASD), and Hierarchical Job Scheduling for Clusters of Workstations (HJS). It compares the algorithms based on parameters like response time, resource utilization, load balancing, and considers factors like architecture, environment, and dynamicity. The document concludes that grid scheduling is important for optimizing resource allocation in distributed, heterogeneous environments.
This document discusses and compares various load balancing techniques in cloud computing. It begins by introducing load balancing as an important issue in cloud computing for efficiently scheduling user requests and resources. Several load balancing algorithms are then described, including honeybee foraging algorithm, biased random sampling, active clustering, OLB+LBMM, and Min-Min. Metrics for evaluating and comparing load balancing techniques are defined, such as throughput, overhead, fault tolerance, migration time, response time, resource utilization, scalability, and performance. The algorithms are then analyzed based on these metrics.
IRJET- Advance Approach for Load Balancing in Cloud Computing using (HMSO) Hy...IRJET Journal
This document proposes a new hybrid multi-swarm optimization (HMSO) algorithm for load balancing in cloud computing. It aims to minimize response time and costs while improving resource utilization and customer satisfaction. The HMSO algorithm uses multi-level particle swarm optimization to find an optimal resource allocation solution. Simulation results show that the proposed HMSO technique reduces response time and datacenter costs compared to other algorithms. It also achieves a more balanced load distribution across resources.
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.
DGBSA : A BATCH JOB SCHEDULINGALGORITHM WITH GA WITH REGARD TO THE THRESHOLD ...IJCSEA Journal
In this paper , we will provide a scheduler on batch jobs with GA regard to the threshold detector. In The algorithm proposed in this paper, we will provide the batch independent jobs with a new technique ,so we can optimize the schedule them. To do this, we use a threshold detector then among the selected jobs, processing resources can process batch jobs with priority. Also hierarchy of tasks in each batch, will be determined with using DGBSA algorithm. Now , with the regard to the works done by previous ,we can provide an algorithm that by adding specific parameters to fitness function of the previous algorithms ,develop a optimum fitness function that in the proposed algorithm has been used. According to assessment done on DGBSA algorithm, in compare with the similar algorithms, it has more performance. The effective parameters that used in the proposed algorithm can reduce the total wasting time in compare with previous algorithms. Also this algorithm can improve the previous problems in batch processing with a new technique.
The document discusses a project that proposes a heuristic algorithm for efficient task scheduling and resource allocation in cloud computing environments. It uses real scientific workflows as input tasks and compares the turnaround and response times to other frameworks, finding the proposed algorithm performs better. The algorithm aims to maximize resource utilization, including CPU, memory, and bandwidth, obtaining the highest utilization results for these computing resources.
Dynamic Three Stages Task Scheduling Algorithm on Cloud Computing
Naglaa Sayed Abdelrehem, Fathi Ahmed Amer, Imane Aly Saroit,
Department of Information Technology, Faculty of Computer and Artificial Intelligence, Cairo University, Cairo, Egypt.
Similar to Job Resource Ratio Based Priority Driven Scheduling in Cloud Computing (20)
Due to availability of internet and evolution of embedded devices, Internet of things can be useful to contribute in energy domain. The Internet of Things (IoT) will deliver a smarter grid to enable more information and connectivity throughout the infrastructure and to homes. Through the IoT, consumers, manufacturers and utility providers will come across new ways to manage devices and ultimately conserve resources and save money by using smart meters, home gateways, smart plugs and connected appliances. The future smart home, various devices will be able to measure and share their energy consumption, and actively participate in house-wide or building wide energy management systems. This paper discusses the different approaches being taken worldwide to connect the smart grid. Full system solutions can be developed by combining hardware and software to address some of the challenges in building a smarter and more connected smart grid.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
Internet of Things - Paradigm Shift of Future Internet Application for Specia...ijsrd.com
In the world more than 15% people are living with disability that also include children below age of 10 years. Due to lack of independent support services specially abled (handicap) people overly rely on other people for their basic needs, that excludes them from being financially and socially active. The Internet of Things (IoT) can give support system and a better quality of life as well as participation in routine and day to day life. For this purpose, the future solutions for current problems has been introduced in this paper. Daunting challenges have been considered as future research and glimpse of the IoT for specially abled person is given in the paper.
A Study of the Adverse Effects of IoT on Student's Lifeijsrd.com
Internet of things (IoT) is the most powerful invention and if used in the positive direction, internet can prove to be very productive. But, now a days, due to the social networking sites such as Face book, WhatsApp, twitter, hike etc. internet is producing adverse effects on the student life, especially those students studying at college Level. As it is rightly said, something which has some positive effects also has some of the negative effects on the other hand. In this article, we are discussing some adverse effects of IoT on student’s life.
Pedagogy for Effective use of ICT in English Language Learningijsrd.com
The use of information and communications technology (ICT) in education is a relatively new phenomenon and it has been the educational researchers' focus of attention for more than two decades. Educators and researchers examine the challenges of using ICT and think of new ways to integrate ICT into the curriculum. However, there are some barriers for the teachers that prevent them to use ICT in the classroom and develop supporting materials through ICT. The purpose of this study is to examine the high school English teachers’ perceptions of the factors discouraging teachers to use ICT in the classroom.
In recent years usage of private vehicles create urban traffic more and more crowded. As result traffic becomes one of the important problems in big cities in all over the world. Some of the traffic concerns are traffic jam and accidents which have caused a huge waste of time, more fuel consumption and more pollution. Time is very important parameter in routine life. The main problem faced by the people is real time routing. Our solution Virtual Eye will provide the current updates as in the real time scenario of the specific route. This research paper presents smart traffic navigation system, based on Internet of Things, which is featured by low cost, high compatibility, easy to upgrade, to replace traditional traffic management system and the proposed system can improve road traffic tremendously.
Ontological Model of Educational Programs in Computer Science (Bachelor and M...ijsrd.com
In this work there is illustrated an ontological model of educational programs in computer science for bachelor and master degrees in Computer science and for master educational program “Computer science as second competence†by Tempus project PROMIS.
Understanding IoT Management for Smart Refrigeratorijsrd.com
1) The document discusses a proposed design for an intelligent refrigerator that leverages sensor technology and wireless communication to identify food items and order more through an internet connection when supplies are low.
2) Key aspects of the proposal include using RFID to uniquely identify each food item, storing item and usage data in an XML database, monitoring usage patterns to determine reordering needs, and executing orders through an online retailer using stored payment details.
3) Security and privacy concerns with such an internet-connected refrigerator are discussed, such as potential hacking of personal information or unauthorized device control. The proposal aims to minimize human interaction for household management.
DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...ijsrd.com
Double wishbone designs allow the engineer to carefully control the motion of the wheel throughout suspension travel. 3-D model of the Lower Wishbone Arm is prepared by using CAD software for modal and stress analysis. The forces and moments are used as the boundary conditions for finite element model of the wishbone arm. By using these boundary conditions static analysis is carried out. Then making the load as a function of time; quasi-static analysis of the wishbone arm is carried out. A finite element based optimization is used to optimize the design of lower wishbone arm. Topology optimization and material optimization techniques are used to optimize lower wishbone arm design.
A Review: Microwave Energy for materials processingijsrd.com
Microwave energy is a latest largest growing technique for material processing. This paper presents a review of microwave technologies used for material processing and its use for industrial applications. Advantages in using microwave energy for processing material include rapid heating, high heating efficiency, heating uniformity and clean energy. The microwave heating has various characteristics and due to which it has been become popular for heating low temperature applications to high temperature applications. In recent years this novel technique has been successfully utilized for the processing of metallic materials. Many researchers have reported microwave energy for sintering, joining and cladding of metallic materials. The aim of this paper is to show the use of microwave energy not only for non-metallic materials but also the metallic materials. The ability to process metals with microwave could assist in the manufacturing of high performance metal parts desired in many industries, for example in automotive and aeronautical industries.
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logsijsrd.com
With an expontial growth of World Wide Web, there are so many information overloaded and it became hard to find out data according to need. Web usage mining is a part of web mining, which deal with automatic discovery of user navigation pattern from web log. This paper presents an overview of web mining and also provide navigation pattern from classification and clustering algorithm for web usage mining. Web usage mining contain three important task namely data preprocessing, pattern discovery and pattern analysis based on discovered pattern. And also contain the comparative study of web mining techniques.
APPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEMijsrd.com
Application of FACTS controller called Static Synchronous Compensator STATCOM to improve the performance of power grid with Wind Farms is investigated .The essential feature of the STATCOM is that it has the ability to absorb or inject fastly the reactive power with power grid . Therefore the voltage regulation of the power grid with STATCOM FACTS device is achieved. Moreover restoring the stability of the power system having wind farm after occurring severe disturbance such as faults or wind farm mechanical power variation is obtained with STATCOM controller . The dynamic model of the power system having wind farm controlled by proposed STATCOM is developed . To validate the powerful of the STATCOM FACTS controller, the studied power system is simulated and subjected to different severe disturbances. The results prove the effectiveness of the proposed STATCOM controller in terms of fast damping the power system oscillations and restoring the power system stability.
Making model of dual axis solar tracking with Maximum Power Point Trackingijsrd.com
Now a days solar harvesting is more popular. As the popularity become higher the material quality and solar tracking methods are more improved. There are several factors affecting the solar system. Major influence on solar cell, intensity of source radiation and storage techniques The materials used in solar cell manufacturing limit the efficiency of solar cell. This makes it particularly difficult to make considerable improvements in the performance of the cell, and hence restricts the efficiency of the overall collection process. Therefore, the most attainable maximum power point tracking method of improving the performance of solar power collection is to increase the mean intensity of radiation received from the source used. The purposed of tracking system controls elevation and orientation angles of solar panels such that the panels always maintain perpendicular to the sunlight. The measured variables of our automatic system were compared with those of a fixed angle PV system. As a result of the experiment, the voltage generated by the proposed tracking system has an overall of about 28.11% more than the fixed angle PV system. There are three major approaches for maximizing power extraction in medium and large scale systems. They are sun tracking, maximum power point (MPP) tracking or both.
A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...ijsrd.com
This document summarizes a review paper on performance and emission testing of a 4-stroke diesel engine using ethanol-diesel blends at different pressures. The paper reviews several previous studies that tested blends of 5-30% ethanol mixed with diesel fuel. The studies found that a 10-20% ethanol blend can improve brake thermal efficiency compared to pure diesel, while also reducing emissions like NOx and smoke. Higher ethanol blends required advancing the injection timing to allow the engine to run. Ethanol-diesel blends were found to have lower density, viscosity, pour point and higher flash point compared to pure diesel. Overall, ethanol shows potential as a renewable fuel to improve engine performance and reduce emissions when blended with diesel
Study and Review on Various Current Comparatorsijsrd.com
This paper presents study and review on various current comparators. It also describes low voltage current comparator using flipped voltage follower (FVF) to obtain the single supply voltage. This circuit has short propagation delay and occupies a small chip area as compare to other current comparators. The results of this circuit has obtained using PSpice simulator for 0.18 μm CMOS technology and a comparison has been performed with its non FVF counterpart to contrast its effectiveness, simplicity, compactness and low power consumption.
Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...ijsrd.com
Power dissipation is a challenging problem for today's system-on-chip design and test. This paper presents a novel architecture which generates the test patterns with reduced switching activities; it has the advantage of low test power and low hardware overhead. The proposed LP-TPG (test pattern generator) structure consists of modified low power linear feedback shift register (LP-LFSR), m-bit counter, gray counter, NOR-gate structure and XOR-array. The seed generated from LP-LFSR is EXCLUSIVE-OR ed with the data generated from gray code generator. The XOR result of the sequence is single input changing (SIC) sequence, in turn reduces the switching activity and so power dissipation will be very less. The proposed architecture is simulated using Modelsim and synthesized using Xilinx ISE9.2.The Xilinx chip scope tool will be used to test the logic running on FPGA.
Defending Reactive Jammers in WSN using a Trigger Identification Service.ijsrd.com
In the last decade, the greatest threat to the wireless sensor network has been Reactive Jamming Attack because it is difficult to be disclosed and defend as well as due to its mass destruction to legitimate sensor communications. As discussed above about the Reactive Jammers Nodes, a new scheme to deactivate them efficiently is by identifying all trigger nodes, where transmissions invoke the jammer nodes, which has been proposed and developed. Due to this identification mechanism, many existing reactive jamming defending schemes can be benefited. This Trigger Identification can also work as an application layer .In this paper, on one side we provide the several optimization problems to provide complete trigger identification service framework for unreliable wireless sensor networks and on the other side we also provide an improved algorithm with regard to two sophisticated jamming models, in order to enhance its robustness for various network scenarios.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
AI for Legal Research with applications, toolsmahaffeycheryld
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Job Resource Ratio Based Priority Driven Scheduling in Cloud Computing
1. IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 2, 2013 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 373
Job Resource Ratio Based Priority Driven Scheduling in Cloud
Computing
Pinal Salot1
Purnima Gandhi2
1,2
Alpha College of Engineering, GTU, Gujarat, India
Abstract— Cloud Computing is an emerging technology in
the area of parallel and distributed computing. Clouds
consist of a collection of virtualized resources, which
include both computational and storage facilities that can be
provisioned on demand, depending on the users’ needs. Job
scheduling is one of the major activities performed in all the
computing environments. Cloud computing is one the
upcoming latest technology which is developing drastically.
To efficiently increase the working of cloud computing
environments, job scheduling is one the tasks performed in
order to gain maximum profit. In this paper we proposed a
new scheduling algorithm based on priority and that priority
is based on ratio of job and resource. To calculate priority of
job we use analytical hierarchy process. In this paper we
also compare result with other algorithm like First come first
serve and round robin algorithms.
Key Words: Priority based scheduling, Job scheduling, cloud
computing, optimization algorithm.
I. INTRODUCTION
There has been various types of scheduling algorithm exist
in distributed computing system. Most of them can be
applied in the cloud environment with suitable verifications.
The main advantage of job scheduling algorithm is to
achieve a high performance computing and the best system
throughput. Traditional job scheduling algorithms are not
able to provide scheduling in the cloud environments.
According to a simple classification, job scheduling
algorithms in cloud computing can be categorized into two
main groups; Batch mode heuristic scheduling algorithms
(BMHA) and online mode heuristic algorithms. In BMHA,
Jobs are queued and collected into a set when they arrive in
the system. The scheduling algorithm will start after a fixed
period of time. The main examples of BMHA based
algorithms are; First Come First Served scheduling
algorithm (FCFS), Round Robin scheduling algorithm (RR).
By On-line mode heuristic scheduling algorithm, Jobs are
scheduled when they arrive in the system. Since the cloud
environment is a heterogeneous system and the speed of
each processor varies quickly, the on-line mode heuristic
scheduling algorithms are more appropriate for a cloud
environment. Most fit task scheduling algorithm (MFTF) is
suitable example of On-line mode heuristic scheduling
algorithm.
First Come First Serve Algorithm:1)
Job in the queue which come first is served. This algorithm
is simple and fast.
Round Robin algorithm:2)
In the round robin scheduling, processes are dispatched in a
FIFO manner but are given a limited amount of CPU time
called a time-slice or a quantum. If a process does not
complete before its CPU-time expires, the CPU is
preempted and given to the next process waiting in a queue.
The preempted process is then placed at the back of the
ready list.
Most fit task scheduling algorithm:3)
In this algorithm task which fit best in queue are executed
first. This algorithm has high failure ratio.
Priority scheduling algorithm:4)
The basic idea is straightforward: each process is assigned a
priority, and priority is allowed to run. Equal-Priority
processes are scheduled in FCFS order. The shortest-Job-
First (SJF) algorithm is a special case of general priority
scheduling algorithm. An SJF algorithm is simply a priority
algorithm where the priority is the inverse of the (predicted)
next CPU burst. That is, the longer the CPU burst, the lower
the priority and vice versa. Priority can be defined either
internally or externally. Internally defined priorities use
some measurable quantities or qualities to compute priority
of a process.
Scheduling ProcessA.
Scheduling process in cloud can be generalized into three
stages namely–
Resource discovering and filtering – Datacentre
Broker discovers the resources present in the network
system and collects status information related to them.
Resource selection – Target resource is selected
based on certain parameters of task and resource. This is
deciding stage.
Task submission -Task is submitted to resource
selected.
Fig. 1. Scheduling Process
2. Job Resource Ratio Based Priority Driven Scheduling in Cloud Computing
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374
II. RELATED WORK
The Following scheduling algorithms are currently prevalent
in clouds.
Resource-Aware-Scheduling algorithm (RASA):A.
Saeed Parsa and Reza Entezari-Maleki [2] proposed a new
task scheduling algorithm RASA. It is composed of two
traditional scheduling algorithms; Max-min and Min-min.
RASA uses the advantages of Max-min and Min-min
algorithms and covers their disadvantages. Though the
deadline of each task, arriving rate of the tasks, cost of the
task execution on each of the resource, cost of the
communication are not considered. The experimental results
show that RASA is outperforms the existing scheduling
algorithms in large scale distributed systems.
RSDC (Reliable Scheduling Distributed in CloudB.
computing):
Arash Ghorbannia Delavar,Mahdi Javanmard , Mehrdad
Barzegar Shabestari and Marjan Khosravi Talebi[1]
proposed a reliable scheduling algorithm in cloud computing
environment. In this algorithm major job is divided to sub
jobs. In order to balance the jobs the request and
acknowledge time are calculated separately. The scheduling
of each job is done by calculating the request and
acknowledges time in the form of a shared job. So that
efficiency of the system is increased.
An Optimal Model for Priority based ServiceC.
Scheduling Policy for Cloud Computing Environment:
Dr. M. Dakshayini, Dr. H. S. Guruprasad [3] proposed a
new scheduling algorithm based on priority and admission
control scheme. In this algorithm priority is assigned to each
admitted queue. Admission of each queue is decided by
calculating tolerable delay and service cost. Advantage of
this algorithm is that this policy with the proposed cloud
architecture has achieved very high (99%) service
completion rate with guaranteed QoS. As this policy
provides the highest precedence for highly paid user service-
requests, overall servicing cost for the cloud also increases.
A Priority based Job Scheduling Algorithm in CloudD.
Computing:
Shamsollah Ghanbari, Mohamed Othman proposed a new
scheduling algorithm based on multi – criteria and multi -
decision priority driven scheduling algorithm. This
scheduling algorithm consist of three level of scheduling:
object level, attribute level and alternate level. In this
algorithm priority can be set by job resource ratio. Then
priority vector can be compared with each queue. This
algorithm has higher throughput and less finish time.
Extended Max-Min Scheduling Using Petri Net andE.
Load Balancing:
El-Sayed T. El-kenawy, Ali Ibraheem El-Desoky, Mohamed
F. Al-rahamawy[5] has proposed a new algorithm based on
impact of RASA algorithm. Improved Max-min algorithm is
based on the expected execution time instead of complete
time as a selection basis. Petri nets are used to model the
concurrent behavior of distributed systems. Max-min
demonstrates achieving schedules with comparable lower
makespan rather than RASA and original Max-min.
An Optimistic Differentiated Job Scheduling System forF.
Cloud Computing:
Shalmali Ambike, Dipti Bhansali, Jaee Kshirsagar, Juhi
Bansiwal[6] has proposed a differentiated scheduling
algorithm with non-preemptive priority queuing model for
activities performed by cloud user in the cloud computing
environment. In this approach one web application
is created to do some activity like one of the file uploading
and downloading then there is need of efficient job
scheduling algorithm. The QoS requirements of the cloud
computing user and the maximum profits of the cloud
computing service provider are achieved with this
algorithm.
Improved Cost-Based Algorithm for Task Scheduling:G.
Mrs.S.Selvarani, Dr.G.Sudha Sadhasivam [7] proposed an
improved cost-based scheduling algorithm for making
efficient mapping of tasks to available resources in cloud.
The improvisation of traditional activity based costing is
proposed by new task scheduling strategy for cloud
environment where there may be no relation between the
overhead application base and the way that different tasks
cause overhead cost of resources in cloud. This scheduling
algorithm divides all user tasks depending on priority of
each task into three different lists. This scheduling algorithm
measures both resource cost and computation performance,
it also Improves the computation/communication ratio.
Performance and Cost evaluation of Gang SchedulingH.
in a Cloud Computing System with Job Migrations and
Starvation Handling:
Ioannis A. Moschakis and Helen D. Karatza has proposed a
gang scheduling algorithm with job migration and starvation
handling in which scheduling parallel jobs, already applied
in the areas of Grid and Cluster computing. The number of
Virtual Machines (VMs) available at any moment is
dynamic and scales according to the demands of the jobs
being serviced. The aforementioned model is studied
through simulation in order to analyze the performance and
overall cost of Gang Scheduling with migrations and
starvation handling. Results highlight that this scheduling
strategy can be effectively deployed on Clouds, and that
cloud platforms can be viable for HPC or high performance
enterprise applications.
III. ANALYTICAL HIERARCHY PROCESS
In this section we explain the Analytical Hierarchy Process
briefly. It is a multi-criteria decision-making (MCDM) and
multi-attribute decision-making (MCDM) model. Basically
architecture of AHP is consisted of three levels which are
objective level, attributes level and alternatives level
respectively. The foundation of AHP is comparison matrix
which can be shown as Eq. (1).
aij = { (1)
Each entry in the matrix A is positive ( ). Also A is a square
matrix ( ). For any arbitrary comparison matrix such as A we
can compute a vector of weights such as associated with A.
Relationship between A and can be shown as Eq.(2)
3. Job Resource Ratio Based Priority Driven Scheduling in Cloud Computing
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375
A = { (2)
An essential step in AHP is to calculate vector of weights.
Vector of weights can be computed through the Eq. (3)
(3)
Actually Eq. (3) is denoted the principal eigenvalue of
A and is denoted the corresponding eigenvector. If A is
absolutely consistent then . In this case A will be
consistent. consistency ratio (CR) can be defined as Eq. (4).
CR = (4)
In Eq. (4), RI is denoted the random index(RI), RI can be
calculated randomly based on rank of comparison matrix.
IV. PROPOSED ALGORITHM
Suppose that is a set of jobs that request
resources in a cloud environment. Also we assume that
is a set of resources available in cloud
environment( ). Each job requests a resource with a
determined priority. The priority of each job is compared
with other jobs separately.
Assume that are d comparison matrixes
of jobs which are created according to priority of resource
accessibilities. For each of comparison matrixes we should
compute a priority vector (vector of weights). The priority
vector can be obtained by solving Eq. (3). There are several
methods for calculating priority vector [1- 5]. An iterative
method for solving Eq. (3) can be found in [6].That method
solves the Eq. (3) by using numerical methods. Using
iterative methods can calculate priority vector (vector of
weights) without concerning about consistency problems. In
this case we can define a normal matrix of jobs level as Eq.
(5).
Δ = ] (5)
It is clear that Δ is a matrix with m (the number of jobs)
rows and d (the number of resources) columns. The next
step of the proposed algorithm is to make a comparison
matrix for resources according to priorities. This matrix
determines that which resource has higher priority than
others based on decision maker(s). In this case, we will have
a matrix with d rows and d columns. Assume that S is
comparison matrix for resources level, thus will be defined
as priority vector of S. The next step of the algorithm is to
calculate PVS which is denoted as priority vector of
scheduling jobs. PVS can be calculated by Eq. (6). Finally,
we choose the maximum element of PVS, then select
corresponding element of ᴪ in order to allocate a suitable
resource.
PVS = Δ.ᵧ (6)
Steps of algorithm :
1) J = set of Jobs
2) C = Set of Resources
3) Make consistent comparison matrix according to
priority of resources
4) Compute priority vector for all matrix
5) Make matrix with priority vector name it ∆.
6) For C compute consistent matrix .
7) Compute priority vector and name it Υ.
8) Compute PVS. PVS = ∆. Υ.
9) Choose a job according to priority value
10) Update list of job according to priority.
V. SIMULATION RESULT
The CloudSim toolkit is used to simulate heterogeneous
resource environment and the communication environment
[4]. CloudSim(2.1.1) simulator is used to verify the
correctness of proposed algorithm. The experiments are
performed with Sequential assignment which is default in
CloudSim and the proposed algorithm. The jobs arrival is
Uniformly Randomly Distributed to get generalized
scenario. The configuration of datacenter created is as
shown below - Number of processing elements – 1 Number
of hosts – 1.
RAM(MB) 2048
Processing Power(MIPS) 1000
VM scheduling Time Shared with Priority
Table 1. Resources of Virtual Machines
The configuration of Virtual Machines used in this
experiment is as shown in Table 2.
Virtual Machines 3
RAM (MB) 256
Processing Power 1000
Processing Element 1
Table 2. Configuration of Virtual Machines
Now we will compare result with existing algorithm with
this configuration. It will take different finish time with
different algorithm. It can be shown by figure 2.
Fig. 2 : Comparison with other algorithm
VI. NUMERIC EXAMPLE
In our example we have 3 resources and 3 jobs. Priority of
each job according to resources can be shown in table.
0 2000400060008000
FCFS
Round Robin
Priority driven
Makespan
Makespan
4. Job Resource Ratio Based Priority Driven Scheduling in Cloud Computing
(IJSRD/Vol. 1/Issue 2/2013/0077)
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376
Priority
Resource
1
Resource
2
Resource
3
Priority
Vector
Resource
1
1 0.25 3 0.213
Resource
2
4 1 7 0.701
Resource
3
1/3 1/7 1 0.085
Table 3: Priority of resources
Resource 1 Job 1 Job 2 Job 3 Priority Vector
Job1 1 4 3 0.632
Job 2 1/4 1 ½ 0.137
Job 3 1/3 2 1 0.239
Table 4: Priority of resource 1 according to jobs
Resource 2 Job 1 Job 2 Job 3 Priority Vector
Job1 1 5 3 0.619
Job 2 1/5 1 1/4 0.096
Job 3 1/3 4 1 0.284
Table 5: Priority of resource 2
Resource 3 Job 1 Job 2 Job 3 Priority Vector
Job1 1 1/3 1/7 0.093
Job 2 3 1 ½ 0.292
Job 3 7 2 1 0.615
Table 6: Priority of resource 3
Comparison matrix can be shown as follows :
[ ]
For other comparison matrixes in table 2 to 4 we should
investigate consistency condition.
According to table 2 to 4 and step 3-5 of proposed algorithm
we have:
[ ]
[ ]
Thus,
[ ]
Job 1 has highest priority then job 3 has 2nd
priority and job
2 has less priority.
VII. CONCLUSION AND FUTURE WORK
Scheduling is one of the most important tasks in cloud
computing environment. In this paper we have analyze
various scheduling algorithm and tabulated various
parameter. Priority is an important issue of job scheduling in
cloud environments. In this paper we have proposed a
priority based job scheduling algorithm which can be
applied in cloud environments. We have named it “PJSC”.
We can get less finish time than any other algorithm. Job
which has maximum priority can be served fast.
The proposed algorithm can be further improved by
considering following suggestions –
By using this algorithm we can also minimize cost
also this can be future work.
Analytic hierarchy process is only method so that
we can choose one of the best alternatives from others.
Complexity is also future work for proposed algorithm.
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