The problem of mutual exclusion arises in distributed systems whenever shared resources are concurrently
accessed by several sites. For correctness, it is required that shared resource must be accessed by a single
site at a time. To decide, which site execute the critical section next, each site communicate with a set of
other sites. A systematic approach is essential to formulate an accurate speciation. Formal methods are
mathematical techniques that provide systematic approach for building and verification of model. We have
used Event-B as a formal technique for construction of our model. Event-B is event driven approach which
is used to develop formal models of distributed systems .It supports generation and discharge of proof
obligations arising due to consistency checking. In this paper, we outline a formal construction of model of
Lamport's mutual exclusion algorithm for distributed system using Event-B. We have considered vector
clock instead of using Lam-port's scalar clock for the purpose of message's time stamping.
A SERIAL COMPUTING MODEL OF AGENT ENABLED MINING OF GLOBALLY STRONG ASSOCIATI...ijcsa
The intelligent agent based model is a popular approach in constructing Distributed Data Mining (DDM) systems to address scalable mining over large scale and ever increasing distributed data. In an agent based
distributed system, variety of agents coordinate and communicate with each other to perform the various
tasks of the Data Mining (DM) process. In this study a serial computing mode of a multi-agent system
(MAS) called Agent enabled Mining of Globally Strong Association Rules (AeMGSAR) is presented based
on the serial itinerary of the mobile agents. A Running environment is also designed for the implementation and performance study of AeMGSAR system.
Probability-Based Analysis to Determine the Performance of Multilevel Feedbac...Eswar Publications
Operating System may work on different types of CPU scheduling algorithms with different mechanism and concepts. The Multilevel Feedback Queue (MLFQ) Scheduling manages a variety of processes among various queues in a better and efficient manner. CPU scheduler appears transition mechanism over various queues. This paper is presented with various schemes of under a probability-based model. The scheduler has random movement over queues with given time quantum. This paper designs general transition model for its functioning
and justifying comparison under different scheduling schemes through a simulation study applied on different data sets in particular cases.
Experimental study of Data clustering using k- Means and modified algorithmsIJDKP
The k- Means clustering algorithm is an old algorithm that has been intensely researched owing to its ease
and simplicity of implementation. Clustering algorithm has a broad attraction and usefulness in
exploratory data analysis. This paper presents results of the experimental study of different approaches to
k- Means clustering, thereby comparing results on different datasets using Original k-Means and other
modified algorithms implemented using MATLAB R2009b. The results are calculated on some performance
measures such as no. of iterations, no. of points misclassified, accuracy, Silhouette validity index and
execution time
A novel nonlinear missile guidance law against maneuvering targets is designed based on the principles of partial stability. It is demonstrated that in a real approach which is adopted with actual situations, each state of the guidance system must have a special behavior and asymptotic stability or exponential stability of all states is not realistic. Thus, a new guidance law is developed based on the partial stability theorem in such a way that the behaviors of states in the closed-loop system are in conformity with a real guidance scenario that leads to collision. The performance of the proposed guidance law in terms of interception time and control effort is compared with the sliding mode guidance law by means of numerical simulations.
Developing Scheduler Test Cases to Verify Scheduler Implementations In Time-T...ijesajournal
Despite that there is a “one-to-many” mapping between scheduling algorithms and scheduler implementations, only a few studies have discussed the challenges and consequences of translating between these two system models. There has been an argument that a wide gap exists between scheduling theory and scheduling implementation in practical systems, where such a gap must be bridged to obtain an effective validation of embedded systems. In this paper, we introduce a technique called “Scheduler Test Case” (STC) aimed at bridging the gap between scheduling algorithms and scheduler implementations in single-processor embedded systems implemented using Time-Triggered Co-operative (TTC) architectures. We will demonstrate how the STC technique can provide a simple and systematic way for documenting, verifying (testing) and comparing various TTC scheduler implementations on particular hardware. However, STC is a generic technique that provides a black-box tool for assessing and predicting the behaviour of representative implementation sets of any real-time scheduling algorithm.
A SERIAL COMPUTING MODEL OF AGENT ENABLED MINING OF GLOBALLY STRONG ASSOCIATI...ijcsa
The intelligent agent based model is a popular approach in constructing Distributed Data Mining (DDM) systems to address scalable mining over large scale and ever increasing distributed data. In an agent based
distributed system, variety of agents coordinate and communicate with each other to perform the various
tasks of the Data Mining (DM) process. In this study a serial computing mode of a multi-agent system
(MAS) called Agent enabled Mining of Globally Strong Association Rules (AeMGSAR) is presented based
on the serial itinerary of the mobile agents. A Running environment is also designed for the implementation and performance study of AeMGSAR system.
Probability-Based Analysis to Determine the Performance of Multilevel Feedbac...Eswar Publications
Operating System may work on different types of CPU scheduling algorithms with different mechanism and concepts. The Multilevel Feedback Queue (MLFQ) Scheduling manages a variety of processes among various queues in a better and efficient manner. CPU scheduler appears transition mechanism over various queues. This paper is presented with various schemes of under a probability-based model. The scheduler has random movement over queues with given time quantum. This paper designs general transition model for its functioning
and justifying comparison under different scheduling schemes through a simulation study applied on different data sets in particular cases.
Experimental study of Data clustering using k- Means and modified algorithmsIJDKP
The k- Means clustering algorithm is an old algorithm that has been intensely researched owing to its ease
and simplicity of implementation. Clustering algorithm has a broad attraction and usefulness in
exploratory data analysis. This paper presents results of the experimental study of different approaches to
k- Means clustering, thereby comparing results on different datasets using Original k-Means and other
modified algorithms implemented using MATLAB R2009b. The results are calculated on some performance
measures such as no. of iterations, no. of points misclassified, accuracy, Silhouette validity index and
execution time
A novel nonlinear missile guidance law against maneuvering targets is designed based on the principles of partial stability. It is demonstrated that in a real approach which is adopted with actual situations, each state of the guidance system must have a special behavior and asymptotic stability or exponential stability of all states is not realistic. Thus, a new guidance law is developed based on the partial stability theorem in such a way that the behaviors of states in the closed-loop system are in conformity with a real guidance scenario that leads to collision. The performance of the proposed guidance law in terms of interception time and control effort is compared with the sliding mode guidance law by means of numerical simulations.
Developing Scheduler Test Cases to Verify Scheduler Implementations In Time-T...ijesajournal
Despite that there is a “one-to-many” mapping between scheduling algorithms and scheduler implementations, only a few studies have discussed the challenges and consequences of translating between these two system models. There has been an argument that a wide gap exists between scheduling theory and scheduling implementation in practical systems, where such a gap must be bridged to obtain an effective validation of embedded systems. In this paper, we introduce a technique called “Scheduler Test Case” (STC) aimed at bridging the gap between scheduling algorithms and scheduler implementations in single-processor embedded systems implemented using Time-Triggered Co-operative (TTC) architectures. We will demonstrate how the STC technique can provide a simple and systematic way for documenting, verifying (testing) and comparing various TTC scheduler implementations on particular hardware. However, STC is a generic technique that provides a black-box tool for assessing and predicting the behaviour of representative implementation sets of any real-time scheduling algorithm.
Scalable Rough C-Means clustering using Firefly algorithm..................................................................1
Abhilash Namdev and B.K. Tripathy
Significance of Embedded Systems to IoT................................................................................................. 15
P. R. S. M. Lakshmi, P. Lakshmi Narayanamma and K. Santhi Sri
Cognitive Abilities, Information Literacy Knowledge and Retrieval Skills of Undergraduates: A
Comparison of Public and Private Universities in Nigeria ........................................................................ 24
Janet O. Adekannbi and Testimony Morenike Oluwayinka
Risk Assessment in Constructing Horseshoe Vault Tunnels using Fuzzy Technique................................ 48
Erfan Shafaghat and Mostafa Yousefi Rad
Evaluating the Adoption of Deductive Database Technology in Augmenting Criminal Intelligence in
Zimbabwe: Case of Zimbabwe Republic Police......................................................................................... 68
Mahlangu Gilbert, Furusa Samuel Simbarashe, Chikonye Musafare and Mugoniwa Beauty
Analysis of Petrol Pumps Reachability in Anand District of Gujarat ....................................................... 77
Nidhi Arora
JAVA BASED VISUALIZATION AND ANIMATION FOR TEACHING THE DIJKSTRA SHORTEST PAT...ijseajournal
Shortest path (SP) algorithms, such as the popular Dijkstra algorithm has been considered as the “basic
building blocks” for many advanced transportation network models. Dijkstra algorithm will find the
shortest time (ST) and the corresponding SP to travel from a source node to a destination node.
Applications of SP algorithms include real-time GPS and the Frank-Wolfe network equilibrium.
For transportation engineering students, the Dijkstra algorithm is not easily understood. This paper
discusses the design and development of a software that will help the students to fully understand the key
components involved in the Dijkstra SP algorithm. The software presents an intuitive interface for
generating transportation network nodes/links, and how the SP can be updated in each iteration. The
software provides multiple visual representations of colour mapping and tabular display. The software can
be executed in each single step or in continuous run, making it easy for students to understand the Dijkstra
algorithm. Voice narratives in different languages (English, Chinese and Spanish) are available.A demo
video of the Dijkstra Algorithm’s animation and result can be viewed online from any web browser using
the website: http://www.lions.odu.edu/~imako001/dijkstra/demo/index.html.
Approaches to online quantile estimationData Con LA
Data Con LA 2020
Description
This talk will explore and compare several compact data structures for estimation of quantiles on streams, including a discussion of how they balance accuracy against computational resource efficiency. A new approach providing more flexibility in specifying how computational resources should be expended across the distribution will also be explained. Quantiles (e.g., median, 99th percentile) are fundamental summary statistics of one-dimensional distributions. They are particularly important for SLA-type calculations and characterizing latency distributions, but unlike their simpler counterparts such as the mean and standard deviation, their computation is somewhat more expensive. The increasing importance of stream processing (in observability and other domains) and the impossibility of exact online quantile calculation together motivate the construction of compact data structures for estimation of quantiles on streams. In this talk we will explore and compare several such data structures (e.g., moment-based, KLL sketch, t-digest) with an eye towards how they balance accuracy against resource efficiency, theoretical guarantees, and desirable properties such as mergeability. We will also discuss a recent variation of the t-digest which provides more flexibility in specifying how computational resources should be expended across the distribution. No prior knowledge of the subject is assumed. Some familiarity with the general problem area would be helpful but is not required.
Speaker
Joe Ross, Splunk, Principal Data Scientist
RELIABILITY ASSESSMENT OF EMBEDDED SYSTEMS USING STOPWATCH PETRI NETSIJCSEA Journal
In this paper, we propose a reliability approach in which feared events define reliability requirements and
taking them into account allows to design systems which will be able to avoid the drift towards a feared
state. The description of feared scenarios since the system design phase enables us to understand the
reasons of the feared behavior in order to envisage the necessary reconfigurations and choose safe
architectures. In order to face the increasing complexity of embedded systems and to represent the
suspension and resumption of task execution we propose to extract directly feared scenarios from
Stopwatch Petri net model avoiding the generation of the associated reachability graph and the eternal
combinative explosion problem.
Automatic time series forecasting using nonlinear autoregressive neural netwo...journalBEEI
This study aims to determine an automatic forecasting method of univariate time series, using the nonlinear autoregressive neural network model with exogenous input (NARX). In this automatic setting, users only need to supply the input of time series. Then, an automatic forecasting algorithm sets up the appropriate features, estimate the parameters in the model, and calculate forecasts, without the users’ intervention. The algorithm method used include preprocessing, tests for trends, and the application of first differences. The time series were tested for seasonality, and seasonal differences were obtained from a successful analysis. These series were also linearly scaled to [−1, +1]. The autoregressive lags and hidden neurons were further selected through the stepwise and optimization algorithms, respectively. The 20 NARX models were fitted with different random starting weights, and the forecasts were combined using the ensemble operator, in order to obtain the final product. This proposed method was applied to real data, and its performance was compared with several available automatic models in the literature. The forecasting accuracy was also measured by mean squared error (MSE) and mean absolute percent error (MAPE), and the results showed that the proposed method outperformed the other automatic models.
Using queuing theory to describe adaptive mathematical models of computing sy...journalBEEI
The article describes the issues of preparation and verification of mathematical models of computing systems with resource virtualization. The object of this study is to verify of mathematical models of computer systems with virtualization experimentally by creating a virtual server on the host platform and monitoring its characteristics under load. Known models cannot be applied to the aircraft with virtualization, because they do not allow a comprehensive analysis to determine the most effective option for the implementation of the initial allocation of resources and its optimization for a specific sphere and task of use. The article for the study used a closed queueing network. Simple models for the analysis of various structures of computer systems are experimentally obtained. To implement the properties of adaptability in the models, triggers are used that monitor and adjust the power of the processing channel in individual Queuing systems, depending on the specified conditions. Experiments prove the obtained results reliable and usable as a flexible tool for studying the virtualization properties when structuring computing systems. This knowledge could be of use for businesses interested in optimizing the server configuration for their IT infrastructure.
Adaptive Control of a Robotic Arm Using Neural Networks Based ApproachWaqas Tariq
A new neural networks and time series prediction based method has been discussed to control the complex nonlinear multi variable robotic arm motion system in 3d environment without engaging the complicated and voluminous dynamic equations of robotic arms in controller design stage, the proposed method gives such compatibility to the manipulator that it could have significant changes in its dynamic properties, like getting mechanical loads, without need to change designs of the controller.
Integration of a Predictive, Continuous Time Neural Network into Securities M...Chris Kirk, PhD, FIAP
This paper describes recent development and test implementation of a continuous time recurrent neural network that has been configured to predict rates of change in securities. It presents outcomes in the
context of popular technical analysis indicators and highlights the potential impact of continuous predictive capability on securities
market trading operations.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The Positive Effects of Fuzzy C-Means Clustering on Supervised Learning Class...Waqas Tariq
Selection of inputs is one of the most substantial components of classification algorithms for data mining and pattern recognition problems since even the best classifier will perform badly if the inputs are not selected very well. Big data and computational complexity are main cause of bad performance and low accuracy for classical classifiers. In other words, the complexity of classifier method is inversely proportional with its classification efficiency. For this purpose, two hybrid classifiers have been developed by using both type-1 and type-2 fuzzy c-means clustering with cascaded a classifier. In this proposed classifier, a large number of data points are reduced by using fuzzy c-means clustering before applied to a classifier algorithm as inputs. The aim of this study is to investigate the effect of fuzzy clustering on well-known and useful classifiers such as artificial neural networks (ANN) and support vector machines (SVM). Then the role of positive effects of these proposed algorithms were investigated on applied different data sets.
A TALE of DATA PATTERN DISCOVERY IN PARALLELJenny Liu
In the era of IoTs and A.I., distributed and parallel computing is embracing big data driven and algorithm focused applications and services. With rapid progress and development on parallel frameworks, algorithms and accelerated computing capacities, it still remains challenging on deliver an efficient and scalable data analysis solution. This talk shares a research experience on data pattern discovery in domain applications. In particular, the research scrutinizes key factors in analysis workflow design and data parallelism improvement on cloud.
With the development of information security, the traditional image encryption methods have become
outdated. Because of amply using images in the transmission process, it is important to protect the confidential image
data from unauthorized access. This paper presents a new chaos based image encryption algorithm, which can improve
the security during transmission more effectively utilizes the chaotic systems properties, such as pseudo-random
appearance and sensitivity to initial conditions. Based on chaotic theory and decomposition and recombination of pixel
values, this new image scrambling algorithm is able to change the position of pixel, simultaneously scrambling both
position and pixel values. Experimental results show that the new algorithm improves the image security effectively to
avoid unscramble, and it also can restore the image as same as the original one, which reaches to the purposes of image
safe and reliable transmission.
Formal Verification of Distributed Checkpointing Using Event-Bijcsit
The development of complex system makes challenging task for correct software development. Due to faulty
specification, software may involve errors. The traditional testing methods are not sufficient to verify the
correctness of such complex system. In order to capture correct system requirements and rigorous
reasoning about the problems, formal methods are required. Formal methods are mathematical techniques
that provide precise specification of problems with their solutions and proof of correctness. In this paper,
we have done formal verification of check pointing process in a distributed database system using Event B.
Event-B is an event driven formal method which is used to develop formal models of distributed database
systems. In a distributed database system, the database is stored at different sites that are connected
together through the network. Checkpoint is a recovery point which contains the state information about
the site. In order to do recovery of a distributed transaction a global checkpoint number (GCPN) is
required. A global checkpoint number decides which transaction will be included for recovery purpose. All
transactions whose timestamp are less than global checkpoint number will be marked as before checkpoint
transaction (BCPT) and will be considered for recovery purpose. The transactions whose timestamp are
greater than GCPN will be marked as after checkpoint transaction (ACPT) and will be part of next global
checkpoint number.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Grid computing is a modularized way of structuring network resources so as to share the information and resources, to perform heavily intense problems. Grid computing is a part of distributed processing which allows the distribution of the problem over multiple computational resources. The formation of grid decides the computation cost, the performance metrics of the operation to be carried out. The grid computing favours the formation of an adhoc structure formed at the time of request (it does not hold an infrastructure) that is termed as virtual organization. This paper presents dynamic source routing for modeling virtual organization.
Scalable Rough C-Means clustering using Firefly algorithm..................................................................1
Abhilash Namdev and B.K. Tripathy
Significance of Embedded Systems to IoT................................................................................................. 15
P. R. S. M. Lakshmi, P. Lakshmi Narayanamma and K. Santhi Sri
Cognitive Abilities, Information Literacy Knowledge and Retrieval Skills of Undergraduates: A
Comparison of Public and Private Universities in Nigeria ........................................................................ 24
Janet O. Adekannbi and Testimony Morenike Oluwayinka
Risk Assessment in Constructing Horseshoe Vault Tunnels using Fuzzy Technique................................ 48
Erfan Shafaghat and Mostafa Yousefi Rad
Evaluating the Adoption of Deductive Database Technology in Augmenting Criminal Intelligence in
Zimbabwe: Case of Zimbabwe Republic Police......................................................................................... 68
Mahlangu Gilbert, Furusa Samuel Simbarashe, Chikonye Musafare and Mugoniwa Beauty
Analysis of Petrol Pumps Reachability in Anand District of Gujarat ....................................................... 77
Nidhi Arora
JAVA BASED VISUALIZATION AND ANIMATION FOR TEACHING THE DIJKSTRA SHORTEST PAT...ijseajournal
Shortest path (SP) algorithms, such as the popular Dijkstra algorithm has been considered as the “basic
building blocks” for many advanced transportation network models. Dijkstra algorithm will find the
shortest time (ST) and the corresponding SP to travel from a source node to a destination node.
Applications of SP algorithms include real-time GPS and the Frank-Wolfe network equilibrium.
For transportation engineering students, the Dijkstra algorithm is not easily understood. This paper
discusses the design and development of a software that will help the students to fully understand the key
components involved in the Dijkstra SP algorithm. The software presents an intuitive interface for
generating transportation network nodes/links, and how the SP can be updated in each iteration. The
software provides multiple visual representations of colour mapping and tabular display. The software can
be executed in each single step or in continuous run, making it easy for students to understand the Dijkstra
algorithm. Voice narratives in different languages (English, Chinese and Spanish) are available.A demo
video of the Dijkstra Algorithm’s animation and result can be viewed online from any web browser using
the website: http://www.lions.odu.edu/~imako001/dijkstra/demo/index.html.
Approaches to online quantile estimationData Con LA
Data Con LA 2020
Description
This talk will explore and compare several compact data structures for estimation of quantiles on streams, including a discussion of how they balance accuracy against computational resource efficiency. A new approach providing more flexibility in specifying how computational resources should be expended across the distribution will also be explained. Quantiles (e.g., median, 99th percentile) are fundamental summary statistics of one-dimensional distributions. They are particularly important for SLA-type calculations and characterizing latency distributions, but unlike their simpler counterparts such as the mean and standard deviation, their computation is somewhat more expensive. The increasing importance of stream processing (in observability and other domains) and the impossibility of exact online quantile calculation together motivate the construction of compact data structures for estimation of quantiles on streams. In this talk we will explore and compare several such data structures (e.g., moment-based, KLL sketch, t-digest) with an eye towards how they balance accuracy against resource efficiency, theoretical guarantees, and desirable properties such as mergeability. We will also discuss a recent variation of the t-digest which provides more flexibility in specifying how computational resources should be expended across the distribution. No prior knowledge of the subject is assumed. Some familiarity with the general problem area would be helpful but is not required.
Speaker
Joe Ross, Splunk, Principal Data Scientist
RELIABILITY ASSESSMENT OF EMBEDDED SYSTEMS USING STOPWATCH PETRI NETSIJCSEA Journal
In this paper, we propose a reliability approach in which feared events define reliability requirements and
taking them into account allows to design systems which will be able to avoid the drift towards a feared
state. The description of feared scenarios since the system design phase enables us to understand the
reasons of the feared behavior in order to envisage the necessary reconfigurations and choose safe
architectures. In order to face the increasing complexity of embedded systems and to represent the
suspension and resumption of task execution we propose to extract directly feared scenarios from
Stopwatch Petri net model avoiding the generation of the associated reachability graph and the eternal
combinative explosion problem.
Automatic time series forecasting using nonlinear autoregressive neural netwo...journalBEEI
This study aims to determine an automatic forecasting method of univariate time series, using the nonlinear autoregressive neural network model with exogenous input (NARX). In this automatic setting, users only need to supply the input of time series. Then, an automatic forecasting algorithm sets up the appropriate features, estimate the parameters in the model, and calculate forecasts, without the users’ intervention. The algorithm method used include preprocessing, tests for trends, and the application of first differences. The time series were tested for seasonality, and seasonal differences were obtained from a successful analysis. These series were also linearly scaled to [−1, +1]. The autoregressive lags and hidden neurons were further selected through the stepwise and optimization algorithms, respectively. The 20 NARX models were fitted with different random starting weights, and the forecasts were combined using the ensemble operator, in order to obtain the final product. This proposed method was applied to real data, and its performance was compared with several available automatic models in the literature. The forecasting accuracy was also measured by mean squared error (MSE) and mean absolute percent error (MAPE), and the results showed that the proposed method outperformed the other automatic models.
Using queuing theory to describe adaptive mathematical models of computing sy...journalBEEI
The article describes the issues of preparation and verification of mathematical models of computing systems with resource virtualization. The object of this study is to verify of mathematical models of computer systems with virtualization experimentally by creating a virtual server on the host platform and monitoring its characteristics under load. Known models cannot be applied to the aircraft with virtualization, because they do not allow a comprehensive analysis to determine the most effective option for the implementation of the initial allocation of resources and its optimization for a specific sphere and task of use. The article for the study used a closed queueing network. Simple models for the analysis of various structures of computer systems are experimentally obtained. To implement the properties of adaptability in the models, triggers are used that monitor and adjust the power of the processing channel in individual Queuing systems, depending on the specified conditions. Experiments prove the obtained results reliable and usable as a flexible tool for studying the virtualization properties when structuring computing systems. This knowledge could be of use for businesses interested in optimizing the server configuration for their IT infrastructure.
Adaptive Control of a Robotic Arm Using Neural Networks Based ApproachWaqas Tariq
A new neural networks and time series prediction based method has been discussed to control the complex nonlinear multi variable robotic arm motion system in 3d environment without engaging the complicated and voluminous dynamic equations of robotic arms in controller design stage, the proposed method gives such compatibility to the manipulator that it could have significant changes in its dynamic properties, like getting mechanical loads, without need to change designs of the controller.
Integration of a Predictive, Continuous Time Neural Network into Securities M...Chris Kirk, PhD, FIAP
This paper describes recent development and test implementation of a continuous time recurrent neural network that has been configured to predict rates of change in securities. It presents outcomes in the
context of popular technical analysis indicators and highlights the potential impact of continuous predictive capability on securities
market trading operations.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The Positive Effects of Fuzzy C-Means Clustering on Supervised Learning Class...Waqas Tariq
Selection of inputs is one of the most substantial components of classification algorithms for data mining and pattern recognition problems since even the best classifier will perform badly if the inputs are not selected very well. Big data and computational complexity are main cause of bad performance and low accuracy for classical classifiers. In other words, the complexity of classifier method is inversely proportional with its classification efficiency. For this purpose, two hybrid classifiers have been developed by using both type-1 and type-2 fuzzy c-means clustering with cascaded a classifier. In this proposed classifier, a large number of data points are reduced by using fuzzy c-means clustering before applied to a classifier algorithm as inputs. The aim of this study is to investigate the effect of fuzzy clustering on well-known and useful classifiers such as artificial neural networks (ANN) and support vector machines (SVM). Then the role of positive effects of these proposed algorithms were investigated on applied different data sets.
A TALE of DATA PATTERN DISCOVERY IN PARALLELJenny Liu
In the era of IoTs and A.I., distributed and parallel computing is embracing big data driven and algorithm focused applications and services. With rapid progress and development on parallel frameworks, algorithms and accelerated computing capacities, it still remains challenging on deliver an efficient and scalable data analysis solution. This talk shares a research experience on data pattern discovery in domain applications. In particular, the research scrutinizes key factors in analysis workflow design and data parallelism improvement on cloud.
With the development of information security, the traditional image encryption methods have become
outdated. Because of amply using images in the transmission process, it is important to protect the confidential image
data from unauthorized access. This paper presents a new chaos based image encryption algorithm, which can improve
the security during transmission more effectively utilizes the chaotic systems properties, such as pseudo-random
appearance and sensitivity to initial conditions. Based on chaotic theory and decomposition and recombination of pixel
values, this new image scrambling algorithm is able to change the position of pixel, simultaneously scrambling both
position and pixel values. Experimental results show that the new algorithm improves the image security effectively to
avoid unscramble, and it also can restore the image as same as the original one, which reaches to the purposes of image
safe and reliable transmission.
Formal Verification of Distributed Checkpointing Using Event-Bijcsit
The development of complex system makes challenging task for correct software development. Due to faulty
specification, software may involve errors. The traditional testing methods are not sufficient to verify the
correctness of such complex system. In order to capture correct system requirements and rigorous
reasoning about the problems, formal methods are required. Formal methods are mathematical techniques
that provide precise specification of problems with their solutions and proof of correctness. In this paper,
we have done formal verification of check pointing process in a distributed database system using Event B.
Event-B is an event driven formal method which is used to develop formal models of distributed database
systems. In a distributed database system, the database is stored at different sites that are connected
together through the network. Checkpoint is a recovery point which contains the state information about
the site. In order to do recovery of a distributed transaction a global checkpoint number (GCPN) is
required. A global checkpoint number decides which transaction will be included for recovery purpose. All
transactions whose timestamp are less than global checkpoint number will be marked as before checkpoint
transaction (BCPT) and will be considered for recovery purpose. The transactions whose timestamp are
greater than GCPN will be marked as after checkpoint transaction (ACPT) and will be part of next global
checkpoint number.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Grid computing is a modularized way of structuring network resources so as to share the information and resources, to perform heavily intense problems. Grid computing is a part of distributed processing which allows the distribution of the problem over multiple computational resources. The formation of grid decides the computation cost, the performance metrics of the operation to be carried out. The grid computing favours the formation of an adhoc structure formed at the time of request (it does not hold an infrastructure) that is termed as virtual organization. This paper presents dynamic source routing for modeling virtual organization.
A Model of Local Area Network Based Application for Inter-office Communicationtheijes
In most organizations, information circulation within offices poses a problem because clerical officers and office messengers usually dispatch letters and memos from one office to another manually. Sequel to this circulation procedure, implementation of decisions is always difficult and slow. On one hand, clerical officers sometimes divulge confidential information during the process of receiving and sending of mails and other documents. On the other hand, money is wasted on the purchase of paper for printing. However, it is cheerful to learn that technology has made it possible for staff, structures and infrastructures to control and share organization resources; hardware; software and knowledge by means of modern electronic communication. One cannot deny the fact that the flow of information is very imperative in every organization as it determines the effectiveness of decision-making and implementation. This feat can be achieved using Object-Oriented System Analysis and Design Methodology (OSADM). This is structurally analyzed with Use Case Diagram (UCD), Class Diagram, Sequence Diagram, State Transition Diagram, and Activity Diagram. Moreover, the system is coded with Java 1.6 version, in a client-server network running on star topology in LAN environment. This is the concept of this paper. The system is designed to work in two parts – the control part that is installed on the server; and the messenger part that is installed in the clients. This research work integrates the utility and organization resources into a shared center for all users to have access to; and for free communication during office hours.
Checkpoint and recovery protocols are commonly used in distributed applications for providing fault
tolerance. A distributed system may require taking checkpoints from time to time to keep it free of arbitrary
failures. In case of failure, the system will rollback to checkpoints where global consistency is preserved.
Checkpointing is one of the fault-tolerant techniques to restore faults and to restart job fast. The algorithms
for checkpointing on distributed systems have been under study for years.
It is known that checkpointing and rollback recovery are widely used techniques that allow a distributed
computing to progress inspite of a failure.There are two fundamental approaches for checkpointing and
recovery.One is asynchronus approach, process take their checkpoints independenty.So,taking checkpoints
is very simple but due to absence of a recent consistent global checkpoint which may cause a rollback of
computation.Synchronus checkpointing approach assumes that a single process other than the application
process invokes the checkpointing algorithm periodically to determine a consistent global checkpoint.
Packet Classification using Support Vector Machines with String KernelsIJERA Editor
Since the inception of internet many methods have been devised to keep untrusted and malicious packets away
from a user’s system . The traffic / packet classification can be used
as an important tool to detect intrusion in the system. Using Machine Learning as an efficient statistical based
approach for classifying packets is a novel method in practice today . This paper emphasizes upon using an
advanced string kernel method within a support vector machine to classify packets .
There exists a paper related to a similar problem using Machine Learning [2]. But the researches mentioned in
their paper are not up-to date and doesn’t account for modern day
string kernels that are much more efficient . My work extends their research by introducing different approaches
to classify encrypted / unencrypted traffic / packets .
FORMAL MODELING AND VERIFICATION OF MULTI-AGENTS SYSTEM USING WELLFORMED NETScsandit
Multi-agent systems are asynchronous and distributed computer systems. These characteristics make them also a discrete-event dynamic system. It is, therefore, important to analyze the behavior of such systems to ensure that they terminate correctly and satisfy other important properties. This paper presents a formal modeling and analysis of MAS, based on Well-formed Nets, in order to ensure the absence of any undesired or unexpected behavior. To validate our ontribution, we consider the timetable problem, which is a multi-agent resource allocation problem.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Efficient Resource Allocation to Virtual Machine in Cloud Computing Using an ...ijceronline
The focus of the paper is to generate an advance algorithm of resource allocation and load balancing that can deduced and avoid the dead lock while allocating the processes to virtual machine. In VM while processes are allocate they executes in queue , the first process get resources , other remains in waiting state .As rest of VM remains idle . To utilize the resources, we have analyze the algorithm with the help of First-Come, First-Served (FCFS) Scheduling, Shortest-Job-First (SJR) Scheduling, Priority Scheduling, Round Robin (RR) and CloudSIM Simulator.
Lately, the Wireless Sensors Networks (WSN) have moved to the concept of the hybrids networks in order to get universal platforms in various types of monitoring and information collecting applications. The work presented in this paper aims in designing a hybrid remote monitoring architecture, largely secured by a high availability and resilience WSN. The modeling approach intends to describe the main operation of polling and dispatching between the communications channels with the purpose of ensuring the information availability and reducing the resilience time. To achieve our goal, we have realized an experimental platform of measuring, processing and routing data through hybrid communications technologies. We have illustrated, via curves, the routing of the data measured by a WSN (ZigBee Technology) to a final user through several communication technologies (HTTPS, SMS, ...).
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
2. 478 Computer Science & Information Technology (CS & IT)
In this paper, formal construction of non token based mutual exclusion algorithm for distributed
system is outlined. We have considered Lamport's algorithm [1], [3] for formal development of
our model. In this algorithm, each site maintains a request queue, which contains its own times
tamped request for mutual exclusion and also request messages received from other sites [3]. If
any site Sx wants to enter the critical section, it broadcasts a time stamped request message
REQUEST-X to all the sites and makes an entry for request message REQUEST-X in its request
queue. When a site Sy receives the request message REQUEST-X sent by site Sx, It makes an
entry of Sx's request( REQUEST-X)in its request queue and returns a time stamped reply message
REPLY-Y to site Sx. After receiving the time stamped reply messages from all the sites, there
questing site Sx enters the critical section if following conditions hold :
1. Time stamp of all received messages are greater than time stamp of request
message REQUEST-X.
2. Time stamp of REQUEST-X is minimum among all requests present in
request queue of site Sx.
After executing the critical section site Sx removes the entry of request message (REQUEST-X)
from its request queue and broadcasts a time stamped release message RELEASE-X to all the
sites. When a site Sy receives the release message RELEASE-X from site Sx, It removes Sx's
request REQUEST-X from its request queue. When a site removes a request from its request
queue then it may possible that next minimum times tamped request is own request, enabling
it to enter the critical section. This algorithm executes critical section requests in the increasing
order of timestamps.
A functional specification of system describes its behavior. A specification contains significant
information about the system. The B Method provides a systematic approach to formulate an
accurate specification. we develop our model in the spirit embedded in Event-B. The model
contains a BROADCAST-REQ event that models the event for requesting critical section. In this
event a requesting site broadcasts a time stamped request message to all sites. Delivery of time
stamped request message is shown by DELIVER-REQ event. The event REPLY models the event
for sending time stamped reply message from a site (receiver of request message) to requesting
site. The event REPLY-RECEIVE models the receiving of time stamped reply message at the
requesting site. At the same time this event also count how many sites have sent the reply
messages. The execution and releasing of critical section is shown by the event EXECUTE-CS
and RELEASE-CS respectively. After the execution of critical section, the requesting site
broadcasts a timestamped release message to all sites. The broadcasting of time stamped release
message is shown by the event BROADCAST-RELEASE. The event DELIVER-RELEASE models
the delivery of times tamped release message at all sites.
The remainder of this paper is organized as follows: Section 2 briefly outline Event B and Rodin
platform, Section 3 describes system model and informal description about events, Section 4
presents Event−B Model of mutual exclusion for distributed system. Section 5 concludes the
paper
3. Computer Science & Information Technology (CS & IT) 479
2. EVENT-B AND RODIN PLATFORM
The B Method [5], [6], [7] is a model oriented state based method. It represent the complete
mathematical development of a Discrete Transition System. Event-B represents a further
evolution of the B method, which has been simplified and is now centered around the general
notion of events. Event-B [8], [9],[10], [11], [12],[13], [14], [15], [16], [17] is event driven
approach used to develop formal models of distributed systems. It is made of several components
of two kinds: machines and contexts. Machines represent the dynamic part of model. This part is
used to provide behavioral properties of model. It contains the variables, invariants, theorems,
and events of a project. A machine is made of a state, which is defined by means of variables.
Variables correspond to mathematical objects: sets, binary relations, functions, numbers, etc.
These variables are constrained by invariants and these invariants are to be preserved while
change the value of variables. The theorem of machine must follow from the context and the
invariants of that machine. Moreover, a machine can be refined by other machines, but each
machine can refine only one machine. Contexts contain the static part of model. It contains sets,
constants, axioms, theorems. Sets may be enumerated or carrier. Axioms are used to describe the
properties of those sets and constants. The context may be seen by machine directly or indirectly.
Besides its state, a machine contains a number of events which specify how the state may evolve.
An event is made up of three elements its name, guards and actions. The guards are the necessary
conditions for the event to occur. An event known as initialization event has no guard and it gives
initial position of the model. An event can be specified in one of following three forms:
Where k denotes parameters that are local to event, v denotes variable of machine containing the
event, P(...) is a predicate denoting the guards of event and S(...) denotes the actions that updates
some variables. Event-B notations are set theoretic notations. The syntax and description of
notations are outlined in [10].
The Event-B Method requires the discharge of proof obligations for consistency checking. What
is to be proved is stated in terms of proof obligations of a model. Proof obligations serve to verify
properties of a model. They also serve to demonstrate that a model is sound with respect to some
behavioral semantics. In this work, we have used Rodin platform. It is an open extensible tool for
specification and verification of Event-B. The tool provides a seamless integration between
modeling and proving. It also provide an environment for generation and discharge of proof
obligations. It is embedded by various plugins such as proof-obligation generator, model
checkers, provers, UML transformers, etc.
3. SYSTEM MODEL
We have considered a distributed system having a set of sites where every site maintains a request
queue. The request queue contains timestamped request messages. In our model, time stamping of
messages are done through vector clock [18]. In a system of vector clock, every site maintains a
4. 480 Computer Science & Information Technology (CS & IT)
vector of size N to represent what that site believes to be the logical time at all other sites (N is
the total number of sites in the system). Assume each site Si maintains a vector clock VTSi, where
VT Si (i)represents a local logical time at Si while VTSi(j) represents the site Si's latest knowledge of the
time at site Sj . Precisely VTSi(j) ( i ≠j )represents the local time at site Sj when the most recent
message was sent from Sj to Si directly or indirectly. Each time when a message is sent by any
particular site a vector time stamp is assigned to message. While sending a message M from site
Si to Sj , sender process Si updates its own time (ith entry of vector) by updating VTSi(i)as
VTSi(i):= VTSi(i)+ 1. The message time stamp VTM of message M is generated as VTM(k) :=
VTSi(k), ∀ k ∈ ( 1..N),,where N is the number of sites in system. A site Si increments its own local
time VTSi(i)only at the time of sending a message.
When a recipient site Sj receives a time stamped message it updates its knowledge by updating
own vector clock. Site Sj updates its vector clock VTSj afterthe delivery of message M as VTSj(k)
:= Max (VTSj(k),VTM(k)). Therefore, inthe vector clock of site Sj , VTSj(i) indicates the number of
messages delivered to site Sj sent by site Si. The delivery order of messages between every pair of
sites must follow FIFO order. The FIFO ordering property says that: If a particular site
broadcasts a message M1 before it broadcast a message M2, then each recipient process delivers
M1 before M2. The informal description of events are as follows:
1. Request for Critical Section: Any site which wants to enters the critical section, broadcasts a
time stamped request message to all the sites. When a site broadcasts a message it increments its
own vector time stamp by one and modified vector time stamp is assigned to message. It also
creates an entry of time stamped request message in its request queue.
2. Delivery of Request Message: When a site receives the time stamped request message, it makes
an entry of received request in its request queue. The delivery order of request message must
follow the FIFO order. This ensures that all the messages which are previously sent by requesting
site before the request message have already been delivered. During the delivery of request
message receiving site also updates its knowledge by updating own vector time stamp with the
time stamp of request message.
3. Reply to Requesting Site: After the delivery of timestamped request message at any site, it
sends a corresponding time stamped reply message to requesting site. For assigning time stamp to
message, a receiving site increments its own vector time stamp by one and modified vector time
stamp is assigned to reply message.
4. Receive Reply Message: The requesting site receives the times tamped reply message sent by
all sites. It makes an entry for each received reply message.The requesting site also count the total
number of replied site. Each time when it receives a reply message it increments the value of total
number of replied site by one. The requesting site also updates its vector time stamp with the time
stamp of replied messages.
5. Execution of Critical Section: After receiving the reply messages from all sites, a requesting
site enters critical section if the time stamp of all received messages are greater than time stamp
of its request message and also the time stamp of own request message is minimum among all
request messages present in request queue.
5. Computer Science & Information Technology (CS & IT) 481
6. Release Critical Section: After performing execution of critical section the requesting site
release it and removes the entry of request message from its request queue.
7. Broadcast Release Message: The requesting site broadcasts a time stamped release message to
all the sites so that they can also remove the entry of request message (which is previously sent by
it) from their request queue.
8. Receive Release Message: After the delivery of timestamped release message at any site, it
removes the entry of corresponding request message from its request queue and updates its vector
time stamp with the time stamp of release message.
4. EVENT-B MODEL OF MUTUAL EXCLUSION FOR DISTRIBUTED
SYSTEM
Our Event-B model contains a context and a machine having eight events. In a context seen by
machine SITE and MESSAGE represent carrier set. The status is defined as enumerated set
containing the element pending, reqcs, execs, releasecs. The type is also defined as enumerated
set and contains the element request, reply, release. Variable sender is defined as a partial
function from MESSAGE to SITE. A mapping of the form (m7→s)∈ sender indicates that
message m was sent by a site s. The variable msgsend is subset of MESSAGE and it contains only
those messages which are sent by any site. The variable reqsites is subset of SITE and it contains
only those sites which have sent request messages. The variable vtss represents vector time stamp
of site. It is declared as:
vtss ∈ SITE → (SITE → Natural)
It is a total function which maps every site to a vector function. The vector function maps each
site to a natural number. The 'Natural' represents a set of natural numbers in B. Therefore, vector
time stamp of any site Si, vtss(Si) is a vector. The length of vector depends on number of sites
present in the set SITE. Assume there are K sites in the system then vtss(Si) is a vector of
((S17→N1),(S27→ N2), (S37→ N3).........(Si7→ Ni)........(Sk7→ Nk)).
Every time when a message is sent by site Si, it increments its own clock value vtss(Si)(Si) by
one. Therefore, vector time stamp of site Si after sending single message is
((S17→N1),(S27→ N2), (S37→ N3)........(Si7→ Ni + 1)........(Sk7→ Nk)).
The variable vtsm represents vector time stamp of message. It is defined as:
6. 482 Computer Science & Information Technology (CS & IT)
It is a total function which maps every message to a vector function. Vector time stamp of any
message mm (vtsm(mm)) is also a vector. Every time when a message mm is sent by site Si, it
increments its own clock value by one and modified vector timestamp of site is assigned to
message mm. This creates thevector timestamp of message mm. The vtss(Si)(Si) represents the
number of messages sent by site Si. The description of other variables are as follows (see Fig. 1):
(i) The variable sitestatus is defined as a total function which maps each site to status. Thus every
site in the set SITE will have one of the following states;pending, reqcs, execs, releasecs.
(ii) The variable messagetype is defined as:
messagetype ∈ msgsend → type
It is a total function which maps every sent message to type. This ensures that every sent message
will have one of the following states; request, reply,release.
(iii) The variable requestqueue is declared as:
The operator ↔ defines the set of relations between SITE and request messages sent by
corresponding sites. A mapping of the form
7. Computer Science & Information Technology (CS & IT) 483
Fig. 2. Broadcasting of request message
requestqueue indicates that request queue of site ss has a request message m sent by site s.
Relational image of site Si under the relation requestqueue is represented by requestqueue[{Si}]
and it contains all request messages sent by corresponding sites i.e., if site Si receives three
request messages M1, M2,M3 sent by sites S1, S2, S3 respectively then requestqueue[{Si}]
contains The vector time stamp of messages can be
found from the variable vtsm.
(iv) When a site receives a request message it sends a corresponding reply message to requesting
site. A reply of request message sent by a site is represented by variable replymsgsent. It is
defined as:
A mapping indicates that a reply message m of a
request message mm has been sent by a site ss.
(v) The variable replymsgrec represents receiving of reply message of a request
message at requesting site.
(vi) The variable deliver represents delivery of message at a site. A mapping of form
deliver represents that a site s has delivered message m.
8. 484 Computer Science & Information Technology (CS & IT)
Fig. 3. Delivery of request message
(vii) The variable delorder represents delivery order of messages at a site. A mapping
indicate that site s has delivered m1 before m2.
(viii) The variable totalrepliedsite maps each site to 'Natural' number. Variable counter is a
integer type which is used to count number of sites from which requesting site has received the
reply messages. A mapping totalrepliedsite represents that 'n' number of sites has sent
reply message to site s. Each time when a requesting site receives a reply message from other
sites the value of counter is incremented by one. Initially, the status of all site is set to as pending
and the value of variable counter is zero. The vector time stamp of all sites and messages are
initialized with zero. The remaining variables contain null values.
Broadcasting and Delivery of Request Message : The event BROADCAST-REQ models the
broadcasting of request message (see Fig. 2). A site ss which wants to enters critical section,
broadcasts a timestamped request message mm to all site. The guard grd6 & grd7 ensures that
message mm has not been sent previously. At the time of broadcasting a message mm, site ss
increments its own clock value vtss(ss)(ss) by one (grd9). The modified vector timestamp of site
is assigned to message mm(act1). The guard grd10 is written as:
9. Computer Science & Information Technology (CS & IT) 485
Fig. 4. Sending of Reply Message
It ensures that request queue of site ss does not contain a request message mm which is sent by it.
The action act2 ensures broadcasting of message mm by site ss and actions act3, act4 add the site
ss and message mm in the set reqsites and msgsend repectively. The type of message mm is set to
as a request through the action act5. The action act6 adds the message mm sent by site ss in the
request queue of ss. The action act7 changes the status of site ss from pending to reqcs.
The event DELIVER-REQ models the delivery of request message (see Fig.3).The request
message mm (grd7) which is sent by site ss (grd8) has not been delivered at site s is ensured by
guard grd10. The site ss is requesting site is ensured by guard grd2. The guard grd9 ensures that
request message mm sent by site ss is not present in the request queue of site s. The guard grd11
ensures FIFO order delivery of message. It confirms that all the messages which are sent by site
ss before message mm has been already delivered to site s. As a consequence of occurrence of this
event delivery of message mm is done at sites (act1) and request is added in the request queue of
site s (act3). The delivery order at site s is also updated such that all messages delivered at site s
must
10. 486 Computer Science & Information Technology (CS & IT)
Fig. 5. Delivery of Reply Message
precede mm (act2). For maintaining the latest knowledge about the system, site
s updates its vector time stamp. It is expressed as act4 :
The operator (overload operator) updates the values in the vector clock of site s by
corresponding values in the vector timestamp of message mm (vtsm(mm)) wherever values in the
recipient site clock (vtss(s)(k)) are less than corresponding values in the message time stamp
(vtsm(mm)(k)).
Sending and Delivery of Reply Message: The event REPLY is given in Fig.4. This event models
the sending of timestamped reply message of corresponding request message. The message mm is
request message is ensured by guard grd5. A reply message m of request message mm has not
11. Computer Science & Information Technology (CS & IT) 487
been sent is ensured by guards grd7& grd9. The guard grd8 ensures that message m is a fresh
message and has not been previously sent by any site. As a consequences of occurrence of
this event, incremented vector time stamp value of site ss is assigned to message m (act1) and it is
added in the set msgsend (act2). The type of message m is set to as reply through action act3. The
action act4 makes site ss as a sender of
m. The action act5 is written as:
It updates variable replymsgsent and creates the entry of reply message m of request message mm
sent by site ss. The event REPLY-RECEIVE models the delivery of reply message at requesting
site (see Fig. 5). Site ss is a requesting site is ensured by guard grd2.
A request message mm has already been sent by site ss is ensured by guards grd4, grd5 & grd6. A
reply mesaage m of mm has been sent by site s is ensured by guard grd10. The guard grd13
ensures that reply m of corresponding request message mm has not been received by site ss. The
guard grd14 ensures FIFO order delivery of message. The action act1 makes the delivery of
message m at sites ss and action act2 updates the delivery order of messages such that all
messages delivered at site ss must precede m. The action act3 is written as:
This makes receiving of reply message m of request message mm at site ss. This event also count
how many sites have sent the reply message to requesting site. Each time when a reply message is
received by requesting site the value of total replied site is incremented by one (act4 & act5). For
maintaining the latest knowledge about the system, site ss updates its vector time stamp through
the action act6 .
Execution and Releasing of Critical Section: The EXECUTE-CS event, given in Fig. 6, models
the execution of critical section. A requesting site ss executes the critical section if following
condition holds:
(i) Site ss has received the reply messages from all sites and time stamp of all received messages
are greater than time stamp of request message which is sent by site ss.
(ii) Time stamp of all request messages which are present in the request queue of site ss are
greater than the time stamp of request message sent by site ss. The guard grd2 ensures that site ss
is requesting site and guard grd4 ensures that status of site ss is reqcs. The message type of mm is
request is ensured by guard grd7. The guard grd8 ensures that request queue of site ss contains a
request message mm which is sent by it. The guard grd9 ensures that site ss has received the reply
messages from all the sites. The guard grd10 ensures that time stamp of request message mm is
less than time stamp of all received replied messages. The guard grd11 ensures that time stamp of
request message mm is minimum among all the requests messages present in request queue of site
ss. The status of site ss is set to as execs through the action act1.
12. 488 Computer Science & Information Technology (CS & IT)
Fig. 6. Execution and Releasing of Critical Section
The RELEASE-CS event models the releasing of critical section (see Fig.6).After performing
execution of critical section the requesting site release it and removes the entry of request
message from its request queue. The site ss is requesting site is ensured by guard grd2. The guard
grd4 ensures that status of site ss is execs. This event set the status of site ss as releasecs (act2)
and removes entry of its request from its request queue (act1).
13. Computer Science & Information Technology (CS & IT) 489
Fig. 7. Broadcasting of Release message
Broadcast and Delivery of Release message: The event BROADCAST-RELEASE is given in
Fig. 7. After releasing of critical section site ss broadcasts a time stamped release message to all
sites so that they can also remove the entry of request message previously sent by it. The guard
grd4 ensures that site ss has performed the execution of critical section. Before broadcasting a
reply message mm site ss increments its vector time stamp (grd9) and this modified vector time
stamp is assigned to the message mm (act1). The action act4 set the type of message mm as
release message. The action act5 removes site ss from request set reqcs. The status of site ss is set
to as pending through the action (act6).
The event DELIVER-RELEASE models the delivery of release message (see Fig. 8). The guard
grd3 ensures that message mm is release message. A site ss has sent the release message mm is
ensured by guard grd4. In the request queue of site s (recipient site) there is an entry of request
message m sent by site ss is ensured by guard grd9. The guard grd10 ensures FIFO order delivery
of messages. The delivery of message mm at site s is done through action act1. The action act2
updates the delivery order such that all the messages which are previously delivered to site s must
precede message mm. The action act3 updates the vector time stamp of site s. The action act4
removes the entry of request message m sent by site ss from the request queue of site s. Removing
a request from request queue makes possible that next minimum time stamped request is own
request, enabling it to enter the critical section.
14. 490 Computer Science & Information Technology (CS & IT)
Fig. 8. Delivery of Release message
5 . CONCLUSIONS
In distributed system, due to absence of global clock and shared memory traditional technique
like semaphore may not be appropriate for solving the problem of mutual exclusion. To decide
which site execute the critical section, a site communicates with other sites by sending a message.
We have considered Lamport's mutual exclusion algorithm [1], [3] for formal construction of our
model. In this algorithm, each site maintains a request queue, which contains its own
timestamped request for mutual exclusion and also request messages received from other sites
[3]. We have considered vector clock [18] instead of using Lamport's scalar clock for assigning
the time stamp to messages. In a system of vector clock, every site maintains a vector to represent
what that site believes to be the logical time at all other sites.
In this paper, modeling of distributed mutual exclusion system is specied using Event-B. This
work is carried out on Rodin tool [16], [17]. The Rodin tool is intended to support construction
and verification of Event-B models. The tool takes the formal text of model and produces proof
obligations. It provides an environment to discharge of proof obligations arising due to
consistency checking. Modeling guidelines outlined in [14] were used and these guidelines
helped us in modeling and discharging proof obligations generated due to consistency checking.
Total sixty four proof obligations were generated by the system and all of them were discharged
automatically. The proofs and invariants together helped us to reason about the system design.We
also found that vector clock can also be used to implement Lamport's mutual exclusion instead of
using scalar clock.
15. Computer Science & Information Technology (CS & IT) 491
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