Packet Reception Rate Research Articles

A Link Quality Prediction Method for Wireless Sensor Networks Based on XGBoost

Link quality is an important factor for nodes selecting communication links in wireless sensor networks. Effective link quality prediction helps to select high quality links for communication, so as to improve stability of communication. We propose the improved fuzzy C-means clustering algorithm (SUBXBFCM) and use it to adaptively divide the link quality grades according to the packet reception rate. The Pearson correlation coefficient is employed to analyse the correlation between the hardware parameters and packet reception rate. The averages of the received signal strength indicator, link quality indicator and the signal to noise ratio are selected as the inputs of the link quality estimation model based on the XGBoost (XGB_LQE). The XGB_LQE is constructed to estimate the current link quality grade, which takes the classification advantages of XGBoost. Based on the estimated results of the XGB_LQE, the link quality prediction model (XGB_LQP) is constructed by using the XGBoost regression algorithm, which can predict the link quality grade at the next moment with historical link quality information. Experiment results in single-hop scenarios of square, laboratory, and grove show that the SUBXBFCM algorithm is effective at dividing the link quality grades compared with the normal division methods. Compared with link quality prediction methods based on the Support Vector Regression and 4C, XGB_LQP makes better predictions in single-hop wireless sensor networks.

Opportunities and Challenges in Health Sensing for Extreme Industrial Environment: Perspectives From Underground Mines

Occupational health and safety hazards in the extreme work environment of underground mines remained a serious concern for both mine management and regulatory agency. Miners are often employed to perform different mining activities across the mine and are always exposed to health risks such as lung cancer. With the technology advancements, it is now possible to keep track of mine individuals and their health parameters. The current practice of health analysis is periodic in nature and is highly dependent on voluntary participation. Wearable health sensing system is an alternative solution to overcome these challenges and is able to provide insights on miners’ health conditions. Timely analysis of physiological parameters of the miners is immensely helpful to minimize the injuries and can also provide preventive measures for potential health hazards. In this paper, we propose a wireless health monitoring system, especially for underground mines. The contributions of this paper are twofold. First, it presents and discusses our proposed system architecture and solution followed by challenges of such system in the context of underground mines. Second, as a preliminary analysis, detailed discussion on the wireless link behavior for reliable data transmission and communication are presented. We performed real-world experimental measurements in an operational underground coal mine considering several deployment settings in straight, near face and curved mine galleries. The communication metrics (e.g., received signal strength and packet reception rate) are extensively evaluated.

In-Band Controllable Radio Interference Generation for Wireless Sensor Networks

Interference signals negatively impact the performance of wireless embedded systems. The increased packet losses, delays, and energy consumption experienced by devices operating in environments subject to interference are particularly critical in constrained systems such as wireless sensor networks. The need to design and test systems for mitigating the effects of interference prompts for the capability of reproducing in a controllable way suitable interference signals. Solutions have been proposed recently, which tackle the problem by making use of 802.15.4 compliant radio transceivers, like those available on board of commonly used sensor nodes, thus paving the way for low cost and repeatable generation of interference which could reliably emulate real-world scenarios, for instance densely deployed networks. In this paper, we present an investigation regarding the emulation of interference sources by means of 802.15.4 radios on novel 32-bit wireless system-on-chip. The study is based on an extensive experimental evaluation, providing novel insights into the main features of the system. In particular, the effects of interference on the communication link, measured in terms of packet reception rate, are investigated for different parameters (namely, duty cycle and power of the interference signal, communication protocols, and payload size), and results are discussed concerning the feasibility of emulating background noise by means of the analyzed techniques.

Suppression Attack Against Multicast Protocol in Low Power and Lossy Networks: Analysis and Defenses.

With increasingly prevalent wireless sensors and devices, low power and lossy networks (LLNs) play an essential role in the realization of ubiquitous computing and communication infrastructure, which, in turn, leads to enhanced data accessibility and availability. A multicast protocol for LLNs (MPL), has been standardized to provide both efficient and reliable multicast communication. Due to the shared wireless medium, lack of tamper resistance, and inherent resource constraints, MPL-based LLNs are undoubtedly vulnerable to various Denial-of-Service (DoS) attacks. In this paper, we propose a heuristic-based detection scheme, called HED, against the suppression attack in MPL-based LLNs, where a malicious node multicasts a series of spoof data messages with continuous sequence numbers to prevent normal nodes from accepting valid data messages and cause them to delete cached data messages. In the HED, each node maintains an increment rate of the minimum sequence number in the Seed Set to detect the potential malicious node by comparing the recent increment of sequence numbers with the heuristically calculated increment threshold of sequence numbers. We evaluate the proposed scheme through extensive simulation experiments using OMNeT++ and compare its performance with original MPL with and without adversary, respectively. The simulation results show high detection rate and packet reception rate but low false detection rate, and indicate that the proposed scheme is a potentially viable approach against the suppression attack in MPL-based LLNs.

Exploiting Linear Support Vector Machine for Correlation-Based High Dimensional Data Classification in Wireless Sensor Networks.

Linear Support Vector Machine (LSVM) has proven to be an effective approach for link classification in sensor networks. In this paper, we present a data-driven framework for reliable link classification that models Kernelized Linear Support Vector Machine (KLSVM) to produce stable and consistent results. KLSVM is a linear classifying technique that learns the “best” parameter settings. We investigated its application to model and capture two phenomena: High dimensional multi-category classification and Spatiotemporal data correlation in wireless sensor network (WSN). In addition, the technique also detects anomalies within the network. With the optimized selection of the linear kernel hyperparameters, the technique models high-dimensional data classification and the examined packet traces exhibit correlations between link features. Link features with Packet Reception Rate (PRR) greater than 50% show a high degree of negative correlation while the other sensor node observations show a moderate degree of positive correlation. The model gives a good visual intuition of the network behavior. The efficiency of the supervised learning technique is studied over real dataset obtained from a WSN testbed. To achieve that, we examined packet traces from the 802.15.4 network. The technique has a good performance on link quality estimation accuracy and a precise anomaly detection of sensor nodes within the network.

Evaluating acousticcommunication performance of micro autonomous underwater vehicles in confined spaces

Micro-sized autonomous underwater vehicles (μAUVs) are well suited to various applications in confined underwater spaces. Acoustic communication is required for many application scenarios of μAUVs to enable data transmission without surfacing. This paper presents the integration of a compact acoustic communication device with a μAUV prototype. Packet reception rate (PRR) and bit error rate (BER) of the acoustic communication link are evaluated in a confined pool environment through experiments while the μAUV is either stationary or moving. We pinpoint several major factors that impact the communication performance. Experimental results show that the multi-path effect significantly affects the synchronization signals of the communication device. The relative motion between the vehicle and the base station also degrades the communication performance. These results suggest future methods towards improvements.

Differentiating Clear Channel Assessment Using Transmit Power Variation

Clear Channel Assessment (CCA) is a core element of Wireless Sensor Network (WSN) Medium Access Control (MAC) protocols which is used on the transmitter and receiver sides. Current CCA implementations cannot determine the device type occupying the media, leaving nodes unable to differentiate between WSN traffic and interference. However, this would be valuable as MAC protocols benefit from reacting differently depending on the channel occupier. In this article, we describe a method called Power Differentiating Clear Channel Assessment (P-DCCA). Transmitters vary the output power of the radio while the packet is being sent. Receivers are able to identify signals with this characteristic, enabling a Differentiating Clear Channel Assessment (DCCA) check to reveal if the medium is currently occupied by WSN traffic or other interference. We present an implementation and thorough evaluation of Power P-DCCA. Using ContikiMAC as an example, we describe how P-DCCA can be integrated within MAC protocols. We show via large-scale testbed experiments and deployments that P-DCCA enabled networks have a significant improved performance. For example, we show that a P-DCCA enabled network can improve Packet Reception Rate (PRR) by up to a factor of 10 while reducing energy usage by more than 80% under heavy interference.

Feasibility for Utilizing IEEE 802.15.4 Compliant Radios Inside Rotating Electrical Machines for Wireless Condition Monitoring Applications

The conventional condition monitoring systems for rotating electrical machines are predominantly based on externally available signals, while the internal signals, especially on the rotor, remain relatively unexplored. To access these internal signals, wireless sensors offer an effective solution in terms of cost and ease of deployment. However, the environment inside an electrical machine deviates from a typical wireless RF application and communication link reliability under such scenarios needs to be assessed. This paper explores the feasibility of utilizing the ubiquitous IEEE 802.15.4-2.4 GHz compliant radios for wireless sensor deployment inside an electrical machine. A series of measurements are made to experimentally investigate the link quality characteristics under the prominent environmental factors such as the multipath effect, Doppler shift, magnetic field interference, and shielding effect of the enclosure. Packet reception rate, received signal strength and link quality indicator are used as the metrics to quantify the link performance. It is observed that contrary to popular belief, the link quality between nodes inside the machine is not deteriorated and in fact is found to be enhanced. A poor link quality is observed for the connection between nodes placed inside and outside the machine. Moreover, the link quality is highly dependent on spatial position and prone to interference. However, a sufficiently stable link can be established at the expense of high transmit power. These experimental findings indicate that wireless RF-based sensor nodes can be deployed inside an electrical machine and it opens an opportunity to explore invasive condition monitoring systems.

A Dynamic Self-Adapting Mechanism for ZigBee Performance Assurance Under Wi-Fi Interference

As the increasing number of the wireless devices, the unlicensed industrial scientific medical band becomes more and more crowded. The highly uncertain cross technology interference (CTI) has shown to adversely affect the performance of low-power wireless sensor networks (WSN). Because of the incompatible physical and medium access control layer, the low-power WSN suffers serious packet loss during the transmission. It raises the need for agile methods that can assess the channel conditions and assure the performance and robustness of wireless sensor networks. In this paper, we present a light-weight and self-adapting CTI mitigation strategy that quantifies the channel idle state and improves the packet reception rate (PRR) of the communication. Based on the background received signal strength indicator, we propose a new metric to quantify the constantly changing channel state in the temporal domain. We employ logistic regression as the machine learning classifier to decide whether the communication is viable over the interfered link. Through the collected Wi-Fi traffic, we find that the channel is idle in most of the time, which motivated the design of our scheme. Extensive experiments show that our scheme can achieve over 91% of the PRR, which gain the improvement of 40%. Carrying on further, our scheme consumes less energy via degrading packet loss rate in the energy consumption part.

A cooperative detection and compensation mechanism against Denial-of-Service attack for cyber-physical systems

This paper is concerned with the detection and compensation co-design issue for cyber-physical systems against Denial-of-Service (DoS) attack. First, a novel supervisory strategy is proposed based on the concept of packet reception rate, which can detect the behavior of a DoS attacker during a given time window. A quantitative description of the relationship among attack times, time window, attack success rate and packet reception rate is analyzed. Based on the attack detection information, the current state under attack can be successfully reconstructed by some past available states. Then, a co-design compensation mechanism is also obtained, which can further guarantee the attacked system is stochastically stable (without the zero-mean Gaussian white noise) or mean square exponentially ultimately bounded (with the zero-mean Gaussian white noise). The corresponding design conditions are derived in terms of linear matrix inequalities. Finally, a numerical example and a practical example are given to show the effectiveness and superiority of the presented design method.

Packet relay‐assisted V2V communication with sectorised relay station employing payload combining scheme

A reliable vehicle-to-vehicle communication (V2VC) is essential to enable safe and highly automated driving system. Addition of a relay station (RS) can improve packet delivery rate (PDR) of CSMA/CA-based V2VC. However, the improvement is limited by packet collision at RS due to a hidden terminal (HT). This HT problem can be alleviated by employing sectorised receive antenna at RS, i.e. sectorised relay-assisted (SR-) V2VC. However, SR-V2VC still faces another problem, i.e. packet congestion at RS under high traffic conditions due to the improved packet reception rate. This leads to packet drop at RS and hence limits the improvement brought by SR-V2VC. Consequently, it is crucial to introduce a kind of traffic congestion avoidance methods to RS. In this article, the authors propose SR-V2VC with a payload combining forwarding (PCF) method (SR-V2VC/PCF) and theoretically evaluate the system performance using a CSMA/CA collision model. Large-scale computer simulations are also conducted to confirm the performance improvement brought by SR-V2VC/PCF. It is shown that the lowest broadcast PDR of 62% for the non-relay system is improved to higher than 81% by SR-V2VC/PCF and the directivity of the sector antenna has impact on the benefit of the proposed scheme.

LoRaWAN multi-hop uplink extension

The coverage of a LoRaWAN network in a city is greatly hampered by the harsh propagation environment. Sensors are sometimes placed under the ground or in places with strong electromagnetic attenuation. Also, for users who have a contract with a network operator, installing another gateway to improve coverage of blind spots is not an option. In other cases, there is no or very weak connectivity (e.g. basements). In the present work, we design and implement a multi-hop uplink solution compatible with the LoRaWAN specification, which can act as an extension to already deployed gateways. End nodes transmit data messages to intermediate nodes, which relay them to gateways by choosing routes based on a simplified version of Destination-Sequenced Distance Vector (DSDV) routing. The routing protocol was successfully implemented and was assessed using a linear and bottleneck topology, where the Packet Reception Rate (PRR) and throughput were measured. On the bottleneck topology it was observed that the PRR of each node did not significantly vary. On the linear topology we observed that the throughput and PRR did not decrease considerably with the increase of hops.

Performance Analysis of IEEE 802.11p Safety Message Broadcast With and Without Relaying at Road Intersection

Dedicated short-range communication (DSRC), which is an essential part of vehicle-to-vehicle/infrastructure communication to enhance the road safety, is often characterized by the IEEE 802.11p standard. Numerous works have been done on the DSRC safety message broadcasting performance for highway scenario. However, up to date, no work has been done on the performance of the IEEE 802.11p safety message broadcasting for the road-intersection scenario in urban environment. An intersection scenario is different from a highway scenario. In a highway scenario, it is often been considered that all the vehicles have the same communication range as well as the same carrier sensing range. However, this is not the case for the intersection scenario, where there exist a lot of obstructions, such as buildings and urban canyons. In an intersection, the communication and carrier sensing ranges of a vehicle heavily depend on the location of that vehicle. This paper first analyzes and then provides solution on improving the broadcasting performance of the DSRC safety message at an intersection while considering the IEEE 802.11p enhanced distributed channel access mechanism. To facilitate different communication and carrier sensing ranges of different vehicles, we divide the intersection region into few parts/areas based on an empirically validated path loss model. We present an analytical study on the packet reception rates and channel access delay which is applicable for the different positions of transmitters and receivers in the intersection areas. The analytical results are verified by the NS-3 simulation. From the results, we find that the overall delivery ratio is very poor when the broadcasting vehicle is not close enough to the intersection-center. To improve the overall broadcast performance of such scenarios, we employ a road side unit (RSU) at the intersection-center to relay the safety messages once. We show the performance improvement via relaying while first using omni-directional and then using special sector antennas, the so-called bidirectional antenna, at the RSU. From the results, it is shown that relaying with the omni-directional antenna gives moderate improvement on the overall delivery ratio, while a significant improvement can be achieved by relaying with sector antenna.

Jamming-Resilient Multipath Routing Protocol for Flying Ad Hoc Networks

As a result of the rapid technological advances on electronic, sensors and communication technologies, and increasingly popular multi-sized unmanned aerial vehicles, also referred to as drones, flying ad hoc networks (FANETs) are rapidly proliferating and leading the emergence of Internet of Drones and its applications. Because of the versatility, flexibility, easy installation, and relatively small operating expenses of drones, FANETs have enormous potential in the public and civil domains. However, due to unique characteristics of FANETs, routing demands of FANETs go beyond the needs of mobile ad hoc networks and vehicular ad hoc networks. In this paper, we propose a jamming-resilient multipath routing protocol, also called JarmRout , so that intentional jamming and disruption or isolated and localized failures do not interrupt the overall network performance of FANETs. To achieve this goal, the JarmRout relies on a combination of three major schemes that are link quality scheme, traffic load scheme, and spatial distance scheme. We present a simple analytical model and its numerical result in terms of RREP packet reception rate of source node. We also evaluate the proposed routing protocol through extensive simulation experiments using the OMNeT++ and compare its performance with three representative routing protocols that are dynamic source routing, optimized link state routing, and split multipath routing. Simulation results show that the JarmRout can not only improve packet delivery ratio and packet delivery latency but also can reduce end-to-end communication outage rate without introducing extra communication overhead, indicating a viable approach to improve network resiliency in the presence of malicious jammers in FANETs.

Model Predictive Power Control for Cooperative Vehicle Safety Systems

In vehicular networking, the heavy traffic can cause channel congestion and hence, degrade the tracking accuracy of cooperative vehicle safety systems. To overcome this problem, a dynamic packet reception model that integrates the packets reception rate and the vehicle density is proposed. Then, a traffic-flow-based vehicle density estimation method is designed. This estimation method is capable of predicting the vehicle density in the scenario, where there exist strong interactions among the vehicles. Based on the vehicle density method, a dynamical transmission power control strategy is developed. This transmission power control strategy employs model predictive control to make the optimal control decisions based on the estimated vehicle density. Experimental analyses demonstrate that the dynamical power control strategy can greatly enhance the vehicle tracking performance of cooperative vehicle safety systems under dynamical traffic situation.

Wake-Up Receiver with Equal-Gain Antenna Diversity †.

Small scale fading signals resulting from multipath propagation can cause signal strength variations in the range of several dB. Resulting from the fluctuating signal strengths, the wake-up packet reception rate can decrease significantly. Using antenna diversity can greatly mitigate these effects. This article presents a novel wireless sensor node with wake-up receiver that uses an equal-gain diversity method with two antennas in the wake-up path. Summation of the two diversity branch signals is done after the passive demodulation of the incoming signals. As a result, the wireless sensor node requires almost no additional active parts that would increase power consumption. Furthermore, we demonstrate experimentally the improved wake-up robustness and reliability achieved by this diversity technique in a multipath environment.

State Estimation with Secrecy against Eavesdroppers

We study the problem of remote state estimation, in the presence of an eavesdropper. An authorized user estimates the state of a linear plant, based on the data received from a sensor, while the data may also be intercepted by the eavesdropper. To maintain confidentiality with respect to state, we introduce a novel control-theoretic definition of perfect secrecy requiring that the user’s expected error remains bounded while the eavesdropper’s expected error grows unbounded. We propose a secrecy mechanism which guarantees perfect secrecy by randomly withholding sensor information, under the condition that the user’s packet reception rate is larger than the eavesdropper’s interception rate. Given this mechanism, we also explore the tradeoff between user’s utility and confidentiality with respect to the eavesdropper, via an optimization problem. Finally, some examples are studied to provide insights about this tradeoff.

Low Energy Fuzzy based Unequal Clustering Multihop Architecture for Wireless Sensor Networks

This paper presents a Low Energy Fuzzy based Unequal Clustering Multihop Architecture (LEFUCMA) for wireless sensor networks consisting of several nodes that send sensed data to a Master Station (MS). LEFUCMA encompasses neighbor finding, cluster head selection, clustering and routing protocols. The neighbor finding protocol organizes the network into a sectored-layers structure. The cluster head selection uses fuzzy logic with residual energy, number of neighboring nodes, packet reception rate and distance of node from MS as fuzzy descriptors for cluster head selection. For even distribution of traffic, LEFUCMA uses fuzzy logic with node density and distance of area from MS as fuzzy descriptors to decide number of cluster heads in a given area. To avoid hot spots problem, LEFUCMA uses an unequal clustering mechanism with clusters closer to MS having smaller sizes than those farther from MS. Finally, inter-cluster routing protocol decides the next hop cluster head considering its residual energy, distance from MS and from current cluster head which represents energy required for communication, number of cluster members which represents intra-cluster traffic and number of descendant nodes which represents inter-cluster traffic. A comparative analysis of LEFUCMA; Unequal Hybrid, Energy Efficient and Distributed Clustering (Ever et al. in Proceedings of international conference on sensor networks, pp 185–193, 2012; Energy Aware Distributed Unequal Clustering (Yu et al. in Hindawi Int J Distrib Sens Netw, Article ID 202145:1–8, 2011); Constructing Optimal Clustering Architecture (Li et al. in J Comput Commun 36(3):256–268, 2013; and Energy Aware Unequal Clustering using Fuzzy logic (EAUCF) (Bagci and Yazici in J Appl Soft Comput 13(4):1741–1749, 2013) shows that LEFUCMA is 32–42% more energy efficient compared to EAUCF. Throughput of LEFUCMA is 46% more and network lifetime is 60–75% more compared to EAUCF.

E3TX: an energy-efficient expected transmission count routing decision strategy for wireless sensor networks

The routing protocol is one of the most important aspects of the wireless sensor network, determining network connectivity, delay, energy balancing, reliability and other factors. Furthermore, a minimum hop-count does not mean minimum delay and energy consumption. To overcome the routing protocol's shortcomings, we proposed an energy-efficient expected transmission count routing decision strategy (E3TX) for wireless sensor networks. E3TX makes use of two physical parameters, received signal strength indicator (RSSI) and battery voltage, to obtain the final decision via our proposed decision strategy. In our strategy, the received signal strength indicator is used to predict the future packet reception rate (PRR), and the battery voltage is used to estimate the residual energy of network nodes to balance their load. In order to estimate the packet reception rate via the received signal strength indicator with greater accuracy, we performed multiple experiments to build the relationship model between RSSI and PRR. In this article, we use NS-2.35 to evaluate and compare the performance of E3TX with AODV, AOMDV and BIETX. Our simulation results show that our proposed E3TX performs well when compared to the previous studies, not only in terms of energy consumption, but also in reliable data transmission and end-to-end delay.

Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine

In the application of Wireless sensor networks (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality estimation mechanism is proposed, which is based on Support vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive signal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link quality is divided into five levels according to Packet reception rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial respectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reasonable. Compared with the recent published link quality estimation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.