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2024 Global Congress on Emerging Technologies, GCET 2024

作者： Djiroun, Rahma Guessoum, Meriem Amel Benkhelifa, El Hadj LSI/USTHB High School of Artificial Intelligence ENSIA Algiers Algeria Staffordshire University Cloud Computing and Application Research Lab United Kingdom

ISBN: (纸本)9798331542603

Online multidimensional analysis typically involves processing large volumes of data, and Business Intelligence (BI) systems offer an efficient and fast solution for this purpose. Decision-making relies on analysing a set of stored data known as data cubes. In this context, the decision maker must search for the most suitable cubes that meet his requirements. Often, he targets the internal company's cubes. However, with the era of Open Data, several companies publish their data on the Web as data cubes or (CSV, EXCEL) files. In this perspective, decision maker tends to be in the loop about external data in order to cope with competition. Unfortunately, in such a situation, the decision maker may encounter an important number of cubes either internal or external whose structures are often unknown. Therefore, such cube's search becomes tedious and time consuming. Consequently, it is necessary to efficiently capture the center of interest of the decision maker by using recommendation techniques. In this regard, we propose in this paper, an approach that enables to recommend a set of relevant data cubes that facilitate the decision making process. This approach is based on Cube's Fusion using Artificial Intelligence techniques such as the Natural Language processing and Clustering techniques. It considers internal as well as external data to suggest the most appropriate cubes that meet the decision maker requirements. To validate this approach, we developed a tool called "OptiCubeRec"that recommends for decision-makers the most pertinent cubes based on their behaviour, preferences, and interactions within the system. An experimental study that evaluates our proposal in terms of relevance and performance is presented. © 2024 IEEE.

关键词： Recommender systems

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An OLAP Internal/External Cube Recommendation Approach based on Artificial Intelligence Techniques

An OLAP Internal/External Cube Recommendation Approach based...

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Emerging Technologies (GCET), Global Congress on

作者： Rahma Djiroun Meriem Amel Guessoum El Hadj Benkhelifa LSI/USTHB High School of Artificial Intelligence ENSIA Algiers Algeria Cloud Computing and Application Research Lab Staffordshire University UK

ISBN: (数字)9798331542603

ISBN: (纸本)9798331542610

Online multidimensional analysis typically involves processing large volumes of data, and Business Intelligence (BI) systems offer an efficient and fast solution for this purpose. Decision-making relies on analysing a set of stored data known as data cubes. In this context, the decision maker must search for the most suitable cubes that meet his requirements. Often, he targets the internal company’s cubes. However, with the era of Open Data, several companies publish their data on the Web as data cubes or (CSV, EXCEL) files. In this perspective, decision maker tends to be in the loop about external data in order to cope with competition. Unfortunately, in such a situation, the decision maker may encounter an important number of cubes either internal or external whose structures are often unknown. Therefore, such cube’s search becomes tedious and time consuming. Consequently, it is necessary to efficiently capture the center of interest of the decision maker by using recommendation techniques. In this regard, we propose in this paper, an approach that enables to recommend a set of relevant data cubes that facilitate the decision making process. This approach is based on Cube’s Fusion using Artificial Intelligence techniques such as the Natural Language processing and Clustering techniques. It considers internal as well as external data to suggest the most appropriate cubes that meet the decision maker requirements. To validate this approach, we developed a tool called "OptiCubeRec" that recommends for decision-makers the most pertinent cubes based on their behaviour, preferences, and interactions within the system. An experimental study that evaluates our proposal in terms of relevance and performance is presented.

关键词： Decision making Companies Natural language processing Business intelligence Proposals Artificial intelligence Recommender systems Open data

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Towards an OLAP Cubes Recommendation Approach in cloud computing Environment

Towards an OLAP Cubes Recommendation Approach in Cloud Compu...

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International Conference on Social Networks Analysis, Management and Security (SNAMS)

作者： Rahma Djiroun Meriem Amel Guessoum Kamel Boukhalfa ElHadj Benkhelifa LSI/USTHB Algeirs Algeria Cloud Computing and Application Research Lab Staffordshire University United Kingdom

ISBN: (纸本)9781665494960

The cloud computing technology is constantly evolving in terms of service provision. Recently, many companies that use OLAP systems for decision-making are deploying their OLAP cubes as services in a cloud environment. The potential of the exploited cubes is growing significantly. Therefore, consumers find difficulties in selecting relevant cubes especially when their needs are dispersed across multiple cubes. Hence, we propose in this paper an approach that allows relevant cubes recommen-dation among the deployed cubes in the cloud as well as the construction of new cubes if the need cannot be met by a single cube. In order to validate our approach, a tool called “Cube-RS” is developed. An experimental study that evaluates our proposal in terms of relevance and performance is presented.

关键词： Computers cloud computing Social networking (online) Decision making Companies Security Proposals

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A Novel cloud Services Recommendation System Based on Automatic Learning Techniques

A Novel Cloud Services Recommendation System Based on Automa...

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International Conference on New Trends in computing Sciences (ICTCS)

作者： Rahma Djiroun Meriem Amel Guessoum Kamel Boukhalfa Elhadj Benkhelifa Department of Computer Science LSI/USTHB Algiers Algeria Cloud Computing and Application Research Lab Staffordshire University UK

ISBN: (纸本)9781538605288

The cloud computing technology is evolving constantly but essence remains the same that is to offer distinct cost saving opportunities by consolidating and restructuring information technology as a service. With the continuously increasing cloud provisions, cloud consumers start to have difficulties to find the best relevant services that suit their requirements. Therefore, selecting best services by cloud users is becoming a greater challenge. In this paper, we present a framework of services' recommendation system in a cloud environment, using automatic learning techniques. The system aims at finding the services that suit the interests and preferences of cloud consumers by combining content based and behaviour based recommendations. In this paper, we present, USTHBcloud, a cloud services recommendation prototype evaluated with an experimental study.

关键词： cloud computing Quality of service Data mining Filtering Clustering algorithms Collaboration Blogs

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A Novel cloud Services Recommendation System Based on Automatic Learning Techniques

A Novel Cloud Services Recommendation System Based on Automa...

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ACS/IEEE International Conference on Computer Systems and applications

作者： Rahma Djiroun Meriem Amel Guesssoum Kamel Boukhalfa Elhadj Benkhelifa Department of Computer Science USTHB Algiers Algeria LSI Dept. of Comput. Sci. USTHB Algiers Algeria Cloud Computing and Application Research Lab Staffordshire University UK

关键词： cloud computing Quality of service Data mining Filtering Clustering algorithms Collaboration Blogs

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Efficient and secure software-defined mobile cloud computing infrastructure

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International Journal of High Performance computing and Networking 2016年第4期9卷 328-341页

作者： Tawalbeh, LO'Ai Haddad, Yousef Khamis, Omar Benkhelifa, Elhadj Jararweh, Yaser AlDosari, Fahd Computer Engineering Department Umm-AlQura University Makka Saudi Arabia Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan Princes Sumaya University for Technology Amman Jordan Cloud Computing and Application Research Lab Staffordshire University Beaconside United Kingdom

This paper proposes an efficient software-based data possession mobile cloud computing framework. The proposed design combines the characteristics of two frameworks. The first one is the provable data possession design built for resource constrained mobile devices and it uses the advantage of trusted computing technology, and the second framework is a lightweight resilient storage outsourcing design for mobile cloud computing systems. The proposed solution utilises the strength aspects found in each framework in order to gain better performance and maintain adequate and comparable security. The proposed framework is a software-defined system, encompassing software-defined storage (SDStore) and software-defined security (SDSec). The evaluation and comparison results showed that our proposed system has better flexibility and efficiency than other related frameworks, individually. © 2016 Inderscience Enterprises Ltd.

关键词： Mobile cloud computing

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User Profiling for Energy Optimisation in Mobile cloud computing

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Procedia Computer Science 2015年 52卷 1159-1165页

作者： Elhadj Benkhelifa Thomas Welsh Loai Tawalbeh Yaser Jararweh Anas Basalamah Cloud Computing and Application Research Lab Staffordshire University Beaconside Stafford ST18 0AD UK Computer Engineering Department Umm-Alqura University Makkah Saudi Arabia Jordan University of Science and Technology Irbid Jordan

Both mobile and cloud computing are two areas which are rapidly expanding in terms of use case and *** mobile and cloud computing are two areas which are rapidly expanding in terms of use case and functionality. This paper reviews current work in energy consumption of mobile cloud computing and then proposes a system whereby user applications may be profiled for their resource consumption locally and then if augmentation is required, they may negotiate with an external cloud for optimum energy consumption. Such a system is particularly useful for cloudlets which contain constrained resources so may need to choose between a number of clients. Whilst mobile computing enables a variety of feature rich functionality for users in a non-fixed location, cloud computing is revolutionising the way in which computing resources are being provisioned, used and optimised for both service providers and end users. These two fields are being combined in order to provide greater functionality for mobile devices in a number of different ways. Augmentation of mobile resources from the cloud has been shown as one way in which the energy consumption and power of mobile devices may be considerably enhanced. However, due to the resource constrained nature of the devices, in particular their power source and communication interfaces, there is often a fine line where offloading of these resources is economical.

关键词： Mobile-cloud-computing Energy Profiling Optimisation Smartphone Networks.

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Threshold-Based Secure and Privacy-Preserving Message Verification in VANETs

Threshold-Based Secure and Privacy-Preserving Message Verifi...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Wei Gao Mingzhong Wang Liehuang Zhu Xiaoping Zhang Language Information Processing and Cloud Computing Application Beijing Institute of Technology National Key Lab of Vehicular Transmission China North Vehicle Research Institute

ISBN: (纸本)9781479965144

Messages spreading inside vehicular ad hoc networks (VANETs) generally need to achieve the property of verifiability and content integrity, while preserving user privacy. Otherwise, VANETs will either fall into chaos, or prevent users from embracing it. To achieve this goal, we propose a protocol, which contains a priori and posteriori countermeasures, to guarantee these features. The a priori process firstly verifies that each message is sent by a vehicle only once. Then it collects and checks whether the count of the message exceeds the threshold value to improve the trustworthiness of the message. The posteriori process verifies the integrity of the message, ensuring it is unchanged during transmission between the vehicle and the road side unit. The privacy is preserved by applying group signature. In case of disruptive events, the proposed solution can trace back to the source vehicle which generates the message.

关键词： Vehicles Privacy Authentication Protocols Public key Servers

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