In-network Data Aggregation Techniques for Wireless Sensor Networks: A Survey

Kiruthiga, T.; Shanmugasundaram, N.

doi:10.1007/978-981-16-0965-7_68

Cited by 15 publications

(7 citation statements)

References 19 publications

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“…It has been calibrated to significantly reduce resource allocation overhead when synchronization operations between different devices on the network change. Kiruthiga et al 25 illustrated that the resource utilization of various nodes (r 1 , r 2 , r 3 … .r n ) is achieved if the scatternet network is a bipartite graph. This can possible if the sum of resources in all intervals transverse the node is ≤1.…”

Section: Related Workmentioning

confidence: 99%

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L‐RUBI: An efficient load‐based resource utilization algorithm for bi‐partite scatternet in wireless personal area networks

Logeshwaran¹,

Nallasamy²,

Lloret

2023

Int J Communication

134

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Recently, much of the wireless personal area network (WPAN) research concerns network protocols, scheduling, and security challenges but the major issue of resource utilization has been very rarely investigated. The design of resource sharing in a network gets more attention when the number of users increases. While optimizing performance, resource utilization plays a critical role. In this paper, the numerical performance of a wireless resource utilization algorithm for a bi-partite scatternet is presented. This algorithm is focused to enhance the bandwidth allocation and power utilization of wireless scatternets.Every node can communicate with a single neighbor at a time with minimum resources. Finally, the performances of the RUBI algorithm are shown. This algorithm is compared with the existing algorithms such as the load adaptive scheduling algorithm and pseudorandom coordinated scheduling scheme in terms of various parametric metrics like reliability, throughput, collision probability, transmission probability, and signal-to-noise ratio (SINR). The proposed L-RUBI achieves 93.4% of reliability, 93.6% of transmission probability, 91.4% of throughput, 76.8% of collision performance, and 72.2% SINR.

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Section: Related Workmentioning

confidence: 99%

“…Here, the Minimum average service time was properly managed. So the users can wait some minimum duration to utilize the resources 5 Kiruthiga et al 25 Resource utilization of various nodes is achieved if the scatternet network using a bipartite graph…”

Section: Scatternet Resource Utilization Problemmentioning

confidence: 99%

L‐RUBI: An efficient load‐based resource utilization algorithm for bi‐partite scatternet in wireless personal area networks

Logeshwaran¹,

Nallasamy²,

Lloret

2023

Int J Communication

134

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“…Kiruthuiga and Shanmugasundaram [23] discussed mobile networks, and it combines clustering and full-duplex connections such that messages could continue even though the mobile infrastructure is largely down. As per simulation results, the proposed clustering method performs well enough in respect of reliability and emission reduction, while clustered construction may enlarge the provided significant.…”

Section: Related Workmentioning

confidence: 99%

OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management

Raja

Logeshwaran²,

Srinivasan³

et al. 2022

Scientific Programming

130

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As an underlayment to cellular 5G communication network, device-to-device (D2D) communications will not only boost capacity utilization and power efficiency but also provide public health and public safety services. One of the most important requirements for these businesses is to have alternate access to cellular networks in the event that they are partially or completely disrupted as a result of a natural disaster. Despite limited communication coverage and bandwidth scarcity, the 3rd Generation Partnership Project (3GPP) must have developed a new device-to-device (D2D) communication method fundamental enhanced mobile that can strengthen spectral efficiencies besides allowing direct communication of gadgets in close propinquity devoid of transitory by elevated-node B (eNB). Unfortunately, enabling data transmission on a cellular connection offers a challenge in terms of two-way radio source administration, because D2D associates recycle cellular users’ uplink radio resources, which might create interference to D2D user equipment’s (DUE) receiving channels. In this study, we concentrate on optimal cluster head selection using the binary flower pollination optimization algorithm by designing an energy-efficient lifetime-aware leisure degree adaptive routing protocol named OptCH_L-LDAR. This topology is constructed with a multi-hop obliging communication system, instructed on the way to wrap an extensive remoteness connecting source and destination. The proposed OptCH_L-LDAR is compared with three state-of-art methods such as binary flower pollination (BFP) algorithm, time division multiple access (TDMA), and data-driven technique (DDT). As a result, the proposed OptCH_L-LDAR achieves 96% of energy efficiency, 89% of lifetime, 97% of outage probability, and 98% of spectral efficiency.

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“…In [40] data aggregation approaches systematically reviewed, examined and categorized into Flat Network and Hierarchical Network based on different factors (e.g., types of networks and algorithms, node heterogeneity, and the aggregator mobility). In-network data aggregation algorithms are surveyed and analyzed in [41] based on various parameters like energy efficiency, aggregation rate, network lifetime, number of alive nodes, throughput, energy-saving techniques, scalability, network security, route overlap, and route repair mechanisms. A review of DC techniques proposed in [42] with objectives to providing a detailed comparison between the maximum amount shortest path (MASP) and zone-based energy-aware (ZEAL) DC protocols and to help researchers in selecting the most suitable protocol for a WSN application.…”

Section: Related Workmentioning

confidence: 99%

Recent Studies Utilizing Artificial Intelligence Techniques for Solving Data Collection, Aggregation and Dissemination Challenges in Wireless Sensor Networks: A Review

et al. 2022

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The growing importance and widespread adoption of Wireless Sensor Network (WSN) technologies have helped the enhancement of smart environments in numerous sectors such as manufacturing, smart cities, transportation and Internet of Things by providing pervasive real-time applications. In this survey, we analyze the existing research trends with respect to Artificial Intelligence (AI) methods in WSN and the possible use of these methods for WSN enhancement. The main goal of data collection, aggregation and dissemination algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this paper, we highlight data collection, aggregation and dissemination challenges in WSN and present a comprehensive discussion on the recent studies that utilized various AI methods to meet specific objectives of WSN, during the span of 2010 to 2021. We compare and contrast different algorithms on the basis of optimization criteria, simulation/real deployment, centralized/distributed kind, mobility and performance parameters. We conclude with possible future research directions. This would guide the reader towards an understanding of up-to-date applications of AI methods with respect to data collection, aggregation and dissemination challenges in WSN. Then, we provide a general evaluation and comparison of different AI methods used in WSNs, which will be a guide for the research community in identifying the mostly adapted methods and the benefits of using various AI methods for solving the challenges related to WSNs. Finally, we conclude the paper stating the open research issues and new possibilities for future studies.

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In-network Data Aggregation Techniques for Wireless Sensor Networks: A Survey

Cited by 15 publications

References 19 publications

L‐RUBI: An efficient load‐based resource utilization algorithm for bi‐partite scatternet in wireless personal area networks

L‐RUBI: An efficient load‐based resource utilization algorithm for bi‐partite scatternet in wireless personal area networks

OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management

Recent Studies Utilizing Artificial Intelligence Techniques for Solving Data Collection, Aggregation and Dissemination Challenges in Wireless Sensor Networks: A Review

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