2017 IEEE International Conference on Web Services (ICWS)最新文献_第9页

EAaaS: Edge Analytics as a Service EAaaS:边缘分析即服务

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.130

Xiaomin Xu, Sheng Huang, Lance Feagan, Yaoliang Chen, Yunjie Qiu, Yu Wang

{"title":"EAaaS: Edge Analytics as a Service","authors":"Xiaomin Xu, Sheng Huang, Lance Feagan, Yaoliang Chen, Yunjie Qiu, Yu Wang","doi":"10.1109/ICWS.2017.130","DOIUrl":"https://doi.org/10.1109/ICWS.2017.130","url":null,"abstract":"In the Internet of Things (IoT) era, with ubiquitous remote sensing devices and other diverse data sources, nearly everything can forward voluminous data continuously, in real-time, which drives demand to perform real-time analytics on uninterrupted IoT data flows. The typical resultant approach is a cloud-centered architecture providing an analytic service for real-time IoT data processing. However, a cloud-centered IoT analytic service cannot guarantee real-time responsiveness has a high-fee pay-as-you-go business model, and opens data privacy concerns. Hence, it becomes rational to shift analytic workloads to the edge and provide a management service for edge analysis. Existing work on providing edge analytics as a service encountered challenges such as lacking a lightweight way to compose IoT applications based on multiple service providers, lacking a flexible and unified way to define domain-specific analytic logic, and maintaining efficiency when processing data on a resource-limited edge. This paper presents EAaaS, a scalable analytic service for enabling real-time edge analytics in IoT scenarios. In this work, we propose a unified rule-based analytic model to ease user's programming efforts in specifying rule-based analytic logic. Moreover, we also designed and implemented a high performance edge engine to apply rule-based analytic on incoming device data streams. To simplify the access to EAaaS service, a group of RESTful web interfaces is also designed for edge analytic management on cloud and flexible composition with external services. EAaaS is implemented as a part of IBM Watson IoT Platform, which is a cloud service for elementary IoT application development on IBM Bluemix cloud announced by IBM recently. We have conducted proof of correctness (PoC) of EAaaS with customers from boat racing in the U.S. and collected valuable feedback from customers for further enhancement of EAaaS’s flexibility and usability","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132351530","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: 28

FB-Diff: A Feature Based Difference Detection Algorithm for Process Models 基于特征的过程模型差分检测算法

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.71

Jiaxing Wang, Bin Cao, Jing Fan, Tianyang Dong

{"title":"FB-Diff: A Feature Based Difference Detection Algorithm for Process Models","authors":"Jiaxing Wang, Bin Cao, Jing Fan, Tianyang Dong","doi":"10.1109/ICWS.2017.71","DOIUrl":"https://doi.org/10.1109/ICWS.2017.71","url":null,"abstract":"Detecting difference between process models is important for many business process management scenarios, such as process version control and process merging. However, it is far from trivial to detect the process difference. Existing work suffers from drawbacks like inappropriate data structure support or expensive computation. In this paper, we propose FB-Diff, a feature-based difference detection approach. Firstly, a semi-ordered tree model called task based process structure tree (TPST) is used to represent a process model, which can correctly describe the structure as well as the behavior (the execution sequence of task nodes). Then FB-Diff adopts a divide and conquer strategy to find the similar parts of two TPSTs. Specically, we divide the TPST into fragments that are represented by feature vectors. A feature vector consists of six features, and each feature describes a key characteristic of the fragment. Based on the similar parts, the edit script that can transform one TPST into the other is generated. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127249350","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

Social-Sensor Cloud Service Selection 社会传感器云服务选择

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.59

Tooba Aamir, A. Bouguettaya, Hai Dong, A. Erradi, Rachid Hadjidj

引用次数: 9

"Learning Relevance" as a Service for Improving Search Results in Technical Discussion Forums “学习相关性”作为在技术讨论论坛中改进搜索结果的服务

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.82

Shubham Atreja, Shivali Agarwal, Gargi Dasgupta, Dennis A. Perpetua

{"title":"\"Learning Relevance\" as a Service for Improving Search Results in Technical Discussion Forums","authors":"Shubham Atreja, Shivali Agarwal, Gargi Dasgupta, Dennis A. Perpetua","doi":"10.1109/ICWS.2017.82","DOIUrl":"https://doi.org/10.1109/ICWS.2017.82","url":null,"abstract":"Search results in technical forums are typically keyword based. The relevance of a link is usually gauged by closest content match. However, it has been shown in literature that users' click behavior is an integral part of deciding the relevance of a search result. Moreover, it is not just the number of clicks that matter, but time spent on a clicked link, order in which the links were clicked etc. also play an important role in the relevance decision. In this paper, we have developed a service that analyzes the click logs of searches performed in the technical forums and learns the new relevance scores for the search results with respect to a query. The computation model for relevance is an optimization problem, the constraints for which have been designed based on real user behavior study. We ingested StackOverflow data for few domains and designed a QA style search to carry out the study. We have developed heuristics to solve the optimization problem and have validated the relevance model using user behavior simulations. The relevance model is shown to yield efficient, robust and effective rank order using DCG (discounted cumulative gains) and stability metrics.","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114242152","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

Security Mechanism for Packaged Web Applications 打包Web应用程序的安全机制

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.72

K. Das, P. Perumal, Joy Bose

引用次数: 1

SPEC2REST: An Approach for Eliciting Web API Resources from Existing Applications SPEC2REST:一种从现有应用程序中获取Web API资源的方法

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.119

Shridhar Choudhary, K. Kimura, Atsuji Sekiguchi

引用次数: 1

Expert as a Service: Software Expert Recommendation via Knowledge Domain Embeddings in Stack Overflow 专家即服务:基于知识域嵌入的堆栈溢出软件专家推荐

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.122

Chaoran Huang, Lina Yao, Xianzhi Wang, B. Benatallah, Quan Z. Sheng

{"title":"Expert as a Service: Software Expert Recommendation via Knowledge Domain Embeddings in Stack Overflow","authors":"Chaoran Huang, Lina Yao, Xianzhi Wang, B. Benatallah, Quan Z. Sheng","doi":"10.1109/ICWS.2017.122","DOIUrl":"https://doi.org/10.1109/ICWS.2017.122","url":null,"abstract":"Question answering (Q&A) communities have gained momentum recently as an effective means of knowledge sharing over the crowds, where many users are experts in the real-world and can make quality contributions in certain domains or technologies. Although the massive user-generated Q&A data present a valuable source of human knowledge, a related challenging issue is how to find those expert users effectively. In this paper, we propose a framework for finding such experts in a collaborative network. Accredited with recent works on distributed word representations, we are able to summarize text chunks from the semantics perspective and infer knowledge domains by clustering pre-trained word vectors. In particular, we exploit a graph-based clustering method for knowledge domain extraction and discern the shared latent factors using matrix factorization techniques. The proposed clustering method features requiring no post-processing of clustering indicators and the matrix factorization method is combined with the semantic similarity of the historical answers to conduct expertise ranking of users given a query. We use Stack Overflow, a website with a large group of users and a large number of posts on topics related to computer programming, to evaluate the proposed approach and conduct extensively experiments to show the effectiveness of our approach.","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121345040","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: 16

Recommending Services for New Mashups through Service Factors and Top-K Neighbors 通过服务因子和Top-K邻居为新mashup推荐服务

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.128

Priyanka Samanta, Xumin Liu

{"title":"Recommending Services for New Mashups through Service Factors and Top-K Neighbors","authors":"Priyanka Samanta, Xumin Liu","doi":"10.1109/ICWS.2017.128","DOIUrl":"https://doi.org/10.1109/ICWS.2017.128","url":null,"abstract":"One of the most interesting research directions in service computing is to leverage current recommendation system solutions to suggest web services for a mashup application. Existing approaches are mainly based on collaborative filtering techniques, which can suffer from the heavy rely on human input, data sparsity and cold start issues, resulting in low accuracy. In this paper, we leverage advanced probabilistic model based approaches to tackle these issues. Our solution is to make service recommendation based on the service features and historical usage. We use the Hierarchical Dirichlet Process (HDP), a nonparametric Bayesian approach to intelligently discover the functionally relevant services based on their specifications. We leverage Probabilistic Matrix Factorization (PMF) to recommend services based on historical usage and tackle the cold start issues for new mashups through their top-K neighbors. We integrate the suggesting results from these two approaches through the Bayesian theorem and take the indicator of quality of service into account to make the final suggestion. We compared our approach with some existing approaches using a real world data set and the result indicates that our approach performs the best.","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"85 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122318671","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: 21

GenServ: Genome Sequencing Services on Scalable Energy Efficient Accelerators GenServ:基于可扩展节能加速器的基因组测序服务

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.97

Chao Wang, Haijie Fang, Shiming Lei, Lei Gong, Aili Wang, Xi Li, Xuehai Zhou

{"title":"GenServ: Genome Sequencing Services on Scalable Energy Efficient Accelerators","authors":"Chao Wang, Haijie Fang, Shiming Lei, Lei Gong, Aili Wang, Xi Li, Xuehai Zhou","doi":"10.1109/ICWS.2017.97","DOIUrl":"https://doi.org/10.1109/ICWS.2017.97","url":null,"abstract":"As a traditional algorithm, the string match meets a challenge with the development of the massive volume of data be-cause of gene sequencing. Surveys show that there will be a huge amount of short read segments during the process of gene sequencing and the need for a highly efficient is urgent. The BWA is an effective algorithm to deal with the short read mapping. Compared with other short read mapping algorithms, the BWA algorithm has a smaller size, and this does not influence its effect. However, there is still not a system is used to accelerate the BWA algorithm especially. Thus we decide to build a system to expedite the algorithm and make it satisfied with the application of gene sequencing. In this paper, we present genome sequencing services on scalable energy-efficient accelerators. Especially, we first in-troduce the BWA algorithm and claim the reason for the choice of the algorithm. Then, we implement an accelerator based on FPGA to improve the performance of the algorithm. Com-pared to the other major platforms in accelerating the algo-rithm, we discuss the advantages of the FPGA platform and the limit of the other platform. Last, we build our hardware platform with a Xilinx ZYNQ FPGA development board, and the result shows that our accelerator can achieve a promising speedup and resource utilization and make it balanced be-tween power and cost.","PeriodicalId":235426,"journal":{"name":"2017 IEEE International Conference on Web Services (ICWS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222315","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: 2

Spotting Fake News: A Social Argumentation Framework for Scrutinizing Alternative Facts 发现假新闻:审查替代事实的社会论证框架

2017 IEEE International Conference on Web Services (ICWS) Pub Date : 2017-06-01 DOI: 10.1109/ICWS.2017.108

Ricky J. Sethi

引用次数: 11