2018 IEEE International Conference on Web Services (ICWS)最新文献

High Performance Visual Inspection Service Architecture - Squeezing the Most Out of Commodity Servers 高性能视觉检测服务架构——最大限度地利用商品服务器

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00065

G. Hu, Peng Ji, Jun Zhu, Bowen Wei, Zhe Yan, Lei He

引用次数: 1

Personalized LSTM Based Matrix Factorization for Online QoS Prediction 基于个性化LSTM的矩阵分解在线QoS预测

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00012

Ruibin Xiong, Jian Wang, Zhongqiao Li, Bing Li, P. Hung

引用次数: 28

URoad: An Efficient Algorithm for Large-Scale Dynamic Ridesharing Service 大规模动态拼车服务的高效算法

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00009

Jing Fan, Jinting Xu, Chenyu Hou, Bin Cao, Tianyang Dong, Shiwei Cheng

{"title":"URoad: An Efficient Algorithm for Large-Scale Dynamic Ridesharing Service","authors":"Jing Fan, Jinting Xu, Chenyu Hou, Bin Cao, Tianyang Dong, Shiwei Cheng","doi":"10.1109/ICWS.2018.00009","DOIUrl":"https://doi.org/10.1109/ICWS.2018.00009","url":null,"abstract":"Nowadays, although there exists many ridesharing services and dynamic matching algorithms for passengers and drivers, there is no service or algorithm that can balance the benefit of passengers and drivers while taking their time and cost constraints into consideration. In this paper, we try to solve the dynamic ridesharing problem by considering all above factors for all the participants. To this end, we present URoad, an efficient algorithm for large-scale dynamic ridesharing service, where a new price cost model is carefully designed to make up for the shortcomings of existing algorithms, and in the meantime a corresponding efficient matching algorithm is proposed to satisfy both the time and cost constraints of passengers and drivers. Specifically, for a given passenger, URoad will find out the optimal driver who can satisfy all the constraints of the passenger and the driver with the minimum detour distance. We design a series of data structures to speed up URoad for large scale ridesharing service application, e.g., Time Index, Grid Index and Greedy Strategy. Through extensive experiments, we prove that URoad can find the optimal driver for a given passenger from more than one hundred thousand drivers within 0.5 second in average.","PeriodicalId":231056,"journal":{"name":"2018 IEEE International Conference on Web Services (ICWS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124819901","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

Confidential Business Process Execution on Blockchain 区块链上的机密业务流程执行

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00015

B. Carminati, Christian Rondanini, E. Ferrari

引用次数: 26

MeCo-TSM: Multi-Entity Complex Process-Oriented Service Modeling Method 多实体复杂面向过程的服务建模方法

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00018

Ying Li, Meng Xi, Yuyu Yin, Zhiling Luo, Honghao Gao, Jianwei Yin

{"title":"MeCo-TSM: Multi-Entity Complex Process-Oriented Service Modeling Method","authors":"Ying Li, Meng Xi, Yuyu Yin, Zhiling Luo, Honghao Gao, Jianwei Yin","doi":"10.1109/ICWS.2018.00018","DOIUrl":"https://doi.org/10.1109/ICWS.2018.00018","url":null,"abstract":"In the modern service industry, both service processes and data structures are becoming increasingly diverse and complex. In addition, interdependences exist among data, such that the use of \"shoe size\" data must be based on the \"type of goods\" data returning \"shoe\". This is also observed for the functions and interfaces in a system, as one can use the function \"order payment\" only after the function \"order generation\". This kind of phenomenon is rather common in service systems nowadays, especially when the service is a transboundary service such as the new retail proposed by Jack Ma. Traditional modeling methods have difficulties in handling such scenarios. There have been studies on service modeling over the past several years, and they have focused mainly on the service processes and interactions among services. In this work, we construct MeCo-TSM based on three sub-models to handle multi-entity complex service process. We verify our model in the real processes of our cooperation company and compare it with related works. MeCo-TSM supports the service better in our cases and shows satisfactory efficiency, effectiveness and reusability.","PeriodicalId":231056,"journal":{"name":"2018 IEEE International Conference on Web Services (ICWS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116882720","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

CommuteShare: A Ridesharing Service for Daily Commuters Using Cross-Domain Urban Big Data 通勤共享:利用跨域城市大数据为日常通勤者提供拼车服务

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00046

Xiaoliang Fan, Chang Xu, Fang Tang, Jianzhong Qi, Xiao Liu, Longbiao Chen, Cheng Wang

{"title":"CommuteShare: A Ridesharing Service for Daily Commuters Using Cross-Domain Urban Big Data","authors":"Xiaoliang Fan, Chang Xu, Fang Tang, Jianzhong Qi, Xiao Liu, Longbiao Chen, Cheng Wang","doi":"10.1109/ICWS.2018.00046","DOIUrl":"https://doi.org/10.1109/ICWS.2018.00046","url":null,"abstract":"Existing ridesharing services have focused on on-demand trip matching, which resembles traditional taxi dispatching. This may encourage more private vehicles on the road, which aggravate traffic congestions in peak hours rather than alleviating them. We propose CommuteShare, a novel ridesharing service for daily commuters that encourages long-term ridesharing among commuters with similar commuting patterns, to increase the traffic efficiency in peak hours. We first identify commuting private vehicles (CPVs) from traffic records and model their commuting patterns. We then design a dynamic model to formulate the intention level of a CPV driver to offer a ride based on the spatio-temporal convenience and dynamic traffic conditions. Based on the commuting patterns of the CPVs and the dynamic model of the CPV drivers, we propose a ridesharing algorithm to compute ridesharing matches among CPVs. We perform extensive experiments on three real-world cross-domain urban big datasets from a major city of China. Experimental results show that, using the proposed CommuteShare service, over 5,300 private vehicles can be reduced daily on average during morning peak hours, with a reduction of 7-minute average waiting time for the riders.","PeriodicalId":231056,"journal":{"name":"2018 IEEE International Conference on Web Services (ICWS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125829620","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

Quality Based Data Integration for Enriching User Data Sources in Service Lakes 基于质量的数据集成，丰富服务湖用户数据源

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00028

H. Alili, Khalid Belhajjame, Rim Drira, Daniela Grigori, H. Ghézala

引用次数: 4

DKEM: A Distributed Knowledge Based Evolution Model for Service Ecosystem DKEM:基于知识的分布式服务生态系统演化模型

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00008

Xianghui Wang, Zhiyong Feng, Shizhan Chen, Keman Huang

{"title":"DKEM: A Distributed Knowledge Based Evolution Model for Service Ecosystem","authors":"Xianghui Wang, Zhiyong Feng, Shizhan Chen, Keman Huang","doi":"10.1109/ICWS.2018.00008","DOIUrl":"https://doi.org/10.1109/ICWS.2018.00008","url":null,"abstract":"With the popularity of cloud computing and micro service architectures, various service ecosystems including services, venders, and service-based processes continuously emerge on Internet or in an enterprise. Semantics of services from different venders may be described by distributed domain ontologies. Distributed knowledge brings difficulty to competition and cooperation among services, and hampers the evolution of a service ecosystem. In this paper, we propose a distributed knowledge based evolution model (DKEM) to promote competition and cooperation among services from different venders. DKEM considers stability as key factor in competition, and a stability evaluation model is designed to compute stability of services, venders, and service-based processes according to service invocation histories. Based on the evaluation model, two evolution patterns are given, and they can automatically explore new and more stable cooperation among services by means of runtime self-adaption mechanism. A prototype system for DKEM is implemented and a series of experiments show that DKEM is effective for competition and cooperation among services with distributed knowledge, and, evolved processes have higher stability and response efficiency.","PeriodicalId":231056,"journal":{"name":"2018 IEEE International Conference on Web Services (ICWS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129539552","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: 13

Adaptive Cache Replacement in Efficiently Querying Semantic Big Data 语义大数据高效查询中的自适应缓存替换

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00063

Usman Akhtar, Sungyoung Lee

{"title":"Adaptive Cache Replacement in Efficiently Querying Semantic Big Data","authors":"Usman Akhtar, Sungyoung Lee","doi":"10.1109/ICWS.2018.00063","DOIUrl":"https://doi.org/10.1109/ICWS.2018.00063","url":null,"abstract":"This paper addresses the problem of querying Knowledge bases (KBs) that store semantic big data. For efficiently querying data the most important factor is cache replacement policy, which determines the overall query response. As cache is limited in size, less frequently accessed data should be removed to provide more space to hot triples (frequently accessed). So, to achieve a similar performance to RDBMS, we proposed an Adaptive Cache Replacement (ACR) policy that predict the hot triples from query log. Moreover, performance bottleneck of triplestore, makes realworld application difficult. To achieve a closer performance similar to RDBMS, we have proposed an Adaptive Cache Replacement (ACR) policy that predict the hot triples from query log. Our proposed algorithm effectively replaces cache with high accuracy. To implement cache replacement policy, we have applied exponential smoothing, a forecast method, to collect most frequently accessed triples. The evaluation result shows that the proposed scheme outperforms the existing cache replacement policies, such as LRU (least recently used) and LFU (least frequently used), in terms of higher hit rates and less time overhead.","PeriodicalId":231056,"journal":{"name":"2018 IEEE International Conference on Web Services (ICWS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129179519","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

HPC2-ARS: An Architecture for Real-Time Analytic of Big Data Streams HPC2-ARS:用于大数据流实时分析的架构

2018 IEEE International Conference on Web Services (ICWS) Pub Date : 2018-07-01 DOI: 10.1109/ICWS.2018.00051

Yingchao Cheng, Z. Hao, Ruichu Cai, Wen Wen

引用次数: 3