Pub Date : 2012-12-01DOI: 10.1109/ICOAC.2012.6416804
A. Meenakshi, V. Mohan
Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Clustering is a data mining technique, which is used to place data elements into related groups without advance knowledge of the group definitions. Here, we propose an incremental clustering technique for managing knowledge in edaphology, a study concerned with the influence of soils on living things, particularly plants. The soil information along with the appropriate plants to be cultivated on it for better yield, collected by edaphologists, are utilized in the proposed system. Initially, an incremental DBSCAN algorithm is applied to a dynamic database where, the data may be frequently updated. Then, the data available in the soil database is grouped into clusters and every new element is added into it without the need of rerunning process. Finally, we have performed the plant prediction using regression model. The experimentation is carried out in soil database to analyze the performance of the proposed system in plant prediction.
{"title":"Localized matching model for plant prediction using incremental clustering","authors":"A. Meenakshi, V. Mohan","doi":"10.1109/ICOAC.2012.6416804","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416804","url":null,"abstract":"Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Clustering is a data mining technique, which is used to place data elements into related groups without advance knowledge of the group definitions. Here, we propose an incremental clustering technique for managing knowledge in edaphology, a study concerned with the influence of soils on living things, particularly plants. The soil information along with the appropriate plants to be cultivated on it for better yield, collected by edaphologists, are utilized in the proposed system. Initially, an incremental DBSCAN algorithm is applied to a dynamic database where, the data may be frequently updated. Then, the data available in the soil database is grouped into clusters and every new element is added into it without the need of rerunning process. Finally, we have performed the plant prediction using regression model. The experimentation is carried out in soil database to analyze the performance of the proposed system in plant prediction.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130730880","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416849
S. GandhimathiaUsha, S. Vasuki, G. Ariputhiran
Remote sensing data provides much essential and critical information for monitoring many applications such as change detection, image fusion and land cover classification. Remotely sensed images are degraded due to the atmospheric effects. The atmospheric correction is one of the important pre processing steps to extract full spectral information from the remotely sensed images. In this paper, transform domain approaches are presented for the removal of atmospheric influences. Soft thresholding technique is adopted in wavelet transform method and gaussian high pass filter is used in homomorphic filtering. The results are tested on Landsat image consisting of 7 multispectral bands and their performance is evaluated using visual and statistical measures. The comparative analysis is done based on statistical parameters such as mean square error (MSE), peak signal to noise ratio (PSNR). Our result shows that wavelet transform is better for the removal of atmospheric effects than homomorphic filtering.
{"title":"Atmospheric correction of remotely sensed multispectral satellite images in transform domain","authors":"S. GandhimathiaUsha, S. Vasuki, G. Ariputhiran","doi":"10.1109/ICOAC.2012.6416849","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416849","url":null,"abstract":"Remote sensing data provides much essential and critical information for monitoring many applications such as change detection, image fusion and land cover classification. Remotely sensed images are degraded due to the atmospheric effects. The atmospheric correction is one of the important pre processing steps to extract full spectral information from the remotely sensed images. In this paper, transform domain approaches are presented for the removal of atmospheric influences. Soft thresholding technique is adopted in wavelet transform method and gaussian high pass filter is used in homomorphic filtering. The results are tested on Landsat image consisting of 7 multispectral bands and their performance is evaluated using visual and statistical measures. The comparative analysis is done based on statistical parameters such as mean square error (MSE), peak signal to noise ratio (PSNR). Our result shows that wavelet transform is better for the removal of atmospheric effects than homomorphic filtering.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413029","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416798
N. Kumar
Mobile devices are becoming very popular now-a-days and along with the misuse of these devices is also increasing. These devices can be lost or can be snatched for misuses then it becomes very important to track these devices as soon as possible. For this purpose, we have contact police till now, but this paper describes a system using which you can locate the mobile device using another mobile device by even sitting at your home. The system only requires the inbuilt GPS and GPRS in the device whose location is to be tracked. “Where are you? - A Location Awareness System” is a project that helps you to locate a friend or a known person without informing that person. The system is primarily designed to aware the people about locations and to help the authorities in tracking the location of a mobile device. The system can also be used to locate a friend.
{"title":"Where are you? A location awareness system","authors":"N. Kumar","doi":"10.1109/ICOAC.2012.6416798","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416798","url":null,"abstract":"Mobile devices are becoming very popular now-a-days and along with the misuse of these devices is also increasing. These devices can be lost or can be snatched for misuses then it becomes very important to track these devices as soon as possible. For this purpose, we have contact police till now, but this paper describes a system using which you can locate the mobile device using another mobile device by even sitting at your home. The system only requires the inbuilt GPS and GPRS in the device whose location is to be tracked. “Where are you? - A Location Awareness System” is a project that helps you to locate a friend or a known person without informing that person. The system is primarily designed to aware the people about locations and to help the authorities in tracking the location of a mobile device. The system can also be used to locate a friend.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114319893","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416862
V. Chitra, M. Sumalatha
The QoS factors such as accuracy and time delay plays a major role in time critical applications. The proposed SVM-instance based algorithm improves the accuracy and reduces the time delay for the recognition of emergency vehicle sound. In this approach, the time delay is reduced by identifying the support vectors which are the data points near the margin of hyper plane and the accuracy is increased by increasing the margin between the classes. The MFCC which is derived from frequency and intensity is used for accurate sound recognition. Thus time delay was reduced and accuracy was improved in recognition of emergency vehicle sound.
{"title":"SVM-instance based approach to improve QoS parameters for time critical applications in WSN","authors":"V. Chitra, M. Sumalatha","doi":"10.1109/ICOAC.2012.6416862","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416862","url":null,"abstract":"The QoS factors such as accuracy and time delay plays a major role in time critical applications. The proposed SVM-instance based algorithm improves the accuracy and reduces the time delay for the recognition of emergency vehicle sound. In this approach, the time delay is reduced by identifying the support vectors which are the data points near the margin of hyper plane and the accuracy is increased by increasing the margin between the classes. The MFCC which is derived from frequency and intensity is used for accurate sound recognition. Thus time delay was reduced and accuracy was improved in recognition of emergency vehicle sound.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114612822","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416861
J. Julie, J. B. Babujee
The binary operations like Cartesian products, normal and lexicographic products on graphs have played a vital role in graph construction. An insight of automata as directed graphs motivated us to study some of these products on these abstract machines. In this paper we operate normal and lexicographic products over automata and analyze the language recognized by these resultant automata. It is observed that the Generalized Parikh vectors of the language of the resultant automata are a family of parallel lines in the two dimensional plane. The lexicographic product of path automata appears as a neural network after a few modifications using reactive automata.
{"title":"Automata resulting from graph operations","authors":"J. Julie, J. B. Babujee","doi":"10.1109/ICOAC.2012.6416861","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416861","url":null,"abstract":"The binary operations like Cartesian products, normal and lexicographic products on graphs have played a vital role in graph construction. An insight of automata as directed graphs motivated us to study some of these products on these abstract machines. In this paper we operate normal and lexicographic products over automata and analyze the language recognized by these resultant automata. It is observed that the Generalized Parikh vectors of the language of the resultant automata are a family of parallel lines in the two dimensional plane. The lexicographic product of path automata appears as a neural network after a few modifications using reactive automata.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129080311","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416806
G. Thomas, J. Veerappan
Delay Tolerant Mobile Network is an approach of computer networks which lack of continuous network connectivity due to its intermittent characteristics of network partitioning. The issues of DTMN is how to maintain, update, and stabilize the mobile nodes present and perform better routing of packets without any packet loss. Our paper addresses this issue of DTMN by defining the basic idea of grouping mobile nodes with similar clustering mobility pattern into a clustering group before routing a packet with high end to end and packet delivery ratio. The initial process starts by identifying similar mobility pattern defined with eminent pair-wise contact probabilities with different mobile nodes with FASO-ECP based EWMA algorithm, if a node wants to be a member of a cluster it should have higher contact probability value than the preset threshold value. Every time the contact probability is updated to have better clustering pattern. Thus after the cluster pattern identification, an adaptive method with Cluster selection and gateway formation being carried out to define the route from source to destination. And Hello packets being added to check for node existence status. Finally the Routing of packets will be done through a best possible route to reach the destination with a better packet delivery rate.
{"title":"FASO-ECP: Fast adaptive and self organized — Enhanced clustering protocol based routing for DTMN","authors":"G. Thomas, J. Veerappan","doi":"10.1109/ICOAC.2012.6416806","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416806","url":null,"abstract":"Delay Tolerant Mobile Network is an approach of computer networks which lack of continuous network connectivity due to its intermittent characteristics of network partitioning. The issues of DTMN is how to maintain, update, and stabilize the mobile nodes present and perform better routing of packets without any packet loss. Our paper addresses this issue of DTMN by defining the basic idea of grouping mobile nodes with similar clustering mobility pattern into a clustering group before routing a packet with high end to end and packet delivery ratio. The initial process starts by identifying similar mobility pattern defined with eminent pair-wise contact probabilities with different mobile nodes with FASO-ECP based EWMA algorithm, if a node wants to be a member of a cluster it should have higher contact probability value than the preset threshold value. Every time the contact probability is updated to have better clustering pattern. Thus after the cluster pattern identification, an adaptive method with Cluster selection and gateway formation being carried out to define the route from source to destination. And Hello packets being added to check for node existence status. Finally the Routing of packets will be done through a best possible route to reach the destination with a better packet delivery rate.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121103527","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416824
Muthukrishanan Umamehaswari, M. Ramprasath, S. Hariharan
A unbearable amount of textual information accessible in electronic form and need to deliver correct answer to user question is important task in Question Answering System (QAS). Question answer system is the form of information retrieval system which aims to deliver the exact answer to the user question rather than whole document. To answer this user need semantic based reformulation techniques can be used to retrieve the accurate answer from enormous number of document retrieved from the search engine. The goal is to generate the pattern from the web based on lexical semantic and syntactic constrain. These constrain should be defined in the question answering system to evaluate and rank the candidate answer. Here we used TREC-8, TREC-9, and TREC-10 collection as training set. Different types of question and corresponding answer can use from TREC collection. The proposed system retrieves the answer automatically from TREC collection. Word net can be used to help the semantic relation and syntactic tag between the questions and answer pair. Finally weight can be given to each candidate answer according to their length, the level of semantic similarity between question and answer pair and distance between the key word. The proposed QAS be different from other reformulation based Question answering system. The experiments on the TREC data set will show the better result which can be calculated with help of the precision and recall.
{"title":"Improved Question Answering System by semantic refomulation","authors":"Muthukrishanan Umamehaswari, M. Ramprasath, S. Hariharan","doi":"10.1109/ICOAC.2012.6416824","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416824","url":null,"abstract":"A unbearable amount of textual information accessible in electronic form and need to deliver correct answer to user question is important task in Question Answering System (QAS). Question answer system is the form of information retrieval system which aims to deliver the exact answer to the user question rather than whole document. To answer this user need semantic based reformulation techniques can be used to retrieve the accurate answer from enormous number of document retrieved from the search engine. The goal is to generate the pattern from the web based on lexical semantic and syntactic constrain. These constrain should be defined in the question answering system to evaluate and rank the candidate answer. Here we used TREC-8, TREC-9, and TREC-10 collection as training set. Different types of question and corresponding answer can use from TREC collection. The proposed system retrieves the answer automatically from TREC collection. Word net can be used to help the semantic relation and syntactic tag between the questions and answer pair. Finally weight can be given to each candidate answer according to their length, the level of semantic similarity between question and answer pair and distance between the key word. The proposed QAS be different from other reformulation based Question answering system. The experiments on the TREC data set will show the better result which can be calculated with help of the precision and recall.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125434359","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416821
T. Bharathi, S. Yuvaraj, D. Steffi, S. Perumal
Vehicle detection from aerial images is becoming an increasingly important research topic in surveillance, traffic monitoring and military applications. The system described in this paper focuses on automatic vehicle detection in the aerial images. This paper introduces a morphological neural network approach to extract vehicle targets from high resolution aerial images. In the approach the Morphological Shared-Pixels Neural Network (MSPN) is used to classify image pixels on roads into vehicle targets and non-vehicle targets, and a morphological preprocessing algorithm is developed to identify candidate vehicle pixels. The proposed method is going to compare with the existing system Dynamic Bayesian Network(DBN). It is going to be proven that the experimental results in MSPN have a good detection performance. The proposed system is going to record all pixel value of aerial images sequentially and filter out the batch or portion of the several vehicle edges. This method is quite better than existing algorithms in identifying the vehicles automatically in aerial images.
{"title":"Vehicle detection in aerial surveillance using morphological shared-pixels neural (MSPN) networks","authors":"T. Bharathi, S. Yuvaraj, D. Steffi, S. Perumal","doi":"10.1109/ICOAC.2012.6416821","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416821","url":null,"abstract":"Vehicle detection from aerial images is becoming an increasingly important research topic in surveillance, traffic monitoring and military applications. The system described in this paper focuses on automatic vehicle detection in the aerial images. This paper introduces a morphological neural network approach to extract vehicle targets from high resolution aerial images. In the approach the Morphological Shared-Pixels Neural Network (MSPN) is used to classify image pixels on roads into vehicle targets and non-vehicle targets, and a morphological preprocessing algorithm is developed to identify candidate vehicle pixels. The proposed method is going to compare with the existing system Dynamic Bayesian Network(DBN). It is going to be proven that the experimental results in MSPN have a good detection performance. The proposed system is going to record all pixel value of aerial images sequentially and filter out the batch or portion of the several vehicle edges. This method is quite better than existing algorithms in identifying the vehicles automatically in aerial images.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114480813","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416807
E. Janani, P. Ganeshkumar
The next generation of wireless sensor networks will monitor critical infrastructure, collect vital signs from patients, and disseminate medical and planning information during emergency responses. In contrast to earlier wireless sensor networks for which best-effort services were sufficient, such systems require predictable performance and high reliability. Failure to meet these requirements may have significant adverse effects. This paper aims at the development of an engineering methodology for predictable wireless sensor networks. A predictable wireless sensor network is a system for which it is possible to check that its requirements are met under reasonable assumptions regarding its workload and network properties. This project enables the development of predictable wireless sensor networks by providing developers with analytical tools to characterize and optimize the performance of sensor network systems. The intellectual merit of the paper includes: (i) Statistical methods for assessing the properties of wireless sensor networks and for provisioning resources to achieve robustness in spite of node failures or temporal variations; (ii) Novel transmission scheduling techniques that ensure a system meets its reliability and real-time requirements; (iii) A new schedulability analysis that bounds network capacity and message latencies under realistic interference models; and (iv) A wireless architecture that instantiates proposed transmission scheduling techniques and the schedulability analysis. In terms of broader impacts, this project will help us to make advancements in our national capability to develop performance-critical wireless systems. The simulation results shown have proved all the considerations made in the paper.
{"title":"Analytical techniques to characterize and optimize the performance of sensor network systems","authors":"E. Janani, P. Ganeshkumar","doi":"10.1109/ICOAC.2012.6416807","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416807","url":null,"abstract":"The next generation of wireless sensor networks will monitor critical infrastructure, collect vital signs from patients, and disseminate medical and planning information during emergency responses. In contrast to earlier wireless sensor networks for which best-effort services were sufficient, such systems require predictable performance and high reliability. Failure to meet these requirements may have significant adverse effects. This paper aims at the development of an engineering methodology for predictable wireless sensor networks. A predictable wireless sensor network is a system for which it is possible to check that its requirements are met under reasonable assumptions regarding its workload and network properties. This project enables the development of predictable wireless sensor networks by providing developers with analytical tools to characterize and optimize the performance of sensor network systems. The intellectual merit of the paper includes: (i) Statistical methods for assessing the properties of wireless sensor networks and for provisioning resources to achieve robustness in spite of node failures or temporal variations; (ii) Novel transmission scheduling techniques that ensure a system meets its reliability and real-time requirements; (iii) A new schedulability analysis that bounds network capacity and message latencies under realistic interference models; and (iv) A wireless architecture that instantiates proposed transmission scheduling techniques and the schedulability analysis. In terms of broader impacts, this project will help us to make advancements in our national capability to develop performance-critical wireless systems. The simulation results shown have proved all the considerations made in the paper.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115022187","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 : 2012-12-01DOI: 10.1109/ICOAC.2012.6416832
P. Reshma, S. Bharathi
Geographic routing has been widely hailed as the most promising approach to generally scalable wireless routing. It has been a big challenge to develop a routing protocol that can meet different application needs and optimize routing paths according to the topology changes in mobile ad hoc networks. However, there is a lack of holistic design for geographic routing to be more efficient and robust in a dynamic environment. Inaccurate local and destination position information can lead to inefficient geographic forwarding and even routing failure. The use of proactive fixed-interval beaconing to distribute local positions introduces high overhead when there is no traffic and cannot capture the topology changes under high mobility. In this work, two self-adaptive on-demand geographic routing schemes are proposed which build efficient paths based on the need of user applications and adapt to various scenarios to provide efficient and reliable routing. On-demand routing mechanism in both protocols reduces control overhead compared to the proactive schemes which are normally adopted in current geographic routing protocols. The route optimization scheme adapts the routing path according to both topology changes and actual data traffic requirements. The simulation studies demonstrate that the proposed routing protocols are more robust and outperform the existing geographic routing protocol and conventional on-demand routing protocols under various conditions including different mobilities, node densities and traffic loads. Specifically, the proposed protocols could reduce the packet delivery latency up to 80 percent as compared to GPSR at high mobility. Both routing protocols could achieve about 98 percent delivery ratios, avoid incurring unnecessary control overhead, have very low forwarding overhead and transmission delay in all test scenarios.
{"title":"Enhanced position updation in manet using self adaption","authors":"P. Reshma, S. Bharathi","doi":"10.1109/ICOAC.2012.6416832","DOIUrl":"https://doi.org/10.1109/ICOAC.2012.6416832","url":null,"abstract":"Geographic routing has been widely hailed as the most promising approach to generally scalable wireless routing. It has been a big challenge to develop a routing protocol that can meet different application needs and optimize routing paths according to the topology changes in mobile ad hoc networks. However, there is a lack of holistic design for geographic routing to be more efficient and robust in a dynamic environment. Inaccurate local and destination position information can lead to inefficient geographic forwarding and even routing failure. The use of proactive fixed-interval beaconing to distribute local positions introduces high overhead when there is no traffic and cannot capture the topology changes under high mobility. In this work, two self-adaptive on-demand geographic routing schemes are proposed which build efficient paths based on the need of user applications and adapt to various scenarios to provide efficient and reliable routing. On-demand routing mechanism in both protocols reduces control overhead compared to the proactive schemes which are normally adopted in current geographic routing protocols. The route optimization scheme adapts the routing path according to both topology changes and actual data traffic requirements. The simulation studies demonstrate that the proposed routing protocols are more robust and outperform the existing geographic routing protocol and conventional on-demand routing protocols under various conditions including different mobilities, node densities and traffic loads. Specifically, the proposed protocols could reduce the packet delivery latency up to 80 percent as compared to GPSR at high mobility. Both routing protocols could achieve about 98 percent delivery ratios, avoid incurring unnecessary control overhead, have very low forwarding overhead and transmission delay in all test scenarios.","PeriodicalId":286985,"journal":{"name":"2012 Fourth International Conference on Advanced Computing (ICoAC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122851979","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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