2014 Sixth International Conference on Advanced Computing (ICoAC)最新文献

{"title":"Advance Map Reduce Task Scheduling algorithm using mobile cloud multimedia services architecture","authors":"S. Saravanan, V. Venkatachalam","doi":"10.1109/ICOAC.2014.7229736","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229736","url":null,"abstract":"There is a massive improvement in the computer technology which leads to infinite number of resources in all over the world stored in the computer. Computing devices have several uses and are necessary for businesses, scientists, governments, engineers. These have to generate data that comes from anywhere. Sensors gathering climate data, a person posting to a social media site, or a cell phone. Furthermore, the data itself may be too large to store on a single machine. In order to reduce the time it takes to process the data, and to have the storage space to store the data, we introduce a technique called map reduce programming model. In this programming method, it has to divide the workload among computers in a network. As a result, the performance of Map Reduce strongly depends on how evenly it distributes this workload among the computer. In Map Reduce, workload distribution depends on the algorithm that partitions the data. To avoid the problems of uneven distribution of data we use data sampling. By using the partitioning mechanism, the partitioned distributes the data depends on how large and representative the sample is and on how well the samples are analyzed. Due to this improves load balancing and memory consumption of the computers. In addition to that we use micro-partitioning methods to divide the workload into small tasks that are dynamically scheduled at runtime. This approach is only effective in systems with high-throughput, low-latency task schedulers and efficient data materialization. To enhance the accuracy in scheduling we propose an innovative method called Map Reduce Task Scheduling algorithm for Deadline constraints. This method allows user specify a job's deadline and tries to make the job be finished before the deadline. Through measuring the node's computing capacity, a node classification algorithm is proposed in MTSD. This algorithm classifies the nodes into several levels in heterogeneous clusters. Under this algorithm, we firstly illuminate a novel data distribution model which distributes data according to the node's capacity level respectively.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129955442","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}

{"title":"Monitoring of soil parameters for effective irrigation using Wireless Sensor Networks","authors":"B. Balaji Bhanu, M. Hussain, P. Ande","doi":"10.1109/ICOAC.2014.7229712","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229712","url":null,"abstract":"WSN (Wireless Sensor Network) has attracted the attention of researchers due to its wide applicability to various fields such as disaster management, health and environment monitoring, agriculture, ecology, industrial automation and in military field applications like battlefield surveillance etc. In agricultural ecosystem -situ - continuous smart monitoring of soil parameters like humidity, pH, irrigation control systems etc. can be measured using WSN with high end precision. In this manuscript, we propose to develop a WSN based Dynamic and Automated Irrigation System design and instrumentation. This process maintains soil type and software for real time sensing and control of agricultural irrigation system. The efficiency of irrigation systems can be enhanced by automated remote sensing and continuous analysis of soil parameters. Thus the data acquired is useful to the agricultural sector, namely pest management, irrigation management and soil management. Ultimately, this reduces the fresh water consumption and irrigation costs by maximizing the crop yield.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730600","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}

{"title":"A low-cost web-based learning platform for CNC machining education","authors":"N. Muthupalaniappan, A. Maruthupandi, S. Pandian, A. John, Paul Antony, Shunmugham R Pan, Dian","doi":"10.1109/ICOAC.2014.7229753","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229753","url":null,"abstract":"Computer numerical control (CNC) machines play a central role in modern manufacturing. CNC machining skills provide high-paying manufacturing jobs to graduates of engineering and technology. Hands-on laboratory instruction is essential for effective student learning in the area of CAD/CAM/Manufacturing Technology, but the high cost of commercial and even educational CNC machines like mills and lathes constrains the scope of instruction in CNC machining. In this paper, an inexpensive two-axis lathe prototype is developed using off-the-shelf materials and components, open source hardware, and open source CAM and CNC software. The machine can be adapted for large scale use in engineering colleges, polytechnics, and industrial training institutes (ITIs). To make the CNC learning even more affordable, accessible and less resource-intensive, a web-based learning platform for using the lathe is developed.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123886283","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}

{"title":"Wireless sensor Network based automated irrigation and crop field monitoring system","authors":"G. Nisha, J. Megala","doi":"10.1109/ICOAC.2014.7229707","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229707","url":null,"abstract":"Wireless sensor Network based automated irrigation system for optimize water use for agricultural purpose. The system consists of distributed wireless sensor network of soli-moisture, and temperature sensors placed in the crop field. To handle the sensor information Zigbee protocol used and control the water quantity programming using an algorithm with threshold values of the sensors to a microcontroller for irrigation system. The system has powered by solar panel and Cellular-internet interface for data inspection. A wireless camera is fixed in crop field to monitor the disease area using image processing technique. The system is low cost and energy autonomy useful in water limited geographically isolated areas.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124871537","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}

{"title":"Predicting the risk of readmission of diabetic patients using MapReduce","authors":"M. Gowsalya, K. Krushitha, C. Valliyammai","doi":"10.1109/ICOAC.2014.7229729","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229729","url":null,"abstract":"From the banking to retail, many sectors have already embraced big data regardless of whether the information comes from public or private sources. In the clinical sphere, the amount of patient data has grown exponentially because of computer based information systems. E-Health monitoring applications have some particularities concerning the importance on data quality. This paper presents a novel solution using Hadoop Mapreduce to analyze large datasets and extract useful insights from the dataset which helps doctors to effectively allocate resources. The successful healthcare delivery and planning strongly rely on data (e.g. sensed data, diagnosis, administration information); the higher quality of the data, the better will be the patient assistance. The applications are also particularly exposed to a contextual environment (i.e., patient's mobility, communication technologies, performance, information heterogeneity, etc.) that has an important impact on information management and application achievement. The main objective of our system is to predict the risk of diabetic patients for readmission in the next 30 days by measuring the probability using MapReduce. This risk score helps the physicians in recommending appropriate care for the patients.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127716086","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}

{"title":"Dynamic Access Control Model for Cloud Computing","authors":"M. Auxilia, K. Raja","doi":"10.1109/ICOAC.2014.7229744","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229744","url":null,"abstract":"Cloud Computing paradigm motivates researchers from both industry and academia with lot of research issues. Right from small and medium sized businesses and large scale businesses and even a single individual start utilizing cloud for their demands in terms of storage, software as well as infrastructure elastically and pay on use basis. But this transition to the cloud poses many security issues. One predominant issue is data security breach at many levels. Traditional cryptographic techniques and access control models like Mandatory, Discretionary and Role Based Access Control models are ill-suited for addressing multifarious security breaches in the cloud. This paper proposes dynamic access control for securing data in the cloud. This approach considers the interrelationship between the requestor, data being requested and action to be performed on that data. We also consider the context of the user for granting access control dynamically. In this paper, we enlighten the framework, its components and furthermore present an initial implementation of our model and some of the results of the same.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133931242","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}

{"title":"An efficient privacy protection mechanism for recommendation using hybrid transformation technique","authors":"M. Parvathy, K. Sundarakantham, S. Shalinie, C. Dhivya","doi":"10.1109/ICOAC.2014.7229742","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229742","url":null,"abstract":"The rapid evolution of the internet led to a development of an effective tool for coping with information overload. Recommendation system is one of the most widely adopted and perceptible technologies for solving information overload issue. Collaborative filtering is the most popular technique used in recommender system. But it has several limitation such as sparsity, scalability and most vital of all privacy. As proposed by the researchers, the sparsity issue can be alleviated by incorporating the trust measure in the recommendation system. Customers mostly provide false information because of privacy breaches which in turn affect the accuracy of the recommendations. In this paper, a hybrid transformation technique is proposed which fuses Principal Component Analysis and Rotation Transformation (PCART) to protect users' privacy with accurate recommendations based on trust. The performance of our method is evaluated experimentally using MovieLens Dataset. Our experimental results shows, the hybrid transformation techniques provides better recommendations with ensuring privacy compared to existing approaches.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115092101","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}

{"title":"Experimenting biocryptic system using similarity distance measure functions","authors":"R. Ramya, T. Sasikala","doi":"10.1109/ICOAC.2014.7229749","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229749","url":null,"abstract":"Biometric data are highly sensitive and vulnerable to misusage in today's world. To prevent from fraudulent use there is a need for secured biometric cryptosystems. E-Passport is one among the systems that has been developed for Biometric authentication. The more the security, the less prone, the system to attacks. With such an aim this paper first focuses on the usage of Biometric Encryption (Biocryptics) in E-Passports and secondly has made an attempt to analyze and experiment with the different similarity distance measure functions, and discusses the dominating performance of Weighted Euclidean Distance.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129985609","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}

{"title":"Efficacy of feature selection techniques for Multilayer Perceptron Neural Network to classify mammogram","authors":"P. Valarmathi, S. Robinson","doi":"10.1109/ICOAC.2014.7229739","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229739","url":null,"abstract":"Mammography aims to detect, characterize and evaluate the findings of breast cancer and related breast diseases. An X-ray of a patient's breast is a diagnostic mammogram which can show anomalies being detected through screening mammography or earlier mammography findings requiring follow-up. In automated mammogram classification, features are extracted and classified. The number of features is high, and the feature set contains irrelevant and redundant features leading to degradation of classifiers. In this work, the features from the mammograms are extracted using Multi-scale filter bank and Genetic Algorithm (GA) based feature selection is evaluated. This study proposes to classify features using Multilayer Perceptron Neural Network (MLPNN). Results show improvement of the proposed method.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130149776","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}

{"title":"Stabilizing the performance and fairness in dynamic p2p system using Do or Die incentive mechanism","authors":"D. Evangeline, R. Asha, P. Anandhakumar","doi":"10.1109/ICOAC.2014.7229716","DOIUrl":"https://doi.org/10.1109/ICOAC.2014.7229716","url":null,"abstract":"Live streaming applications for Video conferencing, E-learning and Telemedicine have become popular over the Internet. Peer-to-Peer network best suites the streaming architecture because p2p distributed network comprises of nodes which communicates with its neighboring nodes to make chunks available to other peer in the network environment. p2p paradigm serves as the effective solution in delivering videos with cost effective infrastructure. “Free Rider” one of the phenomenon which is identified as one of the challenge in the p2p system. These Free Riders are nothing but the node which simply resides in the p2p network, downloads the incoming streams but refuse to contribute or upload the file to other nodes. This serious threat degrades the performance of the overall system. The stream that it keeps downloading will rapidly increase leaving the system heavily loaded. On the other hand, the contributing nodes will be flooded with queries requesting for the streams. This leads to unfairness in the p2p system. This paper proposes an incentive mechanism “Do or Die” which boosts up the contributing nodes, as a sign of encouragement for their contribution, at the same time simultaneously motivates and threatens the Free Riders to contribute, else leave the network. The proposed incentive mechanism works on increment/Decrement point based scheme. Here the individual nodes are given increment points for uploading the file and decrement point for downloading the file. Hence the contributing nodes acquire high points on uploading and the Free Riders gets their points decreased as they only download the file. Hence the Free Riders can be identified and eliminated based on their decrement point. As the no of Free Riders decreases the overall system performance increases. Simulation results prove that the percentage of Free Riders reduced from 60% to 51% in the system and thereby increasing the performance and fairness of the system.","PeriodicalId":325520,"journal":{"name":"2014 Sixth International Conference on Advanced Computing (ICoAC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127661809","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}