Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.74
K. Ravindran
Given cloud-based realization of a distributed system S, QoS auditing enables risk analysis and accounting of SLA violations under various security threats and resource depletions faced by S. The problem of QoS failures and security infringements arises due to the third-party control of cloud resources and components that are used in realizing the application-oriented service exported by S. The less-than-100% trust between the various sub-systems of S is a major issue that necessitates a probabilistic analysis of the application behavior relative to the SLA negotiated with S. In this light, QoS auditing allows reasoning about how good the SLA is complied by S in the face of hostile environment conditions. The paper describes case studies of CDN and replicated web service realized on a cloud.
{"title":"QoS Auditing for Evaluation of SLA in Cloud-based Distributed Services","authors":"K. Ravindran","doi":"10.1109/SERVICES.2013.74","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.74","url":null,"abstract":"Given cloud-based realization of a distributed system S, QoS auditing enables risk analysis and accounting of SLA violations under various security threats and resource depletions faced by S. The problem of QoS failures and security infringements arises due to the third-party control of cloud resources and components that are used in realizing the application-oriented service exported by S. The less-than-100% trust between the various sub-systems of S is a major issue that necessitates a probabilistic analysis of the application behavior relative to the SLA negotiated with S. In this light, QoS auditing allows reasoning about how good the SLA is complied by S in the face of hostile environment conditions. The paper describes case studies of CDN and replicated web service realized on a cloud.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116482560","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.32
Artem Chebotko, John Abraham, P. Brazier, Anthony Piazza, A. Kashlev, Shiyong Lu
Provenance, which records the history of an in-silico experiment, has been identified as an important requirement for scientific workflows to support scientific discovery reproducibility, result interpretation, and problem diagnosis. Large provenance datasets are composed of many smaller provenance graphs, each of which corresponds to a single workflow execution. In this work, we explore and address the challenge of efficient and scalable storage and querying of large collections of provenance graphs serialized as RDF graphs in an Apache HBase database. Specifically, we propose: (i) novel storage and indexing techniques for RDF data in HBase that are better suited for provenance datasets rather than generic RDF graphs and (ii) novel SPARQL query evaluation algorithms that solely rely on indices to compute expensive join operations, make use of numeric values that represent triple positions rather than actual triples, and eliminate the need for intermediate data transfers over a network. The empirical evaluation of our algorithms using provenance datasets and queries of the University of Texas Provenance Benchmark confirms that our approach is efficient and scalable.
{"title":"Storing, Indexing and Querying Large Provenance Data Sets as RDF Graphs in Apache HBase","authors":"Artem Chebotko, John Abraham, P. Brazier, Anthony Piazza, A. Kashlev, Shiyong Lu","doi":"10.1109/SERVICES.2013.32","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.32","url":null,"abstract":"Provenance, which records the history of an in-silico experiment, has been identified as an important requirement for scientific workflows to support scientific discovery reproducibility, result interpretation, and problem diagnosis. Large provenance datasets are composed of many smaller provenance graphs, each of which corresponds to a single workflow execution. In this work, we explore and address the challenge of efficient and scalable storage and querying of large collections of provenance graphs serialized as RDF graphs in an Apache HBase database. Specifically, we propose: (i) novel storage and indexing techniques for RDF data in HBase that are better suited for provenance datasets rather than generic RDF graphs and (ii) novel SPARQL query evaluation algorithms that solely rely on indices to compute expensive join operations, make use of numeric values that represent triple positions rather than actual triples, and eliminate the need for intermediate data transfers over a network. The empirical evaluation of our algorithms using provenance datasets and queries of the University of Texas Provenance Benchmark confirms that our approach is efficient and scalable.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114781535","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.77
Fangfang Yuan, Lidong Zhai, Yanan Cao, Li Guo
In this paper, we proposed an intrusion detection system for detecting anomaly on Android smartphones. The intrusion detection system continuously monitors and collects the information of smartphone under normal conditions and attack state. It extracts various features obtained from the Android system, such as the network traffic of smartphones, battery consumption, CPU usage, the amount of running processes and so on. Then, it applies Bayes Classifying Algorithm to determine whether there is an invasion. In order to further analyze the Android system abnormalities and locate malicious software, along with system state monitoring the intrusion detection system monitors the process and network flow of the smartphone. Finally, experiments on the system which was designed in this paper have been carried out. Empirical results suggest that the proposed intrusion detection system is effective in detecting anomaly on Android smartphones.
{"title":"Research of Intrusion Detection System on Android","authors":"Fangfang Yuan, Lidong Zhai, Yanan Cao, Li Guo","doi":"10.1109/SERVICES.2013.77","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.77","url":null,"abstract":"In this paper, we proposed an intrusion detection system for detecting anomaly on Android smartphones. The intrusion detection system continuously monitors and collects the information of smartphone under normal conditions and attack state. It extracts various features obtained from the Android system, such as the network traffic of smartphones, battery consumption, CPU usage, the amount of running processes and so on. Then, it applies Bayes Classifying Algorithm to determine whether there is an invasion. In order to further analyze the Android system abnormalities and locate malicious software, along with system state monitoring the intrusion detection system monitors the process and network flow of the smartphone. Finally, experiments on the system which was designed in this paper have been carried out. Empirical results suggest that the proposed intrusion detection system is effective in detecting anomaly on Android smartphones.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129408317","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.63
Nabil El Ioini, A. Sillitti, G. Succi
Web Services (WS) are software components accessible over the Internet through a well-defined set of standards. When consumers invoke a service, they expect to receive a valid response. However, the problem is to determine the structure of a valid request [21]. WS specifications are used to solve this problem since they are considered the primary piece of information for building service requests. Unfortunately, existing specifications do not provide enough support for this type information (e.g., WSDL) or there is little support on the client side (e.g., OWL-S). In this paper we address this issue by implementing a technique to reduce the number of faulty requests. We specifically propose an approach for extending WSDL with service input parameters rules that help consumers and integrators to verify their calls on the client side.
{"title":"Using Rules for Web Service Client Side Testing","authors":"Nabil El Ioini, A. Sillitti, G. Succi","doi":"10.1109/SERVICES.2013.63","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.63","url":null,"abstract":"Web Services (WS) are software components accessible over the Internet through a well-defined set of standards. When consumers invoke a service, they expect to receive a valid response. However, the problem is to determine the structure of a valid request [21]. WS specifications are used to solve this problem since they are considered the primary piece of information for building service requests. Unfortunately, existing specifications do not provide enough support for this type information (e.g., WSDL) or there is little support on the client side (e.g., OWL-S). In this paper we address this issue by implementing a technique to reduce the number of faulty requests. We specifically propose an approach for extending WSDL with service input parameters rules that help consumers and integrators to verify their calls on the client side.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123384099","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.78
Zhijie Li, Ming Li
Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.
{"title":"A Hierarchical Cloud Pricing System","authors":"Zhijie Li, Ming Li","doi":"10.1109/SERVICES.2013.78","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.78","url":null,"abstract":"Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133057044","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.11
Brian Xu, S. Kumar, Manonmani Kumar
To address the current need of innovative technologies that blend rapid data processing capabilities of computers with intuitive decision making skills of humans, we have developed a prototype of Cloud Enabled Brain Computer Interface (CEB) decision making technologies. The implemented architecture integrates cloud enabled big data analytics capabilities, networked BCI (Brain Computer Interface) devices, and Decision Making Engine. The novel CEB technology comprises of 1. Cloud-enabled BCI (Brain-Computer Interface) headsets, which is developed and networked in a cloud to enable rapid decision making and 2. Genetic algorithm based decision making engine, to intelligently assist the users in decision making; Advantage of our architecture is that when CEB loads the data, it will automatically recommend the best applicable Machine Learning (ML) algorithms after being evaluated to solve a given problem. Hence, with such automated machine learning techniques, CEB users workload is significantly reduced. Our experiments on DARPA dataset indicate that CEB technologies performed 10 times faster and about 4 times less false negative rate than current computational methods in seeking and understanding information. Our results demonstrate that these CEB technologies would enable humans to accurately and quickly detect meaningful information from a mass amount of data. The novel CEB technologies ensure that the reduced manpower does not result in reduced performance.
{"title":"Cloud Based Architecture for Enabling Intuitive Decision Making","authors":"Brian Xu, S. Kumar, Manonmani Kumar","doi":"10.1109/SERVICES.2013.11","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.11","url":null,"abstract":"To address the current need of innovative technologies that blend rapid data processing capabilities of computers with intuitive decision making skills of humans, we have developed a prototype of Cloud Enabled Brain Computer Interface (CEB) decision making technologies. The implemented architecture integrates cloud enabled big data analytics capabilities, networked BCI (Brain Computer Interface) devices, and Decision Making Engine. The novel CEB technology comprises of 1. Cloud-enabled BCI (Brain-Computer Interface) headsets, which is developed and networked in a cloud to enable rapid decision making and 2. Genetic algorithm based decision making engine, to intelligently assist the users in decision making; Advantage of our architecture is that when CEB loads the data, it will automatically recommend the best applicable Machine Learning (ML) algorithms after being evaluated to solve a given problem. Hence, with such automated machine learning techniques, CEB users workload is significantly reduced. Our experiments on DARPA dataset indicate that CEB technologies performed 10 times faster and about 4 times less false negative rate than current computational methods in seeking and understanding information. Our results demonstrate that these CEB technologies would enable humans to accurately and quickly detect meaningful information from a mass amount of data. The novel CEB technologies ensure that the reduced manpower does not result in reduced performance.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133559272","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.42
S. Shetty
Cloud computing allows users to remotely store their data into the cloud and provides on-demand applications and services from a shared pool of configurable computing resources. The security of the outsourced data in the cloud is dependent on the security of the cloud computing system and network. Though, there have been numerous efforts on securing data on the cloud computing system, evaluation of data security on the network between cloud provider and its users is still a very challenging task. The audit of the cloud computing system and network will provide insights on the security and performance of VMs and the operating system on multiple data centers and the intra-cloud network managed by cloud providers and the wide-area network between the cloud user and cloud provider. Thus, network traffic analysis for cloud auditing is of critical importance so that users can resort to an external audit party to verify the data security on the network between cloud provider and its users. This paper presents the following key technologies required to analyze network traffic in the cloud computing environment: IP geolocation of network devices between cloud provider and its users, monitoring the data security of the cloud network path, and online mining of massive cloud auditing logs generated by cloud network traffic.
{"title":"Auditing and Analysis of Network Traffic in Cloud Environment","authors":"S. Shetty","doi":"10.1109/SERVICES.2013.42","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.42","url":null,"abstract":"Cloud computing allows users to remotely store their data into the cloud and provides on-demand applications and services from a shared pool of configurable computing resources. The security of the outsourced data in the cloud is dependent on the security of the cloud computing system and network. Though, there have been numerous efforts on securing data on the cloud computing system, evaluation of data security on the network between cloud provider and its users is still a very challenging task. The audit of the cloud computing system and network will provide insights on the security and performance of VMs and the operating system on multiple data centers and the intra-cloud network managed by cloud providers and the wide-area network between the cloud user and cloud provider. Thus, network traffic analysis for cloud auditing is of critical importance so that users can resort to an external audit party to verify the data security on the network between cloud provider and its users. This paper presents the following key technologies required to analyze network traffic in the cloud computing environment: IP geolocation of network devices between cloud provider and its users, monitoring the data security of the cloud network path, and online mining of massive cloud auditing logs generated by cloud network traffic.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129161902","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.25
P. Berndt, Johannes Watzl
In order to establish a broader market for cloud computing, offers must be made comparable. Several efforts exist to compare performance of products from different providers and convey an idea of what to expect by means of (periodical) reports. Yet, buying IaaS cloud compute resources remains a blind bargain. The actual performance of a customer's deployment may, for various reasons, be substantially different from such third-party reports. Particularly, a cloud user cannot rely on receiving the same performance, be it because of higher load or arbitrary cloud reconfiguration. To render service levels of different cloud products meaningful and comparable within and across providers, these will have to commit themselves to providing performance according to some reference measure that also regards virtualization, resource allocation and isolation. Though the actual benchmarks will likely differ across application and market niches, the methodology to define, measure and guarantee performance remains the same. In this paper we propose a method for quantifying, determining and ensuring performance on the basis of a performance unit that conveys what performance can be expected from a VM deployment and is suitable for use in SLAs. The abstract approach is exemplified and validated by a case study with concrete benchmarks on a KVM-based cloud.
{"title":"Unitizing Performance of IaaS Cloud Deployments","authors":"P. Berndt, Johannes Watzl","doi":"10.1109/SERVICES.2013.25","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.25","url":null,"abstract":"In order to establish a broader market for cloud computing, offers must be made comparable. Several efforts exist to compare performance of products from different providers and convey an idea of what to expect by means of (periodical) reports. Yet, buying IaaS cloud compute resources remains a blind bargain. The actual performance of a customer's deployment may, for various reasons, be substantially different from such third-party reports. Particularly, a cloud user cannot rely on receiving the same performance, be it because of higher load or arbitrary cloud reconfiguration. To render service levels of different cloud products meaningful and comparable within and across providers, these will have to commit themselves to providing performance according to some reference measure that also regards virtualization, resource allocation and isolation. Though the actual benchmarks will likely differ across application and market niches, the methodology to define, measure and guarantee performance remains the same. In this paper we propose a method for quantifying, determining and ensuring performance on the basis of a performance unit that conveys what performance can be expected from a VM deployment and is suitable for use in SLAs. The abstract approach is exemplified and validated by a case study with concrete benchmarks on a KVM-based cloud.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129249944","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.34
Richard K. Lomotey, R. Deters
The mobile terrain is rapidly establishing itself as the reliable node for accessing cloud hosted data. Today, commodity cloud providers especially from the Infrastructure-as-a-Service (IaaS) cloud expose their service APIs which facilitates the "app-ification" of enterprise workflows on mobile devices. However, these IaaS providers require the customer (i.e., the data consumer) to submit multiple security credentials which are computation intensive for the purposes of authentication and authorization. As a result, the authentication process introduces undesired delays in a mobile network when consuming enterprise data due to the increasing computational demand and the voluminous HTTP header that is transported across the wireless bandwidth.This paper introduces an application called MiLAMob that is a middleware-layer that handles the authentication process on behalf of the consumer devices in real time and with minimal HTTP traffic. The middleware currently supports mobile consumption of data on IaaS clouds such as Amazon S3, Dropbox, and MEGA. Further, the middleware employs the OAuth 2.0 technique (E.g. Facebook, Google+, and Personal Login) to identify the mobile end-user and uses security tokens to handle the tedious authentication with the IaaS cloud. Also, the deployment of the middleware enforces additional data protection because the security credentials and the IaaS abstractions are shielded from the mobile application domain and the end users.
{"title":"SaaS Authentication Middleware for Mobile Consumers of IaaS Cloud","authors":"Richard K. Lomotey, R. Deters","doi":"10.1109/SERVICES.2013.34","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.34","url":null,"abstract":"The mobile terrain is rapidly establishing itself as the reliable node for accessing cloud hosted data. Today, commodity cloud providers especially from the Infrastructure-as-a-Service (IaaS) cloud expose their service APIs which facilitates the \"app-ification\" of enterprise workflows on mobile devices. However, these IaaS providers require the customer (i.e., the data consumer) to submit multiple security credentials which are computation intensive for the purposes of authentication and authorization. As a result, the authentication process introduces undesired delays in a mobile network when consuming enterprise data due to the increasing computational demand and the voluminous HTTP header that is transported across the wireless bandwidth.This paper introduces an application called MiLAMob that is a middleware-layer that handles the authentication process on behalf of the consumer devices in real time and with minimal HTTP traffic. The middleware currently supports mobile consumption of data on IaaS clouds such as Amazon S3, Dropbox, and MEGA. Further, the middleware employs the OAuth 2.0 technique (E.g. Facebook, Google+, and Personal Login) to identify the mobile end-user and uses security tokens to handle the tedious authentication with the IaaS cloud. Also, the deployment of the middleware enforces additional data protection because the security credentials and the IaaS abstractions are shielded from the mobile application domain and the end users.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123834232","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}
Pub Date : 2013-06-28DOI: 10.1109/SERVICES.2013.58
Stamatia Rizou, George Angouras
Self-employed professionals need powerful software tools to manage their daily tasks. The increasing need for mobility support in combination with the emergence of Internet-based services make SaaS solutions an attractive option for freelancers to manage their business. In this paper, we present ORBI, a SaaS solution especially designed to meet the needs of self-employed professionals that is currently available in the Greek market. We present the key concepts behind the design and implementation of the ORBI solution and we discuss its main value proposition. Furthermore, as part of the ongoing and future research activities we present the main research directions in an effort to use ORBI as an industrial test bed to test and validate innovative concepts and tools.
{"title":"ORBI: An Internet Service for Self-Employed Professionals","authors":"Stamatia Rizou, George Angouras","doi":"10.1109/SERVICES.2013.58","DOIUrl":"https://doi.org/10.1109/SERVICES.2013.58","url":null,"abstract":"Self-employed professionals need powerful software tools to manage their daily tasks. The increasing need for mobility support in combination with the emergence of Internet-based services make SaaS solutions an attractive option for freelancers to manage their business. In this paper, we present ORBI, a SaaS solution especially designed to meet the needs of self-employed professionals that is currently available in the Greek market. We present the key concepts behind the design and implementation of the ORBI solution and we discuss its main value proposition. Furthermore, as part of the ongoing and future research activities we present the main research directions in an effort to use ORBI as an industrial test bed to test and validate innovative concepts and tools.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951156","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：