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.
Max Min Fair Scheduling Algorithm using In Grid Scheduling with Load Balancing IJORCS
This paper shows the importance of fair scheduling in grid environment such that all the tasks get equal amount of time for their execution such that it will not lead to starvation. The load balancing of the available resources in the computational grid is another important factor. This paper considers uniform load to be given to the resources. In order to achieve this, load balancing is applied after scheduling the jobs. It also considers the Execution Cost and Bandwidth Cost for the algorithms used here because in a grid environment, the resources are geographically distributed. The implementation of this approach the proposed algorithm reaches optimal solution and minimizes the make span as well as the execution cost and bandwidth cost.
Max Min Fair Scheduling Algorithm using In Grid Scheduling with Load Balancing IJORCS
This paper shows the importance of fair scheduling in grid environment such that all the tasks get equal amount of time for their execution such that it will not lead to starvation. The load balancing of the available resources in the computational grid is another important factor. This paper considers uniform load to be given to the resources. In order to achieve this, load balancing is applied after scheduling the jobs. It also considers the Execution Cost and Bandwidth Cost for the algorithms used here because in a grid environment, the resources are geographically distributed. The implementation of this approach the proposed algorithm reaches optimal solution and minimizes the make span as well as the execution cost and bandwidth cost.
Fixed Point Realization of Iterative LR-Aided Soft MIMO Decoding AlgorithmCSCJournals
Multiple-input multiple-output (MIMO) systems have been widely acclaimed in order to provide high data rates. Recently Lattice Reduction (LR) aided detectors have been proposed to achieve near Maximum Likelihood (ML) performance with low complexity. In this paper, we develop the fixed point design of an iterative soft decision based LR-aided K-best decoder, which reduces the complexity of existing sphere decoder. A simulation based word-length optimization is presented for physical implementation of the K-best decoder. Simulations show that the fixed point result of 16 bit precision can keep bit error rate (BER) degradation within 0.3 dB for 8×8 MIMO systems with different modulation schemes.
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost
constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy
membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the
presented problem. The optimal solution found by the proposed approach is characterized by maximum
reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different
examples taken from the literature to illustrate its efficiency in comparison with other previous methods
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the presented problem. The optimal solution found by the proposed approach is characterized by maximum reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different examples taken from the literature to illustrate its efficiency in comparison with other previous methods.
DESIGN OF DELAY COMPUTATION METHOD FOR CYCLOTOMIC FAST FOURIER TRANSFORMsipij
In this paper the Delay Computation method for Common Sub expression Elimination algorithm is being implemented on Cyclotomic Fast Fourier Transform. The Common Sub Expression Elimination algorithm is combined with the delay computing method and is known as Gate Level Delay Computation with Common Sub expression Elimination Algorithm. Common sub expression elimination is effective
optimization method used to reduce adders in cyclotomic Fourier transform. The delay computing method is based on delay matrix and suitable for implementation with computers. The Gate level delay computation method is used to find critical path delay and it is analyzed on various finite field elements. The presented algorithm is established through a case study in Cyclotomic Fast Fourier Transform over finite field. If Cyclotomic Fast Fourier Transform is implemented directly then the system will have high additive complexities. So by using GLDC-CSE algorithm on cyclotomic fast Fourier transform, the additive
complexities will be reduced and also the area and area delay product will be reduced.
Fault-Tolerance Aware Multi Objective Scheduling Algorithm for Task Schedulin...csandit
Computational Grid (CG) creates a large heterogeneous and distributed paradigm to manage and execute the applications which are computationally intensive. In grid scheduling tasks are assigned to the proper processors in the grid system to for its execution by considering the execution policy and the optimization objectives. In this paper, makespan and the faulttolerance of the computational nodes of the grid which are the two important parameters for the task execution, are considered and tried to optimize it. As the grid scheduling is considered to be NP-Hard, so a meta-heuristics evolutionary based techniques are often used to find a solution for this. We have proposed a NSGA II for this purpose. The performance estimation ofthe proposed Fault tolerance Aware NSGA II (FTNSGA II) has been done by writing program in Matlab. The simulation results evaluates the performance of the all proposed algorithm and the results of proposed model is compared with existing model Min-Min and Max-Min algorithm which proves effectiveness of the model.
FAST ALGORITHMS FOR UNSUPERVISED LEARNING IN LARGE DATA SETScsandit
The ability to mine and extract useful information automatically, from large datasets, is a
common concern for organizations (having large datasets), over the last few decades. Over the
internet, data is vastly increasing gradually and consequently the capacity to collect and store
very large data is significantly increasing.
Existing clustering algorithms are not always efficient and accurate in solving clustering
problems for large datasets.
However, the development of accurate and fast data classification algorithms for very large
scale datasets is still a challenge. In this paper, various algorithms and techniques especially,
approach using non-smooth optimization formulation of the clustering problem, are proposed
for solving the minimum sum-of-squares clustering problems in very large datasets. This
research also develops accurate and real time L2-DC algorithm based with the incremental
approach to solve the minimum
Fixed Point Realization of Iterative LR-Aided Soft MIMO Decoding AlgorithmCSCJournals
Multiple-input multiple-output (MIMO) systems have been widely acclaimed in order to provide high data rates. Recently Lattice Reduction (LR) aided detectors have been proposed to achieve near Maximum Likelihood (ML) performance with low complexity. In this paper, we develop the fixed point design of an iterative soft decision based LR-aided K-best decoder, which reduces the complexity of existing sphere decoder. A simulation based word-length optimization is presented for physical implementation of the K-best decoder. Simulations show that the fixed point result of 16 bit precision can keep bit error rate (BER) degradation within 0.3 dB for 8×8 MIMO systems with different modulation schemes.
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost
constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy
membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the
presented problem. The optimal solution found by the proposed approach is characterized by maximum
reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different
examples taken from the literature to illustrate its efficiency in comparison with other previous methods
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the presented problem. The optimal solution found by the proposed approach is characterized by maximum reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different examples taken from the literature to illustrate its efficiency in comparison with other previous methods.
DESIGN OF DELAY COMPUTATION METHOD FOR CYCLOTOMIC FAST FOURIER TRANSFORMsipij
In this paper the Delay Computation method for Common Sub expression Elimination algorithm is being implemented on Cyclotomic Fast Fourier Transform. The Common Sub Expression Elimination algorithm is combined with the delay computing method and is known as Gate Level Delay Computation with Common Sub expression Elimination Algorithm. Common sub expression elimination is effective
optimization method used to reduce adders in cyclotomic Fourier transform. The delay computing method is based on delay matrix and suitable for implementation with computers. The Gate level delay computation method is used to find critical path delay and it is analyzed on various finite field elements. The presented algorithm is established through a case study in Cyclotomic Fast Fourier Transform over finite field. If Cyclotomic Fast Fourier Transform is implemented directly then the system will have high additive complexities. So by using GLDC-CSE algorithm on cyclotomic fast Fourier transform, the additive
complexities will be reduced and also the area and area delay product will be reduced.
Fault-Tolerance Aware Multi Objective Scheduling Algorithm for Task Schedulin...csandit
Computational Grid (CG) creates a large heterogeneous and distributed paradigm to manage and execute the applications which are computationally intensive. In grid scheduling tasks are assigned to the proper processors in the grid system to for its execution by considering the execution policy and the optimization objectives. In this paper, makespan and the faulttolerance of the computational nodes of the grid which are the two important parameters for the task execution, are considered and tried to optimize it. As the grid scheduling is considered to be NP-Hard, so a meta-heuristics evolutionary based techniques are often used to find a solution for this. We have proposed a NSGA II for this purpose. The performance estimation ofthe proposed Fault tolerance Aware NSGA II (FTNSGA II) has been done by writing program in Matlab. The simulation results evaluates the performance of the all proposed algorithm and the results of proposed model is compared with existing model Min-Min and Max-Min algorithm which proves effectiveness of the model.
FAST ALGORITHMS FOR UNSUPERVISED LEARNING IN LARGE DATA SETScsandit
The ability to mine and extract useful information automatically, from large datasets, is a
common concern for organizations (having large datasets), over the last few decades. Over the
internet, data is vastly increasing gradually and consequently the capacity to collect and store
very large data is significantly increasing.
Existing clustering algorithms are not always efficient and accurate in solving clustering
problems for large datasets.
However, the development of accurate and fast data classification algorithms for very large
scale datasets is still a challenge. In this paper, various algorithms and techniques especially,
approach using non-smooth optimization formulation of the clustering problem, are proposed
for solving the minimum sum-of-squares clustering problems in very large datasets. This
research also develops accurate and real time L2-DC algorithm based with the incremental
approach to solve the minimum
MULTIPROCESSOR SCHEDULING AND PERFORMANCE EVALUATION USING ELITIST NON DOMINA...ijcsa
Task scheduling plays an important part in the improvement of parallel and distributed systems. The problem of task scheduling has been shown to be NP hard. The time consuming is more to solve the problem in deterministic techniques. There are algorithms developed to schedule tasks for distributed environment, which focus on single objective. The problem becomes more complex, while considering biobjective.This paper presents bi-objective independent task scheduling algorithm using elitist Nondominated
sorting genetic algorithm (NSGA-II) to minimize the makespan and flowtime. This algorithm generates pareto global optimal solutions for this bi-objective task scheduling problem. NSGA-II is implemented by using the set of benchmark instances. The experimental result shows NSGA-II generates efficient optimal schedules.
Problems in Task Scheduling in Multiprocessor Systemijtsrd
This Contemporary computer systems are multiprocessor or multicomputer machines. Their efficiency depends on good methods of administering the executed works. Fast processing of a parallel application is possible only when its parts are appropriately ordered in time and space. This calls for efficient scheduling policies in parallel computer systems. In this work deterministic problems of scheduling are considered. The classical scheduling theory assumed that the application in any moment of time is executed by only one processor. This assumption has been weakened recently, especially in the context of parallel and distributed computer systems. This monograph is devoted to problems of deterministic scheduling applications (or tasks according to the scheduling terminology) requiring more than one processor simultaneously. We name such applications multiprocessor tasks. In this work the complexity of open multiprocessor task scheduling problems has been established. Algorithms for scheduling multiprocessor tasks on parallel and dedicated processors are proposed. For a special case of applications with regular structure which allow for dividing it into parts of arbitrary size processed independently in parallel, a method of finding optimal scattering of work in a distributed computer system is proposed. The applications with such regular characteristics are called divisible tasks. The concept of a divisible task enables creation of tractable computation models in a wide class of computer architectures such as chains, stars, meshes, hypercubes, multistage networks. Divisible task method gives rise to the evaluation of computer system performance. Examples of such performance evaluation are presented. This work summarizes earlier works of the author as well as contains new original results. Mukul Varshney | Jyotsna | Abhakiran Rajpoot | Shivani Garg"Problems in Task Scheduling in Multiprocessor System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2198.pdf http://www.ijtsrd.com/computer-science/computer-architecture/2198/problems-in-task-scheduling-in-multiprocessor-system/mukul-varshney
International Refereed Journal of Engineering and Science (IRJES)irjes
The core of the vision IRJES is to disseminate new knowledge and technology for the benefit of all, ranging from academic research and professional communities to industry professionals in a range of topics in computer science and engineering. It also provides a place for high-caliber researchers, practitioners and PhD students to present ongoing research and development in these areas.
With the widespread of smart mobile devices and the
availability of many applications that provide maps, many programs
have spread to find the closest and fastest routes between
two points on the map. While the exactness and effectiveness of
best path depend on the traffic circumstances, the system needs to
add more parameters such as real traffic density and velocity in
road. In addition, because of the restricted resources of phone devices,
it is not reasonable to be used to calculate the exact optimal
solutions by some familiar deterministic algorithms, which are
usually used to find the shortest path with a map of reasonable
node number. To resolve this issue, this paper put forward to use
the genetic algorithm to reduce the computational time. The proposed
system use the genetic algorithm to find the shortest path
time with miscellaneous situations of real traffic conditions. The
genetic algorithm is clearly demonstrate excellent result when applied
on many types of map, especially when the number of nodes
increased.
Traditional interpreted data-flow analysis is executed on whole plans; however, such whole-program psychoanalysis is not
executable for large or uncompleted plans. We suggest fragment data-flow analysis as a substitute approach which
calculates data-flow information for a particular program fragment. The psychoanalysis is parameterized by the extra
information available about the rest of the program. We depict two frameworks for interracial flow-sensitive fragment
psychoanalysis, the relationship amongst fragment psychoanalysis and whole-program analysis, and the necessities ensuring fragment analysis safety and feasibility. We suggest an application of fragment analysis as a second analysis phase after a cheap flow-insensitive whole-program analysis, in order to obtain better data for important program fragments. We also depict the design of two fragment analyses derived from an already existing whole-program flow- and context-sensitive pointer alias analysis for Computer program and present empirical rating of their cost and precision. Our experiments show evidence of dramatic improves precision gettable at a practical cost.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
A comparison of efficient algorithms for scheduling parallel data redistributionIJCNCJournal
Data redistribution in parallel is an often-address
ed issue in modern computer networks. In this conte
xt, we
study the case of data redistribution over a switch
ing network. Data from the source stations need to
be
transferred to the destination stations in the mini
mum time possible. Unfortunately the time required
to
complete the transfer is burdened by each switching
and thus producing an optimal schedule is proven t
o
be computationally intractable. For the purposes of
this paper we consider two algorithms, which have
been proved to be very efficient in the past. To ge
t improved results in comparison to previous approa
ches,
we propose splitting the data in two clusters depen
ding on the size of the data to be transferred. To
prove
the efficiency of our approach we ran experiments o
n all three algorithms, comparing the time span of
the
schedules produced as well as the running times to
produce those schedules. The test cases we ran
indicate that not only our newly proposed algorithm
yields better results in terms of the schedule pro
duced
but runs faster as well.
Constructing a classification model is important in machine learning for a particular task. A
classification process involves assigning objects into predefined groups or classes based on a
number of observed attributes related to those objects. Artificial neural network is one of the
classification algorithms which, can be used in many application areas. This paper investigates
the potential of applying the feed forward neural network architecture for the classification of
medical datasets. Migration based differential evolution algorithm (MBDE) is chosen and
applied to feed forward neural network to enhance the learning process and the network
learning is validated in terms of convergence rate and classification accuracy. In this paper,
MBDE algorithm with various migration policies is proposed for classification problems using
medical diagnosis.
MEDICAL DIAGNOSIS CLASSIFICATION USING MIGRATION BASED DIFFERENTIAL EVOLUTION...cscpconf
Constructing a classification model is important in machine learning for a particular task. A
classification process involves assigning objects into predefined groups or classes based on a
number of observed attributes related to those objects. Artificial neural network is one of the
classification algorithms which, can be used in many application areas. This paper investigates
the potential of applying the feed forward neural network architecture for the classification of
medical datasets. Migration based differential evolution algorithm (MBDE) is chosen and
applied to feed forward neural network to enhance the learning process and the network
learning is validated in terms of convergence rate and classification accuracy. In this paper,
MBDE algorithm with various migration policies is proposed for classification problems using
medical diagnosis.
GRAPH MATCHING ALGORITHM FOR TASK ASSIGNMENT PROBLEMIJCSEA Journal
Task assignment is one of the most challenging problems in distributed computing environment. An optimal task assignment guarantees minimum turnaround time for a given architecture. Several approaches of optimal task assignment have been proposed by various researchers ranging from graph partitioning based tools to heuristic graph matching. Using heuristic graph matching, it is often impossible to get optimal task assignment for practical test cases within an acceptable time limit. In this paper, we have parallelized the basic heuristic graph-matching algorithm of task assignment which is suitable only for cases where processors and inter processor links are homogeneous. This proposal is a derivative of the basic task assignment methodology using heuristic graph matching. The results show that near optimal assignments are obtained much faster than the sequential program in all the cases with reasonable speed-up.
An Examination of Effectuation Dimension as Financing Practice of Small and M...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Does Goods and Services Tax (GST) Leads to Indian Economic Development?iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Childhood Factors that influence success in later lifeiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Emotional Intelligence and Work Performance Relationship: A Study on Sales Pe...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Customer’s Acceptance of Internet Banking in Dubaiiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study of Employee Satisfaction relating to Job Security & Working Hours amo...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Consumer Perspectives on Brand Preference: A Choice Based Model Approachiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Student`S Approach towards Social Network Sitesiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Broadcast Management in Nigeria: The systems approach as an imperativeiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study on Retailer’s Perception on Soya Products with Special Reference to T...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study Factors Influence on Organisation Citizenship Behaviour in Corporate ...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Consumers’ Behaviour on Sony Xperia: A Case Study on Bangladeshiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Design of a Balanced Scorecard on Nonprofit Organizations (Study on Yayasan P...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Public Sector Reforms and Outsourcing Services in Nigeria: An Empirical Evalu...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Media Innovations and its Impact on Brand awareness & Considerationiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Customer experience in supermarkets and hypermarkets – A comparative studyiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Social Media and Small Businesses: A Combinational Strategic Approach under t...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Secretarial Performance and the Gender Question (A Study of Selected Tertiary...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Implementation of Quality Management principles at Zimbabwe Open University (...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Organizational Conflicts Management In Selected Organizaions In Lagos State, ...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Application
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Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Gen AI Study Jams _ For the GDSC Leads in India.pdf
Scheduling Using Multi Objective Genetic Algorithm
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 3, Ver. II (May – Jun. 2015), PP 73-78
www.iosrjournals.org
DOI: 10.9790/0661-17327378 www.iosrjournals.org 73 | Page
Scheduling Using Multi Objective Genetic Algorithm
Anu Dogra1
, Kritika Dhiman2
(Computer Science, Guru Nanak Dev University , Amritsar , India)
Abstract : Multiprocessor task scheduling is considered to be the most important and very difficult issue. Task
scheduling is performed to match the resource requirement of the job with the available resources resulting in
effective utilization of multiprocessor systems. In this paper, a Multi Objective Genetic algorithm (MOGA) is
proposed for static, non- pre-emptive scheduling problem in homogeneous fully connected multiprocessor
systems with the objective of minimizing the job completion time. The proposed GA is used to determine suitable
priorities that lead to a sub-optimal solution. Our proposed GA for a given job scheduling problem proves that
GA results in better sub-optimal solutions.
Keywords: Directed Acyclic Graph, Genetic algorithm, multiprocessing environment, parallel computing,
Task scheduling.
I. Introduction
Today’s applications are made up of several of tasks that is to processed by multiple processors to
achieve a specific goal. So they deal with the allocation of individual tasks to suitable processors and
assignment in proper order of execution of tasks. Parallel scheduling increase the performance by properly
scheduling tasks to processors and reduce the completion time. Well-organized Task scheduling is a necessary
part for appropriate functioning of parallel processing [7]. Efficient task scheduling is one of key factors for
providing high performance on heterogeneous computing. The field of parallel task scheduling is one of the
most advanced and rapidly evolving fields in computer science. High performance computing is expected to
bring a breakthrough in the increase of computing speed [1]. Optimal solution for scheduling is not feasible for
Such Problems which are NP -complete. A large number of algorithms has been proposed which attempt to
bring a sub optimal solution. Mainly four algorithms are proposed in parallel computing for task scheduling
BNP (Bounded Number of Processors) scheduling
UNC (Unbounded Number of Clusters) scheduling
TDB (Task Duplication Based) scheduling
APN (Arbitrary Processors Network) scheduling
Multiprocessor scheduling processor involves mapping a Directed Acyclic Graph (DAG) for a collection of
computational tasks and data precedence onto parallel processing system. The objective of scheduling is to
minimize the overall program finish time by proper allocation of jobs to processors and arrangement of
execution sequencing of tasks [2].
1.1 APN Scheduling
It is one of the scheduling algorithm from the four above parallel scheduling algorithms. Our main
focus is on this algorithm and we want to make such an algorithm which can find better results than one of the
further algorithms of APN that is MH (mapping heuristics). Algorithms in this class take into account specific
features such as the number of processors and their interconnection topology. These algorithms can schedule
tasks on processors and messages over a network communication links. Scheduling of tasks is dependent on the
routing strategy used by the original network [9]. The mapping including the temporal dependencies, is
therefore implicit-without going through a separate clustering phase. In the following, we discuss four such
algorithms.
MH (Mapping Heuristic) algorithm
DLS (Dynamic Level Scheduling) algorithm
BU (Bottom Up) algorithm
BSA (Bubble Scheduling and Allocation) algorithm [5]
To estimate performance for these algorithms we have to analyse the various parameters are
1.1.1 Make span: It is defined as the completion time of the algorithm and it is calculated by the extent of the
finishing time of the algorithm.
1.1.2 Speed up: Speed up is calculated by computing the execution time for the processors running sequential
and parallel. Dividing the finishing time of processors running sequentially by the execution time of processors
running parallel is termed as speed up.
2. Scheduling Using Multi Objective Genetic Algorithm
DOI: 10.9790/0661-17327378 www.iosrjournals.org 74 | Page
1.1.3 Scheduled Length Ratio: It is the proportion of the make span of algorithm to the critical path values of
DAG [10].
1.2 Dag Model
DAG (Directed acyclic Graphs) shows the tasks that are allocated to the uniform processors .It is a task
graph in which various tasks assigned to the processors are represented and set with the purpose of minimizing
the all-purpose finish time by proper share of the tasks such as the maximum throughput can be achieved. DAG
is regular model of parallel program consisting of set of processes amongst which there are dependencies. Each
process is an inseparable unit of execution, articulated by a node. A node has one or more inputs and can have
one or more output to different nodes. When all inputs are available the node is triggered to perform. After its
implementation it generates its output. In this model a set of nodes (𝑛1, 𝑛2,……𝑛 𝑛) are related by a set of
directed edges, which are represented by (𝑛 𝑖 , 𝑛 𝑗 ) where𝑛 𝑖 is called the parent node and 𝑛 𝑗 is called the child
node. A node with no parent is called an Entry node and node without child node called an Exit node. The
weight of a node, denoted by w (𝑛 𝑗 ) represents the process finishing time of a process. Since each edge
correspond to a message transfer from one process to another, the weight of an edge denoted by c (𝑛 𝑖 , 𝑛 𝑗 ) is
equal to the message transmission time from node 𝑛 𝑖 ,to 𝑛 𝑗 . Thus c (𝑛 𝑖 , 𝑛 𝑗 ) becomes zero when 𝑛 𝑖 and 𝑛 𝑗 are
scheduled to same processor because intra processor communication time is negligible compared with the inter
processor communication time. The node and edge weights are usually obtained by estimations. Some variations
in the generic DAG model are described below in fig.1 [3]
Fig.1: Directed Acyclic Graph
1.3 Scheduling Attributes
The main scheduling attributes used in DAG for transfer priority while evaluating the algorithms are as follows:
(1) T- Level: T-level of a node 𝑛 𝑖 in DAG is the length of the greatest path from entry node to 𝑛 𝑖 not including
𝑛 𝑖 . It is addition of all the nodes computational costs and edges weights all along the path.
𝑇 − 𝑙 𝑒𝑣𝑒𝑙 ( 𝑛 𝑖 ) = 𝑚𝑎𝑥 (𝑇 − 𝑙 𝑒𝑣𝑒𝑙 ( 𝑛 𝑚) + 𝑤 𝑚 + 𝑐 𝑚)
where 𝑛 𝑚 € predecessors of 𝑛 𝑖 , 𝑤 𝑚 stands for computational charge, 𝑐 𝑚,𝑖 stands for the message cost and t-
level (𝑛 𝑒𝑛𝑡𝑟𝑦 ) = 0
(2) B- Level: B-level of node 𝑛 𝑖 in DAG is the length of the greatest path from 𝑛 𝑖 to the exit node. It is the
addition of all the nodes computational costs and edges weights all along the path.
𝑏 − 𝑙 𝑒𝑣𝑒𝑙 ( 𝑛 𝑖 ) = 𝑤𝑖 + 𝑚𝑎𝑥 (𝑏 − 𝑙 𝑒𝑣𝑒𝑙 ( 𝑛 𝑚) + 𝑐 𝑚,𝑖 )
Where 𝑛 𝑚 € successors of 𝑛 𝑖 , 𝑤 𝑚 stand for computational cost, 𝑐 𝑚,𝑖 stands for the message cost and b- level
(𝑛 𝑒𝑥𝑖𝑡 ) = w (𝑣 𝑒𝑥𝑖𝑡 ).
(3) SL (Static Level): If the edges weights are not taken while considering the b-level , it is called static level.
𝑆𝐿 ( 𝑛 𝑖 ) = 𝑤𝑖 + 𝑚𝑎𝑥 (𝑆𝐿 (𝑛 𝑚))
Where 𝑛 𝑚 € successors of 𝑛 𝑖 and SL (𝑛 𝑒𝑥𝑖𝑡 ) = w (𝑣 𝑒𝑥𝑖𝑡 )
(4) CP (Critical Path): It is the length of the longest path from station node to the exit node in DAG.
(5) EST (Earliest Start Time): It is same as the t-level.
𝐸𝑆𝑇 ( 𝑛 𝑖 ) = 𝑚𝑎𝑥 (𝐸𝑆𝑇 ( 𝑛 𝑚) + 𝑤 𝑚 + 𝑐 𝑚,𝑖 )
3. Scheduling Using Multi Objective Genetic Algorithm
DOI: 10.9790/0661-17327378 www.iosrjournals.org 75 | Page
Where 𝑛 𝑚 € predecessors of 𝑛 𝑖 , 𝑤 𝑚 stands for computational cost, 𝑐 𝑚,𝑖 stands for the computational cost and
EST (𝑛 𝑒𝑛𝑡𝑟𝑦 ) = 0
(6) LST (Latest Starting Time): Latest Starting Time of node is computed by follow the path starting from exit
node upwards till the preferred node is reached.
𝐿𝑆𝑇 ( 𝑛 𝑖 ) = 𝑚𝑖 𝑛 ( 𝐿𝑆𝑇 ( 𝑛 𝑚) − 𝑐 𝑚,𝑖 ) − 𝑤 𝑚
Where 𝑛 𝑚 € predecessors of 𝑛 𝑖 , 𝑤 𝑚 stands for computational cost, 𝑐 𝑚,𝑖 stands for the computational cost and
LST (𝑛 𝑒𝑥𝑖𝑡 ) = EST (𝑛 𝑒𝑥𝑖𝑡 ).
(7) DL (Dynamic level): Dynamic Level of the node is considered by subtracting the earliest start time from the
static level.
𝐷𝐿 = 𝑆𝐿 − 𝐸𝑆𝑇
Where SL stands for Static Level and EST stands for Early Start Time [4].
1.4 Genetic Algorithms
GAs motivated by DARWINs theory about continued existence of the fittest. Since in nature ,
competition among individuals for resources consequences in fittest individuals dominating over the weaker
ones. Planned and developed in 1960s by John Holland. These algorithms are search algorithms based on
natural selection and natural genetics [6]. It works under population of solution rather than a particular solution.
Here investigate begins by initializing a population of individuals. Individual solutions are chosen from the
population and after mating them a new children is generated. The mating is done by crossing over genetic
material from two parents and as a result transfers the data from one production to next. This sometimes
promotes the diversity. Fitness function is used to measures the quality of each candidate.
The three main steps applied in genetic algorithm are [7]
1.4.1 Selection: Selection improves the superiority of population by generous chromosomes a better chance to
get derivative in the next generation. It gives first choice to better individuals, allow them to pass on their genes
to the next generation. The integrity of each individual depends on its fitness. Fitness is resolute by a fitness
function which may be one-sided, objective or judgement.
1.4.2 Crossover: The two new offspring is generated from mating in excess of the two individuals that are
selected from population by means of selection method and set them into the next generation. By recombining
portions of good quality individuals, this process is expected to create even better individuals.
1.4.3 Mutation: Mutate a chromosome to form new chromosomes. Figure a new chromosome by randomly
pick chromosome. This operator modify one or more genetic material values in an individual. The result of this
modification can be completely new gene values being added to the same group. The genetic algorithm may be
accomplished to reach at better solution with these new gene values [8].
II. Literature Survey
S.Sharma et al. (2014) Author described various parallel scheduling algorithms and their drawbacks.
Out of static algorithms the DCP (Dynamic Critical Path) is the best algorithm having admissible time
complexity and cheap in terms of number of processors used. But multiprocessors problem is NP-complete in
nature and becomes more complex under calm assumptions. Therefore a genetic approach based was proposed
to get together the goals of high performance, scalability and fast running time called parallel genetic scheduling
algorithm [8].
A.sharma et al. (2013) developed Parallel processing is a field in which diverse systems run together to
save the time of processing and to increase the presentation of the system and to balance load in this paper we
have combined HLFET, MCP, DLS , ETF with fuzzy logics to check out effects on parameters like speedup,
process utilization , make span. So it has established that fuzzy logic execute better than single algorithms [3].
A.Kaur et al. (2013) Author designed Mapping Heuristic method where list is prepared according to
maximum priority node. Here routing table is maintained with each processor straight path between processing
element is also maintained in this table. Route from source to destination gets busy when message is sent and
become free when received by the receiver and accordingly updation in routing table is complete. Also applying
genetic in this approach may find an optimal result and can perform better than simple mapping heuristic [6].
P.Kaur (2013) Author developed Scheduling and mapping of task graphs to the processors which is one
of the most critical problems in parallel computing. Due to NP- completeness of any problem, the optimal
solution can not be find in a sensible time. The existing heuristics is that they can assess the problem size which
are very small. Author implements APN Dynamic Level Scheduling algorithm by using genetic operators for
task scheduling in parallel multiprocessor system with communication delays to reduce the completion time and
to boost the throughput of the system. The parameters used are make span time, processor operation and
4. Scheduling Using Multi Objective Genetic Algorithm
DOI: 10.9790/0661-17327378 www.iosrjournals.org 76 | Page
scheduled length ratio. The graphs show better results of dynamic level scheduling with genetic operators as
compared to simple dynamic level scheduling algorithm [9].
P.Sharma et al.(2013) Author proposed genetic algorithms for a superior solution in parallel processing.
Adaptive parameter approach is applied to enlarge the performance of genetic algorithm. Paper presents GA
implementation. Results shows with amplify in number of nodes, speedup increases but communication below
also increases [7].
P.Gupta et al. (2012) Discussed one of the algorithm of APN scheduling which is to be explained in
detail called as mapping heuristic (MH) APN scheduling algorithm. It is implemented for task processing in
parallel multiprocessor system including the communication delays to reduce the completion time and
throughput of the system. [4]
N.Arora (2012) Author proposed Directed acyclic Graphs which schedule the tasks to reduce the
completion time. Various algorithms of scheduling tasks are analyzed which are categorized in four groups. The
performance is the important factor in every algorithm. Also the performance is measured using these
algorithms by manipulative some parameters. [10].
W.Nasri (2012) Author explained efficient task scheduling which is one of the key factors to provide
high presentation in heterogeneous systems. Directed Acyclic Graphs are explained for the scheduling in
heterogeneous systems. In this work, author has addressed the problem of DAG scheduling on heterogeneous
platforms made of clusters of clusters. To be sure, author has developed a new algorithm called SMC
(Scheduling on Multi Clusters) based on two principal phases: the organization of tasks and the project of tasks
to the most appropriate processors. SMC algorithm gives an improvement in the first phase which is a very
important leading to an perfection of performance [1].
R.Kaur (2012) Author claims the designed Genetic Algorithm as the more efficient and finds more
optimal solution than the parallel computing algorithms. To evaluate the performance the future GA is
experienced by mapping the tasks into the Directed Acyclic Graph. Performance study of static algorithms of
BNP and future GAs for a given difficulty shows that GAs are better than BNP scheduling [2].
P.Kaur (2011) Author surveys algorithms that assign parallel tasks represented by an edge-directed
acyclic graph (DAG). Taking purpose to minimize the execution time, assess and evaluate the performance of
the individual algorithms to find the best algorithm. Dissimilar algorithms are analyzed and classified into four
groups. BNP algorithm is study and discussed, and to measure the performance of BNP algorithm and evaluate
the best algorithm. So it is concluded from above results that DLS is one of the efficient algorithms [12].
E.S.C et al. (2003) Author shows problem in allocating non identical tasks in multiprocessor model
assumes identical processors and at a time only one processor may execute one task. Here GA approach is
proposed to finding optimal solution for arbitrary task graph.GA provides set of optimal solutions. GA is free of
List Scheduling Algorithms anomalies [11].
I.Ahmed et al. (1995) Author Compared various algorithms for scheduling and also compare one of the
class of the algorithms called APN scheduling algorithms. He discussed the designs ,philosophies and
principles behind these algorithms and access their merits and deficiencies. Also APN algorithms can be
complicated so further research is required in this area [5].
III. Nature of the problem
● The Mapping Heuristic problem of parallel Job Scheduling is NP-complete.
● The MH-problem may take super polynomial time to solve task scheduling. This is because they are not
scalable in nature.
● Accurate methods such as Branch and Bound method and dynamic programming take considerable
computing time if an optimal solution exists.
IV. Purpose
APN scheduling: These algorithms execute scheduling of tasks amongst various processors in which the
processors are connected via a network of arbitrary topology. The algorithm in this class take into account some
specific features such as number of processors and interconnection topology. They also list messages on the
network message links.
MH scheduling: It is one of the class of APN scheduling. It performs scheduling on the basis of priorities
assigned to the nodes. It assigns priorities by computing static B-level of the nodes. Nodes with highest priority
will be assigned processor first and accordingly scheduling is done.
The mapping Heuristic problem of parallel Job Scheduling is NP-complete. The MH-problem may take super
polynomial time to solve task scheduling. This is because they are not scalable in nature. Exact methods such as
Branch and Bound method and dynamic programming take considerable computing time if an optimal solution
exists
5. Scheduling Using Multi Objective Genetic Algorithm
DOI: 10.9790/0661-17327378 www.iosrjournals.org 77 | Page
This paper deals with the use of Genetic Algorithm in field of Arbitrary Processors Network scheduling
algorithm. Our purpose is to overcome the limitations of earlier techniques, it is more sensible to obtain a good
solution near the optimal one. So this work will use genetic algorithm to obtain good solution near the optimal
one. The overall objective is to reduce the make span time along with the reduction of execution time of genetic
algorithm.
V. Objectives
1. To reduce the computational complexity of Mapping Heuristic in APN scheduling algorithm, the multi
objective genetic programming will be used.
2. To establish a practical relationship between the development of Genetic algorithm and parallel scheduling in
MH of APN scheduling .
3. To evaluate the effect of job size on the proposed algorithm.
4.To verify the proposed algorithm following parameters will be used
Speed up
SLR
Makespan
VI. Methodology
Proposed Mapping Heuristic scheduling using multiple objective Genetic algorithm . It searches
optimal solution from entire solution space. We will overcome the drawbacks of previously explained
algorithms of APN scheduling and try to attain our objectives using multiple objective Genetic Algorithm .
Genetic algorithm is a method that works on the chromosomes. Mainly three operators are used in it:
Selection operator
Crossover operator
Mutation operator
Genetic Algorithm works in the following steps:
STEP 1[Start]: Create random population of chromosomes, to be exact suitable solutions for the problem.
STEP 2[Fitness]: Calculate the fitness of each chromosome by resources of fitness function.
STEP 3[New population]: Create a new population by repeating following steps until new population is
complete.
[SELECTION] Select two parent chromosomes from a population according to their fitness. Better the fitness,
the bigger chance to be selected to be the parent.
[CROSSOVER] Crossover the parents to form the new offspring, that is children. If no crossover was
performed then off spring will be the exact copy of the parents.
[MUTATION] Using mutation mutate new offspring at each locus.
[ACCEPTING] Then new offspring is placed in the new population.
STEP 4[Replace]: Replace with new generated population for further execution of the process.
STEP 5[Test]: Finally if the end condition is satisfied then stop and return the final result to the in the current
population.
STEP 6[Loop]: Go to step 2.
Below the flow chart will explain the working of the genetic algorithm in fig. 2 (Directed Acyclic Graph)
6. Scheduling Using Multi Objective Genetic Algorithm
DOI: 10.9790/0661-17327378 www.iosrjournals.org 78 | Page
VII. Conclusion
Scheduling system makes everyone’s job easier. It provides a means of holding down costs through
better use of personnel and equipment. it makes better use of multiprogramming capabilities. It may predict the
effects of an increased workload, future equipment and personnel needs. It gives the full advantage of
computational power provided by multiprocessors. It also increases throughput and reduces complexity. As
planning out tasks is an important part of good business. So to achieve high performance, an efficient scheduling
with an optimal solution is to be developed.
References
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[9]. Kaur, Prabhjot, and Amanpreet Kaur. "Implementation of Dynamic Level Scheduling Algorithm using Genetic Operators."
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Ejército de los Andes 950 - Local 106 5700 - San Luis, Argentina. Universidad Nacional de San Luis and the ANPCYT (National
Agency to Promote Science and Technology), 2003
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