Diego Rivera, N. Kushik, C. Fuenzalida, A. Cavalli, N. Yevtushenko
In this paper, we present a framework for evaluating the QoE of a service that includes functional and non-functional service requirements. Non-functional requirements are classified into objective, subjective, and business parameters that affect Quality of Service (QoS), Quality of Experience (QoE), and Quality of Business (QoBiz), correspondingly. As those metrics have a strong dependency between each other, we discuss how the QoE of a web-based Over-The-Top service (OTT) can be evaluated taking into account subjective, objective and business parameters. The functional service behavior is described by an Extended Finite State Machine (EFSM) in which non-functional objective, subjective and business-related parameters are tracked using context variables and corresponding updating functions. These parameters are used to evaluate the QoE of the service. We show that the corresponding model allows to keep a track of a user-service interaction. Moreover, the model of the service integrates subjective, objective and business parameters, and thus, can be applied to the QoE evaluation of any OTT service.
{"title":"QoE Evaluation Based on QoS and QoBiz Parameters Applied to an OTT Service","authors":"Diego Rivera, N. Kushik, C. Fuenzalida, A. Cavalli, N. Yevtushenko","doi":"10.1109/ICWS.2015.86","DOIUrl":"https://doi.org/10.1109/ICWS.2015.86","url":null,"abstract":"In this paper, we present a framework for evaluating the QoE of a service that includes functional and non-functional service requirements. Non-functional requirements are classified into objective, subjective, and business parameters that affect Quality of Service (QoS), Quality of Experience (QoE), and Quality of Business (QoBiz), correspondingly. As those metrics have a strong dependency between each other, we discuss how the QoE of a web-based Over-The-Top service (OTT) can be evaluated taking into account subjective, objective and business parameters. The functional service behavior is described by an Extended Finite State Machine (EFSM) in which non-functional objective, subjective and business-related parameters are tracked using context variables and corresponding updating functions. These parameters are used to evaluate the QoE of the service. We show that the corresponding model allows to keep a track of a user-service interaction. Moreover, the model of the service integrates subjective, objective and business parameters, and thus, can be applied to the QoE evaluation of any OTT service.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125229323","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}
The emergence of ubiquitous computing, and the wide adoption of smart phones over the past few years require many Web services to function in a context-aware manner. In such services, not only the functional attributes, but also the QoS attributes (e.g., Response time and availability) also depend on the context of the service. Trust (i.e., The degree of compliance of a service to its specification) and the QoS evaluation of a service and a system composed of such services should also consider these context dependencies. Our work proposes a model that uses such context-QoS dependency information of individual services and inter-service interaction patterns to get predictions for the QoS and trust of service compositions at the design phase. The predictions can be used to make better design and implementation decisions of composed systems in early phases of the software lifecycle thereby reducing cost, time and effort. The preliminary results show that the proposed framework provides more accurate predictions than the prevalent approaches.
{"title":"A QoS and Trust Prediction Framework for Context-Aware Composed Distributed Systems","authors":"Dimuthu Gamage, Lahiru S. Gallege, R. Raje","doi":"10.1109/ICWS.2015.16","DOIUrl":"https://doi.org/10.1109/ICWS.2015.16","url":null,"abstract":"The emergence of ubiquitous computing, and the wide adoption of smart phones over the past few years require many Web services to function in a context-aware manner. In such services, not only the functional attributes, but also the QoS attributes (e.g., Response time and availability) also depend on the context of the service. Trust (i.e., The degree of compliance of a service to its specification) and the QoS evaluation of a service and a system composed of such services should also consider these context dependencies. Our work proposes a model that uses such context-QoS dependency information of individual services and inter-service interaction patterns to get predictions for the QoS and trust of service compositions at the design phase. The predictions can be used to make better design and implementation decisions of composed systems in early phases of the software lifecycle thereby reducing cost, time and effort. The preliminary results show that the proposed framework provides more accurate predictions than the prevalent approaches.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126501244","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}
REST Chart is a Petri-Net based XML modeling framework for REST API. This paper presents two important enhancements and extensions to REST Chart modeling - Hyperlink Decoration and Hierarchical REST Chart. In particular, the proposed Hyperlink Decoration decomposes resource connections from resource representation, such that hyperlinks can be defined independently of schemas. This allows a Navigation-First Design by which the important global connections of a REST API can be designed first and reused before the local resource representations are implemented and specified. Hierarchical REST Chart is a powerful mechanism to rapidly decompose and extend a REST API in several dimensions based on Hyperlink Decoration. These new mechanisms can be used to manage the complexities in large scale REST APIs that undergo frequent changes as in some large scale open source development projects. This paper shows that these new capabilities can fit nicely in the REST Chart XML with very minor syntax changes. These enhancements to REST Chart are applied successfully in designing and verifying REST APIs for software-defined-networking (SDN) and Cloud computing.
REST Chart是一个基于Petri-Net的REST API XML建模框架。本文提出了对REST图建模的两个重要增强和扩展——超链接修饰和分层REST图。特别地，建议的超链接装饰将资源连接从资源表示中分解，这样就可以独立于模式定义超链接。这允许导航优先设计，通过这种设计，可以首先设计REST API的重要全局连接，并在实现和指定本地资源表示之前重用它们。分层REST图是一种强大的机制，可以基于超链接装饰在多个维度上快速分解和扩展REST API。这些新机制可用于管理大型REST api中的复杂性，这些api在一些大型开源开发项目中经常发生变化。本文表明，这些新功能可以很好地适应REST Chart XML，只需对语法进行很小的更改。这些对REST图的增强成功地应用于设计和验证软件定义网络(SDN)和云计算的REST api。
{"title":"Designing Large Scale REST APIs Based on REST Chart","authors":"Li Li, W. Chou","doi":"10.1109/ICWS.2015.89","DOIUrl":"https://doi.org/10.1109/ICWS.2015.89","url":null,"abstract":"REST Chart is a Petri-Net based XML modeling framework for REST API. This paper presents two important enhancements and extensions to REST Chart modeling - Hyperlink Decoration and Hierarchical REST Chart. In particular, the proposed Hyperlink Decoration decomposes resource connections from resource representation, such that hyperlinks can be defined independently of schemas. This allows a Navigation-First Design by which the important global connections of a REST API can be designed first and reused before the local resource representations are implemented and specified. Hierarchical REST Chart is a powerful mechanism to rapidly decompose and extend a REST API in several dimensions based on Hyperlink Decoration. These new mechanisms can be used to manage the complexities in large scale REST APIs that undergo frequent changes as in some large scale open source development projects. This paper shows that these new capabilities can fit nicely in the REST Chart XML with very minor syntax changes. These enhancements to REST Chart are applied successfully in designing and verifying REST APIs for software-defined-networking (SDN) and Cloud computing.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129424375","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}
Wei Xiong, Bing Li, Xiaohui Cui, Yutao Ma, Rong Yang, Peng He
Service computing is a popular development paradigm in information technology. The functional properties of Web services assure correct functionality of cloud applications, while the nonfunctional properties such as reliability might significantly influence the user-perceived availability evaluation. Reliability rankings provide valuable information for making optimal cloud service selection from a set of functionally-equivalent candidate services. There existed several approaches that can conduct reliability ranking prediction for Web services. Those approaches acquire different rankings with different preference functions. It is arduous to determine whether there exists the best one in them, and what is the best one if not. This paper proposes a learning approach to reliability ranking prediction for Web services which utilizes past service invocation logs to train preference function. To validate the proposed approach, large-scale experiments are conducted based on a real-world Web service dataset, WSDream. The results show that our proposed approach achieves higher prediction accuracy than the existing approaches.
{"title":"A Learning Approach to the Prediction of Reliability Ranking for Web Services","authors":"Wei Xiong, Bing Li, Xiaohui Cui, Yutao Ma, Rong Yang, Peng He","doi":"10.1109/ICWS.2015.32","DOIUrl":"https://doi.org/10.1109/ICWS.2015.32","url":null,"abstract":"Service computing is a popular development paradigm in information technology. The functional properties of Web services assure correct functionality of cloud applications, while the nonfunctional properties such as reliability might significantly influence the user-perceived availability evaluation. Reliability rankings provide valuable information for making optimal cloud service selection from a set of functionally-equivalent candidate services. There existed several approaches that can conduct reliability ranking prediction for Web services. Those approaches acquire different rankings with different preference functions. It is arduous to determine whether there exists the best one in them, and what is the best one if not. This paper proposes a learning approach to reliability ranking prediction for Web services which utilizes past service invocation logs to train preference function. To validate the proposed approach, large-scale experiments are conducted based on a real-world Web service dataset, WSDream. The results show that our proposed approach achieves higher prediction accuracy than the existing approaches.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130881123","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}
Application Programming Interfaces (APIs), which are emerging web services in general, are increasing with a rapid speed in recent years. With so many APIs, many management platforms have been developed and deployed, leading to the boom of API markets, that are similar to the mobile App markets. Meanwhile, it has become more and more difficult to select and manage APIs. In reality, most existing management platforms typically recommend currently popular APIs to developers. However, the fact that popularity of API varies over time is ignored in those platforms, leading to the difficulty of recommending APIs that are just released but may be popular in the near future. To tackle this challenge, an approach of predicting the popularity of APIs is proposed in this paper. Predicting the popularity of API can not only be used for API ranking, recommendation and selection, but also make it more convenient for API providers and consumers to manage or select API respectively. In this paper, we propose a time-aware linear model to predict the API popularity, using time series feature of APIs and API's self-features such as its' provider ranking and description features, which are called heterogeneous features in our paper. Comprehensive experiments have been conducted on a real-world Programmable Web dataset with 613 real APIs. The experimental results show that our model has a better performance, when compared with some other state-of-the-art prediction models.
{"title":"Time-Aware API Popularity Prediction via Heterogeneous Features","authors":"Yao Wan, Liang Chen, Jian Wu, Qi Yu","doi":"10.1109/ICWS.2015.63","DOIUrl":"https://doi.org/10.1109/ICWS.2015.63","url":null,"abstract":"Application Programming Interfaces (APIs), which are emerging web services in general, are increasing with a rapid speed in recent years. With so many APIs, many management platforms have been developed and deployed, leading to the boom of API markets, that are similar to the mobile App markets. Meanwhile, it has become more and more difficult to select and manage APIs. In reality, most existing management platforms typically recommend currently popular APIs to developers. However, the fact that popularity of API varies over time is ignored in those platforms, leading to the difficulty of recommending APIs that are just released but may be popular in the near future. To tackle this challenge, an approach of predicting the popularity of APIs is proposed in this paper. Predicting the popularity of API can not only be used for API ranking, recommendation and selection, but also make it more convenient for API providers and consumers to manage or select API respectively. In this paper, we propose a time-aware linear model to predict the API popularity, using time series feature of APIs and API's self-features such as its' provider ranking and description features, which are called heterogeneous features in our paper. Comprehensive experiments have been conducted on a real-world Programmable Web dataset with 613 real APIs. The experimental results show that our model has a better performance, when compared with some other state-of-the-art prediction models.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126916612","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}
One of the major goals of Web services is to make easier their composition to form more complex services, modeled as workflows. A key role in the Web services composition is the selection of a proper service for each activity in the workflow. In general, this requires the exchange of sensitive information of users, requiring the composition, as well as of involved service providers. So far this problem has been investigated in the setting of orchestrated service composition, under the assumption of the presence of a broker coordinating the composition. However, a promising alternative approach is the one of choreography, where each service involved in the service composition has to locally manage service selection and invocation. In this paper, we propose a framework to enforce user and provider requirements in the scenario of service choreography in a privacy-preserving way, that is, without the releasing of any private information of users and providers. To achieve this result we make use of different privacy-preserving protocols. As it will be shown in the paper, the proposed solution does not implies relevant overhead.
{"title":"A Privacy-Preserving Framework for Constrained Choreographed Service Composition","authors":"B. Carminati, E. Ferrari, N. Tran","doi":"10.1109/ICWS.2015.48","DOIUrl":"https://doi.org/10.1109/ICWS.2015.48","url":null,"abstract":"One of the major goals of Web services is to make easier their composition to form more complex services, modeled as workflows. A key role in the Web services composition is the selection of a proper service for each activity in the workflow. In general, this requires the exchange of sensitive information of users, requiring the composition, as well as of involved service providers. So far this problem has been investigated in the setting of orchestrated service composition, under the assumption of the presence of a broker coordinating the composition. However, a promising alternative approach is the one of choreography, where each service involved in the service composition has to locally manage service selection and invocation. In this paper, we propose a framework to enforce user and provider requirements in the scenario of service choreography in a privacy-preserving way, that is, without the releasing of any private information of users and providers. To achieve this result we make use of different privacy-preserving protocols. As it will be shown in the paper, the proposed solution does not implies relevant overhead.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125703247","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 rapid adoption of Service Oriented Architecture (SOA), increasingly more application-level services are developed through composing service components offered by different service providers. While such application development mode offers advantages in terms of cost-effectiveness and flexibility, application developers cannot understand or deal with risks potentially resulting from vulnerabilities within composed services due to non-transparency of the service providers. Furthermore, some of the vulnerabilities in practice are deeply hidden in dependency structures underlying composed services, thus making even the service providers fail to know the vulnerabilities. This paper proposes a risk-evaluation assisted service selection system, called Risk Evaluation-as-a-Service(or REaaS), which aims to assist application developers to understand vulnerability risks hidden within alternative services when the developers at first attempt to adopt their applications. In particular, for a given application developer's service selection requirement, REaaS produces a ranking list based upon vulnerability risks of alternative services to serve as a guideline regarding which service has the lowest potential risks (e.g., Bugs) for this application deployment. REaaS achieves this goal through the following three steps: 1) generating a package dependency graph for each alternative service, 2) assigning threat-degrees to packages in each dependency graph, and 3) analyzing each dependency graph and evaluating service-risk of each service. We have built a REaaS prototype and used real case study to demonstrate the practicality of REaaS.
{"title":"A Risk-Evaluation Assisted System for Service Selection","authors":"Ennan Zhai, Liang Gu, Yumei Hai","doi":"10.1109/ICWS.2015.94","DOIUrl":"https://doi.org/10.1109/ICWS.2015.94","url":null,"abstract":"With the rapid adoption of Service Oriented Architecture (SOA), increasingly more application-level services are developed through composing service components offered by different service providers. While such application development mode offers advantages in terms of cost-effectiveness and flexibility, application developers cannot understand or deal with risks potentially resulting from vulnerabilities within composed services due to non-transparency of the service providers. Furthermore, some of the vulnerabilities in practice are deeply hidden in dependency structures underlying composed services, thus making even the service providers fail to know the vulnerabilities. This paper proposes a risk-evaluation assisted service selection system, called Risk Evaluation-as-a-Service(or REaaS), which aims to assist application developers to understand vulnerability risks hidden within alternative services when the developers at first attempt to adopt their applications. In particular, for a given application developer's service selection requirement, REaaS produces a ranking list based upon vulnerability risks of alternative services to serve as a guideline regarding which service has the lowest potential risks (e.g., Bugs) for this application deployment. REaaS achieves this goal through the following three steps: 1) generating a package dependency graph for each alternative service, 2) assigning threat-degrees to packages in each dependency graph, and 3) analyzing each dependency graph and evaluating service-risk of each service. We have built a REaaS prototype and used real case study to demonstrate the practicality of REaaS.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130446619","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}
The increasing availability of positioning data from mobile devices facilitates new opportunities for location analytics systems, which provide insights into the movement behavior of targets across various localities. Similar to web analytics systems, positioning data can be utilized to count, for example, returning visitors in venues, calculate visit frequencies for certain time intervals, or to identify typical movement paths for different groups of visitors inside and outside buildings. However, a major challenge for location analytics is still to deal with the heterogeneity of data from various positioning systems. In thispaper we present a platform that enables location analytics as a service and copes with the heterogeneous spatiotemporal data of diverse accuracy, frequency, and coverage. Furthermore, it allows to query large positioning datasets according to various data dimensions and metrics. In an additional four-month field trial the applicability of our approach was reviewed using the example of WLAN positioning data from an office environment.
{"title":"Location Analytics as a Service: Providing Insights for Heterogeneous Spatiotemporal Data","authors":"B. Deva, Peter Ruppel","doi":"10.1109/ICWS.2015.114","DOIUrl":"https://doi.org/10.1109/ICWS.2015.114","url":null,"abstract":"The increasing availability of positioning data from mobile devices facilitates new opportunities for location analytics systems, which provide insights into the movement behavior of targets across various localities. Similar to web analytics systems, positioning data can be utilized to count, for example, returning visitors in venues, calculate visit frequencies for certain time intervals, or to identify typical movement paths for different groups of visitors inside and outside buildings. However, a major challenge for location analytics is still to deal with the heterogeneity of data from various positioning systems. In thispaper we present a platform that enables location analytics as a service and copes with the heterogeneous spatiotemporal data of diverse accuracy, frequency, and coverage. Furthermore, it allows to query large positioning datasets according to various data dimensions and metrics. In an additional four-month field trial the applicability of our approach was reviewed using the example of WLAN positioning data from an office environment.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116552564","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}
Zhaotai Pan, X. Liang, Yu Chen Zhou, Y. Ge, G. Zhao
Push notification is an important approach to distribute interesting information to users timely. With the fast development of mobile devices and mobile applications, push notification is getting more and more popular. The convergence of mobile and IoT also bring new challenges on how the system can handle the mixed push channels designed for M2M communication and human interaction, and enable the effective interaction with both human and IoT devices involved. IoT devices may push notifications of sensor data in a high frequency. To enable push notification for both of mobile devices and IoT devices, the push notification system is required to achieve high throughput to handle the frequent notifications, and support content matching to filter out the undesired notifications. To enable effective push notification with both human and IoT devices involved, the system is required to understand the users' interests for notifications with the IoT devices providing the users' contexts. That is to say users need an intelligent push notification system. In this paper we propose a high performance context-aware push notification system for the converged mobile and IoT messaging. We designed high performance content matching engine as the core to enable efficient message dispatching for push notification according to highly personalized interest to ensure IoT messages to be involved in push notification. A user's interest of notifications is highly related with his context. Therefore, based on the content-matching engine, a framework for efficient context information fusion is built to support various types of context-aware push notification, towards intelligent push notification. Also we designed shared connection scheme to reduce the resource cost. Based on the content-match engine and context-aware features, the proposed push notification service can support both of group push notification and bi-directional push notification. Tests are conducted for performance evaluation.
{"title":"Intelligent Push Notification for Converged Mobile Computing and Internet of Things","authors":"Zhaotai Pan, X. Liang, Yu Chen Zhou, Y. Ge, G. Zhao","doi":"10.1109/ICWS.2015.92","DOIUrl":"https://doi.org/10.1109/ICWS.2015.92","url":null,"abstract":"Push notification is an important approach to distribute interesting information to users timely. With the fast development of mobile devices and mobile applications, push notification is getting more and more popular. The convergence of mobile and IoT also bring new challenges on how the system can handle the mixed push channels designed for M2M communication and human interaction, and enable the effective interaction with both human and IoT devices involved. IoT devices may push notifications of sensor data in a high frequency. To enable push notification for both of mobile devices and IoT devices, the push notification system is required to achieve high throughput to handle the frequent notifications, and support content matching to filter out the undesired notifications. To enable effective push notification with both human and IoT devices involved, the system is required to understand the users' interests for notifications with the IoT devices providing the users' contexts. That is to say users need an intelligent push notification system. In this paper we propose a high performance context-aware push notification system for the converged mobile and IoT messaging. We designed high performance content matching engine as the core to enable efficient message dispatching for push notification according to highly personalized interest to ensure IoT messages to be involved in push notification. A user's interest of notifications is highly related with his context. Therefore, based on the content-matching engine, a framework for efficient context information fusion is built to support various types of context-aware push notification, towards intelligent push notification. Also we designed shared connection scheme to reduce the resource cost. Based on the content-match engine and context-aware features, the proposed push notification service can support both of group push notification and bi-directional push notification. Tests are conducted for performance evaluation.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132829810","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}
V. P. Modekurthy, K. K. Fletcher, Xiaoqing Frank Liu, M. Leu
The growing number of Additive Manufacturing Web (AMW) services, offered by different providers over the Internet, makes it challenging for consumers to compare these AMW services to select a service of their choice. In addition, it is even more challenging for consumers to compare these AMW services against their personal preferences. This is because, consumers personal preferences on multiple non-functional attributes such as price, material, accuracy and schedule, should be considered for AMW service selection. The decentralized nature of AMW services coupled by the need to consider consumers personal preferences during AMW service selection, requires a system that will serve as a broker between AMW services and consumers. In this paper, we propose a service broker system for AMW services that provides consumers with a single point of access to a large number of AMW services from many additive manufacturing service providers. This broker system also incorporates the first real application of service selection with fuzzy logic based personalized preferences and trade-off. We develop a method to generate fuzzy membership functions for each non-functional attribute. This makes it easy for consumers to specify their fuzzy membership functions. Finally, we present an application case study to demonstrate the feasibility of brokerage in AMW services and also evaluate our method in terms of performance.
{"title":"Personal Preference and Trade-Off Based Additive Manufacturing Web Service Selection","authors":"V. P. Modekurthy, K. K. Fletcher, Xiaoqing Frank Liu, M. Leu","doi":"10.1109/ICWS.2015.65","DOIUrl":"https://doi.org/10.1109/ICWS.2015.65","url":null,"abstract":"The growing number of Additive Manufacturing Web (AMW) services, offered by different providers over the Internet, makes it challenging for consumers to compare these AMW services to select a service of their choice. In addition, it is even more challenging for consumers to compare these AMW services against their personal preferences. This is because, consumers personal preferences on multiple non-functional attributes such as price, material, accuracy and schedule, should be considered for AMW service selection. The decentralized nature of AMW services coupled by the need to consider consumers personal preferences during AMW service selection, requires a system that will serve as a broker between AMW services and consumers. In this paper, we propose a service broker system for AMW services that provides consumers with a single point of access to a large number of AMW services from many additive manufacturing service providers. This broker system also incorporates the first real application of service selection with fuzzy logic based personalized preferences and trade-off. We develop a method to generate fuzzy membership functions for each non-functional attribute. This makes it easy for consumers to specify their fuzzy membership functions. Finally, we present an application case study to demonstrate the feasibility of brokerage in AMW services and also evaluate our method in terms of performance.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133114980","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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