This document describes a proposed multi-agent system for searching distributed data. The system uses three types of agents - coordinator agents, search agents, and local agents. Coordinator agents coordinate the retrieval process by creating search agents and collecting results. Search agents carry queries to nodes containing relevant databases. Local agents reside at nodes with databases, accept queries from search agents, search the databases for answers, and return results to the search agents. The system aims to retrieve data from distributed databases with minimum network bandwidth consumption using this multi-agent approach.
USE OF NETWORK FORENSIC MECHANISMS TO FORMULATE NETWORK SECURITYIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel
interested in obtaining knowledge in securing communication devices/infrastructure. This research
provides a framework that can be used in an organization to eliminate digital anomalies through network
forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also
enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
An efficient approach on spatial big data related to wireless networks and it...eSAT Journals
Abstract
Spatial big data acts as a important key role in wireless networks applications. In that spatial and spatio temporal problems contains the distinct role in big data and it’s compared to common relational problems. If we are solving those problems means describing the three applications for spatial big data. In each applications imposing the specific design and we are developing our work on highly scalable parallel processing for spatial big data in Hadoop frameworks by using map reduce computational model. Our results show that enables highly scalable implementations of algorithms using Hadoop for the purpose of spatial data processing problems. Inspite of developing these implementations requires specialized knowledge and user friendly.
Keywords: Spatial Big Data, Hadoop, Wireless Networks, Map reduce
Coordination issues of multi agent systems in distributed data miningIAEME Publication
This document discusses coordination issues in multi-agent systems for distributed data mining. It proposes an agent-based approach for distributed data clustering and classification. The key points are:
1. Distributed data mining uses multiple agents that can autonomously access decentralized data sources for mining. This addresses issues of data distribution, privacy and security.
2. The proposed approach uses different agent types like client agents, service agents, and mobile agents to coordinate the distributed data mining process.
3. Coordination challenges include handling multiple concurrent data mining tasks, enabling agent reuse and coordination, and ensuring scalability and adaptability to changes in data sources.
TREND-BASED NETWORKING DRIVEN BY BIG DATA TELEMETRY FOR SDN AND TRADITIONAL N...ijngnjournal
Organizations face a challenge of accurately analyzing network data and providing automated action
based on the observed trend. This trend-based analytics is beneficial to minimize the downtime and
improve the performance of the network services, but organizations use different network management
tools to understand and visualize the network traffic with limited abilities to dynamically optimize the
network. This research focuses on the development of an intelligent system that leverages big data
telemetry analysis in Platform for Network Data Analytics (PNDA) to enable comprehensive trendbased networking decisions. The results include a graphical user interface (GUI) done via a web
application for effortless management of all subsystems, and the system and application developed in
this research demonstrate the true potential for a scalable system capable of effectively benchmarking
the network to set the expected behavior for comparison and trend analysis. Moreover, this research
provides a proof of concept of how trend analysis results are actioned in both a traditional network and
a software-defined network (SDN) to achieve dynamic, automated load balancing.
Centralized Data Verification Scheme for Encrypted Cloud Data ServicesEditor IJMTER
Cloud environment supports data sharing between multiple users. Data integrity is violated
due to hardware / software failures and human errors. Data owners and public verifiers are involved to
efficiently audit cloud data integrity without retrieving the entire data from the cloud server. File and
block signatures are used in the integrity verification process.
“One Ring to RUle Them All” (Oruta) scheme is used for privacy-preserving public auditing process. In
oruta homomorphic authenticators are constructed using Ring Signatures. Ring signatures are used to
compute verification metadata needed to audit the correctness of shared data. The identity of the signer
on each block in shared data is kept private from public verifiers. Homomorphic authenticable ring
signature (HARS) scheme is applied to provide identity privacy with blockless verification. Batch
auditing mechanism supports to perform multiple auditing tasks simultaneously. Oruta is compatible
with random masking to preserve data privacy from public verifiers. Dynamic data management process
is handled with index hash tables. Traceability is not supported in oruta scheme. Data dynamism
sequence is not managed by the system. The system obtains high computational overhead
The proposed system is designed to perform public data verification with privacy. Traceability features
are provided with identity privacy. Group manager or data owner can be allowed to reveal the identity of
the signer based on verification metadata. Data version management mechanism is integrated with the
system.
Performing initiative data prefetchingKamal Spring
Abstract—This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
Anomaly detection in the services provided by multi cloud architectures a surveyeSAT Publishing House
This document summarizes various anomaly detection techniques that can be used in multi-cloud architectures. It discusses statistical, data mining, and machine learning based techniques. A table compares 11 different anomaly detection models or frameworks, outlining their advantages and disadvantages. The document concludes that combining multiple techniques may generate better results for anomaly detection in clouds. Future work could optimize existing techniques or use unsupervised "black box" approaches without human intervention.
This document proposes an improved hierarchical multi-pass learning vector quantization (LVQ) algorithm for classifying large web data. The algorithm aims to provide both high accuracy and speed by combining the advantages of hierarchical LVQ and multi-pass LVQ. It works in a hierarchical manner, generating models at each level using multi-pass LVQ. Sub-models are also constructed and evaluated, and inaccurate ones are rejected to maintain accuracy at each level quickly. The approach is intended to more accurately classify large and complex web data sets with high efficiency.
USE OF NETWORK FORENSIC MECHANISMS TO FORMULATE NETWORK SECURITYIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel
interested in obtaining knowledge in securing communication devices/infrastructure. This research
provides a framework that can be used in an organization to eliminate digital anomalies through network
forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also
enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
An efficient approach on spatial big data related to wireless networks and it...eSAT Journals
Abstract
Spatial big data acts as a important key role in wireless networks applications. In that spatial and spatio temporal problems contains the distinct role in big data and it’s compared to common relational problems. If we are solving those problems means describing the three applications for spatial big data. In each applications imposing the specific design and we are developing our work on highly scalable parallel processing for spatial big data in Hadoop frameworks by using map reduce computational model. Our results show that enables highly scalable implementations of algorithms using Hadoop for the purpose of spatial data processing problems. Inspite of developing these implementations requires specialized knowledge and user friendly.
Keywords: Spatial Big Data, Hadoop, Wireless Networks, Map reduce
Coordination issues of multi agent systems in distributed data miningIAEME Publication
This document discusses coordination issues in multi-agent systems for distributed data mining. It proposes an agent-based approach for distributed data clustering and classification. The key points are:
1. Distributed data mining uses multiple agents that can autonomously access decentralized data sources for mining. This addresses issues of data distribution, privacy and security.
2. The proposed approach uses different agent types like client agents, service agents, and mobile agents to coordinate the distributed data mining process.
3. Coordination challenges include handling multiple concurrent data mining tasks, enabling agent reuse and coordination, and ensuring scalability and adaptability to changes in data sources.
TREND-BASED NETWORKING DRIVEN BY BIG DATA TELEMETRY FOR SDN AND TRADITIONAL N...ijngnjournal
Organizations face a challenge of accurately analyzing network data and providing automated action
based on the observed trend. This trend-based analytics is beneficial to minimize the downtime and
improve the performance of the network services, but organizations use different network management
tools to understand and visualize the network traffic with limited abilities to dynamically optimize the
network. This research focuses on the development of an intelligent system that leverages big data
telemetry analysis in Platform for Network Data Analytics (PNDA) to enable comprehensive trendbased networking decisions. The results include a graphical user interface (GUI) done via a web
application for effortless management of all subsystems, and the system and application developed in
this research demonstrate the true potential for a scalable system capable of effectively benchmarking
the network to set the expected behavior for comparison and trend analysis. Moreover, this research
provides a proof of concept of how trend analysis results are actioned in both a traditional network and
a software-defined network (SDN) to achieve dynamic, automated load balancing.
Centralized Data Verification Scheme for Encrypted Cloud Data ServicesEditor IJMTER
Cloud environment supports data sharing between multiple users. Data integrity is violated
due to hardware / software failures and human errors. Data owners and public verifiers are involved to
efficiently audit cloud data integrity without retrieving the entire data from the cloud server. File and
block signatures are used in the integrity verification process.
“One Ring to RUle Them All” (Oruta) scheme is used for privacy-preserving public auditing process. In
oruta homomorphic authenticators are constructed using Ring Signatures. Ring signatures are used to
compute verification metadata needed to audit the correctness of shared data. The identity of the signer
on each block in shared data is kept private from public verifiers. Homomorphic authenticable ring
signature (HARS) scheme is applied to provide identity privacy with blockless verification. Batch
auditing mechanism supports to perform multiple auditing tasks simultaneously. Oruta is compatible
with random masking to preserve data privacy from public verifiers. Dynamic data management process
is handled with index hash tables. Traceability is not supported in oruta scheme. Data dynamism
sequence is not managed by the system. The system obtains high computational overhead
The proposed system is designed to perform public data verification with privacy. Traceability features
are provided with identity privacy. Group manager or data owner can be allowed to reveal the identity of
the signer based on verification metadata. Data version management mechanism is integrated with the
system.
Performing initiative data prefetchingKamal Spring
Abstract—This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
Anomaly detection in the services provided by multi cloud architectures a surveyeSAT Publishing House
This document summarizes various anomaly detection techniques that can be used in multi-cloud architectures. It discusses statistical, data mining, and machine learning based techniques. A table compares 11 different anomaly detection models or frameworks, outlining their advantages and disadvantages. The document concludes that combining multiple techniques may generate better results for anomaly detection in clouds. Future work could optimize existing techniques or use unsupervised "black box" approaches without human intervention.
This document proposes an improved hierarchical multi-pass learning vector quantization (LVQ) algorithm for classifying large web data. The algorithm aims to provide both high accuracy and speed by combining the advantages of hierarchical LVQ and multi-pass LVQ. It works in a hierarchical manner, generating models at each level using multi-pass LVQ. Sub-models are also constructed and evaluated, and inaccurate ones are rejected to maintain accuracy at each level quickly. The approach is intended to more accurately classify large and complex web data sets with high efficiency.
An adaptive algorithm for task scheduling for computational grideSAT Journals
Abstract
Grid Computing is a collection of computing and storage resources that are collected from multiple administrative domains. Grid resources can be applied to reach a common goal. Since computational grids enable the sharing and aggregation of a wide variety of geographically distributed computational resources, an effective task scheduling is vital for managing the tasks. Efficient scheduling algorithms are the need of the hour to achieve efficient utilization of the unused CPU cycles distributed geographically in various locations. The existing job scheduling algorithms in grid computing are mainly concentrated on the system’s performance rather than the user satisfaction. This research work presents a new algorithm that mainly focuses on better meeting the deadlines of the statically available jobs as expected by the users. This algorithm also concentrates on the better utilization of the available heterogeneous resources.
Keywords: Task Scheduling, Computational Grid, Adaptive Scheduling and User Deadline.
The huge volume of text documents available on the internet has made it difficult to find valuable
information for specific users. In fact, the need for efficient applications to extract interested knowledge
from textual documents is vitally important. This paper addresses the problem of responding to user
queries by fetching the most relevant documents from a clustered set of documents. For this purpose, a
cluster-based information retrieval framework was proposed in this paper, in order to design and develop
a system for analysing and extracting useful patterns from text documents. In this approach, a pre-
processing step is first performed to find frequent and high-utility patterns in the data set. Then a Vector
Space Model (VSM) is performed to represent the dataset. The system was implemented through two main
phases. In phase 1, the clustering analysis process is designed and implemented to group documents into
several clusters, while in phase 2, an information retrieval process was implemented to rank clusters
according to the user queries in order to retrieve the relevant documents from specific clusters deemed
relevant to the query. Then the results are evaluated according to evaluation criteria. Recall and Precision
(P@5, P@10) of the retrieved results. P@5 was 0.660 and P@10 was 0.655.
This document provides an overview of multi agent-based distributed data mining. It discusses how data mining techniques have challenges when dealing with large, distributed data sources. Multi-agent systems can help address these challenges by allowing for distributed problem solving across decentralized data sources. The document then discusses how agent computing is well-suited for distributed data mining applications due to properties like decentralization, autonomy, and reactivity. It provides examples of application domains for distributed data mining and outlines key aspects like interoperability, dynamic system configuration, and performance that agent-based distributed data mining systems should address.
Mobile Location Indexing Based On Synthetic Moving ObjectsIJECEIAES
Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation.
Stream Processing Environmental Applications in Jordan ValleyCSCJournals
This document discusses stream processing applications for environmental monitoring in Jordan Valley. It presents statistical data collected from weather stations in different Jordan Valley locations. Stream processing is important for continuous monitoring systems to detect events in real-time. The document outlines considerations for stream processing engine design like communication, computation, and flexibility. It also describes Jordan's Irrigation Management Information System, which uses real-time meteorological data from weather stations to optimize water usage for agriculture.
The advent of Big Data has seen the emergence of new processing and storage challenges. These challenges are often solved by distributed processing. Distributed systems are inherently dynamic and unstable, so it is realistic to expect that some resources will fail during use. Load balancing and task scheduling is an important step in determining the performance of parallel applications. Hence the need to design load balancing algorithms adapted to grid computing. In this paper, we propose a dynamic and hierarchical load balancing strategy at two levels: Intrascheduler load balancing, in order to avoid the use of the large-scale communication network, and interscheduler load balancing, for a load regulation of our whole system. The strategy allows improving the average response time of CLOAK-Reduce application tasks with minimal communication. We first focus on the three performance indicators, namely response time, process latency and running time of MapReduce tasks.
Grid scheduling is a process of mapping Grid jobs to resources over multiple administrative domains.
A Grid job can be split into many small tasks.
The scheduler has the responsibility of selecting resources and scheduling jobs in such a way that the user and application requirements are met,in terms of overall execution time (throughput) and cost of the resources utilized.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
CYBER INFRASTRUCTURE AS A SERVICE TO EMPOWER MULTIDISCIPLINARY, DATA-DRIVEN S...ijcsit
In supporting its large scale, multidisciplinary scientific research efforts across all the university campuses and by the research personnel spread over literally every corner of the state, the state of Nevada needs to build and leverage its own Cyber infrastructure. Following the well-established as-a-service model, this state-wide Cyber infrastructure that consists of data acquisition, data storage, advanced instruments, visualization, computing and information processing systems, and people, all seamlessly linked together through a high-speed network, is designed and operated to deliver the benefits of Cyber infrastructure-as-aService (CaaS).There are three major service groups in this CaaS, namely (i) supporting infrastructural
services that comprise sensors, computing/storage/networking hardware, operating system, management tools, virtualization and message passing interface (MPI); (ii) data transmission and storage services that provide connectivity to various big data sources, as well as cached and stored datasets in a distributed
storage backend; and (iii) processing and visualization services that provide user access to rich processing and visualization tools and packages essential to various scientific research workflows. Built on commodity hardware and open source software packages, the Southern Nevada Research Cloud(SNRC)and a data repository in a separate location constitute a low cost solution to deliver all these services around CaaS. The service-oriented architecture and implementation of the SNRC are geared to encapsulate as much detail of big data processing and cloud computing as possible away from end users; rather scientists only need to learn and access an interactive web-based interface to conduct their collaborative, multidisciplinary, dataintensive research. The capability and easy-to-use features of the SNRC are demonstrated through a use case that attempts to derive a solar radiation model from a large data set by regression analysis.
Review of big data analytics (bda) architecture trends and analysis Conference Papers
This document reviews big data analytics (BDA) architecture trends and analysis. It discusses the evolution of data analytics from ancient times to modern technologies like Hadoop and Spark. It describes key features of BDA like flexibility, scalability, and fault tolerance. Common BDA architectures like lambda and kappa architectures are summarized. The lambda architecture uses batch, speed, and serving layers to handle both real-time and batch processing. The kappa architecture simplifies this by removing the batch layer and handling all processing through streaming. Overall, the document provides a high-level overview of BDA architectures and technologies.
IRJET- Comparative Study on Embedded Feature Selection Techniques for Interne...IRJET Journal
This document presents a comparative study on embedded feature selection techniques for internet traffic classification. It discusses using machine learning and deep learning algorithms like Naive Bayes, Random Forest, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) on network traffic datasets to classify traffic. The performance of these techniques is analyzed in terms of error metrics, with the results showing that the proposed deep learning approach using MLP outperforms existing machine learning techniques. The document also provides background on internet traffic classification and related work applying techniques like K-means clustering, C5.0 decision trees, and SVM to classify network application traffic based on flow features.
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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 DEVELOPMENT AND STUDY OF THE METHODS AND ALGORITHMS FOR THE CLASSIFICATIO...IJCNCJournal
This document summarizes a study on developing methods and algorithms for classifying data flows of cloud applications in the network of a virtual data center. The researchers developed a hybrid approach using data mining and machine learning methods to classify traffic flows in real-time. They created an algorithm for classifying and adaptively routing cloud application traffic flows, which was implemented as a module in the software-defined network controller. This solution aims to improve the efficiency of handling user requests to cloud applications and reduce response times.
CONTENT BASED DATA TRANSFER MECHANISM FOR EFFICIENT BULK DATA TRANSFER IN GRI...ijgca
A new class of Data Grid infrastructure is needed to support management, transport, distributed access, and analysis of terabyte and peta byte of data collections by thousands of users. Even though some of the existing data management systems (DMS) of Grid computing infrastructures provides methodologies to handle bulk data transfer. These technologies are not usable in addressing some kind of simultaneous data
access requirements. Often, in most of the scientific computing environments, a common data will be needed to access from different locations. Further, most of such computing entities will wait for a common scientific data (such as a data belonging to an astronomical phenomenon) which will be published only
when it is available. These kinds of data access needs were not yet addressed in the design of data component Grid Access to Secondary Storage (GASS) or GridFTP. In this paper, we address an application layer content based data transfer scheme for grid computing environments. By using the
proposed scheme in a grid computing environment, we can simultaneously move bulk data in an efficient way using simple subscribe and publish mechanism.
CIRCUIT BREAK CONNECT MONITORING TO 5G MOBILE APPLICATIONijcsit
This document describes a proposed circuit breaker monitoring system using mobile apps. Key points:
- The system would replace traditional circuit breakers with mobile app-controlled breakers for remote management of home appliances for safety and energy savings.
- It would include a home security system against intrusion using a mobile app-controlled door lock and gas leak detection.
- The proposed system architecture uses ESP 32 microcontrollers and Bluetooth modules in each "slave" unit installed at circuit breakers to collect data, and a "master" unit to store and process the collected data from all slaves.
IRJET- Top-K Query Processing using Top Order Preserving Encryption (TOPE)IRJET Journal
This document proposes a method called Top Order Preserving Encryption (TOPE) to support top-k queries on encrypted data outsourced to public clouds. TOPE extends existing Order Preserving Encryption (OPE) schemes to preserve order when encrypting data, allowing comparison operations and queries to be run directly on the encrypted data. The proposed method uses TOPE to encrypt data before outsourcing to the cloud, and stores the encrypted data in min-heap and max-heap trees indexed by attributes. This allows the cloud to efficiently retrieve the top-k most relevant tuples for a given query while preserving data privacy during query processing.
Implementing Proof of Retriavaibility for Multiple Replica of Data File using...IRJET Journal
1. The document proposes a protocol for implementing proof of retrievability for multiple replicas of data files stored on cloud servers using a NoSQL database. It aims to verify the integrity of data when both the cloud storage server and third party auditor cannot fully be trusted.
2. The proposed system replaces a relational database with a NoSQL database to improve data operation performance and scaling for large datasets. It designs a protocol where the third party auditor generates signatures for dataset blocks and integrity proofs, which are then verified by the user to check the trustworthiness of the third party auditor.
3. Experimental results show that the time required for operations like tag generation and challenge-proof-verify are lower than previous solutions,
This document compares the k-means data mining and outlier detection approaches for network-based intrusion detection. It analyzes four datasets capturing network traffic using both approaches. The k-means approach clusters traffic into normal and abnormal flows, while outlier detection calculates an outlier score for each flow. The document finds that k-means was more accurate and precise, with a better classification rate than outlier detection. It requires less computer resources than outlier detection. This comparison of the approaches can help network administrators choose the best intrusion detection method.
Network Monitoring and Traffic Reduction using Multi-Agent TechnologyEswar Publications
In this paper the algorithms which could improve Transmission band and Network Traffic reduction for computer network has been shown. Problem solving is an area with which many Multiagent-based applications are concerned. Multiagent systems are computational systems in which several agents interact or work together to achieve some purposes. It includes distributed solutions to problems, solving distributed problems and distributed techniques for problem solving. Multiagent using for maximizing group performance with planning, execution, monitoring, communication and coordination. This paper also addresses some critical issues in developing
Multi agent-based traffic control and monitoring systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of Multiagent technology in traffic control and monitoring systems are discussed.
Implementation of Agent Based Dynamic Distributed ServiceCSCJournals
This document proposes a design for agent migration between distributed systems using ACL (Agent Communication Language) messages. It involves serializing an agent's code and state into an ACL message that is sent from one system to another. The receiving system deserializes the agent to restore its execution. The design includes defining an ontology for migration messages, a migration protocol specifying the message flow, and components for handling class loading, agent migration, and conversation protocols. The performance of this distributed agent migration approach is evaluated by applying it to a distributed prime number calculation application.
An adaptive algorithm for task scheduling for computational grideSAT Journals
Abstract
Grid Computing is a collection of computing and storage resources that are collected from multiple administrative domains. Grid resources can be applied to reach a common goal. Since computational grids enable the sharing and aggregation of a wide variety of geographically distributed computational resources, an effective task scheduling is vital for managing the tasks. Efficient scheduling algorithms are the need of the hour to achieve efficient utilization of the unused CPU cycles distributed geographically in various locations. The existing job scheduling algorithms in grid computing are mainly concentrated on the system’s performance rather than the user satisfaction. This research work presents a new algorithm that mainly focuses on better meeting the deadlines of the statically available jobs as expected by the users. This algorithm also concentrates on the better utilization of the available heterogeneous resources.
Keywords: Task Scheduling, Computational Grid, Adaptive Scheduling and User Deadline.
The huge volume of text documents available on the internet has made it difficult to find valuable
information for specific users. In fact, the need for efficient applications to extract interested knowledge
from textual documents is vitally important. This paper addresses the problem of responding to user
queries by fetching the most relevant documents from a clustered set of documents. For this purpose, a
cluster-based information retrieval framework was proposed in this paper, in order to design and develop
a system for analysing and extracting useful patterns from text documents. In this approach, a pre-
processing step is first performed to find frequent and high-utility patterns in the data set. Then a Vector
Space Model (VSM) is performed to represent the dataset. The system was implemented through two main
phases. In phase 1, the clustering analysis process is designed and implemented to group documents into
several clusters, while in phase 2, an information retrieval process was implemented to rank clusters
according to the user queries in order to retrieve the relevant documents from specific clusters deemed
relevant to the query. Then the results are evaluated according to evaluation criteria. Recall and Precision
(P@5, P@10) of the retrieved results. P@5 was 0.660 and P@10 was 0.655.
This document provides an overview of multi agent-based distributed data mining. It discusses how data mining techniques have challenges when dealing with large, distributed data sources. Multi-agent systems can help address these challenges by allowing for distributed problem solving across decentralized data sources. The document then discusses how agent computing is well-suited for distributed data mining applications due to properties like decentralization, autonomy, and reactivity. It provides examples of application domains for distributed data mining and outlines key aspects like interoperability, dynamic system configuration, and performance that agent-based distributed data mining systems should address.
Mobile Location Indexing Based On Synthetic Moving ObjectsIJECEIAES
Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation.
Stream Processing Environmental Applications in Jordan ValleyCSCJournals
This document discusses stream processing applications for environmental monitoring in Jordan Valley. It presents statistical data collected from weather stations in different Jordan Valley locations. Stream processing is important for continuous monitoring systems to detect events in real-time. The document outlines considerations for stream processing engine design like communication, computation, and flexibility. It also describes Jordan's Irrigation Management Information System, which uses real-time meteorological data from weather stations to optimize water usage for agriculture.
The advent of Big Data has seen the emergence of new processing and storage challenges. These challenges are often solved by distributed processing. Distributed systems are inherently dynamic and unstable, so it is realistic to expect that some resources will fail during use. Load balancing and task scheduling is an important step in determining the performance of parallel applications. Hence the need to design load balancing algorithms adapted to grid computing. In this paper, we propose a dynamic and hierarchical load balancing strategy at two levels: Intrascheduler load balancing, in order to avoid the use of the large-scale communication network, and interscheduler load balancing, for a load regulation of our whole system. The strategy allows improving the average response time of CLOAK-Reduce application tasks with minimal communication. We first focus on the three performance indicators, namely response time, process latency and running time of MapReduce tasks.
Grid scheduling is a process of mapping Grid jobs to resources over multiple administrative domains.
A Grid job can be split into many small tasks.
The scheduler has the responsibility of selecting resources and scheduling jobs in such a way that the user and application requirements are met,in terms of overall execution time (throughput) and cost of the resources utilized.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
CYBER INFRASTRUCTURE AS A SERVICE TO EMPOWER MULTIDISCIPLINARY, DATA-DRIVEN S...ijcsit
In supporting its large scale, multidisciplinary scientific research efforts across all the university campuses and by the research personnel spread over literally every corner of the state, the state of Nevada needs to build and leverage its own Cyber infrastructure. Following the well-established as-a-service model, this state-wide Cyber infrastructure that consists of data acquisition, data storage, advanced instruments, visualization, computing and information processing systems, and people, all seamlessly linked together through a high-speed network, is designed and operated to deliver the benefits of Cyber infrastructure-as-aService (CaaS).There are three major service groups in this CaaS, namely (i) supporting infrastructural
services that comprise sensors, computing/storage/networking hardware, operating system, management tools, virtualization and message passing interface (MPI); (ii) data transmission and storage services that provide connectivity to various big data sources, as well as cached and stored datasets in a distributed
storage backend; and (iii) processing and visualization services that provide user access to rich processing and visualization tools and packages essential to various scientific research workflows. Built on commodity hardware and open source software packages, the Southern Nevada Research Cloud(SNRC)and a data repository in a separate location constitute a low cost solution to deliver all these services around CaaS. The service-oriented architecture and implementation of the SNRC are geared to encapsulate as much detail of big data processing and cloud computing as possible away from end users; rather scientists only need to learn and access an interactive web-based interface to conduct their collaborative, multidisciplinary, dataintensive research. The capability and easy-to-use features of the SNRC are demonstrated through a use case that attempts to derive a solar radiation model from a large data set by regression analysis.
Review of big data analytics (bda) architecture trends and analysis Conference Papers
This document reviews big data analytics (BDA) architecture trends and analysis. It discusses the evolution of data analytics from ancient times to modern technologies like Hadoop and Spark. It describes key features of BDA like flexibility, scalability, and fault tolerance. Common BDA architectures like lambda and kappa architectures are summarized. The lambda architecture uses batch, speed, and serving layers to handle both real-time and batch processing. The kappa architecture simplifies this by removing the batch layer and handling all processing through streaming. Overall, the document provides a high-level overview of BDA architectures and technologies.
IRJET- Comparative Study on Embedded Feature Selection Techniques for Interne...IRJET Journal
This document presents a comparative study on embedded feature selection techniques for internet traffic classification. It discusses using machine learning and deep learning algorithms like Naive Bayes, Random Forest, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) on network traffic datasets to classify traffic. The performance of these techniques is analyzed in terms of error metrics, with the results showing that the proposed deep learning approach using MLP outperforms existing machine learning techniques. The document also provides background on internet traffic classification and related work applying techniques like K-means clustering, C5.0 decision trees, and SVM to classify network application traffic based on flow features.
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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 DEVELOPMENT AND STUDY OF THE METHODS AND ALGORITHMS FOR THE CLASSIFICATIO...IJCNCJournal
This document summarizes a study on developing methods and algorithms for classifying data flows of cloud applications in the network of a virtual data center. The researchers developed a hybrid approach using data mining and machine learning methods to classify traffic flows in real-time. They created an algorithm for classifying and adaptively routing cloud application traffic flows, which was implemented as a module in the software-defined network controller. This solution aims to improve the efficiency of handling user requests to cloud applications and reduce response times.
CONTENT BASED DATA TRANSFER MECHANISM FOR EFFICIENT BULK DATA TRANSFER IN GRI...ijgca
A new class of Data Grid infrastructure is needed to support management, transport, distributed access, and analysis of terabyte and peta byte of data collections by thousands of users. Even though some of the existing data management systems (DMS) of Grid computing infrastructures provides methodologies to handle bulk data transfer. These technologies are not usable in addressing some kind of simultaneous data
access requirements. Often, in most of the scientific computing environments, a common data will be needed to access from different locations. Further, most of such computing entities will wait for a common scientific data (such as a data belonging to an astronomical phenomenon) which will be published only
when it is available. These kinds of data access needs were not yet addressed in the design of data component Grid Access to Secondary Storage (GASS) or GridFTP. In this paper, we address an application layer content based data transfer scheme for grid computing environments. By using the
proposed scheme in a grid computing environment, we can simultaneously move bulk data in an efficient way using simple subscribe and publish mechanism.
CIRCUIT BREAK CONNECT MONITORING TO 5G MOBILE APPLICATIONijcsit
This document describes a proposed circuit breaker monitoring system using mobile apps. Key points:
- The system would replace traditional circuit breakers with mobile app-controlled breakers for remote management of home appliances for safety and energy savings.
- It would include a home security system against intrusion using a mobile app-controlled door lock and gas leak detection.
- The proposed system architecture uses ESP 32 microcontrollers and Bluetooth modules in each "slave" unit installed at circuit breakers to collect data, and a "master" unit to store and process the collected data from all slaves.
IRJET- Top-K Query Processing using Top Order Preserving Encryption (TOPE)IRJET Journal
This document proposes a method called Top Order Preserving Encryption (TOPE) to support top-k queries on encrypted data outsourced to public clouds. TOPE extends existing Order Preserving Encryption (OPE) schemes to preserve order when encrypting data, allowing comparison operations and queries to be run directly on the encrypted data. The proposed method uses TOPE to encrypt data before outsourcing to the cloud, and stores the encrypted data in min-heap and max-heap trees indexed by attributes. This allows the cloud to efficiently retrieve the top-k most relevant tuples for a given query while preserving data privacy during query processing.
Implementing Proof of Retriavaibility for Multiple Replica of Data File using...IRJET Journal
1. The document proposes a protocol for implementing proof of retrievability for multiple replicas of data files stored on cloud servers using a NoSQL database. It aims to verify the integrity of data when both the cloud storage server and third party auditor cannot fully be trusted.
2. The proposed system replaces a relational database with a NoSQL database to improve data operation performance and scaling for large datasets. It designs a protocol where the third party auditor generates signatures for dataset blocks and integrity proofs, which are then verified by the user to check the trustworthiness of the third party auditor.
3. Experimental results show that the time required for operations like tag generation and challenge-proof-verify are lower than previous solutions,
This document compares the k-means data mining and outlier detection approaches for network-based intrusion detection. It analyzes four datasets capturing network traffic using both approaches. The k-means approach clusters traffic into normal and abnormal flows, while outlier detection calculates an outlier score for each flow. The document finds that k-means was more accurate and precise, with a better classification rate than outlier detection. It requires less computer resources than outlier detection. This comparison of the approaches can help network administrators choose the best intrusion detection method.
Network Monitoring and Traffic Reduction using Multi-Agent TechnologyEswar Publications
In this paper the algorithms which could improve Transmission band and Network Traffic reduction for computer network has been shown. Problem solving is an area with which many Multiagent-based applications are concerned. Multiagent systems are computational systems in which several agents interact or work together to achieve some purposes. It includes distributed solutions to problems, solving distributed problems and distributed techniques for problem solving. Multiagent using for maximizing group performance with planning, execution, monitoring, communication and coordination. This paper also addresses some critical issues in developing
Multi agent-based traffic control and monitoring systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of Multiagent technology in traffic control and monitoring systems are discussed.
Implementation of Agent Based Dynamic Distributed ServiceCSCJournals
This document proposes a design for agent migration between distributed systems using ACL (Agent Communication Language) messages. It involves serializing an agent's code and state into an ACL message that is sent from one system to another. The receiving system deserializes the agent to restore its execution. The design includes defining an ontology for migration messages, a migration protocol specifying the message flow, and components for handling class loading, agent migration, and conversation protocols. The performance of this distributed agent migration approach is evaluated by applying it to a distributed prime number calculation application.
Grid computing or network computing is developed to make the available electric power in the similar way
as it is available for the grid. For that we just plug in the power and whoever needs power, may use it. In
grid computing if a system needs more power than available it can share the computing with other
machines connected in a grid. In this way we can use the power of a super computer without a huge cost
and the CPU cycles that were wasted previously can also be utilized. For performing grid computation in
joined computers through the internet, the software must be installed which supports grid computation on
each computer inside the VO. The software handles information queries, storage management, processing
scheduling, authentication and data encryption to ensure information security.
IRJET- Monitoring and Detecting Abnormal Behaviour in Mobile Cloud Infrastruc...IRJET Journal
This document presents a new mobile cloud infrastructure that combines mobile devices and cloud services to provide virtual mobile instances through cloud computing. It discusses possible security threats in this new infrastructure and proposes an architecture to detect abnormal behavior. Machine learning techniques like random forest algorithms are used to test the methodology. The system aims to address challenges in existing systems and provide end-to-end security and abnormal behavior detection in the mobile cloud without requiring specific software installation on user devices.
International Journal of Engineering (IJE) Volume (2) Issue (1)CSCJournals
The document summarizes an intelligent GIS-based road accident analysis and real-time monitoring system that uses WiMAX/GPRS. It discusses the motivation and need for such a system to better analyze accidents and identify accident-prone locations. It then describes the system architecture, which utilizes telegeoinformatics to enable interoperability across different components. It also discusses strategies for adapting the system to different client devices. Finally, it outlines the use of terminal-centric and network-centric positioning methods like A-GPS and CGI-TA for location services and monitoring within an open, IP-based telecommunications network.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document discusses distance evaluation using mobile agent technology. It begins by explaining client-server technology and some of its limitations for distance evaluation, including lack of support for subjective questions, delivery of dynamic content, and offline examinations. It then introduces mobile agent technology as an alternative that can address these limitations. Mobile agents are software processes that can migrate between machines to access resources and services. The document proposes using a mobile agent approach to design and implement a computer assisted testing and evaluation system for distance education that considers the full examination process from paper setting to evaluation. Key advantages of mobile agents for this application include reduced network traffic, asynchronous autonomous interaction, and support for heterogeneous environments.
Mobile agents in a distributed multimedia dabase system(synopsis)Mumbai Academisc
This document discusses using mobile agents in distributed multimedia database systems. It proposes a model that uses mobile agents to facilitate the storage and retrieval of multimedia data from distributed databases. The key points are:
1) Mobile agents can travel to the host where data is physically stored, which is useful for distributed multimedia databases that contain large binary objects.
2) The proposed model integrates mobile agent technology with database services like transaction handling and security.
3) It uses different agents (client, server, query, and database agents) to dispatch requests and queries to retrieve multimedia data from across distributed databases more efficiently than traditional client-server models.
Agent based frameworks for distributed association rule mining an analysis ijfcstjournal
Distributed Association Rule Mining (DARM) is the task for generating the globally strong association
rules from the global frequent itemsets in a distributed environment. The intelligent agent based model, to
address scalable mining over large scale distributed data, is a popular approach to constructing
Distributed Data Mining (DDM) systems and is characterized by a variety of agents coordinating and
communicating with each other to perform the various tasks of the data mining process. This study
performs the comparative analysis of the existing agent based frameworks for mining the association rules
from the distributed data sources.
A CLOUD BASED ARCHITECTURE FOR WORKING ON BIG DATA WITH WORKFLOW MANAGEMENTIJwest
In real environment there is a collection of many noisy and vague data, called Big Data. On the other hand,
to work on the data middleware have been developed and is now very widely used. The challenge of
working on Big Data is its processing and management. Here, integrated management system is required
to provide a solution for integrating data from multiple sensors and maximize the target success. This is in
situation that the system has constant time constrains for processing, and real-time decision-making
processes. A reliable data fusion model must meet this requirement and steadily let the user monitor data
stream. With widespread using of workflow interfaces, this requirement can be addressed. But, the work
with Big Data is also challenging. We provide a multi-agent cloud-based architecture for a higher vision to
solve this problem. This architecture provides the ability to Big Data Fusion using a workflow management
interface. The proposed system is capable of self-repair in the presence of risks and its risk is low.
The document discusses security issues in distributed database systems. It begins by defining distributed databases and their architecture. It then discusses three main security aspects: access control, authentication, and encryption. The document also discusses distributed database system design considerations like concurrency control and data fragmentation. Emerging security tools for distributed databases mentioned include data warehousing, data mining, collaborative computing, distributed object systems, and web applications. Maintaining security when building and querying data warehouses from multiple sources is highlighted as a key challenge.
This document discusses stream computing and its applications. Stream computing involves processing continuous streams of data in real-time, as opposed to batch processing of large static datasets. It describes key aspects of stream computing like filtering data streams and producing output streams. It also provides examples of applications that can benefit from stream computing, such as efficient traffic management, real-time surveillance, critical care monitoring in hospitals, and intrusion detection systems. The document concludes that stream computing platforms like System S are well-suited for scalable and adaptive real-time data processing.
SECURE & FAULT TOLERANCE HANDOFF IN VANET USING SPECIAL MOBILE AGENTcscpconf
This document proposes a fault tolerant mobile agent based information retrieval system for handoffs in vehicular ad hoc networks (VANETs). Special mobile agents are dispatched from client vehicles to neighboring vehicles to retrieve information needed for seamless handoffs as the client vehicle moves. The system uses checkpointing and replication to increase reliability, storing copies of data at each visited node. A timestamp and threshold ensure data validity and prevent excessive resource usage. Authentication with digital signatures secures communication between agents and nodes. The proposed approach aims to provide reliable information retrieval to support fault tolerant handoffs in VANETs.
Secure & fault tolerance handoff in vanet using special mobile agentcsandit
Vehicular Traffic poses an emerging issue nowadays. The critical factors for the data
communication are speed and time tradeoffs. For data communication, gathering and retrieving
information many cost-effective and tested techniques are required in VANET. Client server
architectures being coercive are commonly used in spite of having drawbacks of fault and time
in-effectiveness. This paper elaborates a proposed method in VANET for fault tolerance
information retrieval based on theory of bandwidth and timestamp. Mobile Agents, with the
feature of autonomy, social ability, learning, and most importantly mobility, regarded as an
appropriate technology to build applications for instance information retrieval system in mobile
computing environment.
A Survey of Agent Based Pre-Processing and Knowledge RetrievalIOSR Journals
Abstract: Information retrieval is the major task in present scenario as quantum of data is increasing with a
tremendous speed. So, to manage & mine knowledge for different users as per their interest, is the goal of every
organization whether it is related to grid computing, business intelligence, distributed databases or any other.
To achieve this goal of extracting quality information from large databases, software agents have proved to be
a strong pillar. Over the decades, researchers have implemented the concept of multi agents to get the process
of data mining done by focusing on its various steps. Among which data pre-processing is found to be the most
sensitive and crucial step as the quality of knowledge to be retrieved is totally dependent on the quality of raw
data. Many methods or tools are available to pre-process the data in an automated fashion using intelligent
(self learning) mobile agents effectively in distributed as well as centralized databases but various quality
factors are still to get attention to improve the retrieved knowledge quality. This article will provide a review of
the integration of these two emerging fields of software agents and knowledge retrieval process with the focus
on data pre-processing step.
Keywords: Data Mining, Multi Agents, Mobile Agents, Preprocessing, Software Agents
Grid computing is the sharing of computer resources from multiple administrative domains to achieve common goals. It allows for independent, inexpensive access to high-end computational capabilities. Grid computing federates resources like computers, data, software and other devices. It provides a single login for users to access distributed resources for tasks like drug discovery, climate modeling and other data-intensive applications. Current grids are used for distributed supercomputing, high-throughput computing, on-demand computing and other methods. Grids benefit scientists, engineers and other users who need to solve large problems or collaborate globally.
Survey on Synchronizing File Operations Along with Storage Scalable MechanismIRJET Journal
The document summarizes research on efficient file operations and storage scalability mechanisms. It discusses how data is divided into chunks and distributed to nodes for transmission in peer-to-peer networks. The proposed system aims to provide efficient load balancing, eliminate single points of failure, and ensure synchronization and security during data transmission. It uses synchronization algorithms and a hybrid distribution model combining features of peer-to-peer and client-server networks. The system is designed to securely handle insertions, deletions, splits, and concatenations of file chunks in a distributed storage system.
A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing IJECEIAES
Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...IJERA Editor
Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and imagestorage and processing or map-reduce type) still remain off bounds since they require large computation and storage capabilities.Recent research has attempted to address these issues by employing remote servers, such as clouds and peer mobile devices.For mobile devices deployed in dynamic networks (i.e., with frequent topology changes because of node failure/unavailability andmobility as in a mobile cloud), however, challenges of reliability and energy efficiency remain largely unaddressed. To the best of ourknowledge, we are the first to address these challenges in an integrated manner for both data storage and processing in mobilecloud, an approach we call k-out-of-n computing. In our solution, mobile devices successfully retrieve or process data, in the mostenergy-efficient way, as long as k out of n remote servers are accessible. Through a real system implementation we prove the feasibilityof our approach. Extensive simulations demonstrate the fault tolerance and energy efficiency performance of our framework in largerscale networks.
Similar to SEARCHING DISTRIBUTED DATA WITH MULTI AGENT SYSTEM (20)
Since so many years a problem occurs in KSB Pump Va mbori for casting process i.e. cracks occurs in the castings & it is repeated one. Therefore the compan y has given opportunity to me to solve this problem . In case of steel casting there are mainly cracks & also blo w holes induced due to the casting procedure. There are many factors for the casting defects .The factor is unev en material feeding in casting & also due to the mo uld material & also the core material. These cracks finally brea k directly the component of the casting i.e. in cas e of pump the casting component is like Impeller,Volute casing & casing cover. At the time of feeding of steel material in to the casting the material is in liquid us form i.e. it i s hot material & this material is feeding into casting at the time o f feeding it develop different region of heat. At o ne side the temp is high &at other side the temp is low this also pr oduce cracks. To simulate that casting we use the M AGMA SOFTWARE for simulation & validate it using NDT.
A COMPARATIVE STUDY OF DESIGN OF SIMPLE SPUR GEAR TRAIN AND HELICAL GEAR TRAI...ijiert bestjournal
The document describes the design of a simple spur gear train and helical gear train with an idler gear using the AGMA (American Gear Manufacturers Association) standard method. Key steps of the design process include selecting input parameters, creating a preliminary drawing, selecting materials, and performing theoretical calculations to determine dimensions and check for bending and contact stresses based on AGMA equations. A comparative study is carried out to select the optimal gear train design that meets the strength requirements for the given input parameters and load conditions.
COMPARATIVE ANALYSIS OF CONVENTIONAL LEAF SPRING AND COMPOSITE LEAFijiert bestjournal
A leaf spring is a simple form of spring,commonly used for the suspension in wheeled vehicles. It is also one of the oldest forms of spring. Sometimes referred to as a semielliptical l eaf spring (SELS) it takes the form of a slender ar c-shaped length of spring steel of rectangular cross section. The centre of the arc p rovides location for the axle,while tie holes are provided at either end for attaching to the vehicle body. In the present work,a seven-leaf steel spring use d in passenger cars is replaced with a composite mu lti leaf spring made of glass/epoxy composites. The dimensions sand the num ber of leaves for both steel leaf spring and compos ite leaf springs are considered to be the same. The primary objective is to compare their load carrying capacity,stiffness and weight savings of composite leaf spring. Finally,fatigue life of steel and com posite leaf spring is also predicted using life dat a
Brimmed diffuser is collection�acceleration device which shrouds a wind turbine.For a given turbine di ameter,the power augmentation can be achieved by brimmed diffuser,p opularly known as wind lens. The present numerical investigation deals with the effect of low pressure region created by wind l ens and hence to analyze the strong vortices formed by a brim attached to the shroud diffuser at exit. Also in this analysis,a c omparative numerical prediction of mass flow rates through the wind turbine has been carried out with various types of wind lens wh ich in turn helps to optimize the torque augmentati on. It has been numerically proved that there is significant increase in the wa ke formation & vortex strength when brimming effect is added to a diffuser
FINITE ELEMENT ANALYSIS OF CONNECTING ROD OF MG-ALLOY ijiert bestjournal
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Robotic welding requires specialized fixtures to ac curately hold the work piece during the welding operation. Despite the large variety of welding fix tures available today the focus has shifted in maki ng the welding arms more versatile,not the fixture. T he new fixture design reduces cycle time and operat or labor while increasing functionality;and allows co mplex welding operations to be completed on simple two axis welding arms
ADVANCED TRANSIENT THERMAL AND STRUCTURAL ANALYSIS OF DISC BRAKE BY USING ANS...ijiert bestjournal
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REVIEW ON MECHANICAL PROPERTIES OF NON-ASBESTOS COMPOSITE MATERIAL USED IN BR...ijiert bestjournal
Metallic matrix composites are combinations of two or more different metals inter metallic compounds or second phases in which dispersed phases are embe dded within the metallic matrix. They are produced by controlling the morphologies of the constituents to achieve optimum combination of properties. Properties of the composites depend on the properti es of the constituent phases,their relative amount,and dispersed phase geometry including particle siz e,shape and orientation in the matrix. In this pap er,The mechanical properties,behaviour and micro stru ctural evolution of aluminium metal matrix metallic composites fabricated under various process conditi ons were investigated to understand their process- structure�property relations by optimization proces s. Addition of silicon carbide to aluminum has show n an increase in its mechanical properties.
PERFORMANCE EVALUATION OF TRIBOLOGICAL PROPERTIES OF COTTON SEED OIL FOR MULT...ijiert bestjournal
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Magnetic abrasive finishing is a machining process where the tooling allowance is remove by media wi th both magnetic and abrasive properties,with a magnetic f ield acting as a binder of a grain. Such machining falls into the category of erosion by abrasive suspension and lend itself to the finishing of any type of surface . The possibility of finishing complex surfaces is a spec ial benefit of this machining. Magnetic abrasive fi nishing process is most suitable for obtaining quality fini sh on metallic and non-metallic surfaces. Magnetic abrasive finishing used for complicated product finishing & Roughness and tolerance band achieved that is diffi cult using conventional machine process. The product dimension al requirement easily possible with taking trial wi th MAF parameters.
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The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
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The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
SEARCHING DISTRIBUTED DATA WITH MULTI AGENT SYSTEM
1. Novateur Publication’s
International Journal of Innovation in Engineering, Research and Technology [IJIERT]
ICITDCEME’15 Conference Proceedings
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SEARCHING DISTRIBUTED DATA WITH MULTI AGENT SYSTEM
Vishal D. Lipte
Asst. Prof.SRES COE
Kopargaon,Maharashtra vishallipte@yahoo.co.in
Sandip A. Shivarkar
Asst. Prof. SRES COE
Kopargaon,Maharashtra sandip.shivarakar@gmail.com
Ajit A. Muzumdar
Asst. Prof SRES COE
Kopargaon,Maharashtra ajit_muzumdar@yahoo.com
Pravinkumar B. Landge
Asst. Prof. SRES COE
Kopargaon, Maharashtra pravinkumar.landge@gmail.com
ABSTRACT
In distributed systems, to search out information is costly task because they have to be compel led to transfer
information from node containing information to the node wherever query is generated, this will l consume latency,
network traffic etc.For reducing these parameters mobile agents are accustomed fetch information from nodes
wherever information resides. Alongside mobile agents directory containing information concerning database kept
on completely different nodes is employed to focus retrieval method solely to those nodes that are containing
answers to the query. 3 kinds of agents area unit accustomed fetch data specifically ly coordinator, search and local
agent.
KEYWORDS
Mobile agents, data retrieval, distributed data, Natural Language Processing.
INTRODUCTION
Traditional Client-Server architecture for distributed data retrieval do not offer much flexibility. There are several
steps in client server architecture ; set up a connection between client and server, sending request to database servers
and receive results from all database servers. But client has to send requests to each database server containing
distributed data. With increase in no. of servers no. of requests increase which increase bandwidth consumption.
Also heterogeneity of databases affect retrieval. Another approach is to transfer database to a node where request is
generated. But this approach also consumes huge amount of bandwidth. Also unnecessary data is transferred over
the network. The challenge is retrieving data from distributed databases, usually
Heterogeneous, with minimum consumption of network bandwidth. In mobile computing atmosphere, users will
access
information freelance of their location . But accessing this info shouldn’t prohibit quality of application. From
information management purpose of reading data, mobile users will handle solely fraction of information since
mobile devices area unit having restricted resources. The invention of low price and nonetheless moveable mobile
devices has enabled mobile users to figure from anyplace, at anytime. Along with growing technology scores of
folks area unit exploitation these devices and through that these area unit accessing distributed information residing
on distributed nodes. So there is ought to develop a system that ought to give required information to those mobile
devices with a minimum use of resources. These days mobile devices area unit developed to use web. These devices
area unit GPRS enabled that provide the simplest way to attach alternative devices
to transfer information or to request information. These devices are often wont to access distributed access through
GPRS therefore on preserve limited resources of those mobile devices. The devices area unit preserved by
exploitation mobile agents. By this technology all the computations are performed at the nodes themselves.
Mobile agent technology is used as a useful and efficient tool for searching and retrieving data in distributed
environment where the data is stored at a various nodes of the system. A mobile agent is an executing program that
2. Novateur Publication’s
International Journal of Innovation in Engineering, Research and Technology [IJIERT]
ICITDCEME’15 Conference Proceedings
ISSN No - 2394-3696
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can migrate during execution from machine to machine in a heterogeneous network.[18] . The advantage of mobile
agent is that it searches for info rather than users. Mobile agents carry code of execution or query to be applied on
information. They run the query on the information and returns to the node that who had created that agent. This
agent carries answer to the query .It is an economical alternative to transfer information and additionally it reduces
execution time. Therefore by exploitation of mobile agents we are able to cut back bandwidth needed for operation.
during this paper we’ve got urged a query retrieval approach by exploitation directories and multi agent system. The
Distributed Information Retrieval task deals with the collection of information from multiple and usually
heterogeneous information sources that exist in a distributed environment. One way to address these issues is to use
information agents. These Distributed Information Retrieval agents should be able to:
• Ready to serve a request for information from user ,
• Convert the request into a code that can be understood by resources,
• determine the knowledge sources that contain information relevant to the request,
• send the request to those sources,
• collect the corresponding results, and methods for returning results.
The remaining part of the paper is organized as follows: Section 2 reviews recent related works. Section 3 introduces
to the proposed data retrieval system. Section 4 discusses about expected results from the system. Finally, we
conclude the paper in Section 5.
RELATED WORK
With development of distributed applications need for retrieving data from scattered data arised.Many approaches
are made for retrieval of distributed data. In [1] the process involving distributed data access from a mobile device,
using mobile agents is described. To answer any query in the distributed environment the search is conducted to
answer the query only in the databases, which are present in the systems. This approach is useful in situations where
required data is scattered on most of the nodes. But in case where data is concentrated to very few nodes. Because
unnecessary search agents are sent to the nodes where required data is not present. In [3] the planning issues and
implementation details of an entire MAP(Multi Agent Platform) model addresses numerous problems like security
mechanisms, fault tolerance, methods for building network-aware mobile agents etc.The MAP system has been has
been implemented in Java and optimized for network and systems management applications. In [4],a system
supported mobile crawlers which uses mobile agent is planned. The approach implements mobile agents to crawl the
pages .Aglet platform [19] is used for implementation of mobile agents. These mobile crawlers or mobile agents that
crawl the pages determine the changed pages at the remote web site while not downloading them. But it downloads
those pages solely, which have truly been changed since last crawl. therefore it‘ll cut back the net traffic and load on
the remote web site. Distributed info framework supported mobile agent is planned in [5],which represents agent
distribution and also the advancement of every agent .The distributed info system is meant and enforced by the
employment of agent technology in developing information gathering management application platform of Down
Hole Operation Company. Under the IBM Aglet development platform the distributed question system is
accomplished supported Mobile Agents, the running results of system shows high pertinence and capability of the
model. In [6], Papastavrou et. Al. have suggested the framework for accessing Web-based distributed data For that
they have used mobile agents. The suggested system also supports for light-weight, portable, and autonomous
clients. Also it is able to operate on slower networks. The implementation of the mobile agents is done by using the
aglet platform. The system performs well in wireless and dial-up environments and also for average size
transactions; As compared to a client-server platform the proposed system provides a performance improvement of
roughly multiples of ten. For the fixed network, the gains are near about 20% and 30%, respectively. In [7] an
experimental mobile-agent system searching technical reports distributed across multiple machines is proposed. The
application was implemented on the DA gents system[20].It uses statistical information retrieval system called
Smart. Smart uses the vector-space model to measure the textual similarity between documents and is wrapped
inside a stationary agent on each node. Kawamura et al. [8] have proposed three types of agents to process accessing
of data from distributed databases namely direct access, stationery agent access, and mobile agent access. Also,
Ismail et al. [9] have analyzed the comparisons between a Java applet-based approach and a mobile agent
technology in accessing distributed databases from the Web.It presents a performance evaluation of the mobile agent
paradigm in comparison to the client/server paradigm. It is implemented on top of the Java environment, using
respectively RMI, the Aglets mobile agents platform and a mobile agents prototype.Menczer [10] designed and
implemented My spiders, a multi-agent system for information discovery in the Internet.Myspiders is a threaded
multivalent system designed for information discovery. It uses an adaptive population of intelligent agents mining
the Web online at query time. The usage of mobile agents for information filtering is studied by Thiemann et
3. Novateur Publication’s
International Journal of Innovation in Engineering, Research and Technology [IJIERT]
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ISSN No - 2394-3696
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al.[11].It implements mobile agents for filtering distributed information resources and coordinating mobile agent
dissemination that minimizes communication costs. Nguyen et.al. [12] has developed an agent system that helps
information retrieval from the Internet. Their system differs from My spiders because it uses consensus methods for
resolving differences in response sets i.e. answers from various nodes and it uses multiple agents like managing
agents and search agents for the retrieval task. Tool used for implementation of mobile agents is JADE(Java Agent
Development Framework)[13].JADE is a Framework which is implemented in Java language. It works as a middle-
ware for developing mobile agents. JADE platform follows all guidelines suggested by FIPA(Foundation for
Intelligent Physical Agents)[14] specifications. JADE also allows debugging and deployment of mobile agents.FIPA
is an IEEE Computer Society standards organization. It works for agent technology and the interoperability with
other technologies. In
JADE, this platform can be distributed across nodes of the distributed system. Also JADE facilitates mobility of
agents from one node to another one when it is necessary. JADE is used as add-on to JAVA. When it is used with
netbeans it should be added to libraries of our project in order to use it.
PROPOSED SYSTEM
3.1 System Architecture
Figure 1: Proposed system
The figure shows proposed system for distributed data retrieval. The architecture shows a multi agent system for
retrieving data from distributed databases. We have followed this approach in developing our homogeneous retrieval
system for the Database Servers. The overall agent architecture is as follows.
The inter-agent communication is based on standard Query Manipulation Language (QML). The National Language
Processing Convert chunks of text from the base station into more formal representations such as first-order logic
structures that are easier for computer programs to understand. Our system supports a collection of Database
Domains. The concept of database domain is used to describe a logical entity. This entity contains a set of data or
databases. Actually it is a logical clustering of distributed database sites. This will make searching easier. Each such
site contains search and local agent. The search agent periodically scans through all the database sources,
represented by query. These can be domain name or table name of the of various database groups, for example. The
search agent traverses through all the local agent (e.g. database belonging to Company or Employee group). It
classifies each such domain as referred by query and extracts results from each domain For example, it will Search
all the Employee Information from Employee Domain like Name, Designation, Gender and sends the result back to
NLP.The NLP Convert information from computer databases into readable human language. It uses Natural
Language Generation (NLG) for generating natural language from a machine representation system such as a
knowledge base or a logical form. The converted output can be viewed from mobile unit.
4. Novateur Publication’s
International Journal of Innovation in Engineering, Research and Technology [IJIERT]
ICITDCEME’15 Conference Proceedings
ISSN No - 2394-3696
4 | P a g e
Finally, these important features are passed to the co-coordinator agent. The co-coordinator agent handles the query
answering process. It acts as an information gateway to the records sources it manages. In contrast to the above, the
user agent is the one that the end user interacts with. It formulates the user’s query, entered via a application,
translates into an appropriate query message format and displays the answers. The user agent makes use of the
services of a corresponding Co-coordinator agent. This agent accepts requests from user agents. It has the role to
identify which database the user is actually referring. Concluding with the overall agent architecture, there are three
agents: the co-coordinator agent, the search agent and local agent.
3.2. Mathematical Model
Problem description
Let s be MAS which will process a query such that
s = {M,B,C,A,L,D}
where
M is set of mobile phones.
B is set of base stations
C is set of coordinator agents
A is set of search agents
L is set of local agents
D is set of database servers
A = {a0, a1, a2, a3}
M = {m0,m1, .........,mn}
B = b0
C = c0
L = {l0, l1, l2, l3}
D = {d0, d1, d2, d3}
note:-Since only four distributed databases are considered for implementation so only four elements are considered.
DFA theory
Definition:
A deterministic finite automaton (DFA)
1. A finite set of states (often denoted Q)
2. A finite set S of symbols (alphabet)
3. A transition function that takes as argument a state
and symbol and returns a state (often denoted d) The transition function d is a function in d: Q × S = Q
4. A start state often denoted s0
5. A set of final or accepting states (often denoted F)
So a DFA is mathematically represented as a 5-tuple
(Q, S, d, s0, F)
3.3. Dynamic Programming and Serialization
Proposed system can be divided into two main parts; mobile and stationary. Mobile part includes all mobile agents
used in the system. In proposed system search agents are mobile, travelling across network .These agents carry
query which is to be fired on database .Stationary part includes local and coordinator agents .Local agents are
present at nodes where database resides. These agents accept query from search agent, fire it on the database, collect
results and forward these results to search agent. Local agents are well aware of DBMS which is maintaining
distributed database. Coordinator agent coordinates retrieval process. Coordinator agent carry out retrieval process
by creating search agents, sending them to appropriate nodes and collecting results from those search agents.
3.4. Data independence and Data Flow architecture
As shown in figures, query for data is accepted through mobile device. This query is accepted through simple
GUI.The communication between mobile and base station (coordinator machine) is done through GPRS.At base
station coordinator agent is present which accepts the Natural language query and converts it to SQL query by using
NLP.Then coordinator agent identifies node(s) which are having answers to given query by using a directory .This
directory is maintained at base station which contains information about data present in distributed databases
.Suppose N no. of nodes are containing answers to given query then coordinator agent creates N no. of search agents
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.Each search agent contains query .Search agents travel through network and reaches to their respective nodes
.These nodes are containing database servers which are containing distributed data .Also local agents are present at
these nodes .Search agents forward query to these local agents .As local agents are having information about how to
retrieve data from their databases they do so after accepting a query from search agent. Local agent searches for
answers to given query, retrieves them and forwards them to search agent. Search agents returns back to its
originator i.e. at base station. Same data is accessed by mobile user through his mobile phone as a web page.
Figure 2: Data flow diagram Level 0
3.5. Multiplexer Logic
The GUI which is provided to mobile users can be accessed from many mobile users simultaneously because it is
developed as java server pages(jsp).So multiple users can retrieve data simultaneously independent of each other.For
each request separate set of agents are created.These agents work independent of each other,find results independent
of each other.Also inputs are provided independent of each other.To serve each request a thread of coordinator is
created.Each coordinator thread is having its own set of search and local agents.All work without interfering others.
Different jar files are added to library of project so they can be used by all modules of the project.e.g.-fileupload is
used to for all file operations.
Following are the states from which system transits as shown in figure.
• Base station(S0):- This is a state of the system when mobile user is sending request or getting results.This is initial
and final state of the system.
• Coordinator agent(S1):- The system will enter to this state when coordinator agent is working i.e. either creating
search agents or collecting results from search agents.
• Natural Language Processing(S2):- The system will enter in this state when it will convert English query in SQL
command by using single token matching.
• Search Agent(S3):- SQL query is given to search agent,it will travel to node having distributed
database,then,system will be in this state. Also when local agent will provide results to search agent then also the
system will enter in this state.
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Figure 3: Data flow diagram Level 1
3.6 Turing Machine
Figure 4:State diagram
• Local Agent(S4):- When search agent forwards the query to local agent.Local agent will fire that query on its
database.The system will be in this state until it retrieves all records.After collecting all records the system will leave
this state when it will forward these results to search agent.
RESULTS AND DISCUSSION
In our project we have implemented NLP approach by using this only specified mobile agents will be activated
where in base system or existing system all agents were getting activated for each and every query.So the
performance ratio was 1:N where N represents no. of agents.Ratio is no. of queries to no. of activated agents for
query.But in proposed system this ratio will be 1:1 so performance is increased by factor (N-1).Because we are
sending search agent to only those nodes whose domain matches with the query.In other words query is fired to only
those databases which contain answer to query .This system will work best in the databases where we are well
aware of what type of data is stored in distributed dtabases.
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In future this system can be improved by working about security of agents,implementing the same concept for
homogeneous type of distributed database.Also to work on maintenance of directory about data stored in databases
which specifies domain of the databases.
CONCLUSION
In this way we can improve system performance by using mobile agent system and Natural Language
Processing.NLP approach will improve system efficiency ,reduce system overhead ,data congestion and network
overhead.
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