Search Results (515)

Breast cancer remains one of the primary causes of cancer-related deaths among women globally. Early detection via mammography is essential for improving prognosis and survival rates. However, mammogram diagnostic accuracy is severely hindered by dense breast tissue, which can obstruct potential malignancies, complicating early detection. To tackle this pressing issue, this study introduces an innovative approach that leverages Generative Adversarial Networks (GANs), specifically CycleGAN and GANHopper, to transform breast density in mammograms. The aim is to diminish the masking effect of dense tissue, thus enhancing the visibility of underlying malignancies. The method uses unsupervised image-to-image translation to gradually alter breast density (from high (ACR-D) to low (ACR-A)) in mammographic images, detecting obscured lesions while preserving original diagnostic features. We applied this approach to multiple mammographic datasets, demonstrating its effectiveness in diverse contexts. Experimental results exhibit substantial improvements in detecting potential malignancies concealed by dense breast tissue. The method significantly improved precision, recall, and F1-score metrics across all datasets, revealing previously obscured malignancies and image quality assessments confirmed the diagnostic relevance of transformed images. The study introduces a novel mammogram analysis method using advanced machine-learning techniques, enhancing diagnostic accuracy in dense breasts and potentially improving early breast cancer detection and patient outcomes. Full article

In order to address the problems of low spectrum efficiency in current communication systems and extend the lifetime of energy-constrained relay devices, this paper proposes a novel dual-hop free-space optical (FSO) system that integrates cognitive radio (CR) and energy harvesting (EH). In this system, the source node communicates with two users at the terminal via FSO and terahertz (THz) hard-switching links, as well as a multi-antenna relay for non-orthogonal multiple access (NOMA). There is another link whose relay acts as both the power beacon (PB) in the EH system and the primary network (PN) in the CR system, achieving the double function of auxiliary transmission. In addition, based on the three possible practical working scenarios of the system, three different transmit powers of the relay are distinguished, thus enabling three different working modes of the system. Closed-form expressions are derived for the interruption outage probability per user for these three operating scenarios, considering the Gamma–Gamma distribution for the FSO link, the $\alpha -\mu$ distribution for the THz link, and the Rayleigh fading distribution for the radio frequency (RF) link. Finally, the numerical results show that this novel system can be adapted to various real-world scenarios and possesses unique advantages. Full article

In this paper, we demonstrate the realistic test of a 2.4 GHz multi-hop wireless network for mountainous forest and watercourse environments. A multi-hop network using IEEE 802.15.4 XBee3 micro-modules and a communication protocol among nodes were developed. A wireless node deployment solution was introduced for practical testing. The proposed system’s communication reliability was tested in two different scenarios: a mountainous forest with sloping areas and trees and a watercourse, which referred to environmental and flooding monitoring applications. Wireless network performances were evaluated through the received signal strength indicator (RSSI) level of each wireless link, a packet delivery ratio (PDR), as the successful rate of packet transmission, and the end-to-end delay (ETED) of all data packets from the transmitter to the receiver. The experimental results demonstrate the success of the multi-hop WSN deployment and communication in both scenarios, where the RSSI of each link was kept at the accepted level and the PDR achieved the highest result. Furthermore, as a real-time response, the data from the source could be sent to the sink with a small ETED. Full article

When there are time division multiple access (TDMA) signals with large bandwidth, waveform aliasing, and fast frequency-hopping in space, current methods have difficulty achieving the accurate localization of radiation sources and signal-sorting from multiple network stations. To solve the above problems, a distributed passive positioning and network stations sorting method for broadband frequency-hopping signals based on two-level parameter estimation and joint clustering is proposed in this paper. Firstly, a two-stage filtering structure is designed to achieve control filtering for each frequency point. After narrowing down the parameter estimation range through adaptive threshold detection, the time difference of arrival (TDOA) and the velocity difference of arrival (VDOA) can be obtained via coherent accumulating based on the cross ambiguity function (CAF). Then, a multi-station positioning method based on the TDOA/VDOA is used to estimate the position of the target. Finally, the distributed joint eigenvectors of the multi-stations are constructed, and the signals belonging to different network stations are effectively classified using the improved K-means method. Numerical simulations indicate that the proposed method has a better positioning and sorting effect in low signal-to-noise (SNR) and low snapshot conditions compared with current methods. Full article

Due to the rapid development of smart vehicles, such as self-driving cars, the demand for mobile data traffic by vehicle users has increased so much that base stations cannot handle it, causing delays in content provision. The burden on the base station can be alleviated through roadside units (RSUs) to distribute the demand. However, outage zones, which fall outside the communication range of RSUs, still exist due to their high deployment cost. Existing schemes for covering outage zones have only considered single-hop precaching vehicles to provide precached content, which is insufficient to reduce outage zones effectively. Therefore, we propose a scheme to reduce outage zones by maximizing the amount of precached content using multi-hop precaching vehicles. The proposed scheme optimally selects precaching vehicles through a numerical model that calculates the amount of precached content. It enhances the process of multi-hop precaching by comparing the connection time of vehicles with the dark area time in the outage zone. To prevent excessive overheads due to frequent precaching vehicle handovers, the proposed scheme limits the selection to vehicles with a longer communication time, based on a precaching restriction indicator in the multi-hop precaching vehicle selection process. The simulation results show that our scheme outperforms representative schemes based on single-hop precaching. Full article

Batched network coding (BNC) is a practical realization of random linear network coding (RLNC) designed for reliable network transmission in multi-hop networks with packet loss. By grouping coded packets into batches and restricting the use of RLNC within the same batch, BNC resolves the issue of RLNC that has high computational and storage costs at the intermediate nodes. A simple and common way to apply BNC is to fire and forget the recoded packets at the intermediate nodes, as BNC can act as an erasure code for data recovery. Due to the finiteness of batch size, the recoding strategy is a critical design that affects the throughput, the storage requirements, and the computational cost of BNC. The gain of the recoding strategy can be enhanced with the aid of a feedback mechanism, however the utilization and development of this mechanism is not yet standardized. In this paper, we investigate a multi-phase recoding mechanism for BNC. In each phase, recoding depends on the amount of innovative information remained at the current node after the transmission of the previous phases was completed. Relevant information can be obtained via hop-by-hop feedback; then, a more precise recoding scheme that allocates networking resources can be established. Unlike hop-by-hop retransmission schemes, the reception status of individual packets does not need to be known and packets to be sent in the next phase may not be the lost packets in the previous phase. Further, due to the loss-tolerance feature of BNC, it is unnecessary to pass all innovative information to the next node. This study illustrates that multi-phase recoding can significantly boost the throughput and reduce the decoding time as compared with the traditional single-phase recoding approach This opens a new window in developing better strategies for designing BNC rather than sending more batches in a blind manner. Full article

The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is a widely used method for managing energy consumption in Wireless Sensor Networks (WSNs). However, it has limitations that affect network longevity and performance. This paper presents an improved version of the LEACH protocol, termed MFG-LEACH, which incorporates the Mean Field Game (MFG) theory to optimize energy efficiency and network lifetime. The proposed MFG-LEACH protocol addresses the imbalances in energy consumption by modeling the interactions among nodes as a game, where each node optimizes its transmission energy based on the collective state of the network. We conducted extensive simulations to compare MFG-LEACH with Enhanced Zonal Stable Election Protocol (EZ-SEP), Energy-Aware Multi-Hop Routing (EAMR), and Balanced Residual Energy routing (BRE) protocols. The results demonstrate that MFG-LEACH significantly reduces energy consumption and increases the number of packets received across different node densities, thereby validating the effectiveness of our approach. Full article

The increasing adoption of Internet of Things (IoT) technologies has facilitated the creation of advanced applications in various industries, notably in complex workplaces where safety and efficiency are paramount. This paper addresses the challenge of monitoring worker presence in vast workplaces such as shipyards, large factories, warehouses, and other construction sites due to a lack of traditional network infrastructure. In this context, we developed a novel system integrating Bluetooth Low Energy (BLE) beacons with multi-hop IoT networks by using the ESP-NOW communications protocol, first introduced by Espressif Systems in 2017 as part of its ESP8266 and ESP32 platforms. ESP-NOW is designed for peer-to-peer communication between devices without the need for a WiFi router, making it ideal for environments where traditional network infrastructure is limited or nonexistent. By leveraging the BLE beacons, the system provides real-time presence data of workers to enhance safety protocols. ESP-NOW, a low-power communications protocol, enables efficient, low-latency communication across extended ranges, making it suitable for complex environments. Utilizing ESP-NOW, the multi-hop IoT network architecture ensures extensive coverage by deploying multiple relay nodes to transmit data across large areas without Internet connectivity, effectively overcoming the spatial challenges of complex workplaces. In addition, the Message Queuing Telemetry Transport (MQTT) protocol is used for robust and efficient data transmission, connecting edge devices to a central Node-RED server for real-time remote monitoring. Moreover, experimental results demonstrate the system’s ability to maintain robust communication with minimal latency and zero packet loss, enhancing worker safety and operational efficiency in large, complex environments. Furthermore, the developed system enhances worker safety by enabling immediate identification during emergencies and by proactively identifying hazardous situations to prevent accidents. Full article

Currently, underwater sensor networks are extensively applied for environmental monitoring, disaster prediction, etc. Nevertheless, owing to the complicacy of the underwater environment, the limited energy of underwater sensor nodes, and the high latency of hydroacoustic channels, the energy-efficient operation of underwater sensor networks has become an important challenge. In this paper, a high-efficiency clustering routing protocol in AUV-assisted underwater sensor networks (HECRA) is proposed to address the energy limitations and low data transmission reliability in underwater sensor networks. The protocol optimizes the cluster head selection strategy of the traditional low-energy adaptive clustering hierarchy (LEACH) protocol by introducing the residual energy and node degree in the cluster head selection phase and performs some optimizations in the cluster formation and data transmission phases, including selecting clusters for joining by ordinary nodes based on the residual energy of the cluster head nodes and weight computation based on the depth and residual energy of the cluster head nodes to select the optimal message forwarding nodes. In addition, this paper introduces an autonomous underwater vehicle (AUV) as a dynamic relay node to improve network transmission efficiency. According to the simulation results, compared with the existing LEACH, the energy efficient routing protocol based on layers and unequal clusters in underwater wireless sensor networks (EERBLC) and energy-efficient clustering multi-hop routing protocol in a UWSN (EECMR), the HECRA significantly improves network lifetime, the residual node energy, and the number of successfully transmitted packets, which can effectively prolong network lifetime and ensure efficient data transmission. Full article

In recent years, LoRa technology has emerged as a solution for wide-area coverage IoT applications. Deploying a LoRa single-hop network on applications may be challenging in cases of network deployments that require the installation of linear sensor network topologies covering very large distances over unpopulated areas with limited access to cellular networks and energy grids. In such cases, multi-hop communication may provide better alternative solutions to support these challenges. This research aims to study the deployment of multi-hop linear sensor networks that are energy efficient. The focus will be on assessing the coverage, throughput, and energy consumption benefits that can be achieved and the related tradeoffs that have to be considered when using multi-hop solutions. Since monitoring systems in long-distance infrastructures may benefit from solutions based on multi-hop communication, we consider oil pipeline infrastructures in the Saudi Arabian desert as a case study. An analytical model is considered for estimating the above-stated parameters and evaluating the performance of the multi-hop LoRa WSN (MHWSN) against the single-hop LoRa WSN (SHWSN). In addition, the model is used to study the tradeoffs between throughput and energy consumption in different settings of MHWSNs. Scenarios of oil pipeline monitoring systems in Saudi Arabia are specified for studying the proposed multi-hop system’s performance. The obtained results show that when we have a large-scale network, such as an oil pipeline with medium traffic load requirements, multi-hop topologies may be an efficient deployment solution. Full article

The advancement of communication technologies has facilitated the deployment of numerous sensors, terminal human–machine interfaces, and smart devices in various complex environments for data collection and analysis, providing automated and intelligent services. The increasing urgency of monitoring demands in complex environments necessitates low-cost and efficient network deployment solutions to support various monitoring tasks. Distributed networks offer high stability, reliability, and economic feasibility. Among various Low-Power Wide-Area Network (LPWAN) technologies, Long Range (LoRa) has emerged as the preferred choice due to its openness and flexibility. However, traditional LoRa networks face challenges such as limited coverage range and poor scalability, emphasizing the need for research into distributed routing strategies tailored for LoRa networks. This paper proposes the Optimizing Link-State Routing Based on Load Balancing (LB-OLSR) protocol as an ideal approach for constructing LoRa distributed multi-hop networks. The protocol considers the selection of Multipoint Relay (MPR) nodes to reduce unnecessary network overhead. In addition, route planning integrates factors such as business communication latency, link reliability, node occupancy rate, and node load rate to construct an optimization model and optimize the route establishment decision criteria through a load-balancing approach. The simulation results demonstrate that the improved routing protocol exhibits superior performance in node load balancing, average node load duration, and average business latency. Full article

In this paper, we present the development and evaluation of a contextually relevant, cost-effective, multihop cluster-based agricultural Internet of Things (MCA-IoT) network. This network utilizes commercial off-the-shelf (COTS) Bluetooth Low-Energy (BLE) and LoRa communication technologies, along with the Raspberry Pi 3 Model B+ (RPi 3 B+), to address the challenges of climate change-induced global food insecurity in smart farming applications. Employing the lean engineering design approach, we initially implemented a centralized cluster-based agricultural IoT (CA-IoT) hardware testbed incorporating BLE, RPi 3 B+, STEMMA soil moisture sensors, UM25 m, and LoPy low-power Wi-Fi modules. This system was subsequently adapted and refined to assess the performance of the MCA-IoT network. This study offers a comprehensive reference on the novel, location-independent MCA-IoT technology, including detailed design and deployment insights for the agricultural IoT (Agri-IoT) community. The proposed solution demonstrated favorable performance in indoor and outdoor environments, particularly in water-stressed regions of Northern Ghana. Performance evaluations revealed that the MCA-IoT technology is easy to deploy and manage by users with limited expertise, is location-independent, robust, energy-efficient for battery operation, and scalable in terms of task and size, thereby providing a versatile range of measurements for future applications. Our results further demonstrated that the most effective approach to utilizing existing IoT-based communication technologies within a typical farming context in sub-Saharan Africa is to integrate them. Full article

With the continuous progress and development of technology, the Internet of Everything (IoE) is gradually becoming a research hotspot. More companies and research institutes are focusing on the connectivity and transmission between multiple devices in asymmetric networks, such as V2X, Industrial Internet of Things (IIoT), environmental monitoring, disaster management, agriculture, and so on. The number of devices and business volume of these applications have rapidly increased in recent years, which will lead to a large load of terminals and affect the transmission efficiency of IoE data transmission. To deal with this issue, it has been proposed to perform data transmission via multipath cooperative transmission with multihop transmission. This approach aims to improve transmission latency, energy consumption, reliability, and throughput. This paper designs a channel-sensing-based cooperative transmission mechanism (CSCTM) with hybrid automatic repeat request (HARQ) for user equipment (UE) aggregation mechanism in future asymmetric IoE scenarios, which ensures that IoE devices data can be transmitted quickly and reliably, and supports real-time data processing and analysis. The main contents of this proposed method include strategies of cooperative transmission and redundancy version (RV) determination, a joint combination of decoding process at the receiving side, and a design of transmission priority through ascending offset sort (AOS) algorithm based on channel sensing. In addition, multihop technology is designed for the multipath cooperative transmission strategy, which enables cooperative nodes (CN) to help UE to transmit data. As a result, it can be obtained that CSCTM provides significant advancements in latency and energy consumption for the whole system. It demonstrates improvements in enhanced coverage, improved reliability, and minimized latency. Full article

The emergence of the Internet of Things (IoT) has attracted significant attention in industrial environments. These applications necessitate meeting stringent latency and reliability standards. To address this, the IEEE 802.15.4e standard introduces a novel Medium Access Control (MAC) protocol called Time Slotted Channel Hopping (TSCH). Designing a centralized scheduling system that simultaneously achieves the required Quality of Service (QoS) is challenging due to the multi-objective optimization nature of the problem. This paper introduces a novel optimization algorithm, QoS-aware Multi-objective enhanced Differential Evolution optimization (QMDE), designed to handle the QoS metrics, such as delay and packet loss, across multiple services in heterogeneous networks while also achieving the anticipated service throughput. Through co-simulation between TSCH-SIM and Matlab, R2023a we conducted multiple simulations across diverse sensor network topologies and industrial QoS scenarios. The evaluation results illustrate that an optimal schedule generated by QMDE can effectively fulfill the QoS requirements of closed-loop supervisory control and condition monitoring industrial services in sensor networks from 16 to 100 nodes. Through extensive simulations and comparative evaluations against the Traffic-Aware Scheduling Algorithm (TASA), this study reveals the superior performance of QMDE, achieving significant enhancements in both Packet Delivery Ratio (PDR) and delay metrics. Full article

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab’s EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1–6 s warning window, slightly behind the 1.5–6.75 s of the internet-based performance of CRISiSLab’s system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration. Full article