Maede Fotros, Mohammad Mansour Riahi Kashani, J. Rezazadeh, J. Ayoade
{"title":"A Timely VANET Multi-hop Routing Method in IoT","authors":"Maede Fotros, Mohammad Mansour Riahi Kashani, J. Rezazadeh, J. Ayoade","doi":"10.1109/PDCAT46702.2019.00015","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00015","url":null,"abstract":"Vehicular Ad hoc Networks (VANET) is a promising technology in the Internet of Things (IoT) which enables communication in vehicle to vehicle (V2V) and vehicle to infrastructure (V2I). VANETs attracts great attention in various applications such as automakers, universities, and traffic police. There are some challenges that to be addressed. The main challenge is routing due to high speed movement of vehicles. Several methods have been proposed to tackle the problem of end-to-end delay in routing. They are still issues from delay to select next-hop relay node. This delay in dense environment broadcast storm problem. Therefore, we proposed new multi-hop routing method that takes the advantages of periodic hello messages to conduct routing tables and select efficient node for rebroadcasting messages. In order to show the performance of the proposed method, extensive results carried out using Network Simulator (NS2) and compare it with other related routing methods. The simulation results indicates that removing contention phase to select rebroadcast node results better end-to-end delay and reduce redundant packets.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124884833","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":"Comparison of Binary Rain Prediction on HIMAWARI using MPI and CUDA","authors":"Aisya Nafiisyanti","doi":"10.1109/PDCAT46702.2019.00084","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00084","url":null,"abstract":"Predictions of rainfall events are very important to determine the preventive steps needed to avoid adverse effects with climate change that slowly changing the impact of rain events in Indonesia's area. One way to calculate the prediction of rain events is to use the Lookup Table and Probability of Rain method. To perform that, parallel programming is conducted to help solve large and complex computational problems. In this study, CPU (Central Processing Unit) programming and GPU (Graphical Processing Unit) programming are done to see each performance where computation design and Lookup Table design are implemented on both programming. The results show that CPU programming is more effective for the given case and data rather than GPU programming. Meanwhile, non-ranged Lookup Table design in CPU programming gives more accurate predictions even though it takes more time in computation.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127054217","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":"Infinite Propagation Speed for a Two-Component Camassa-Holm Equation","authors":"Wenjun Cui, Yidong Li","doi":"10.1109/PDCAT46702.2019.00106","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00106","url":null,"abstract":"The use of Partial Differential Equation models for studying traffic flows has a fairly long history. This paper deals with the Cauchy problem of a two-component Camassa-Holm equation. First, we prove that the solution ρ keeps the property of having compact support for any further time provided the initial data ρ_0 has compact support. While the initial data m_0 has compact support then the solution m will remain compactly supported, only if ρ is also initially compactly supported. Then, we get the infinite propagation speed in the sense that the solution u with compactly supported initial data does not have compact support any longer in its lifespan. Although the nontrivial solution u is no longer compactly supported, a detailed description about the profile of the solution u is shown as it evolves over time.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128983581","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":"Quantifying the Impact of Design Strategies for Big Data Cyber Security Analytics: An Empirical Investigation","authors":"Faheem Ullah, M. Babar","doi":"10.1109/PDCAT46702.2019.00037","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00037","url":null,"abstract":"Big Data Cyber Security Analytics (BDCA) systems use big data technologies (e.g., Hadoop and Spark) for collecting, storing, and analyzing a large volume of security event data to detect cyber-attacks. The state-of-the-art uses various design strategies (e.g., feature selection and alert ranking) to help BDCA systems to achieve the desired levels of accuracy and response time. However, the use of these strategies in the state-of-the-art is not consistent, which exposes a lack of consensus on \"when to use (and not to use) these design strategies?\" In this paper, we follow a systematic experimentation framework to quantify the impact of four design strategies on the accuracy and response time with respect to three contextual factors i.e., security data, machine learning model employed in the system, and the execution mode of the system. For the aimed quantification, we performed experiments on a Hadoop-based BDCA system using four security datasets, five machine learning models, and three execution modes. Our findings lead us to formulate a set of design guidelines that will help researchers and practitioners to decide when to use (and not to use) the design strategies.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130479857","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":"Image Preprocessing Algorithm Based on K-Means","authors":"Xiaofan Zhao, Manchun Cai, Yuan Ren, Fan Yang","doi":"10.1109/PDCAT46702.2019.00104","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00104","url":null,"abstract":"With the development of image acquisition and storage technology, the image data is greatly increased. How to process the increasing image data quickly has become the main problem of image processing. In this paper, the image data are processed by K-means algorithm in Python language environment, and the original image and the image processed by K-means algorithm are classified and trained in convolution neural network. The experimental results show that the time consumed by the image processed by K-means algorithm is 20 s to 30 s less than that of the original image in convolution neural network. It can effectively improve the efficiency of image processing.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127940949","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":"[Copyright notice]","authors":"","doi":"10.1109/pdcat46702.2019.00003","DOIUrl":"https://doi.org/10.1109/pdcat46702.2019.00003","url":null,"abstract":"","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123259020","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":"Task Merging and Scheduling for Parallel Deep Learning Applications in Mobile Edge Computing","authors":"Xin Long, W. Jigang, Yalan Wu, Long Chen","doi":"10.1109/PDCAT46702.2019.00022","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00022","url":null,"abstract":"Mobile edge computing enables the execution of compute-intensive applications, e.g. deep learning applications, on the end devices with limited computation resources. However, the deep learning applications bring the performance bottleneck in mobile edge computing, due to the movements of a large amount of data incurred by the large number of layers and millions of weights. In this paper, the computing model for parallel deep learning applications in mobile edge computing is proposed, by considering the occupancy allocation of processors, cost of context switch, and multi-processors in edge server and remote cloud. The problem of minimizing the completion time for deep learning applications is formulated, and the NP-hardness of the problem is proved. To solve the problem, an integrated algorithm by merging and scheduling is proposed. Moreover, a real-world distributed platform is developed for evaluating the proposed algorithm. Experimental results show that, the completion time of deep learning application for the proposed algorithm is decreased by 63% and 75%, respectively, without extra control costs, compared with the existing algorithms.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126466184","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":"Ultra Reliable Communication : Availability Analysis in 5G Cellular Networks","authors":"Yosra Benchaabene, Noureddine Boujnah, F. Zarai","doi":"10.1109/PDCAT46702.2019.00029","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00029","url":null,"abstract":"To meet the growing demand of users, the fifth generation (5G) will continue to provide services to higher data rates with higher carrier frequencies and wider bandwidths. As part of the 5G communication paradigm, ultra-reliable communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. Ultra Reliable Communication (URC) is considered an important technology that why it has become an active research topic. In this work, we analyze the availability of a service in the space domain. We characterize spatially available areas consisting of all locations that meet a performance requirement with confidence, and we define cell availability and system availability, individual user availability and user-oriented System Availability. Poisson point process (PPP) and Voronoi tessellation are adopted to model the spatial characteristics of a cell deployment in heterogeneous networks. Numerical results are presented, also highlighting the effect of different system parameters on the achievable link availability","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126083155","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":"Fault-Tolerant Logical Hadamard Gates Implementation in Reed-Muller Quantum Codes","authors":"Dongxiao Quan, Li Niu, Lili Zhu, Changxing Pei","doi":"10.1109/PDCAT46702.2019.00040","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00040","url":null,"abstract":"We investigate how to implement fault-tolerant logical Hadamard gates in Reed-Muller quantum codes(RMQCs) using the gauge-fixing method. During the realization, we consider the influence of random single-qubit errors by performing the error-detecting measurements. Moreover, some error-detecting stabilizers are simplified by the existing syndromes. Then we identify the errors and modify the syndromes, and refer to the modified syndromes to select the fix operations, and finally perform the error-correcting and fix operations together. Further, we establish a graph model for the RMQCs and exhibit a progress of how to find the fix operations for the unsatisfied stabilizers. We simulate the progress of finding corresponding fix operations for 31-quibt and 63-qubit RMQCs and the whole process of realizing logical Hadamard gate with random single-qubit errors for 15-qubit and 31-quibt RMQCs. Results show that correct fix operations can be obtained and fault-tolerant logical Hadamard gates can be realized as expected. With the implementation of the logical Hadamard gate, a universal fault-tolerant gate set is achieved in single RMQC.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"466 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115860231","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}
Yimu Ji, Shuai Chen, Haichang Yao, Houzhi Fang, Kui Li, Shangdong Liu, Zhengyuan Xie, Kairui Wang
{"title":"Multi-Thread Concurrent Compression Algorithm for Genomic Big Data","authors":"Yimu Ji, Shuai Chen, Haichang Yao, Houzhi Fang, Kui Li, Shangdong Liu, Zhengyuan Xie, Kairui Wang","doi":"10.1109/PDCAT46702.2019.00093","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00093","url":null,"abstract":"At present, there are many excellent genome compression algorithms with high genome compression ratio. However, there is a lack of highly efficient compression algorithms for simultaneous compression of a large number of genomes. This manuscript presents an algorithm, which is called FastLNGC, for simultaneous compression of a large amount of genome data based on multi-thread concurrency. This algorithm is based on the LNGC (Large Number of Genomes Compressor) algorithm, and adopts multi-thread technology to achieve concurrent processing of genome data compression. A large number of experiments show that FastLNGC has better performance on compression of a large number of genes. The source code of FastLNGC is available at https://github.com/APandaThief/FastLNGC.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121525845","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}