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2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)最新文献

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Advance Lighting and Water Pumping System using Artificial Intelligence 使用人工智能的先进照明和抽水系统
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745742
Ekta, V. Garg
{"title":"Advance Lighting and Water Pumping System using Artificial Intelligence","authors":"Ekta, V. Garg","doi":"10.1109/PDGC.2018.8745742","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745742","url":null,"abstract":"Electricity demand is increasing day by day and there is a gap between electricity generation and demand. The consumption of electricity is far greater than generation of electricity. The way of using appliances plays a major role in this mismatch. Lightning system and water pumping system of any home/building plays vital role in the consumption of electricity. In India, the management of lightning and pumping system is not so good which causes power wastage. This method reduces the loss by huge amount. Hence, it will be highly beneficial for the electrical applications. This application will automatically control the on/off of exterior lights and water pumping system of a house so that it will save the electrical energy which gets wasted in normal condition. Also time scheduling has been done by using fuzzy controller which controls the operation on time basis also. Hence this technique will cover a broad area of electrical consumption that is lightning system and water pumping system. It will be effective in both the cases.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128347484","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}
引用次数: 1
Performance Factor Analysis and Scope of Optimization for Big Data Processing on Cluster 集群大数据处理的性能因素分析及优化范围
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745857
Hanuman Godara, Mahesh Chandra Govil, E. Pilli
{"title":"Performance Factor Analysis and Scope of Optimization for Big Data Processing on Cluster","authors":"Hanuman Godara, Mahesh Chandra Govil, E. Pilli","doi":"10.1109/PDGC.2018.8745857","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745857","url":null,"abstract":"Use of computational cluster for large-scale Big Data processing has attracted attention as a technology trend for its time efficiency. Modern cluster equipped with latest multi, many-core distributed shared architecture, high speed interconnect and file system, ensures high performance using message passing and multi-threading parallel approaches, also handles batch, micro-batch and stream processing of high dimensional massive dataset but running data-intensive Big Data application on compute-centric cluster imposes challenges to its performance because of several runtime overheads. In order to alleviate these bottlenecks and exploit full potential of the cluster a state of the practice, performance-oriented technical analysis covering all relevant aspects is presented in the context of Terascale Big data processing on TeraFLOPS cluster PARAM-Kanchenjunga, with identification of major factors influencing the performance or sources of these overheads related to computation, communication or IPC, memory, I/O contention, scheduling, load imbalance, synchronization, latency and network jitter; by determining their impact. As existing approaches found insufficient, to achieve possible speedup advance methods with a variety of alternatives as RDMA enabled libraries, PFS, MPI-Integrated extensions, loop tiling, hybrid parallelization are provided to consider for optimization purposes. This paper will assist to prepare performance aware design of experiments and performance modeling.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128865453","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}
引用次数: 0
Dynamic resource allocation in Vehicular cloud computing systems using game theoretic based algorithm 基于博弈论的车载云计算系统动态资源分配算法
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745913
P. Mohanty, L. Kumar, Madhuri Malakar, S. K. Vishwakarma, Motahar Reza
{"title":"Dynamic resource allocation in Vehicular cloud computing systems using game theoretic based algorithm","authors":"P. Mohanty, L. Kumar, Madhuri Malakar, S. K. Vishwakarma, Motahar Reza","doi":"10.1109/PDGC.2018.8745913","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745913","url":null,"abstract":"The availability of high-capacity networks, low-cost computers, storage devices as well as the widespread adoption of hardware virtualization, service-oriented architecture, and autonomic and utility computing has led to growth in cloud computing. In today's era of cloud-based services, all intelligent transportation systems are connected to improve transportation safety and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. We propose to integrate cloud computing and vehicular networks in such a way that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126913827","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}
引用次数: 6
Two phase fuzzy based prediction model to predict Soil nutrient 基于两阶段模糊的土壤养分预测模型
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745759
Ravinder Singh, Rubleen Kaur, Anshu Singla
{"title":"Two phase fuzzy based prediction model to predict Soil nutrient","authors":"Ravinder Singh, Rubleen Kaur, Anshu Singla","doi":"10.1109/PDGC.2018.8745759","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745759","url":null,"abstract":"Soil nutrients play significant role in the crop productivity. The ‘pH’ is one of the main factor which can be used to predict the concentration of nutrients in the soil. In this article, authors have proposed two phase approach to predict soil nutrients. Phase 1 predicts pH value of soil depending on previous time series pH value of soil by using fuzzy model. Phase 2 employs regression model to predict soil nutrients such as Nitrogen (N), Phosphorus (P), potassium (K) based on predicted pH value. The result analysis shows that the experimental results outperforms over statistical parameters.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124981759","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}
引用次数: 4
Hybridized Active Learning Model Based On Most Certain and Uncertain Label Selection 基于最确定和最不确定标签选择的混合主动学习模型
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745769
Simranjeet Kaur, Anshu Singla
{"title":"Hybridized Active Learning Model Based On Most Certain and Uncertain Label Selection","authors":"Simranjeet Kaur, Anshu Singla","doi":"10.1109/PDGC.2018.8745769","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745769","url":null,"abstract":"In order to correctly classify the huge amount of unlabeled data, supervised classification paradigms necessitated the requirement of labeled data. But the availability of labeled data is too scarce and labeling is too expensive. To decrease the human labeling efforts, through selecting the much meaningful data from unlabeled data and add to label data, active learning techniques have been proven to be efficient. Active Learning is based on the principle of selection of most uncertain and non-redundant instances in each iteration. In this paper, authors have considered not only the most uncertain instances but also the most certain instances have been selected which helped in improving the efficiency of learning model. Extensive experiment has been carried out on different datasets to confirm the effectiveness of proposed model.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125021614","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}
引用次数: 0
Designing of Smart Drip Irrigation System for Remote hilly Areas 偏远山区智能滴灌系统的设计
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745934
Dhawan Singh, Aditi Thakur
{"title":"Designing of Smart Drip Irrigation System for Remote hilly Areas","authors":"Dhawan Singh, Aditi Thakur","doi":"10.1109/PDGC.2018.8745934","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745934","url":null,"abstract":"Agriculture has been the backbone of our country's economy and it will remain to continue for a long time. Over 70 percent of the rural population depends on agriculture. The contribution of agriculture to the gross domestic product (GDP) is about to 18% and have contributed up to 50% of the country's employment. The prognosis indicates that requirement to feed a world population of 9.1 billion people in 2050 necessitates the raise of total meal production nearby 70% between 2005 and 2050. Consequently, production would need to be almost doubled in the developing countries. In this context, we have proposed a new design concept of smart drip irrigation system for remote hilly areas where electricity and water connectivity are poor. The proposed system is powered through solar energy and provide a better alternative to conventional automatic irrigation systems. Thus, conserve electricity and water by reducing their usage.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131202253","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}
引用次数: 4
GPU-Accelerated Scalable Solver for Large Linear Systems over Finite Fields 有限域上大型线性系统的gpu加速可扩展求解器
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745743
Indivar Gupta, P. Verma, Vinay D. Deshpande, N. Vydyanathan, Bharatkumar Sharma
{"title":"GPU-Accelerated Scalable Solver for Large Linear Systems over Finite Fields","authors":"Indivar Gupta, P. Verma, Vinay D. Deshpande, N. Vydyanathan, Bharatkumar Sharma","doi":"10.1109/PDGC.2018.8745743","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745743","url":null,"abstract":"Solving large and dense linear systems over finite fields (GF(2)) forms the basis for several crypt-analytic techniques. Many popular cryptographic algorithms like Number Field Sieve for Integer Factorization, Discrete Log Problem, Cryptanalysis of Ciphers and Algebraic attack requires solving dense systems of linear equations. Gaussian Elimination is the natural and popular approach for solving such systems. However, its cubic time complexity makes it very slow and hence, parallelization is made mandatory. In this paper, we propose a GPU-accelerated linear solver over GF(2), based on Gaussian Elimination. Our parallel solver is implemented using NVIDIA CUDA and MPI to utilize the multi-level parallelism on multi-node, multi-GPU systems, which are becoming increasingly common. CUDA-aware MPI is used to leverage GPUDirect P2P and GPUDirect RDMA for optimized intra- and inter-node communication. Our experimental results show that the proposed solver is able to effectively utilize the memory bandwidth on a single Tesla P100 GPU and shows a parallel efficiency of 95% on a 4 X Tesla P100 multi-GPU node. We see 89% and 94% parallel efficiency on DGX systems with 8, Tesla P100 and Tesla V100 GPUs respectively.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132937522","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}
引用次数: 1
Devanagari Ancient Character Recognition using HOG and DCT Features 基于HOG和DCT特征的梵语古汉字识别
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745903
S. Narang, M. Jindal, Pooja Sharma
{"title":"Devanagari Ancient Character Recognition using HOG and DCT Features","authors":"S. Narang, M. Jindal, Pooja Sharma","doi":"10.1109/PDGC.2018.8745903","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745903","url":null,"abstract":"In the present work, a system for recognition of ancient documents in Devanagari script is presented. Two feature extraction techniques, namely, DCT(Discrete Cosine Transformation) zigzag features and Histogram of oriented gradients are considered for extracting features of Devanagari ancient manuscripts. For recognition, three classification techniques, namely, SVM (Support Vector Machine), decision tree, and Naïve Bayes are used. A database for the experiments is collected from various libraries and museums. Using SVM classifier with RBF kernel, a recognition accuracy of 90.70% with DCT zigzag feature vector of length 100 has been reported. A recognition accuracy of 90.70% with a partitioning strategy of dataset (80% data as training data and the remaining 20% data as testing data) has been achieved.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":" 44","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114053402","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}
引用次数: 12
Matlab Based GUI for ECG Arrhythmia Detection Using Pan-Tompkin Algorithm 基于Matlab的基于泛汤普金算法的心电心律失常检测GUI
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745865
Bhawna Jindal, Saudagar, Ekta, R. Devi
{"title":"Matlab Based GUI for ECG Arrhythmia Detection Using Pan-Tompkin Algorithm","authors":"Bhawna Jindal, Saudagar, Ekta, R. Devi","doi":"10.1109/PDGC.2018.8745865","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745865","url":null,"abstract":"The purpose of paper is to detect heart arrhythmia which is generated due to irregular heart rhythm. The heart problem of a person can be noticed by examining the ECG (Electrocardiogram) signal and withdrawing the various features of the ECG signal like RR interval, width of QRS complex, P wave, R wave and heart rate. Data for electrocardiogram signal occupied from MIT-BIH arrhythmia database. Graphical user interface (GUI) has been developed for the detection of arrhythmia using Pan-Tompkins algorithm. Modification has been done in the Pan-Tompkins algorithm for the detection of abnormalities related to heart by calculating various parameters. This toolbox is developed in MATLAB software. Developed GUI is an efficient and effective way to diagnose heart diseases","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114814521","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}
引用次数: 3
A Novel Context-Based Approach of Identifying Congestion Detection 一种新的基于上下文的拥塞检测识别方法
2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC) Pub Date : 2018-12-01 DOI: 10.1109/PDGC.2018.8745958
Pratik Dutta
{"title":"A Novel Context-Based Approach of Identifying Congestion Detection","authors":"Pratik Dutta","doi":"10.1109/PDGC.2018.8745958","DOIUrl":"https://doi.org/10.1109/PDGC.2018.8745958","url":null,"abstract":"Traffic congestion detection is one of the major key issues in traffic management. The existing works, in general, focus on the speed and density of the vehicles for detecting congestion. But the contextual information could be another major input that affects the performance of congestion detection algorithm. Practically, a context can be used to characterize the situation of an entity. Thus the solutions, those are not considering contexts, may not be suitable for the real-life application. In this work, an attempt has been made to offer a context-based probabilistic graph model. The model is capable to generate a new context and delivers the result accordingly. The simulation of the proposed mechanism has been done and the results substantiate the claim i.e. the effectiveness of the proposed model.","PeriodicalId":303401,"journal":{"name":"2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124018613","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}
引用次数: 1
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