Computer Science & Information Technology ( CS & IT ), 2013
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
Environmental Pollution in India is growing by leaps and bounds. Air pollution, water contaminati... more Environmental Pollution in India is growing by leaps and bounds. Air pollution, water contamination, and noise pollution are the three basic types of pollution. Rising population, rapid growth in industrialization and rising demands for automobiles in India are worsening air pollution levels. Air pollution has been contributing significantly to the country's burden of ill health. In contrast to most other developing countries, India has failed to establish a timeframe for meeting its national Air Quality Standards. Air pollution is rapidly becoming a serious public health concern that has a negative impact on our quality of life and economy. This research examines the state of air pollution in India, as well as the application of machine learning approaches to anticipate air quality. It also highlights some challenges and proposed developments for future.
Summarization is the process of converting any given long text into a lossy compressed version wh... more Summarization is the process of converting any given long text into a lossy compressed version while preserving the overall essence and meaning of the original given text. A problem in natural language processing is the task of summarizing a voluminous text. This research, lays emphasis on abstractive summarization of the text, a process which generates a coherent, short and meaningful text by learning the context from given input source text. This work is a preliminary attempt to generate abstractive summary. The proposed work uses the Attentional Encoder and Decoder based Sequence to Sequence Recurrent Neural Network model. The proposed research's primary objective is to get insights on the working of the mentioned Sequence architecture and the intricacies of different subcomponents of the encoders and the decoders architecture working together so as to give a particular end result. The scope of this paper covers an experimentation of performing text summarization process using Encoder and Decoder based Sequential Learning Recurrent Neural Network design. Satisfactory summary results are obtained after the model is experimented and analyzed on the Amazon Fine Food reviews.
Basic Sciences Journal of Textile Universities, 2022
A Data warehouse is a collection of non-volatile, historical, summarized data that is gathered fr... more A Data warehouse is a collection of non-volatile, historical, summarized data that is gathered from transactional databases over time. Data warehouse systems are beneficial in supporting decisionmaking since they are optimized for On-Line Analytical Processing. The ability of an online analytical tool to deliver information when needed, or to provide "just in time" information for efficient decision-making, is a vital sign of success. It is important to evaluate the performance of these On-Line Analytical Processing applications in the early stages of their development. In this paper we simulate a typical On-Line Analytical Processing query sent to a Data warehouse to know its response time. By creating and resolving the Software Execution Model for a Data warehouse system, we are able to retrieve the Performance metrics. A weather case study is used to discuss the findings.
India conducts both state and federal elections using paperless electronic voting machines. India... more India conducts both state and federal elections using paperless electronic voting machines. Indian authorities have never allowed a meaningful, independent investigation of the security of the devices despite mounting fears of fraud. Blockchain is a technology that has gained a lot of attention recently because it uses an immutable distributed ledger to offer security and anonymity. In applications where trust is of the utmost significance, Blockchain is extensively used because of its reliable consensus mechanism and tamper-proof data storage. By combining all of the individually encrypted votes into one encrypted tally using the homomorphic property, you may obtain the separated-out tallies without compromising the privacy of individual votes. Homomorphic encryption methods are employed to work on the encrypted data without the knowledge of private key. If database data is lost, it may still be possible to recover it from the blockchain cloud. Data that has been encrypted can be operated on without having to first decrypt it. Data may be transferred and stored securely in cloud systems using Blockchain and Homomorphic mechanisms. In this paper we have expla ined the design, implementation and working of a dependable and trustworthy electronic voting application.
A Data Warehouse is characterized by a huge amount of data centralized in a single database. A Da... more A Data Warehouse is characterized by a huge amount of data centralized in a single database. A Data Warehouse architecture is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients. Architecture is an important part of any IT infrastructure because it helps to optimize the performance of the entire system. Query processing in centralized Data Warehouse is different from query processing in distributed Data Warehouse due to the amount of data processed at each site. A three-tier architecture provides an efficient query processing as compared to two-tier architecture because of the presence of precomputed results present in the middle tier. In this research paper, we discuss the primary types of architectures available and the query performance metrics. We are simulating the performance of Data Warehouse system in two types of architectures The result of our simulation clearly shows how the query performance of distributed Data Warehouse and three tier architecture is efficient as compared to their respective counterparts.
International Journal of Advanced Research in Computer Science, 2017
Class Point approach has been proposed to estimate software size of Object-Oriented Systems, syst... more Class Point approach has been proposed to estimate software size of Object-Oriented Systems, systems that involve classes, encapsulation, inheritance and message passing. Another similar approach called Class Method Points has also been proposed in the literature to estimate the size of Object-Oriented software systems. We demonstrate estimation of the effort and size of OLAP system using Class Point approach and Class Method Points approach in the early stages of their development life cycle.
Due to the rapid rise in the identification of digital materials, automatic image classification ... more Due to the rapid rise in the identification of digital materials, automatic image classification has emerged as the most difficult topic of computer vision. In comparison to human vision, automatic visual understanding and analysis by a system is challenging. The findings of many experiments that were done to fix problems of automatic picture classification with the current categorization method were simple picture primitives. However, those methods don't accurately classify photos. In this research work, a system has been created that makes use of deep learning to deliver the necessary results in the area of computer vision. Our technology automatically categorizes photographs using Convolutional Neural Network, a popular machine learning method. Our algorithm classifies grayscale photos using the Digit of MNIST dataset as a benchmark. The dataset that is employed for the training of the system contains grayscale images, which demand higher processing resources for image categorization. By employing Convolution Neural Network to train the photos, we were able to attain higher accuracy results in the experimental section, demonstrating that our model is highly accurate at classifying images.
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
International journal of computer applications, Oct 18, 2014
The increasing demands for interactive response time from the users makes query performance one o... more The increasing demands for interactive response time from the users makes query performance one of the central problems of Data warehouse systems today. Performance is an important quality aspect of Data warehouse systems. Predicting the performance of Data warehouse systems during early design stages of their development is significant. Software Performance Engineering(SPE) promotes the idea that the integration of performance analysis into the software development process, from the earliest stages to the end, can ensure that the system will meet its performance objectives. This paper describes the features and use of a prototype tool, DWPPT(Data Warehouse Performance Prediction Tool) which is designed to analyze the performance of the Data warehouse in different environmental conditions. The tool supports SPE process for Data warehouse systems. The tool is useful for Data warehouse managers in identifying critical components, diagnosing problems and hence optimizing the overall design. Our objective is to investigate the impact of Data warehouse design factors on OLAP performance for different user populations and hardware configurations. An analytical and simulation modeling approach is used for the tool to predict performance of Data warehouse systems.
Journal of Computational and Theoretical Nanoscience, 2020
Digital data in huge amount is being persistently generated at an unparalleled and exponential ra... more Digital data in huge amount is being persistently generated at an unparalleled and exponential rate. In this digital era where internet stands the prime source for generating incredible information, it is vital to develop better means to mine the available information rapidly and most capably. Manual extraction of the salient information from the large input text documents is a time consuming and inefficient task. In this fast-moving world, it is difficult to read all the text-content and derive insights from it. Automatic methods are required. The task of probing for relevant documents from the large number of sources available, and consuming apt information from it is a challenging task and is need of the hour. Automatic text summarization technique can be used to generate relevant and quality information in less time. Text Summarization is used to condense the source text into a brief summary maintaining its salient information and readability. Generating summaries automatically ...
2009 Sixth International Conference on Information Technology: New Generations, 2009
On line analytical Processing (OLAP) systems have become increasingly popular in many application... more On line analytical Processing (OLAP) systems have become increasingly popular in many application areas as they considerably ease the process of analyzing large amounts of enterprise data. Two major physical implementations exist today, relational online analytical processing systems (ROLAP) and multidimensional online analytical processing system (MOLAP). In this paper we present the object oriented OLAP framework using UML models. This
The increasing demands for interactive response time from the users makes query performance one o... more The increasing demands for interactive response time from the users makes query performance one of the central problems of Data warehouse systems today. Performance is an important quality aspect of Data warehouse systems. Predicting the performance of Data warehouse systems during early design stages of their development is significant. Software Performance Engineering(SPE) promotes the idea that the integration of performance analysis into the software development process, from the earliest stages to the end, can ensure that the system will meet its performance objectives. This paper describes the features and use of a prototype tool, DWPPT(Data Warehouse Performance Prediction Tool) which is designed to analyze the performance of the Data warehouse in different environmental conditions. The tool supports SPE process for Data warehouse systems. The tool is useful for Data warehouse managers in identifying critical components, diagnosing problems and hence optimizing the overall de...
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the T...
Online analytical systems based on multidimensional data models enable analysts and decision make... more Online analytical systems based on multidimensional data models enable analysts and decision makers to have fast and interactive responses to queries posed against the data stored in very large databases. Materialized views can speed up the execution of many queries. Materialization of all the possible views is constrained by the storage space and maintenance cost and one needs to select a subset of views to be materialized. Algorithms to determine the views to be materialized need the size of views as input. However, often the task of determining the actual number of rows present in a view can itself be computationally very expensive because of the large sizes of the tables and views. Counting actual number of rows present in each view takes considerable time in an extremely large database environment. Thus, methods to determine a good estimate of the size of a view in reasonable time instead of determining its actual size are very important. We explore the use of sampling to estimate the size of views. In this paper, we propose a hybrid estimator that takes into account the degree of skew in the data and combines Jackknife estimator with the Schlosser's estimator and guaranteed error estimator to estimate the size of the view more accurately. The proposed hybrid estimator has been used to estimate the view size and simulation results show better estimated values as compared to individual estimators.
Query Performance Analysis Tool for Distributed Systems
The increasing demands for fast interactive response times make query performance one of the cent... more The increasing demands for fast interactive response times make query performance one of the central problems of Distributed Systems. A sophisticated design is necessary to ensure high performance of Distributed Systems. Software Performance Engineering (SPE) is an approach that builds and solves quantitative performance models to assess the performance of the system early in the software development lifecycle. The most common and popular approach for solving the performance models developed is to use simulation. Simulation is a powerful tool for modeling and analysis of complex Distributed Systems where obtaining a closed-form analytical solution is extremely difficult. Simulation modeling is used extensively in industry for alternative system architectures. If the performance of a Distributed System is determined to be unacceptable at the time of “acceptance testing”, it can result in very expensive redesign, delayed delivery or, in the worst case, complete non-use of the system. ...
Computer Science & Information Technology ( CS & IT ), 2013
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
Environmental Pollution in India is growing by leaps and bounds. Air pollution, water contaminati... more Environmental Pollution in India is growing by leaps and bounds. Air pollution, water contamination, and noise pollution are the three basic types of pollution. Rising population, rapid growth in industrialization and rising demands for automobiles in India are worsening air pollution levels. Air pollution has been contributing significantly to the country's burden of ill health. In contrast to most other developing countries, India has failed to establish a timeframe for meeting its national Air Quality Standards. Air pollution is rapidly becoming a serious public health concern that has a negative impact on our quality of life and economy. This research examines the state of air pollution in India, as well as the application of machine learning approaches to anticipate air quality. It also highlights some challenges and proposed developments for future.
Summarization is the process of converting any given long text into a lossy compressed version wh... more Summarization is the process of converting any given long text into a lossy compressed version while preserving the overall essence and meaning of the original given text. A problem in natural language processing is the task of summarizing a voluminous text. This research, lays emphasis on abstractive summarization of the text, a process which generates a coherent, short and meaningful text by learning the context from given input source text. This work is a preliminary attempt to generate abstractive summary. The proposed work uses the Attentional Encoder and Decoder based Sequence to Sequence Recurrent Neural Network model. The proposed research's primary objective is to get insights on the working of the mentioned Sequence architecture and the intricacies of different subcomponents of the encoders and the decoders architecture working together so as to give a particular end result. The scope of this paper covers an experimentation of performing text summarization process using Encoder and Decoder based Sequential Learning Recurrent Neural Network design. Satisfactory summary results are obtained after the model is experimented and analyzed on the Amazon Fine Food reviews.
Basic Sciences Journal of Textile Universities, 2022
A Data warehouse is a collection of non-volatile, historical, summarized data that is gathered fr... more A Data warehouse is a collection of non-volatile, historical, summarized data that is gathered from transactional databases over time. Data warehouse systems are beneficial in supporting decisionmaking since they are optimized for On-Line Analytical Processing. The ability of an online analytical tool to deliver information when needed, or to provide "just in time" information for efficient decision-making, is a vital sign of success. It is important to evaluate the performance of these On-Line Analytical Processing applications in the early stages of their development. In this paper we simulate a typical On-Line Analytical Processing query sent to a Data warehouse to know its response time. By creating and resolving the Software Execution Model for a Data warehouse system, we are able to retrieve the Performance metrics. A weather case study is used to discuss the findings.
India conducts both state and federal elections using paperless electronic voting machines. India... more India conducts both state and federal elections using paperless electronic voting machines. Indian authorities have never allowed a meaningful, independent investigation of the security of the devices despite mounting fears of fraud. Blockchain is a technology that has gained a lot of attention recently because it uses an immutable distributed ledger to offer security and anonymity. In applications where trust is of the utmost significance, Blockchain is extensively used because of its reliable consensus mechanism and tamper-proof data storage. By combining all of the individually encrypted votes into one encrypted tally using the homomorphic property, you may obtain the separated-out tallies without compromising the privacy of individual votes. Homomorphic encryption methods are employed to work on the encrypted data without the knowledge of private key. If database data is lost, it may still be possible to recover it from the blockchain cloud. Data that has been encrypted can be operated on without having to first decrypt it. Data may be transferred and stored securely in cloud systems using Blockchain and Homomorphic mechanisms. In this paper we have expla ined the design, implementation and working of a dependable and trustworthy electronic voting application.
A Data Warehouse is characterized by a huge amount of data centralized in a single database. A Da... more A Data Warehouse is characterized by a huge amount of data centralized in a single database. A Data Warehouse architecture is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients. Architecture is an important part of any IT infrastructure because it helps to optimize the performance of the entire system. Query processing in centralized Data Warehouse is different from query processing in distributed Data Warehouse due to the amount of data processed at each site. A three-tier architecture provides an efficient query processing as compared to two-tier architecture because of the presence of precomputed results present in the middle tier. In this research paper, we discuss the primary types of architectures available and the query performance metrics. We are simulating the performance of Data Warehouse system in two types of architectures The result of our simulation clearly shows how the query performance of distributed Data Warehouse and three tier architecture is efficient as compared to their respective counterparts.
International Journal of Advanced Research in Computer Science, 2017
Class Point approach has been proposed to estimate software size of Object-Oriented Systems, syst... more Class Point approach has been proposed to estimate software size of Object-Oriented Systems, systems that involve classes, encapsulation, inheritance and message passing. Another similar approach called Class Method Points has also been proposed in the literature to estimate the size of Object-Oriented software systems. We demonstrate estimation of the effort and size of OLAP system using Class Point approach and Class Method Points approach in the early stages of their development life cycle.
Due to the rapid rise in the identification of digital materials, automatic image classification ... more Due to the rapid rise in the identification of digital materials, automatic image classification has emerged as the most difficult topic of computer vision. In comparison to human vision, automatic visual understanding and analysis by a system is challenging. The findings of many experiments that were done to fix problems of automatic picture classification with the current categorization method were simple picture primitives. However, those methods don't accurately classify photos. In this research work, a system has been created that makes use of deep learning to deliver the necessary results in the area of computer vision. Our technology automatically categorizes photographs using Convolutional Neural Network, a popular machine learning method. Our algorithm classifies grayscale photos using the Digit of MNIST dataset as a benchmark. The dataset that is employed for the training of the system contains grayscale images, which demand higher processing resources for image categorization. By employing Convolution Neural Network to train the photos, we were able to attain higher accuracy results in the experimental section, demonstrating that our model is highly accurate at classifying images.
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
International journal of computer applications, Oct 18, 2014
The increasing demands for interactive response time from the users makes query performance one o... more The increasing demands for interactive response time from the users makes query performance one of the central problems of Data warehouse systems today. Performance is an important quality aspect of Data warehouse systems. Predicting the performance of Data warehouse systems during early design stages of their development is significant. Software Performance Engineering(SPE) promotes the idea that the integration of performance analysis into the software development process, from the earliest stages to the end, can ensure that the system will meet its performance objectives. This paper describes the features and use of a prototype tool, DWPPT(Data Warehouse Performance Prediction Tool) which is designed to analyze the performance of the Data warehouse in different environmental conditions. The tool supports SPE process for Data warehouse systems. The tool is useful for Data warehouse managers in identifying critical components, diagnosing problems and hence optimizing the overall design. Our objective is to investigate the impact of Data warehouse design factors on OLAP performance for different user populations and hardware configurations. An analytical and simulation modeling approach is used for the tool to predict performance of Data warehouse systems.
Journal of Computational and Theoretical Nanoscience, 2020
Digital data in huge amount is being persistently generated at an unparalleled and exponential ra... more Digital data in huge amount is being persistently generated at an unparalleled and exponential rate. In this digital era where internet stands the prime source for generating incredible information, it is vital to develop better means to mine the available information rapidly and most capably. Manual extraction of the salient information from the large input text documents is a time consuming and inefficient task. In this fast-moving world, it is difficult to read all the text-content and derive insights from it. Automatic methods are required. The task of probing for relevant documents from the large number of sources available, and consuming apt information from it is a challenging task and is need of the hour. Automatic text summarization technique can be used to generate relevant and quality information in less time. Text Summarization is used to condense the source text into a brief summary maintaining its salient information and readability. Generating summaries automatically ...
2009 Sixth International Conference on Information Technology: New Generations, 2009
On line analytical Processing (OLAP) systems have become increasingly popular in many application... more On line analytical Processing (OLAP) systems have become increasingly popular in many application areas as they considerably ease the process of analyzing large amounts of enterprise data. Two major physical implementations exist today, relational online analytical processing systems (ROLAP) and multidimensional online analytical processing system (MOLAP). In this paper we present the object oriented OLAP framework using UML models. This
The increasing demands for interactive response time from the users makes query performance one o... more The increasing demands for interactive response time from the users makes query performance one of the central problems of Data warehouse systems today. Performance is an important quality aspect of Data warehouse systems. Predicting the performance of Data warehouse systems during early design stages of their development is significant. Software Performance Engineering(SPE) promotes the idea that the integration of performance analysis into the software development process, from the earliest stages to the end, can ensure that the system will meet its performance objectives. This paper describes the features and use of a prototype tool, DWPPT(Data Warehouse Performance Prediction Tool) which is designed to analyze the performance of the Data warehouse in different environmental conditions. The tool supports SPE process for Data warehouse systems. The tool is useful for Data warehouse managers in identifying critical components, diagnosing problems and hence optimizing the overall de...
Software size estimation at early stages of project development holds great significance to meet ... more Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the execution time for decision support queries. We perform a case study based on the T...
Online analytical systems based on multidimensional data models enable analysts and decision make... more Online analytical systems based on multidimensional data models enable analysts and decision makers to have fast and interactive responses to queries posed against the data stored in very large databases. Materialized views can speed up the execution of many queries. Materialization of all the possible views is constrained by the storage space and maintenance cost and one needs to select a subset of views to be materialized. Algorithms to determine the views to be materialized need the size of views as input. However, often the task of determining the actual number of rows present in a view can itself be computationally very expensive because of the large sizes of the tables and views. Counting actual number of rows present in each view takes considerable time in an extremely large database environment. Thus, methods to determine a good estimate of the size of a view in reasonable time instead of determining its actual size are very important. We explore the use of sampling to estimate the size of views. In this paper, we propose a hybrid estimator that takes into account the degree of skew in the data and combines Jackknife estimator with the Schlosser's estimator and guaranteed error estimator to estimate the size of the view more accurately. The proposed hybrid estimator has been used to estimate the view size and simulation results show better estimated values as compared to individual estimators.
Query Performance Analysis Tool for Distributed Systems
The increasing demands for fast interactive response times make query performance one of the cent... more The increasing demands for fast interactive response times make query performance one of the central problems of Distributed Systems. A sophisticated design is necessary to ensure high performance of Distributed Systems. Software Performance Engineering (SPE) is an approach that builds and solves quantitative performance models to assess the performance of the system early in the software development lifecycle. The most common and popular approach for solving the performance models developed is to use simulation. Simulation is a powerful tool for modeling and analysis of complex Distributed Systems where obtaining a closed-form analytical solution is extremely difficult. Simulation modeling is used extensively in industry for alternative system architectures. If the performance of a Distributed System is determined to be unacceptable at the time of “acceptance testing”, it can result in very expensive redesign, delayed delivery or, in the worst case, complete non-use of the system. ...
Uploads
Papers by madhu bhan