Pub Date : 2015-11-30DOI: 10.1109/CLOUDTECH.2015.7336992
E. Badidi, Hayat Routaib
Over the last few years, we are witnessing the proliferation of mobile Internet devices (MIDs) and the wide spread adoption of cloud computing for both personal and corporate usages. These technologies are converging in what is known as mobile cloud computing (MCC) paradigm. This paradigm aims at addressing resource poverty of mobile devices. Several works investigated the challenges of mobile cloud computing. With the growing heterogeneity of mobile devices, personalization of services remains a challenging issue. In this paper, we propose a conceptual framework to address the issue of personalization in a mobile cloud computing environment. It aims at satisfying the mobile user needs and preferences for service provisioning. The mobile cloud service provider composes its service from a set of in-house services and from third party services using a composition plan, which adapts services by taking into account the user's profile and preferences.
{"title":"A conceptual framework for personalization of mobile cloud services","authors":"E. Badidi, Hayat Routaib","doi":"10.1109/CLOUDTECH.2015.7336992","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336992","url":null,"abstract":"Over the last few years, we are witnessing the proliferation of mobile Internet devices (MIDs) and the wide spread adoption of cloud computing for both personal and corporate usages. These technologies are converging in what is known as mobile cloud computing (MCC) paradigm. This paradigm aims at addressing resource poverty of mobile devices. Several works investigated the challenges of mobile cloud computing. With the growing heterogeneity of mobile devices, personalization of services remains a challenging issue. In this paper, we propose a conceptual framework to address the issue of personalization in a mobile cloud computing environment. It aims at satisfying the mobile user needs and preferences for service provisioning. The mobile cloud service provider composes its service from a set of in-house services and from third party services using a composition plan, which adapts services by taking into account the user's profile and preferences.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129961495","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 : 2015-11-30DOI: 10.1109/CLOUDTECH.2015.7337009
Siham Yousfi, D. Chiadmi
Big Data analytics and Cloud Computing are the new trending that submerged the IT industry. In fact, Big Data technology is providing methods and tools for storing managing and analyzing a large amount of data, and cloud computing provides IT services in a scalable way via internet to a number of clients at low costs. While big data environment requires powerful cluster infrastructure, new ideas about combining this two paradigms were born to enhance business agility and productivity and enable greater efficiencies and reduce costs. Big data as-a-service (BDAAS) refers to common big data services provided as cloud hosted services. These services are intended to provide Big Data features in the cloud. The objective of our research is to describe a BDAAS solution based on Hadoop ecosystem that extracts data from social network and constructs a graph that could be used later for further analysis. As a prototype, we built a graph representing the feeling of a citizen toward a particular deputy. The analysis of the resulting graph will allow citizens and political parties identifying the most popular deputy by analyzing the most significant node.
大数据分析和云计算是淹没IT行业的新趋势。事实上，大数据技术提供了存储、管理和分析大量数据的方法和工具，而云计算通过互联网以一种可扩展的方式以低成本向许多客户提供IT服务。虽然大数据环境需要强大的集群基础设施，但将这两种范式结合起来的新想法诞生了，以增强业务敏捷性和生产力，并实现更高的效率和降低成本。BDAAS (Big data as-a-service)是指以云托管服务形式提供的常见大数据服务。这些服务旨在提供云中的大数据功能。我们研究的目的是描述一个基于Hadoop生态系统的BDAAS解决方案，该解决方案可以从社交网络中提取数据，并构建一个可以稍后用于进一步分析的图形。作为一个原型，我们建立了一个代表公民对特定代表的感觉的图表。对结果图的分析将允许公民和政党通过分析最重要的节点来确定最受欢迎的代表。
{"title":"Big Data-as-a-service solution for building graph social networks","authors":"Siham Yousfi, D. Chiadmi","doi":"10.1109/CLOUDTECH.2015.7337009","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7337009","url":null,"abstract":"Big Data analytics and Cloud Computing are the new trending that submerged the IT industry. In fact, Big Data technology is providing methods and tools for storing managing and analyzing a large amount of data, and cloud computing provides IT services in a scalable way via internet to a number of clients at low costs. While big data environment requires powerful cluster infrastructure, new ideas about combining this two paradigms were born to enhance business agility and productivity and enable greater efficiencies and reduce costs. Big data as-a-service (BDAAS) refers to common big data services provided as cloud hosted services. These services are intended to provide Big Data features in the cloud. The objective of our research is to describe a BDAAS solution based on Hadoop ecosystem that extracts data from social network and constructs a graph that could be used later for further analysis. As a prototype, we built a graph representing the feeling of a citizen toward a particular deputy. The analysis of the resulting graph will allow citizens and political parties identifying the most popular deputy by analyzing the most significant node.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240310","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 : 2015-11-30DOI: 10.1109/CLOUDTECH.2015.7337012
Mohammed Jouad, S. Diouani, H. Houmani, Ali Zaki
Organizations and governments consider security as a must-have due to the increasing rate of attacks which is threatening both security and privacy. In this paper, we present a survey of IDPS which led us to perform a classification of methods depending on the techniques used in intrusions detection and prevention systems. We also discuss the advantages and drawbacks of these methods. Afterwards, we discuss the various problems complicating the proper functionality and efficiency of the current IDPS and also analyze its challenges in cloud computing, smart-phones and smart cities.
{"title":"Security challenges in intrusion detection","authors":"Mohammed Jouad, S. Diouani, H. Houmani, Ali Zaki","doi":"10.1109/CLOUDTECH.2015.7337012","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7337012","url":null,"abstract":"Organizations and governments consider security as a must-have due to the increasing rate of attacks which is threatening both security and privacy. In this paper, we present a survey of IDPS which led us to perform a classification of methods depending on the techniques used in intrusions detection and prevention systems. We also discuss the advantages and drawbacks of these methods. Afterwards, we discuss the various problems complicating the proper functionality and efficiency of the current IDPS and also analyze its challenges in cloud computing, smart-phones and smart cities.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126022001","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7336972
C. Loubna, Ezziyyani Mostafa, E. Annas, H. Mohammed
Despite the large and spectacular development in the field of vehicle safety, particularly in the context of driver safety needs, solutions remain insufficient and independent. In this paper, we propose a new system that has been dubbed 3SD "Security and Surveillance System for Drivers". It is a multifunction system as a complete package based on intelligent sensors and cameras that constantly monitor the vehicle's environment and the behavior of the driver to detect early so potentially dangerous situations. In critical driving situations, these systems alert and actively help the driver; if necessary, they automatically intervene to prevent or mitigate the consequences of an accident. The package proposed includes an application comprising a set of pre-registered drivers in a specialized social network interconnected to a geolocation server for distributed real-time sharing of information and data useful for security and traffic. The system is founded mainly on learning systems for face recognition based on advanced algorithms “Viola and Jones method” and “PCA method” as well as management of drivers profiles based on preferences to provide the following features: early detection of sleep, unconsciousness and poor driver behavior, security against theft of vehicles, driver comfort and control and sharing of traffic information in real time between the conductors.
尽管汽车安全领域取得了巨大的发展，特别是在驾驶员安全需求的背景下，解决方案仍然不足和独立。在本文中，我们提出了一个新的系统，被称为3SD“司机安全与监控系统”。它是一个多功能系统，作为一个完整的软件包，基于智能传感器和摄像头，不断监测车辆的环境和驾驶员的行为，以及早发现潜在的危险情况。在紧急驾驶情况下，这些系统会发出警报并主动帮助驾驶员;如果有必要，它们会自动干预以防止或减轻事故的后果。该方案包括一个应用程序，其中包括一组预先注册的司机，这些司机在一个专门的社交网络中与地理定位服务器相连，用于分布式实时共享对安全和交通有用的信息和数据。该系统主要建立在基于高级算法“Viola and Jones method”和“PCA method”的人脸识别学习系统和基于偏好的驾驶员档案管理之上，提供了以下功能:早期发现驾驶员睡眠、无意识和不良行为，车辆防盗，驾驶员舒适和控制，以及在售票员之间实时共享交通信息。
{"title":"Data extraction for user profile management based on behavior","authors":"C. Loubna, Ezziyyani Mostafa, E. Annas, H. Mohammed","doi":"10.1109/CLOUDTECH.2015.7336972","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336972","url":null,"abstract":"Despite the large and spectacular development in the field of vehicle safety, particularly in the context of driver safety needs, solutions remain insufficient and independent. In this paper, we propose a new system that has been dubbed 3SD \"Security and Surveillance System for Drivers\". It is a multifunction system as a complete package based on intelligent sensors and cameras that constantly monitor the vehicle's environment and the behavior of the driver to detect early so potentially dangerous situations. In critical driving situations, these systems alert and actively help the driver; if necessary, they automatically intervene to prevent or mitigate the consequences of an accident. The package proposed includes an application comprising a set of pre-registered drivers in a specialized social network interconnected to a geolocation server for distributed real-time sharing of information and data useful for security and traffic. The system is founded mainly on learning systems for face recognition based on advanced algorithms “Viola and Jones method” and “PCA method” as well as management of drivers profiles based on preferences to provide the following features: early detection of sleep, unconsciousness and poor driver behavior, security against theft of vehicles, driver comfort and control and sharing of traffic information in real time between the conductors.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123587110","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7336975
A. Maarouf, Mahmoud El Hamlaoui, A. Marzouk, A. Haqiq
A Service Level Agreement (SLA) is a legal contract between parties to ensure the Quality of Service (QoS). It specifies one or more service level objectives (SLO), to ensure that the QoS delivered has met customer expectations. However, It becomes hard to guarantee QoS levels and detect SLA violations. Therefore, we propose to use MDE (Model Driven Engineering) to express the SLA contract requirements. This latter, created with a specific modeling language (DSML), will be used harmonically with a Multi-agent systems (MASs) in order to monitor SLA violations in real-time. Indeed, MASs are suitable tools for self-detection of failures and self-monitoring of cloud operations and services, QoS negotiation and SLA management. They are designed to operate in a dynamically changing environment. Our main motivation is firstly to use MDE technology for the creation of the SLA contract and then to integrate MASs in order to control the quality of service contract and guarantee transparency and symmetry with respect to the SLA contract between prospective signatories.
{"title":"Combining multi-agent systems and MDE approach for monitoring SLA violations in the Cloud Computing","authors":"A. Maarouf, Mahmoud El Hamlaoui, A. Marzouk, A. Haqiq","doi":"10.1109/CLOUDTECH.2015.7336975","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336975","url":null,"abstract":"A Service Level Agreement (SLA) is a legal contract between parties to ensure the Quality of Service (QoS). It specifies one or more service level objectives (SLO), to ensure that the QoS delivered has met customer expectations. However, It becomes hard to guarantee QoS levels and detect SLA violations. Therefore, we propose to use MDE (Model Driven Engineering) to express the SLA contract requirements. This latter, created with a specific modeling language (DSML), will be used harmonically with a Multi-agent systems (MASs) in order to monitor SLA violations in real-time. Indeed, MASs are suitable tools for self-detection of failures and self-monitoring of cloud operations and services, QoS negotiation and SLA management. They are designed to operate in a dynamically changing environment. Our main motivation is firstly to use MDE technology for the creation of the SLA contract and then to integrate MASs in order to control the quality of service contract and guarantee transparency and symmetry with respect to the SLA contract between prospective signatories.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125532797","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7336964
Ridouane. Chalh, Z. Bakkoury, D. Ouazar, M. Hasnaoui
Nowadays Big Data are becoming a popular topic and a comparatively new technological concept focused on many different disciplines like environmental science, social media and networks, industry and healthcare. Data volumes are on an upward trajectory associated with increased data velocity, and variety. Furthermore, they are needed to develop effective solutions to support intelligent, proactive and predictive processes. In this paper we exploit Big Data concepts for environmental sciences and water resources. The aim of this article is to present the concept and architecture of our Big Data Open Platform used for supporting Water Resources Management. This Platform has been designed to provide effective tools that allow water system managers to solve complex water resources systems, water modeling issues and help in decision making. The Platform brings a variety of information technology tools including stochastic aspects, high performance computing, simulation models, hydraulic and hydrological models, grid computing, decision tools, Big Data analysis system, communication and diffusion system, database management, geographic information system (GIS) and Knowledge based expert system. The operators' objectives of this Big Data Open Platform are to solve and discuss water resources problems that are featured by a huge volume of collected, analyzed and visualized data, to analyze the heterogeneity of data resulting from various sources including structured, unstructured and semi-structured data, also to prevent and/or avoid a catastrophic event related to floods and/or droughts, through hydraulic infrastructures designed for such purposes or strategic planning. This first paper will focus on the first part developed and based on J2EE platform and specifically the hypsometrical approach considered as a decision tool allowing users to compare the effects of different current and future management scenarios and make choice to preserve the environment and natural resources.
{"title":"Big data open platform for water resources management","authors":"Ridouane. Chalh, Z. Bakkoury, D. Ouazar, M. Hasnaoui","doi":"10.1109/CLOUDTECH.2015.7336964","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336964","url":null,"abstract":"Nowadays Big Data are becoming a popular topic and a comparatively new technological concept focused on many different disciplines like environmental science, social media and networks, industry and healthcare. Data volumes are on an upward trajectory associated with increased data velocity, and variety. Furthermore, they are needed to develop effective solutions to support intelligent, proactive and predictive processes. In this paper we exploit Big Data concepts for environmental sciences and water resources. The aim of this article is to present the concept and architecture of our Big Data Open Platform used for supporting Water Resources Management. This Platform has been designed to provide effective tools that allow water system managers to solve complex water resources systems, water modeling issues and help in decision making. The Platform brings a variety of information technology tools including stochastic aspects, high performance computing, simulation models, hydraulic and hydrological models, grid computing, decision tools, Big Data analysis system, communication and diffusion system, database management, geographic information system (GIS) and Knowledge based expert system. The operators' objectives of this Big Data Open Platform are to solve and discuss water resources problems that are featured by a huge volume of collected, analyzed and visualized data, to analyze the heterogeneity of data resulting from various sources including structured, unstructured and semi-structured data, also to prevent and/or avoid a catastrophic event related to floods and/or droughts, through hydraulic infrastructures designed for such purposes or strategic planning. This first paper will focus on the first part developed and based on J2EE platform and specifically the hypsometrical approach considered as a decision tool allowing users to compare the effects of different current and future management scenarios and make choice to preserve the environment and natural resources.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121887627","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7336986
Mohammad-Mahdi Bazm, R. Khatoun, Y. Begriche, L. Khoukhi, Xiuzhen Chen, A. Serhrouchni
Cloud computing aims to provide enormous resources and services, parallel processing and reliable access for users on the networks. The flexible resources of clouds could be used by malicious actors to attack other infrastructures. Cloud can be used as a platform to perform these attacks, a virtual machine(VM) in the Cloud can play the role of a malicious VM belonging to a Botnet and sends a heavy traffic to the victim. For cloud service providers, preventing their infrastructure from being turned into an attack platform is very challenging since it requires detecting attacks at the source, in a highly dynamic and heterogeneous environment. In this paper, an approach to detect these malicious behaviors in the Cloud based on the analysis of network parameters is proposed. This approach is a source-based attack detection, which applies both Entropy and clustering methods on network parameters. The environment of Cloud is simulated on Cloudsim. The data clustering allows achieving high performance, with a high percentage of correctly clustered VMs.
{"title":"Malicious virtual machines detection through a clustering approach","authors":"Mohammad-Mahdi Bazm, R. Khatoun, Y. Begriche, L. Khoukhi, Xiuzhen Chen, A. Serhrouchni","doi":"10.1109/CLOUDTECH.2015.7336986","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336986","url":null,"abstract":"Cloud computing aims to provide enormous resources and services, parallel processing and reliable access for users on the networks. The flexible resources of clouds could be used by malicious actors to attack other infrastructures. Cloud can be used as a platform to perform these attacks, a virtual machine(VM) in the Cloud can play the role of a malicious VM belonging to a Botnet and sends a heavy traffic to the victim. For cloud service providers, preventing their infrastructure from being turned into an attack platform is very challenging since it requires detecting attacks at the source, in a highly dynamic and heterogeneous environment. In this paper, an approach to detect these malicious behaviors in the Cloud based on the analysis of network parameters is proposed. This approach is a source-based attack detection, which applies both Entropy and clustering methods on network parameters. The environment of Cloud is simulated on Cloudsim. The data clustering allows achieving high performance, with a high percentage of correctly clustered VMs.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121492730","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7336966
Widad Ettazi, H. Hafiddi, M. Nassar, S. Ebersold
Advances in wireless communications and mobility have increased the use of smart mobile applications. As a result of the remarkable increase of mobile devices and the pervasive wireless networks, a large number of mobile users are requiring personalization services customized to their context. The mobile cloud-computing paradigm from a context-aware perspective aims to find effective ways to make cloud services aware of the context of their customers and applications. Another major challenge for context-aware cloud services is to exploit the benefits of cloud computing to manage transaction processing throughout the life cycle of a service. In this paper, we focused on the need of loosely coupled context-supporting components that work with a transaction-aware service infrastructure to adapt services to the context of the user and his mobile device. We propose a cloud-based middleware for transactional service adaptation (CM4TSA) by adding the “Adaptation as a Service” layer into basic cloud architecture, to perform the correct execution of transactional service according to the user context.
{"title":"A cloud-based architecture for transactional services adaptation","authors":"Widad Ettazi, H. Hafiddi, M. Nassar, S. Ebersold","doi":"10.1109/CLOUDTECH.2015.7336966","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7336966","url":null,"abstract":"Advances in wireless communications and mobility have increased the use of smart mobile applications. As a result of the remarkable increase of mobile devices and the pervasive wireless networks, a large number of mobile users are requiring personalization services customized to their context. The mobile cloud-computing paradigm from a context-aware perspective aims to find effective ways to make cloud services aware of the context of their customers and applications. Another major challenge for context-aware cloud services is to exploit the benefits of cloud computing to manage transaction processing throughout the life cycle of a service. In this paper, we focused on the need of loosely coupled context-supporting components that work with a transaction-aware service infrastructure to adapt services to the context of the user and his mobile device. We propose a cloud-based middleware for transactional service adaptation (CM4TSA) by adding the “Adaptation as a Service” layer into basic cloud architecture, to perform the correct execution of transactional service according to the user context.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132335158","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7337000
Meriem Thabet, M. Boufaida
Nowadays, companies are increasingly adopting the technology of cloud computing. This technology allows them to innovate and to improve their business. Plus, the presence of numerous cloud providers would be beneficial for providers and companies if some collaboration among clouds will be achieved. This collaboration lets companies to choose and to move their applications and data among clouds without being tied to any provider. We have embedded the Service Component Architecture in the cloud computing domain. The proposed model aims at facilitating the data sharing between multiple cloud service providers regardless their infrastructure, tools and platforms. Indeed, we have opted for SCA standard to promote the interoperability mechanism by moving and converting data formats exchanged among clouds. Our model allows many providers to interact among each other by overcoming the syntactic heterogeneity in order to satisfy companies' needs.
{"title":"A SCA based model for resolving syntactic heterogeneity among clouds","authors":"Meriem Thabet, M. Boufaida","doi":"10.1109/CLOUDTECH.2015.7337000","DOIUrl":"https://doi.org/10.1109/CLOUDTECH.2015.7337000","url":null,"abstract":"Nowadays, companies are increasingly adopting the technology of cloud computing. This technology allows them to innovate and to improve their business. Plus, the presence of numerous cloud providers would be beneficial for providers and companies if some collaboration among clouds will be achieved. This collaboration lets companies to choose and to move their applications and data among clouds without being tied to any provider. We have embedded the Service Component Architecture in the cloud computing domain. The proposed model aims at facilitating the data sharing between multiple cloud service providers regardless their infrastructure, tools and platforms. Indeed, we have opted for SCA standard to promote the interoperability mechanism by moving and converting data formats exchanged among clouds. Our model allows many providers to interact among each other by overcoming the syntactic heterogeneity in order to satisfy companies' needs.","PeriodicalId":293168,"journal":{"name":"2015 International Conference on Cloud Technologies and Applications (CloudTech)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115738152","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 : 2015-06-02DOI: 10.1109/CLOUDTECH.2015.7337001
Meryeme El Houari, Maryem Rhanoui, B. El Asri
Nowadays Big Data becomes one of the biggest buzz concepts in IT world especially with the vertiginous development driving the increase of data encouraged by the emergence of high technologies of storage like cloud computing. Big Data can create efficient challenging solutions in health, security, government and more; and usher in a new era of analytics and decisions. Knowledge Management comprises a set of strategies and practices used to identify, create, represent, distribute, and enable creating experience that can constitute a real immaterial capital. However, to bring significant meaning to the perpetual tsunami of data and manage them, Big Data needs Knowledge Management. In the same way, to broaden the scope of its targeted analyzes, Knowledge Management requires Big Data. Thus, there is a complementary relation between these two major concepts. This paper presents a state of art where we try to explore Big Data within the context of Knowledge Management. We discuss the bi-directional relationship linking this two fundamental concepts and their strategic utility in making analytics valuable especially with the combination of their interactions which create an effective Big Knowledge to build experience.
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