A performance simulation tool for the analysis of data gathering in both terrestrial and underwater sensor networks

Wireless sensor networks (WSNs) have greatly contributed to human-associated technologies. The deployment of WSNs has transcended several paradigms. Two of the most significant features of WSNs are the intensity of deployment and the criticalness of the applications that they govern. The tradeoff between volume and cost requires justified investments for evaluating the multitudes of hardware and complementary software options. In underwater sensor networks (USNs), testing any technique is not only costly but also difficult in terms of full deployment. Therefore, evaluation prior to the actual procurement and setup of a WSN and USN is an extremely important step. The spectrum of performance analysis tools encompassing the test-bed, analysis, and simulation has been able to provide the prerequisites that these evaluations require. Simulations have proven to be an extensively used tool for analysis in the computer network field. A number of simulation tools have been developed for wired/wireless radio networks. However, each simulation tool has several restrictions when extended to the analysis of WSNs. These restrictions are largely attributed to the unique nature of each WSN within a designated area of research. In addition, these tools cannot be used for underwater environments with an acoustic communication medium, because there is a wide range of differences between radio and acoustic communications. The primary purpose of this paper is to present, propose, and develop a discrete event simulation designed specifically for mobile data gathering in WSNs. In addition, this simulator has the ability to simulate 2-D USNs. This simulator has been tailored to cater to both mobile and static data gathering techniques for both topologies, which are either dense or light. The results obtained using this simulator have shown an evolving efficient simulator for both WSNs and USNs. The developed simulator has been extensively tested in terms of its validity and scope of governance

Understanding the Characteristics of Pedestrians when Passing Obstacles of Different Sizes: An Experimental Study

The aim of this study is to understand the collective movements of individuals and to observe how individuals interact within a physical environment in a crowd dynamic, which has drawn the attention of many researchers. We conducted an experimental study to observe interactions in the collective motions of people and to identify characteristics of pedestrians when passing obstacles of different sizes (bar-shaped, 1.2 m, 2.4 m, 3.6 m and 4.8 m), going through one narrow exit and employing three different flow rates in walking and running conditions. According to the results of our study, there were no differences in collision-avoidance behaviour of pedestrians when walking or running. The pedestrians reacted early to the obstacles and changed the direction in which they were walking by quickly turning to the left or to the right. In terms of the speed of the pedestrians, the average velocity was significantly affected while performing these tasks, decreasing as the size of the obstacle increased; therefore, the size of obstacles will affect flow and speed levels. Travel time was shorter when participants were in the medium-flow rate experiments. In terms of the distance of each individual’s travel, our data showed that there was no significant difference in all the flow rate experiments for both speed levels. Our results also show that when the pedestrians crossed an obstacle, the lateral distance averaged from 0.3 m to 0.7 m, depending on the flow rate and speed level. We then explored how the body sways behaved while avoiding obstacles. It is observed that the average sway of the body was less in the high-speed conditions compared to the low-speed conditions – except for the HF & 4.8 m experiment. These results are expected to provide an insight into the characteristics of the behaviour of pedestrians when avoiding objects, and this could help enhance agent-based models

Does dental students' attendance in classroom lectures depend on the mode of attendance tracking?

Purpose: The necessity to attend classroom lectures is a disputable topic among dental schools globally. Since there is an ongoing debate on different aspects of this problem in literature, the purpose of this study was to compare students’ attitudes toward classroom attendance and investigate if stricter attendance tracking methods could lead to better classroom attendance at two dental schools utilising different modes of tracking students’ attendance. Method: This was an observational, cross-sectional survey distributed among dental students enrolled at King Abdul-Aziz University (KAU) and King Saud University (KSU) in Saudi Arabia. The survey included questions on demographics, average travel time, student's attitudes toward classroom lectures and common reasons for absenteeism. Collected data were analysed and summarised as frequencies and percentages and then compared using the Chi-square test for statistical significance. Findings: The study involved 678 participants from KAU and 475 participants from KSU. In general, there was a significant difference in students’ attendance between both schools in which 26.8% of KAU dental students skipped 5 or more lectures/month compared to 11.5% of students at KSU. Among the factors affecting classroom lecture attendance, commuting time was a major one reported by students (44.8% of students at KSU and 51.4% at KAU needed 30-60 min to reach their schools). The availability of lectures through online resources and the necessity to study for exams were additional factors reported by students of both schools. Implications for research and practices: Based on the current data, the school’s method to track students’ attendance may have a role in the pattern of classroom absenteeism

A Method for Distributed Pipeline Burst and Leakage Detection in Wireless Sensor Networks Using Transform Analysis

Bursts and leakages have turned out to be one of the most frequent malfunctions in liquid pipeline distribution systems. In recent years, the issue has gained a lot of attention in research community due to associated financial costs, environmental hazards, and safety considerations. Wireless sensor network (WSN) based leakage detection and localization can provide an exceptional level of operational efficiency, safety assurance, and real-time parametric view of the entire pipeline network. In this paper, we propose a transient pressure wave based technique coupled with wavelet analysis to achieve reliable detection and localization of abrupt bursts and leakages. The presented technique uses the information carried in the transient pressure signal. A specific pattern is induced on the pressure traces within the pipeline due to leak; we use wavelet analysis to detect these local singularities. The proposed algorithm is distributed in nature and run on low power sensor nodes. The algorithm is deployed in field on a custom pipeline test bed and performance results are documented for various testing scenarios. A comparison of proposed wavelet technique with other widely used methods has been carried out. The technique provides more than 90% accuracy in a number of deployment scenarios for high noise generating long pipeline networks

A Predictive Data Reliability Method for Wireless Sensor Network Applications

International audienc

A Predictive Data Reliability Method for Wireless Sensor Network Applications

International audienc

MMSPEED: Multipath multi-SPEED protocol for QoS guarantee of reliability and timeliness in wireless sensor networks

Abstract—In this paper, we present a novel packet delivery mechanism called Multi-Path and Multi-SPEED Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. These mechanisms for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates for local decision inaccuracies as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements up to 50 percent (12 flows versus 18 flows)