Pub Date : 2019-09-18DOI: 10.36548/jtcsst.2019.1.004
Neelaveni R Dr
The vehicular-adhocnetwork (adhocNet) termed to be prominent way of information transfer using vehicles plays a significant role in the development of the intelligent and safe transportation, to avoid the unwanted causalities. They provide a more comfortable way of driving and travelling; by providing the complete details entailed for the travel, utilizing the nearby vehicles and the roadside unit. But due to certain security issues arising in the information transmission by the conventional methods of the vehicular- adhocNet, the conventional method of vehicular- adhocNet seems to be inefficient. So the paper proposes a modified vehicular- adhocNet that replaces the cloud computing in the place of the road side unit to provide a enhance security in the information transmission, thus improving the performance of the vehicular- adhocNet as a whole. The performance evaluation of the proposed method using the NS-2 on terms of the improve security, delay and the throughput proves its significance.
{"title":"PERFORMANCE ENHANCEMENT AND SECURITY ASSISTANCE FOR VANET USING CLOUD COMPUTING","authors":"Neelaveni R Dr","doi":"10.36548/jtcsst.2019.1.004","DOIUrl":"https://doi.org/10.36548/jtcsst.2019.1.004","url":null,"abstract":"The vehicular-adhocnetwork (adhocNet) termed to be prominent way of information transfer using vehicles plays a significant role in the development of the intelligent and safe transportation, to avoid the unwanted causalities. They provide a more comfortable way of driving and travelling; by providing the complete details entailed for the travel, utilizing the nearby vehicles and the roadside unit. But due to certain security issues arising in the information transmission by the conventional methods of the vehicular- adhocNet, the conventional method of vehicular- adhocNet seems to be inefficient. So the paper proposes a modified vehicular- adhocNet that replaces the cloud computing in the place of the road side unit to provide a enhance security in the information transmission, thus improving the performance of the vehicular- adhocNet as a whole. The performance evaluation of the proposed method using the NS-2 on terms of the improve security, delay and the throughput proves its significance.","PeriodicalId":107574,"journal":{"name":"Journal of Trends in Computer Science and Smart Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132493998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-12DOI: 10.36548/jtcsst.2019.1.003
Duraipandian M Dr
The rapid advances in wireless communication technology has led to an extraordinary progress in the adhoc type of networking. The mobile adhoc networks being a subtype of the adhoc network almost poses the same characteristics of the adhoc network, presenting multiple challenges in framing a route for the transmission of the information from the source to the destination. So the paper proposes a routing method developed based on the reinforcement learning, exploiting the node information’s to establish a route that is short and stable. The proposed method scopes to minimize the energy consumption, transmission delay, and improve the delivery ratio of the packets, enhancing the throughput. The efficiency of the proposed method is determined by validating its performance in the network simulator-II, in terms of the energy consumption, delay in the transmission and the packet delivery ratio.
{"title":"PERFORMANCE EVALUATION OF ROUTING ALGORITHM FOR MANET BASED ON THE MACHINE LEARNING TECHNIQUES","authors":"Duraipandian M Dr","doi":"10.36548/jtcsst.2019.1.003","DOIUrl":"https://doi.org/10.36548/jtcsst.2019.1.003","url":null,"abstract":"The rapid advances in wireless communication technology has led to an extraordinary progress in the adhoc type of networking. The mobile adhoc networks being a subtype of the adhoc network almost poses the same characteristics of the adhoc network, presenting multiple challenges in framing a route for the transmission of the information from the source to the destination. So the paper proposes a routing method developed based on the reinforcement learning, exploiting the node information’s to establish a route that is short and stable. The proposed method scopes to minimize the energy consumption, transmission delay, and improve the delivery ratio of the packets, enhancing the throughput. The efficiency of the proposed method is determined by validating its performance in the network simulator-II, in terms of the energy consumption, delay in the transmission and the packet delivery ratio.","PeriodicalId":107574,"journal":{"name":"Journal of Trends in Computer Science and Smart Technology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117120319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-08DOI: 10.36548/jtcsst.2019.1.002
Iwin Thanakumar Joseph S Dr
The Intelligent computing system, described to be a collection of the connected device working in mutual understanding to attain a particular purpose, is an incorporation of artificial intelligence and the computational intelligence, and are employed in variety of applications. The paper presents the survey on the data mining algorithms and the techniques that could be employed with the intelligent computing system, presenting a basic conception of the data mining along with the prominent algorithms of the data mining and the classification of its techniques, further the survey concludes with the challenges included in the overview of the survey done along with the future enhancement in the research that analyses the data mining techniques in the intelligent computing applications.
{"title":"SURVEY OF DATA MINING ALGORITHM’S FOR INTELLIGENT COMPUTING SYSTEM","authors":"Iwin Thanakumar Joseph S Dr","doi":"10.36548/jtcsst.2019.1.002","DOIUrl":"https://doi.org/10.36548/jtcsst.2019.1.002","url":null,"abstract":"The Intelligent computing system, described to be a collection of the connected device working in mutual understanding to attain a particular purpose, is an incorporation of artificial intelligence and the computational intelligence, and are employed in variety of applications. The paper presents the survey on the data mining algorithms and the techniques that could be employed with the intelligent computing system, presenting a basic conception of the data mining along with the prominent algorithms of the data mining and the classification of its techniques, further the survey concludes with the challenges included in the overview of the survey done along with the future enhancement in the research that analyses the data mining techniques in the intelligent computing applications.","PeriodicalId":107574,"journal":{"name":"Journal of Trends in Computer Science and Smart Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127765559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-02DOI: 10.36548/jtcsst.2019.1.001
Bhalaji N Dr
The autonomous mobile nodes framing an instantaneous network, utilizing the nearby available device that volunteer in establishing network is coined as the fly wire network. These adhoc type of network framed simultaneously are prone to various vulnerabilities, developing alterations in the information’s or hacking of information’s or the blocking of services. These security threats causing losses in the information transmitted, makes it necessary for the trust evaluation of the nodes to identify the selfish nodes. So the paper proposes the block chain trust management of nodes to avoid the vulnerabilities in the transmission path, enhancing the performance of the network. The performance of the proposed method is validated in the network simulator –II to ensure its capability in terms of the quality of service and the security (defense).
{"title":"QOS AND DEFENSE ENHANCEMENT USING BLOCK CHAIN FOR FLY WIRELESS NETWORKS","authors":"Bhalaji N Dr","doi":"10.36548/jtcsst.2019.1.001","DOIUrl":"https://doi.org/10.36548/jtcsst.2019.1.001","url":null,"abstract":"The autonomous mobile nodes framing an instantaneous network, utilizing the nearby available device that volunteer in establishing network is coined as the fly wire network. These adhoc type of network framed simultaneously are prone to various vulnerabilities, developing alterations in the information’s or hacking of information’s or the blocking of services. These security threats causing losses in the information transmitted, makes it necessary for the trust evaluation of the nodes to identify the selfish nodes. So the paper proposes the block chain trust management of nodes to avoid the vulnerabilities in the transmission path, enhancing the performance of the network. The performance of the proposed method is validated in the network simulator –II to ensure its capability in terms of the quality of service and the security (defense).","PeriodicalId":107574,"journal":{"name":"Journal of Trends in Computer Science and Smart Technology","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115827818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-28DOI: 10.36548/jtcsst.2019.1.006
Pasumpon Pandian A Dr
The edge computing that is an efficient alternative of the cloud computing, for handling of the tasks that are time sensitive, has become has become very popular among a vast range of IOT based application especially in the industrial sides. The huge amount of information flow and the services requisition from the IOT has made the traditional cloud computing incompatible on the time of big data flow. So the paper proposes an enhanced edge model for the by incorporating the artificial intelligence along with the integration of caching to the edge for handling of the big data flow in the applications of the internet of things. The performance evaluation of the same in the network simulator 2 for enormous flow of task that are time sensitive , evinces that the proposed method has a minimized delay compared the traditional cloud computing models.
{"title":"ENHANCED EDGE MODEL FOR BIG DATA IN THE INTERNET OF\u0000THINGS BASED APPLICATIONS","authors":"Pasumpon Pandian A Dr","doi":"10.36548/jtcsst.2019.1.006","DOIUrl":"https://doi.org/10.36548/jtcsst.2019.1.006","url":null,"abstract":"The edge computing that is an efficient alternative of the cloud computing, for handling of the tasks that are time sensitive, has become has become very popular among a vast range of IOT based application especially in the industrial sides. The huge amount of information flow and the services requisition from the IOT has made the traditional cloud computing incompatible on the time of big data flow. So the paper proposes an enhanced edge model for the by incorporating the artificial intelligence along with the integration of caching to the edge for handling of the big data flow in the applications of the internet of things. The performance evaluation of the same in the network simulator 2 for enormous flow of task that are time sensitive , evinces that the proposed method has a minimized delay compared the traditional cloud computing models.","PeriodicalId":107574,"journal":{"name":"Journal of Trends in Computer Science and Smart Technology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128503983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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