4 research outputs found
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A mobile assisted coverage hole patching scheme based on particle swarm optimization for WSNs
Wireless sensor networks (WSNs) have drawn much research attention in recent years due to the superior performance in multiple applications, such as military and industrial monitoring, smart home, disaster restoration etc. In such applications, massive sensor nodes are randomly deployed and they remain static after the deployment, to fully cover the target sensing area. This will usually cause coverage redundancy or coverage hole problem. In order to effectively deploy sensors to cover whole area, we present a novel node deployment algorithm based on mobile sensors. First, sensor nodes are randomly deployed in target area, and they remain static or switch to the sleep mode after deployment. Second, we partition the network into grids and calculate the coverage rate of each grid. We select grids with lower coverage rate as candidate grids. Finally, we awake mobile sensors from sleep mode to fix coverage hole, particle swarm optimization (PSO) algorithm is used to calculate moving position of mobile sensors. Simulation results show that our algorithm can effectively improve the coverage rate of WSNs
Recommended from our members
A mobile assisted coverage hole patching scheme based on particle swarm optimization for WSNs
Wireless sensor networks (WSNs) have drawn much research attention in recent years due to the superior performance in multiple applications, such as military and industrial monitoring, smart home, disaster restoration etc. In such applications, massive sensor nodes are randomly deployed and they remain static after the deployment, to fully cover the target sensing area. This will usually cause coverage redundancy or coverage hole problem. In order to effectively deploy sensors to cover whole area, we present a novel node deployment algorithm based on mobile sensors. First, sensor nodes are randomly deployed in target area, and they remain static or switch to the sleep mode after deployment. Second, we partition the network into grids and calculate the coverage rate of each grid. We select grids with lower coverage rate as candidate grids. Finally, we awake mobile sensors from sleep mode to fix coverage hole, particle swarm optimization (PSO) algorithm is used to calculate moving position of mobile sensors. Simulation results show that our algorithm can effectively improve the coverage rate of WSNs
Opportunities and challenges posed by disruptive and converging information technologies for Australia\u27s future defence capabilities: A horizon scan
Introduction: The research project\u27s objective was to conduct a comprehensive horizon scan of Network Centric Warfare (NCW) technologies—specifically, Cyber, IoT/IoBT, AI, and Autonomous Systems. Recognised as pivotal force multipliers, these technologies are critical to reshaping the mission, design, structure, and operations of the Australian Defence Force (ADF), aligning with the Department of Defence (Defence)’s offset strategies and ensuring technological advantage, especially in the Indo-Pacific\u27s competitive landscape.
Research process: Employing a two-pronged research approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 415 professionals and six experts across STEM, law enforcement, and ICT, aimed to assess the impact, deployment likelihood, and developmental timelines of the identified technologies.
Findings: Key findings revealed significant overlaps in technology clusters, highlighting 11 specific technologies or trends as potential force multipliers for the ADF. Among these, Cyber and AI technologies were recognised for their immediate potential and urgency, suggesting a prioritisation for development investment. The analysis presented a clear imperative for urgent and prioritised technological investments, specifically in Cyber and AI technologies, followed by IoT/IoBT and autonomous systems technologies. The recommended strategic focus entails enhancing cyber security of critical infrastructure, optimising network communications, and harnessing smart sensors, among others.
Implications: To maintain a competitive edge, the ADF and the Australian government must commit to significant investments in these priority technologies. This involves not only advancing the technological frontier but also fostering a flexible, innovation-friendly environment conducive to leveraging non-linear opportunities in technology innovation. Such an approach requires a concerted effort from both public and private sectors to invest resources effectively, ensuring the ADF\u27s adaptability and strategic overmatch in a rapidly changing technological landscape.
Conclusion: Ultimately, this research illuminates the path forward for the ADF and Defence at large, highlighting the need for strategic investments in emerging technologies. By identifying strategic gaps, potential alliances, and sovereign technologies of high potential, this report serves as a blueprint for enhancing Australia\u27s defence capabilities and securing its strategic interests in the face of global technological shifts