Model–View–Controller pattern has been adopted as an architecture for World Wide Web applications in major programming languages. Though, many commercial and noncommercial web frameworks are very popular and applied widely, they are not particularly suitable for small applications. In this paper, the principle and basic components of MVC pattern are analyzed. Another new very Lightweight MVC framework was created, written by PHP and deployed on Linux, and then was applied to an online paper submission system as a demonstration which aims to improve the code re-usability and maintainability of small applications.
{"title":"Research on L-MVC Framework","authors":"Xiaohong Li, Na Liu","doi":"10.1109/PDCAT.2016.043","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.043","url":null,"abstract":"Model–View–Controller pattern has been adopted as an architecture for World Wide Web applications in major programming languages. Though, many commercial and noncommercial web frameworks are very popular and applied widely, they are not particularly suitable for small applications. In this paper, the principle and basic components of MVC pattern are analyzed. Another new very Lightweight MVC framework was created, written by PHP and deployed on Linux, and then was applied to an online paper submission system as a demonstration which aims to improve the code re-usability and maintainability of small applications.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125204524","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}
With the diversified development of the digital devices, such as computer, mobile phone, pad and television, how to resize an image or video to adapt to different display screens has been attracting more and more peoples' attention. Seam carving has been an important method for image resizing. If multiple removed or inserted seams are located within a certain region, it can lead to discontinuity image content. Besides, the salient objects tend to be destroyed if the energy function only contains the gradient information. Therefore, we propose an accumulative energy-based seam carving method for image resizing. When removing a certain seam, we distribute the energy of each pixel on the seam to its adjacent 8-connected pixels in order to avoid the extreme concentration of seams, especially within a texture region. In addition, we add the image saliency and the edge information into the energy function to reduce the distortion. Since the computational complexity of seam carving method is very high, we use parallel computing environment to achieve efficient computation. Experimental results show that compared with the existing methods, our method can both avoid the discontinuity of image content and distortions as well as better maintain the shape of the salient objects.
{"title":"Accumulative Energy-Based Seam Carving for Image Resizing","authors":"Yuqing Lin, Yuzhen Niu, Jiawen Lin, Haifeng Zhang","doi":"10.1109/PDCAT.2016.084","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.084","url":null,"abstract":"With the diversified development of the digital devices, such as computer, mobile phone, pad and television, how to resize an image or video to adapt to different display screens has been attracting more and more peoples' attention. Seam carving has been an important method for image resizing. If multiple removed or inserted seams are located within a certain region, it can lead to discontinuity image content. Besides, the salient objects tend to be destroyed if the energy function only contains the gradient information. Therefore, we propose an accumulative energy-based seam carving method for image resizing. When removing a certain seam, we distribute the energy of each pixel on the seam to its adjacent 8-connected pixels in order to avoid the extreme concentration of seams, especially within a texture region. In addition, we add the image saliency and the edge information into the energy function to reduce the distortion. Since the computational complexity of seam carving method is very high, we use parallel computing environment to achieve efficient computation. Experimental results show that compared with the existing methods, our method can both avoid the discontinuity of image content and distortions as well as better maintain the shape of the salient objects.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122516210","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}
In cloud manufacturing, manufacturing resources are services that can be looked up and accessed over the Internet. Manufacturing ontologies are used to store the service information. Manufacturers use service rules to control the access to their resources. The rules are normally written in natural language. Thus, they need to be converted to semantic rules that can be understood by the search engine of the manufacturing ontologies. Our previous work investigated converting service rules to semantic rules automatically. However, the scheme is not flexible enough. This paper proposed an improvement to the scheme in our previous work. The proposed scheme allows a wider range of service rules to be converted to semantic rules accurately.
{"title":"Identify the Semantic Meaning of Service Rules with Natural Language Processing","authors":"Xinfeng Ye","doi":"10.1109/PDCAT.2016.028","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.028","url":null,"abstract":"In cloud manufacturing, manufacturing resources are services that can be looked up and accessed over the Internet. Manufacturing ontologies are used to store the service information. Manufacturers use service rules to control the access to their resources. The rules are normally written in natural language. Thus, they need to be converted to semantic rules that can be understood by the search engine of the manufacturing ontologies. Our previous work investigated converting service rules to semantic rules automatically. However, the scheme is not flexible enough. This paper proposed an improvement to the scheme in our previous work. The proposed scheme allows a wider range of service rules to be converted to semantic rules accurately.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133624291","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}
Yueming Wei, Yichao Wang, Linjin Cai, W. Tang, Bei Wang, S. Ethier, S. See, James Lin
Accelerator-based heterogeneous computing is of paramount importance to High Performance Computing. The increasing complexity of the cluster architectures requires more generic, high-level programming models. OpenACC is a directive-based parallel programming model, which provides performance on and portability across a wide variety of platforms, including GPU, multicore CPU, and many-core processors. GTC-P is a discovery-science-capable real-world application code based on the Particle-In-Cell (PIC) algorithm that is well-established in the HPC area. Several native versions of GTC-P have been developed for supercomputers on TOP500 with different architectures, including Titan, Mira, etc. Motivated by the state-of-art portability, we implemented the first OpenACC version of GTC-P and evaluated its performance portability across NVIDIA GPUs, Intel x86 and OpenPOWER CPUs. In this paper, we also proposed two key optimization methods for OpenACC implementation of PIC algorithm on multicore CPU and GPU including removing atomic operation and taking advantage of shared memory. OpenACC shows both impressive productivity and performance in a perspective of portability and scalability. The OpenACC version achieves more than 90% performance compared with the native versions with only about 300 LOC.
{"title":"Performance and Portability Studies with OpenACC Accelerated Version of GTC-P","authors":"Yueming Wei, Yichao Wang, Linjin Cai, W. Tang, Bei Wang, S. Ethier, S. See, James Lin","doi":"10.1109/PDCAT.2016.019","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.019","url":null,"abstract":"Accelerator-based heterogeneous computing is of paramount importance to High Performance Computing. The increasing complexity of the cluster architectures requires more generic, high-level programming models. OpenACC is a directive-based parallel programming model, which provides performance on and portability across a wide variety of platforms, including GPU, multicore CPU, and many-core processors. GTC-P is a discovery-science-capable real-world application code based on the Particle-In-Cell (PIC) algorithm that is well-established in the HPC area. Several native versions of GTC-P have been developed for supercomputers on TOP500 with different architectures, including Titan, Mira, etc. Motivated by the state-of-art portability, we implemented the first OpenACC version of GTC-P and evaluated its performance portability across NVIDIA GPUs, Intel x86 and OpenPOWER CPUs. In this paper, we also proposed two key optimization methods for OpenACC implementation of PIC algorithm on multicore CPU and GPU including removing atomic operation and taking advantage of shared memory. OpenACC shows both impressive productivity and performance in a perspective of portability and scalability. The OpenACC version achieves more than 90% performance compared with the native versions with only about 300 LOC.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130327960","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}
How to design a low-latency and accurate approach for user behavior anomaly detection over data streams has become a great challenge. However, existing studies cannot meet low-latency and accurate requirements, due to a large number of subsequences and sequential relationship in behaviors. This paper presents BADSM, a user behavior anomaly detection approach based on sequence mining over data streams that seeks to address such challenge. BADSM uses self-adaptive behavior pruning algorithm to adaptively divide data stream into behaviors and decrease the number of subsequences to improve the efficiency of sequence mining. Meanwhile, the top-k abnormal scoring algorithm is used to reduce the complexity of traversal and obtain quantitative detection result to improve accuracy. We design and implement a streaming anomaly detection system based on BADSM to perform online detection. Extensive experiments confirm that BADSM significantly reduces processing delay by at least 36.8% and false positive rate by 6.4% compared with the classic sequence mining approach PrefixSpan.
{"title":"A User Behavior Anomaly Detection Approach Based on Sequence Mining over Data Streams","authors":"Yong Zhou, Yijie Wang, Xingkong Ma","doi":"10.1109/PDCAT.2016.086","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.086","url":null,"abstract":"How to design a low-latency and accurate approach for user behavior anomaly detection over data streams has become a great challenge. However, existing studies cannot meet low-latency and accurate requirements, due to a large number of subsequences and sequential relationship in behaviors. This paper presents BADSM, a user behavior anomaly detection approach based on sequence mining over data streams that seeks to address such challenge. BADSM uses self-adaptive behavior pruning algorithm to adaptively divide data stream into behaviors and decrease the number of subsequences to improve the efficiency of sequence mining. Meanwhile, the top-k abnormal scoring algorithm is used to reduce the complexity of traversal and obtain quantitative detection result to improve accuracy. We design and implement a streaming anomaly detection system based on BADSM to perform online detection. Extensive experiments confirm that BADSM significantly reduces processing delay by at least 36.8% and false positive rate by 6.4% compared with the classic sequence mining approach PrefixSpan.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127839841","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}
Falling accidents, including slipping, tripping and falling, are the primary reason of injury related to death not only for elderly, but for young people or worker happening at workplace also. If falling accident can be early detected in pre-fall or critical fall phase, called pre-impact fall detection, it will be very useful such as conducting airbag inflation. Furthermore, various detection methods, with an uncomplicated threshold detection method, do maximizing the true positive prediction values but the lead-time, time before subject impacts to the floor, will likely increases the chance of false alarms. Consequently the researcher found that the using of adaptive threshold may reduce false alarms. In this paper, the dynamic threshold method, automatically adjustable threshold for pre-impact fall detection in wearable device, has been proposed and experimented. For our evaluation, 192 instances of several kinds of activity of daily living and falling, were captured. All activities were performed by 6 different young healthy volunteers, 4 males and 2 females, aged between 19 and 21. The several experiments were conducted for performance evaluation including sensitivity, specificity and accuracy measurements. The results of proposed method can detect the pre-impact fall from normal activities of daily living with 99.48% sensitivity, 95.31% specificity and 97.40% accuracy with 365.12 msec of lead time. The results confirm that our proposed method with automatically adjustable threshold based on motion history, is suitable for using in pre-impact fall detection system than fixed threshold based method.
{"title":"Pre-Impact Fall Detection Based on Wearable Device Using Dynamic Threshold Model","authors":"Nuth Otanasap","doi":"10.1109/PDCAT.2016.083","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.083","url":null,"abstract":"Falling accidents, including slipping, tripping and falling, are the primary reason of injury related to death not only for elderly, but for young people or worker happening at workplace also. If falling accident can be early detected in pre-fall or critical fall phase, called pre-impact fall detection, it will be very useful such as conducting airbag inflation. Furthermore, various detection methods, with an uncomplicated threshold detection method, do maximizing the true positive prediction values but the lead-time, time before subject impacts to the floor, will likely increases the chance of false alarms. Consequently the researcher found that the using of adaptive threshold may reduce false alarms. In this paper, the dynamic threshold method, automatically adjustable threshold for pre-impact fall detection in wearable device, has been proposed and experimented. For our evaluation, 192 instances of several kinds of activity of daily living and falling, were captured. All activities were performed by 6 different young healthy volunteers, 4 males and 2 females, aged between 19 and 21. The several experiments were conducted for performance evaluation including sensitivity, specificity and accuracy measurements. The results of proposed method can detect the pre-impact fall from normal activities of daily living with 99.48% sensitivity, 95.31% specificity and 97.40% accuracy with 365.12 msec of lead time. The results confirm that our proposed method with automatically adjustable threshold based on motion history, is suitable for using in pre-impact fall detection system than fixed threshold based method.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114807512","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}
In this paper, we consider the problem of constructing scale-free networks in a semi-deterministic manner. Scale-free networks have several favorable properties as the topology of interconnection networks such as the short diameter and the quick message propagation. The proposed algorithm is an extension of the Bulut's algorithm for constructing scale-free networks with designated minimum degree k and maximum degree m, such that: 1) it determines the ideal number of edges derived from the ideal degree distribution, and 2) after connecting each new node to k existing nodes as in the Bulut's algorithm, it adjusts the number of edges to the ideal value by conducting add/removal of edges. We prove that such an adjustment is always possible if the number of nodes in the network exceeds m2/k+m.
{"title":"Improved Semi-Deterministic Scheme to Generate Limited Scale-Free Networks","authors":"Naoki Takeuchi, S. Fujita","doi":"10.1109/PDCAT.2016.051","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.051","url":null,"abstract":"In this paper, we consider the problem of constructing scale-free networks in a semi-deterministic manner. Scale-free networks have several favorable properties as the topology of interconnection networks such as the short diameter and the quick message propagation. The proposed algorithm is an extension of the Bulut's algorithm for constructing scale-free networks with designated minimum degree k and maximum degree m, such that: 1) it determines the ideal number of edges derived from the ideal degree distribution, and 2) after connecting each new node to k existing nodes as in the Bulut's algorithm, it adjusts the number of edges to the ideal value by conducting add/removal of edges. We prove that such an adjustment is always possible if the number of nodes in the network exceeds m2/k+m.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121709690","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}
Security threats targeting mobile phones have increased significantly in recent years as mobile phone technology continues to advance and mobile phone usage skyrockets. Young generation uses mobile phone frequently, and being exposed to these vulnerability and threats in daily life. This paper discussed current mobile security threat environment, and reports a survey study of 262 college students in the United States, examined their mobile phone usage patterns and security concerns, and compared the results with the ones from previous studies.
{"title":"A Survey Study of Young Generation's Mobile Phone Usage and Security Concerns","authors":"Sonya Zhang, Saree Costa","doi":"10.1109/PDCAT.2016.075","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.075","url":null,"abstract":"Security threats targeting mobile phones have increased significantly in recent years as mobile phone technology continues to advance and mobile phone usage skyrockets. Young generation uses mobile phone frequently, and being exposed to these vulnerability and threats in daily life. This paper discussed current mobile security threat environment, and reports a survey study of 262 college students in the United States, examined their mobile phone usage patterns and security concerns, and compared the results with the ones from previous studies.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129910591","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}
Collaborative Filtering (CF) is a successful technology that has been implemented in E-commerce recommender systems. However, the risks of shilling attacks have already aroused increasing concerns of the society. Current solutions mainly focus on attack detection methods and robust CF algorithms that have flaws of unassured prediction accuracy. Furthermore, attack detection methods require a threshold to distinguish normal users from fake users and suffer from the problems of false positive if the threshold is too high and false negative if too low. This paper proposes a soft-decision method, Neighbor Selection with Variable-Length Partitions (VLPNS), to reduce false positive rate through marking suspicious fakers instead of deleting them directly such that misclassified normal users can still contribute to the similarity calculation. The method works as follows: First, it gets user's suspicion probability by applying SVM. It then generates partitions of variable sizes from which different numbers of neighbors can be selected by using the bisecting c-means clustering algorithm. Finally, it chooses neighbors considering the user's suspicion degree and similarity with target user at the same time. Theoretical and experimental analysis show that our approach ensures an excellent prediction accuracy against shilling attacks.
{"title":"An Improved Collaborative Filtering Recommendation Algorithm against Shilling Attacks","authors":"Ruoxuan Wei, Hong Shen","doi":"10.1109/PDCAT.2016.077","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.077","url":null,"abstract":"Collaborative Filtering (CF) is a successful technology that has been implemented in E-commerce recommender systems. However, the risks of shilling attacks have already aroused increasing concerns of the society. Current solutions mainly focus on attack detection methods and robust CF algorithms that have flaws of unassured prediction accuracy. Furthermore, attack detection methods require a threshold to distinguish normal users from fake users and suffer from the problems of false positive if the threshold is too high and false negative if too low. This paper proposes a soft-decision method, Neighbor Selection with Variable-Length Partitions (VLPNS), to reduce false positive rate through marking suspicious fakers instead of deleting them directly such that misclassified normal users can still contribute to the similarity calculation. The method works as follows: First, it gets user's suspicion probability by applying SVM. It then generates partitions of variable sizes from which different numbers of neighbors can be selected by using the bisecting c-means clustering algorithm. Finally, it chooses neighbors considering the user's suspicion degree and similarity with target user at the same time. Theoretical and experimental analysis show that our approach ensures an excellent prediction accuracy against shilling attacks.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128538355","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}
Given a set of multiple requests sent by clients, where each request contains multiple data items, multi-antenna data retrieval problem refers that finds an access pattern (to retrieve multiple requests by using multiple antennae) such that the access latency of each antenna is minimized and the total access latency in all antennae keeps balance. The problem has great value in mobile computing applications. Although almost researches have focused on data retrieval problem when the clients equipped with one antenna send single request and multiple requests, there are few studies on data retrieval problem with multiple requests sent by clients equipped with multiple antennae. Therefore, this paper proposes two algorithms that adopt two different grouping schemes (SG and WG) such that the requests can be reasonably retrieved by each antenna. For retrieving each request, we propose an algorithm that converts wireless data broadcast system to a super tree for finding an access pattern to download all requested data items in minimal access latency. Through experiments, the proposed scheme has currently most efficiency in existing schemes.
{"title":"Efficient Data Retrieval Algorithm for Multi-Request in Multi-Antenna Wireless Networks","authors":"Ping He, Zheng Huo","doi":"10.1109/PDCAT.2016.025","DOIUrl":"https://doi.org/10.1109/PDCAT.2016.025","url":null,"abstract":"Given a set of multiple requests sent by clients, where each request contains multiple data items, multi-antenna data retrieval problem refers that finds an access pattern (to retrieve multiple requests by using multiple antennae) such that the access latency of each antenna is minimized and the total access latency in all antennae keeps balance. The problem has great value in mobile computing applications. Although almost researches have focused on data retrieval problem when the clients equipped with one antenna send single request and multiple requests, there are few studies on data retrieval problem with multiple requests sent by clients equipped with multiple antennae. Therefore, this paper proposes two algorithms that adopt two different grouping schemes (SG and WG) such that the requests can be reasonably retrieved by each antenna. For retrieving each request, we propose an algorithm that converts wireless data broadcast system to a super tree for finding an access pattern to download all requested data items in minimal access latency. Through experiments, the proposed scheme has currently most efficiency in existing schemes.","PeriodicalId":203925,"journal":{"name":"2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133739553","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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