BENRAZEK Ala-Eddine | 8 Mai 1945 à Guelma (original) (raw)

Papers by BENRAZEK Ala-Eddine

Research paper thumbnail of A Survey on Big IoT Data Indexing: Potential Solutions, Recent Advancements, and Open Issues

Future Internet, 2021

The past decade has been characterized by the growing volumes of data due to the widespread use o... more The past decade has been characterized by the growing volumes of data due to the widespread use of the Internet of Things (IoT) applications, which introduced many challenges for efficient data storage and management. Thus, the efficient indexing and searching of large data collections is a very topical and urgent issue. Such solutions can provide users with valuable information about IoT data. However, efficient retrieval and management of such information in terms of index size and search time require optimization of indexing schemes which is rather difficult to implement. The purpose of this paper is to examine and review existing indexing techniques for large-scale data. A taxonomy of indexing techniques is proposed to enable researchers to understand and select the techniques that will serve as a basis for designing a new indexing scheme. The real-world applications of the existing indexing techniques in different areas, such as health, business, scientific experiments, and soc...

Research paper thumbnail of A Survey on Big IoT Data Indexing: Potential Solutions, Recent Advancements, and Open Issues

Future Internet, 2021

The past decade has been characterized by the growing volumes of data due to the widespread use o... more The past decade has been characterized by the growing volumes of data due to the widespread use of the Internet of Things (IoT) applications, which introduced many challenges for efficient data storage and management. Thus, the efficient indexing and searching of large data collections is a very topical and urgent issue. Such solutions can provide users with valuable information about IoT data. However, efficient retrieval and management of such information in terms of index size and search time require optimization of indexing schemes which is rather difficult to implement. The purpose of this paper is to examine and review existing indexing techniques for large-scale data. A taxonomy of indexing techniques is proposed to enable researchers to understand and select the techniques that will serve as a basis for designing a new indexing scheme. The real-world applications of the existing indexing techniques in different areas, such as health, business, scientific experiments, and social networks, are presented. Open problems and research challenges, e.g., privacy and large-scale data mining, are also discussed.

Research paper thumbnail of Efficient Camera Clustering Method Based on Overlapping FoVs for WMSNs

The paper presents a new method of clustering cameras in a wireless multimedia sensor network bas... more The paper presents a new method of clustering cameras in a wireless multimedia sensor network based on overlapping camera fields of view. This method aims to group as many overlapping cameras as possible using the Bron-Kerbosch algorithm. The algorithm allows to find a maximum number of cliques, where they represent camera clusters with strongly overlapping fields of view. The main objective of this method is to form clusters of cameras that have a large overlap area between them in order to restrict the communication area only within the cluster. The method also avoids network congestion and reduce the redundancy of detected data to limit the rapid decrease in energy resulting from the acquisition, processing and transmission of redundant multimedia data. The simulation results show that the proposed method is more effective in extending network lifetime and reducing overhead costs.

Research paper thumbnail of Ascending Hierarchical Classification for Camera Clustering Based on FoV Overlaps for WMSN

IET Wireless Sensor Systems

Research paper thumbnail of Efficient Camera Clustering Method Based on Overlapping FoVs for WMSNs

International Journal of Informatics and Applied Mathematics, 2019

In this paper, we present a new method of clustering cameras in the wireless multimedia sensor ne... more In this paper, we present a new method of clustering cameras in the wireless multimedia sensor network based on overlapping camera fields of view. In this method, we try to group as many overlapping cameras as possible together using the Bron-Kerbosch algorithm that allows us to find maximum cliques, where they represent camera clusters with strongly overlapping fields of view. The main objective of this method is to form clusters of cameras that have a large overlap area between them in order to restrict the communication area only in the cluster to avoid network congestion and reduce the redundancy of detected data to limit the rapid decrease in energy resulting from the acquisition, processing and transmission of redundant multimedia data. The simulation results demonstrate that the proposed method is more effective in extending the life of the network and reducing network overhead costs.

Research paper thumbnail of A Survey on Big IoT Data Indexing: Potential Solutions, Recent Advancements, and Open Issues

Future Internet, 2021

The past decade has been characterized by the growing volumes of data due to the widespread use o... more The past decade has been characterized by the growing volumes of data due to the widespread use of the Internet of Things (IoT) applications, which introduced many challenges for efficient data storage and management. Thus, the efficient indexing and searching of large data collections is a very topical and urgent issue. Such solutions can provide users with valuable information about IoT data. However, efficient retrieval and management of such information in terms of index size and search time require optimization of indexing schemes which is rather difficult to implement. The purpose of this paper is to examine and review existing indexing techniques for large-scale data. A taxonomy of indexing techniques is proposed to enable researchers to understand and select the techniques that will serve as a basis for designing a new indexing scheme. The real-world applications of the existing indexing techniques in different areas, such as health, business, scientific experiments, and soc...

Research paper thumbnail of A Survey on Big IoT Data Indexing: Potential Solutions, Recent Advancements, and Open Issues

Future Internet, 2021

The past decade has been characterized by the growing volumes of data due to the widespread use o... more The past decade has been characterized by the growing volumes of data due to the widespread use of the Internet of Things (IoT) applications, which introduced many challenges for efficient data storage and management. Thus, the efficient indexing and searching of large data collections is a very topical and urgent issue. Such solutions can provide users with valuable information about IoT data. However, efficient retrieval and management of such information in terms of index size and search time require optimization of indexing schemes which is rather difficult to implement. The purpose of this paper is to examine and review existing indexing techniques for large-scale data. A taxonomy of indexing techniques is proposed to enable researchers to understand and select the techniques that will serve as a basis for designing a new indexing scheme. The real-world applications of the existing indexing techniques in different areas, such as health, business, scientific experiments, and social networks, are presented. Open problems and research challenges, e.g., privacy and large-scale data mining, are also discussed.

Research paper thumbnail of Efficient Camera Clustering Method Based on Overlapping FoVs for WMSNs

The paper presents a new method of clustering cameras in a wireless multimedia sensor network bas... more The paper presents a new method of clustering cameras in a wireless multimedia sensor network based on overlapping camera fields of view. This method aims to group as many overlapping cameras as possible using the Bron-Kerbosch algorithm. The algorithm allows to find a maximum number of cliques, where they represent camera clusters with strongly overlapping fields of view. The main objective of this method is to form clusters of cameras that have a large overlap area between them in order to restrict the communication area only within the cluster. The method also avoids network congestion and reduce the redundancy of detected data to limit the rapid decrease in energy resulting from the acquisition, processing and transmission of redundant multimedia data. The simulation results show that the proposed method is more effective in extending network lifetime and reducing overhead costs.

Research paper thumbnail of Ascending Hierarchical Classification for Camera Clustering Based on FoV Overlaps for WMSN

IET Wireless Sensor Systems

Research paper thumbnail of Efficient Camera Clustering Method Based on Overlapping FoVs for WMSNs

International Journal of Informatics and Applied Mathematics, 2019

In this paper, we present a new method of clustering cameras in the wireless multimedia sensor ne... more In this paper, we present a new method of clustering cameras in the wireless multimedia sensor network based on overlapping camera fields of view. In this method, we try to group as many overlapping cameras as possible together using the Bron-Kerbosch algorithm that allows us to find maximum cliques, where they represent camera clusters with strongly overlapping fields of view. The main objective of this method is to form clusters of cameras that have a large overlap area between them in order to restrict the communication area only in the cluster to avoid network congestion and reduce the redundancy of detected data to limit the rapid decrease in energy resulting from the acquisition, processing and transmission of redundant multimedia data. The simulation results demonstrate that the proposed method is more effective in extending the life of the network and reducing network overhead costs.