Communications Networks
M. Z. Rahman; J. E. Giti; S. A.H. Chowdhury; M. S Anower
Abstract
Background and Objectives: Node counting is undoubtedly an essential task since it is one of the important parameters to maintain proper functionality of any wireless communications network including undersea acoustic sensor networks (UASNs). In undersea communications networks, protocol-based node counting ...
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Background and Objectives: Node counting is undoubtedly an essential task since it is one of the important parameters to maintain proper functionality of any wireless communications network including undersea acoustic sensor networks (UASNs). In undersea communications networks, protocol-based node counting techniques suffer from poor performance due to the unique propagation characteristics of the medium. To solve the issue of counting nodes of an undersea network, an approach based on cross-correlation (CC) of Gaussian signals has been previously introduced. However, the limited bandwidth (BW) of undersea communication presents a significant challenge to the node counting technique based on CC, which traditionally uses Gaussian signals with infinite BW. This article aims to investigate this limitation. Methods: To tackle the infinite BW issue, a band-limited Gaussian signal is employed for counting nodes, impacting the cross-correlation function (CCF) and the derived estimation parameters. To correlate the estimation parameters for finite and infinite BW scenarios, a scaling factor (SF) is determined for a specific BW by averaging their ratios across different node counts. Results: Error-free estimation in a band-limited condition is reported in this work if the SF for that BW is known. Given the typical undersea BW range of 1–15 kHz, it is also important to establish a relationship between the SF and BW. This relationship, derived and validated through simulation, allows for determining the SF and achieving accurate node count under any band-limited condition within the 1–15 kHz range. Furthermore, an evaluation of node counting performance in terms of a statistical parameter called the coefficient of variation (CV) is performed for finite BW scenarios. As a side contribution, the effect of noise on the CC-based undersea node counting approach is also explored.Conclusion: This research reveals that successful node counting can be achieved using the CC-based technique in the presence of finite undersea BW constraints.
Communications Networks
M. Hosseini Shirvani; A. Akbarifar
Abstract
Background and Objectives: Wireless sensor networks (WSNs) are ad-hoc technologies that have various applications in different industries such as in healthcare systems, environment and military surveillance, manufacturing, and IoT context in general. Expanding the scope of sensor network applications ...
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Background and Objectives: Wireless sensor networks (WSNs) are ad-hoc technologies that have various applications in different industries such as in healthcare systems, environment and military surveillance, manufacturing, and IoT context in general. Expanding the scope of sensor network applications has led researchers to develop solutions to provide sustainable communications and networks for distributed environments, as well as how to secure these methods with limited resources.Methods: The lack of infrastructure space and the vulnerable nature of these networks make it difficult to design security models and algorithms for them. So, to run the sensor network in safe mode, any type of attack must be detected before any security breach is materialized. According to the importance of the network and also the nature of the sensor networks along with the critical challenge of energy consumption, solutions and defensive lines such as intrusion prevention and intrusion detection systems will be selected.Results: This paper surveys subjectively the intrusion and anomaly detection system in WSNs to determine potentials and challenges for further processing. Therefore, designing an efficient and optimal intrusion detection solution applicable to wireless sensor networks, IoT, and other ad-hoc networks has been a major challenge that will help the researcher to design or choose the best approach for their future research.Conclusion: This research also pave the way of interested researchers to find existing challenges and shortcomings for further processing.
Communications Networks
M. Ghaderi; V. Tabataba Vakili; M. Sheikhan
Abstract
Background and Objectives: Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques ...
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Background and Objectives: Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to the sink. Spatiotemporal CS (STCS), with the use of spatial and temporal correlation of sensor readings, can increase the compression rate in WSNs, thereby reducing the cost of communication. Methods: In this paper, a new method of STCS technique based on the geographic adaptive fidelity (GAF) protocol is proposed which can effectively reduce the communication cost and energy consumption in WSNs. In the proposed method, temporal data is obtained from random selection of temporal readings of cluster head (CH) sensors located in virtual cells in the clustered sensors' area and spatial data will be formed from the data readings of CHs located on the routes. Accordingly, a new structure of sensing matrix will be created. Results: The results of proposed method show that the proposed method as compared to the method proposed in [29], which is the most similar method in the literature, reduces energy consumption in the range of 22% to 43% in various scenarios which were implemented based on the number of required measurements at the sink (M) and the number of measurements in the routes (mr). Conclusion: In the proposed method, based on spatio-temporal CS (STCS), a new structure of sensing matrix is created that can increase the compression rate, thereby reducing the communication cost in the WSNs.======================================================================================================Copyrights©2018 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.======================================================================================================
