This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy.
Due to the massive growth of mobile users, the demand for data traffic along with coverage enhancement has significantly increased and put a significant burden on the pre-existing system like infrastructure based cellular networks, etc., especially in the urban zone. The inabilities and inefficiencies of pre-existing systems in handling a large number of traffic demands is a major concern. One way by which the existing infrastructure based cellular network can fulfill the above requirements by the increasing power level of radiations.But increasing the radiation power levels above a safety value defined by international exposure standards results in adverse health effects in the society. The impact is more on the urban societies because of congestion dwelling than rural areas. A vital solution to the above challenges of full filling the user's demand capacity as well as prevent the society from adverse health effects are to control ground-level data plane network aerially. That is not to make mobile users utterly dependent on the existing base stations. This could be possible through such as Loon Technology, Tethered Balloon, unmanned aerial vehicles (UAVs) concept, etc. The key objective is to efficiently deploy a HetNet wireless network using UAVs in urban canyons for great coverage and capacity enhancement and reduce the effects of radiations. The simulation results show the betterment in spectral efficiency, transmission range, transmission delays, and efficient packet delivery.
Summary The traditional centralized cloud computing (CC) model faces a range of problems with the exponential growth of the Internet of Things (IoT) applications, like high latency, reduced bandwidth, and network instability. Fog computing (FC) takes the cloud closer to IoT computers to overcome these problems. Rather than moving them to the cloud, the FC provides local IoT data processing and storage on IoT computers. This paper focuses on the Routing Protocol for Low‐Power and Lossy Network (RPL), a universally routing protocol for a static environment that is used for reducing energy consumption, delay, and packet loss with data aggregation at the border router using a fog simulation model in Contiki Cooja. The objective function (OF) choice has an impact on network topology, as each node selects a set of potential parents to send to the destination. However, no systematic analysis of the effects of OF behavior in the RPL environment has been undertaken. Here, three different OFs, Objective Function Zero (OF0), Advanced Objective Function Zero (AOF0), and Minimum Rank with Hysteresis Objective Function (MRHOF) for RPL in the static environment for different node numbers, have been compared. The findings demonstrate that altering all three OFs has a significant impact on RPL. The energy consumption is reduced in the case of the AOF0 in the fog node by 50.86%, which is less than the case of the OF0 and MRHOF function. Extensive simulations show that AOF0 outperforms the existing OFs.
As the number of user equipment (UE) in any heterogeneous network (HetNet) assisted by unmanned aerial vehicles (UAV) continues to grow, so does the number of intruder nodes. The intruder/malicious nodes are able to interfere with the ongoing data transmission in the network and carry out different kinds of active and passive attacks such as spoofing, masquerading, impersonating, and so on in the network thus requiring an optimized security technique for the network. This article implements the novel functional encryption (FE) technique in the proposed UAV assisted HetNet model for the dense urban area to secure data against such intrusions. In this network model, UAV acts as a relay node for those UE which are in nonline‐of‐sight communication with macro based station (MBS). For securing the data transmission among UAV, UE, and MBS, FE technique is implemented in the network in two phases: the first phase between UE and MBS and the second phase between MBS and UE through UAV. During implementation, the Dolev‐Yao attack model is considered in which intruders are able to intercept or modify the UE data. The main objective of the FE technique implementation is to provide security from such intrusion attacks. The proposed methodology is validated using automated validation of Internet security protocols and applications (AVISPA) tool. The results of the AVISPA tool clearly indicate that the proposed technique is safe to implement in the UAV assisted HetNet, even in the presence of intruder nodes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.