scholarly journals Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

Technologies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 76
Author(s):  
Gul Sahar ◽  
Kamalrulnizam Abu Bakar ◽  
Sabit Rahim ◽  
Naveed Ali Khan Kaim Khani ◽  
Tehmina Bibi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Data Model ◽  
Data Driven ◽  
Wireless Sensor ◽  
Specific Data ◽  
Recent Advancement ◽  
Rich Data

Wireless sensor networks (WSNs) are considered producers of large amounts of rich data. Four types of data-driven models that correspond with various applications are identified as WSNs: query-driven, event-driven, time-driven, and hybrid-driven. The aim of the classification of data-driven models is to get real-time applications of specific data. Many challenges occur during data collection. Therefore, the main objective of these data-driven models is to save the WSN’s energy for processing and functioning during the data collection of any application. In this survey article, the recent advancement of data-driven models and application types for WSNs is presented in detail. Each type of WSN is elaborated with the help of its routing protocols, related applications, and issues. Furthermore, each data model is described in detail according to current studies. The open issues of each data model are highlighted with their challenges in order to encourage and give directions for further recommendation.

scholarly journals Data Collection Protocols in Wireless Sensor Networks

2020 ◽  
Author(s):  
Koppala Guravaiah ◽  
Arumugam Kavitha ◽  
Rengaraj Leela Velusamy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Directional Antennas ◽  
Wireless Sensor ◽  
Duty Cycling ◽  
Iot Applications ◽  
Wide Range ◽  
Future Work

In recent years, wireless sensor networks have became the effective solutions for a wide range of IoT applications. The major task of this network is data collection, which is the process of sensing the environment, collecting relevant data, and sending them to the server or BS. In this chapter, classification of data collection protocols are presented with the help of different parameters such as network lifetime, energy, fault tolerance, and latency. To achieve these parameters, different techniques such as multi-hop, clustering, duty cycling, network coding, aggregation, sink mobility, directional antennas, and cross-layer solutions have been analyzed. The drawbacks of these techniques are discussed. Finally, the future work for routing protocols in wireless sensor networks is discussed.

A Secure and Verifiable Continuous Data Collection Algorithm in Wireless Sensor Networks

2021 ◽  
Author(s):  
Taochun Wang ◽  
Chengmei Lv ◽  
Xin Jin ◽  
Fulong Chen ◽  
Chengtian Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Wireless Sensor ◽  
Continuous Data

Latency-efficient Data Collection Scheduling in Battery-free Wireless Sensor Networks

2020 ◽  
Vol 16 (3) ◽  
pp. 1-21
Author(s):  
Tongxin Zhu ◽  
Jianzhong Li ◽  
Hong Gao ◽  
Yingshu Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Wireless Sensor ◽  
Efficient Data ◽  
Efficient Data Collection

scholarly journals Distributed and morphological operation-based data collection algorithm

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771759 ◽  
Author(s):  
Yalin Nie ◽  
Haijun Wang ◽  
Yujie Qin ◽  
Zeyu Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Algorithm Analysis ◽  
Wireless Sensor ◽  
Morphological Operation ◽  
Event Monitoring ◽  
Binary Images ◽  
Structuring Element

When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions.

scholarly journals Capacity of data collection in randomly-deployed wireless sensor networks

2010 ◽  
Vol 17 (2) ◽  
pp. 305-318 ◽  
Author(s):  
Siyuan Chen ◽  
Yu Wang ◽  
Xiang-Yang Li ◽  
Xinghua Shi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Wireless Sensor
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