Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azeddine; Toral-Cruz, Homero

doi:10.1109/access.2018.2821445

Cited by 132 publications

(59 citation statements)

References 29 publications

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“…That lack of deterioration is because the mobile agents migrate to the machines where the BD is located, processing it there, and then returning back with results of manipulation only. This provides an efficient solution to what is called the transmission challenge, which occurs because small sizes of codes (i.e., agents) migrate via the network channel to end tasks, rather than transmitting huge sizes of BD to the manipulating machines [18,19,20].…”

Section: Importance Of Abst In Distributed Systemsmentioning

confidence: 99%

A Survey: Agent-based Software Technology Under the Eyes of Cyber Security, Security Controls, Attacks and Challenges

Alluhaybi¹,

Alrahhal²,

Alzhrani³

et al. 2019

IJACSA

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Recently, agent-based software technology has received wide attention by the research community due to its valuable benefits, such as reducing the load on networks and providing an efficient solution for the transmission challenge problem. However, the major concern in building agent-based systems is related to the security of agents. In this paper, we explore the techniques used to build controls that guarantee both the protection of agents against malicious destination machines and the protection of destination machines against malicious agents. In addition, statistical-based analyses are employed to evaluate the level of maturity of the protection techniques to preserve the protection goals (the code and data, state, and itinerary of the agent), with and without the threat of attacks. Challenges regarding the security of agents are presented and highlighted by seven research questions related to satisfying cyber security requirements, protecting the visiting agent and the visited host machine from each other, providing robustness against advanced attacks that target protection goals, quantifying the security in agent-based systems, and providing features of self-protection and self-communication to the agent itself.

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Section: Importance Of Abst In Distributed Systemsmentioning

confidence: 99%

A Survey: Agent-based Software Technology Under the Eyes of Cyber Security, Security Controls, Attacks and Challenges

Alluhaybi¹,

Alrahhal²,

Alzhrani³

et al. 2019

IJACSA

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“…Data clustering is mostly utilized to reduce correlated data for achieving energy conservation in WSNs [6][7][8][9]. In particular, several data clustering techniques have been explored including principal component analysis based aggregation (PCAg) [10], multiple-PCA [11], candid covariance-free incremental PCA (CCIPCA) [5], data aggregative window function (DAWF) [12], projection basis PCA [13], distributed PCA [14], K-means [15], enhanced K-means [9], K-medoids [16], singular value decomposition (SVD) [17], auto-regressive moving average (ARMA) [18], and least mean square (LMS) [19].…”

Section: Introductionmentioning

confidence: 99%

Error-Aware Data Clustering for In-Network Data Reduction in Wireless Sensor Networks

Alam

Aziz

Latif

et al. 2020

Sensors

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A wireless sensor network (WSN) deploys hundreds or thousands of nodes that may introduce large-scale data over time. Dealing with such an amount of collected data is a real challenge for energy-constraint sensor nodes. Therefore, numerous research works have been carried out to design efficient data clustering techniques in WSNs to eliminate the amount of redundant data before transmitting them to the sink while preserving their fundamental properties. This paper develops a new error-aware data clustering (EDC) technique at the cluster-heads (CHs) for in-network data reduction. The proposed EDC consists of three adaptive modules that allow users to choose the module that suits their requirements and the quality of the data. The histogram-based data clustering (HDC) module groups temporal correlated data into clusters and eliminates correlated data from each cluster. Recursive outlier detection and smoothing (RODS) with HDC module provides error-aware data clustering, which detects random outliers using temporal correlation of data to maintain data reduction errors within a predefined threshold. Verification of RODS (V-RODS) with HDC module detects not only random outliers but also frequent outliers simultaneously based on both the temporal and spatial correlations of the data. The simulation results show that the proposed EDC is computationally cheap, able to reduce a significant amount of redundant data with minimum error, and provides efficient error-aware data clustering solutions for remote monitoring environmental applications.

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“…The rapid expansion in raw data sets has led to the establishment of a technology known as 'big data' [41]. Large amounts of raw data prove to be challenging to process and maintain if traditional dataset methodologies are used [42]. Big data presents several methodologies that prove to be efficient for processing and storing large dataset volumes.…”

Section: An Introduction To Industry 40mentioning

confidence: 99%

“…The benefits of big data systems are increased data processing speed and efficient data storage. This, in turn, aids cyber-physical system scalability [42]. Industry 4.0 ecosystems rely on continuous information exchange; therefore, the absence of big data infrastructure and methodologies reduces the robustness and effectiveness of information exchange processes.…”

Section: An Introduction To Industry 40mentioning

confidence: 99%

Towards Industry 4.0: A Roadmap for the South African Heavy Industry Sector

Prinsloo

Vosloo

Mathews

2019

SAJIE

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The rapid growth and expansion of the Internet, as well as technical advances in the area of sensor technology, allow for the interconnection of physical objects for the purpose of achieving collective goals, which paves the way for the Fourth Industrial Revolution. The Industry 4.0 paradigm is a relatively new concept that still requires detailed investigation and discussion. Standards, technologies, and overall guidelines need to be presented; thus this review paper aims to address key questions to provide some clarity on navigating the tide of Industry 4.0. The key enabling technologies, and the extent to which these technologies can be applied in industry to achieve the fundamental goals of Industry 4.0, are presented and discussed. Current challenges that hinder

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Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks

Cited by 132 publications

References 29 publications

A Survey: Agent-based Software Technology Under the Eyes of Cyber Security, Security Controls, Attacks and Challenges

A Survey: Agent-based Software Technology Under the Eyes of Cyber Security, Security Controls, Attacks and Challenges

Error-Aware Data Clustering for In-Network Data Reduction in Wireless Sensor Networks

Towards Industry 4.0: A Roadmap for the South African Heavy Industry Sector

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