Dependability is a keyword within the recent discussion about the operation of Wireless Sensor Network (WSN) as a vital part of the ever-growing Internet of Things (IoT). However, while focusing on, e.g., reliable routing it is often neglected that the energy supply is an important factor to enable dependable WSN, and thus IoT operation. Using the example of the Routing Protocol for Low power and Lossy

The design of the forthcoming fifth generation (5G) system shall meet the severe requirement of managing an always increasing amount of traffic generated by both humans and machines, while guaranteeing data security. Among the enabling technologies that will turn 5G into a reality, Device-to-Device (D2D) and Multicasting will certainly play a key role because of their capability to largely improve

There has been growing interest in device to device (D2D) millimeterwave (mmwave) communication, due to the promising high speeds and immense amounts of unused bandwidth available. However, mmwaves suffer from unusually high attenuation, through free space, and especially through obstacles. The accepted way to avoid such attenuation is to break up the transmission path into multiple short hops, such

Beyond 5G networks are expected to support massive traffic through decentralized solutions and advanced networking mechanisms. This paper aims at contributing towards this vision through the integration of device-centric wireless networks, including Device-to-Device (D2D) communications, and the Next Generation of Opportunistic networking (NGO). This integration offers multiple communication modes

D2D communication has been identified as one of the technologies for meeting the unique traffic demands of the fifth-generation wireless network communication. However, the effectiveness of D2D highly depends on the proximity of devices. In other words, whenever such devices are far apart, communication becomes ineffective. Thus, relay assisted D2D positions itself as an approach by which some of the

Localization is one of the essential problems in the Internet of Things (IoT) and other wireless sensor applications. Most traditional range-free localization algorithms ignore the anisotropy factors, which are frequently observed in Wireless Sensor Networks (WSNs) and result in low positioning precision. To mitigate the impact of anisotropy on localization, we propose an accurate localization approach

Artificial intelligence has been widely used in daily wireless networks for its flexibility and adaptability in solving extremely complex problems in real-time. These wireless network applications using artificial intelligence will generate a lot of valuable data. Knowledge graph is able to mine and store useful information from these large amounts of data and make data-driven wireless network applications

The advent of mobile charging with wireless energy transfer technology has perpetuated the omnipresent wireless rechargeable sensor networks. The existing literature finds that on-demand recharging of the sensor nodes (SNs) can significantly improve the charging performance while using multiple charging vehicles (MCVs) and multi-node charging model. Most of the existing schemes ignore the heterogeneous

In most supervised action recognition methods, sufficient labeled training instances are needed for each class, the learned model can only recognize the samples belonging to classes covered by the training data, and lacks the ability to deal with previously unseen classes. In this paper, we tackle the above challenges by proposing a novel Video Disentangling Attentive Relation Network (VDARN), which

Accuracy and reliability are the main problems to be considered when using wireless sensor networks for target tracking. Deep learning has a good prospect in visual object tracking, in which Siamese based trackers achieve a balance between performance and computational efficiency.Template adaptability and feature expression of the target are crucial for Siamese trackers which aim to locate the target

This paper describes the novel wireless routing protocol made for mobile ad hoc networks or wireless sensor networks using the bio-inspired technique. Bio-inspired algorithms include the routing capabilities taken from the social behavior of ant colonies, bird flocking, honey bee dancing, etc and promises to be capable of catering to the challenges posed by wireless sensors. Some of the challenges

Despite the rapid increase of research on individual identification in recent years, most of them focused on extracting the invariant visual cues of individuals. However, few efforts have been devoted to exploring the inherent feature caused by physiological differences. The main challenge in this task arises from two aspects: (i) the individual inherent feature (style) of each pose may be unique;

It is acknowledged that images taken under low-light conditions are easily affected by low visible light and noise, which can cause important image information loss, low signal-to-noise ratio, blurred edges, and poor subjective vision. Related researchers have targeted some solutions are proposed for the above problems, such as histogram equalization and gamma correction, but all have problems such

The cognitive radio network has been proposed to overcome the frailty of existing spectrum allocation strategies, by dynamically accessing the licensed spectrum instead of conventional static spectrum access. Thereby, the increasing traffic on the unlicensed wireless spectrum is diverted to unused licensed spectrum bands for providing spectrum space to new wireless users. Wireless services have a diverse

Improvements in small sized sensors allow the easy detection of the presence of Volatile Organic Compounds (VOCs) in the air using easy-to-deploy Internet of Things (IoT) devices. However, classifying what VOC exists in the environment still remains as a complex task. Knowing what VOCs are in the air can help us remove the main cause that vents VOC materials as a way to maintain clean air quality.

Ever-increasing performance at decreasing price has fueled camera deployments in a wide variety of real-world applications—making the case stronger for battery-powered, continuous-vision camera systems. However, given the state-of-the-art battery technology and embedded systems, most battery-powered mobile devices still do not support continuous vision. In order to reduce energy and storage requirements

Due to the prevalence of human activity in urban spaces, recommending ROIs (region-of-interests) to users, especially irregular ROIs, becomes an important task in location-based social networks. A fundamental problem is how to aggregate users’ preferences over POIs (point-of-interests) to infer the users’ region-level mobility patterns. The majority of existing studies ignore the users’ implicit interactions

With the advancement of connected vehicles, high-bandwidth wireless technologies such as DSRC and WiFi are envisioned to be pervasively available on vehicles. Such empowered vehicles can form large-scale vehicular ad hoc networks (VANETs), which contain rich bandwidth and storage resources. Despite their critical importance for core safety-related VANET applications, these resources are underutilized

The proliferation of “Things” over a network creates the Internet of Things (IoT), where sensors integrate to collect data from the environment over long periods of time. The growth of IoT applications will inevitably involve co-locating multiple wireless sensor networks, each serving different applications with, possibly, different needs and constraints. Since energy is scarce in sensor nodes equipped

Wireless power transfer technology opens up possibilities for charging the batteries of sensors wirelessly by wireless charging vehicles (WCVs), which increases the lifetime of Wireless Rechargeable Sensor Networks (WRSNs). Most of the existing studies do not consider the energy depletion of WCVs’ batteries during their travel through the network area, which may cause WCVs stranded in between their

In emergency situations, unmanned aerial vehicle (UAV) can be quickly deployed as air base station to provide users with communication services. The outdoor transmission model and outdoor–indoor transmission model cannot be normalized, and an effective hybrid transmission model is difficult to establish when the UAV serves both indoor users and outdoor users. We propose a ”indoor-outdoor-iterative

Despite the promising progress made in recent years, individual identification from biological motion remains a challenging task due to the drastic changes in human poses produced by various covariate factors. A variety of algorithms have been proposed to solve this challenging problem by extracting the invariant features of individuals. There exist two main bottlenecks for these methods. One is the

As Internet of Things (IoT) applications have gained increasing popularity, mechanisms to deal with congestion control owing to the large number of nodes have become a critical requirement. The Constrained Application Protocol (CoAP) is designed for low-power and lossy networks, using messages on the UDP, which relies on simple congestion control mechanisms. This method is suitable for IoT environments

DoA estimation using channel state information (CSI) is an important technology for localization in Wi-Fi network. Existing direction of arrival (DoA) estimation algorithms such as multiple signal classification (MUSIC) algorithm may provide feasible DoA estimation accuracy, if the array gain-phase error can be well calibrated in commodity Wi-Fi devices. However, for multipath propagation environment

Wireless body area network (WBAN) is a network of wearable devices placed on the body of patients to collect and transmit their biomedical data to medical servers through open wireless channels. These collected data are sensitive and their transmission via the open wireless channels makes them vulnerable to attacks by unauthorized users. Therefore, secure authentication and data encryption mechanisms

Salient object detection on hyperspectral images has made some progress in recent years, benefiting from the development of wireless network and hyperspectral imaging technology. However, most object detection methods on hyperspectral images focus more on the spectrum and do not fully mine the spatial information, especially high-level spatial–spectral information. In this paper, we propose a salient

The large-scale, scalable, flexible characteristics make the researches of online update more important in the Internet of Things (IoT). Gradient Boosting Decision Tree (GBDT) is commonly used to deal with the numerical data, while it cannot be updated online. To better solve the prediction problems, we propose a more generalized approach, M-GBDT2NN, based on GBDT2NN. Compared with GBDT2NN, the new

Unmanned Aerial Vehicles (UAV) have revolutionized the aircraft industry in this decade. UAVs are now capable of carrying out remote sensing, remote monitoring, courier delivery, and a lot more. A lot of research is happening on making UAVs more robust using energy harvesting techniques to have a better battery lifetime, network performance and to secure against attackers. UAV networks are many times

Fourier ptychographic microscopy (FPM) is a newly developed technique to capture wide field-of-view (FOV) and high-resolution images that meet the demands of Internet of Things (IoT). FPM enlarges the equivalent numerical aperture of the system and achieves phase imaging by simply employing an angle-varied illumination module. Recently, researches propose to perform the FPM reconstruction with deep

The massive multiple-input-multiple-output (mMIMO) antenna systems are well known for their capability to achieve high spectral efficiency in wireless communication systems thanks to millimeter waves (mmWaves) which allow a large number of antennas to be deployed at the base stations (BSs). Aside from communication-based services, mMIMO BSs are presently being exploited for location estimation of user

The Full Dimension-MIMO (FD-MIMO) technology is capable of achieving huge improvements in network throughput with simultaneous connectivity of a large number of mobile wireless devices, unmanned aerial vehicles, and the Internet of Things (IoT). In the Long Term Evolution (LTE), with a large number of antennae at the base station and the ability to perform beamforming, the capacity of the physical

To provide wireless coverage in challenging industrial environments, IEEE802.15.4 Time-Slotted Channel Hopping (TSCH) presents a robust medium access protocol. Using multiple Physical Layers (PHYs) could improve TSCH even more in these heterogeneous environments. However, TSCH only defines one fixed-duration timeslot structure allowing one packet transmission. Using multiple PHYs with various data

Leveraging peer-to-peer energy sharing solutions between nodes, energy balancing aims to balance energy among the nodes in a network towards prolonging the network lifetime especially when external energy supply is not available. Previous studies target an energy balance among the devices as fast as possible but they waste energy in the network during this process due to the excessive interactions

Recently, the Internet of Things (IoT) devices have been widely used in all sectors of society, especially in the field of wireless multimedia sensor networks (WMSNs). However, massive IoT video data requires efficient back-end processing to detect and track prominent objects for performing interconnection feedback. Correlation filter (CF)-based trackers present favorable properties for our back-end

As electromagnetic waves fade rapidly when passing through the human body, interferences may significantly degrade communication over wireless body area networks (WBANs). However, due to the limited power and resource restrictions in WBAN devices, existing interference mitigation methods may not fully address this issue. In this study, considering the architecture and equipment capacity of WBANs, the

In emergency situations like the recent Australian bushfires, it is crucial for civilians and firefighters to receive critical information such as available escape routes with guarantees on accuracy, timeliness, reliability, and completeness. Mobile Ad-hoc Networks (MANETs) can provide communications in bushfires but guaranteeing information delivery that meets user needs is not easy with current MANET

Deep Neural Networks has shown superior performance in various applications. But it is often seen as black box in real world applications, which is challenging to explain from the viewpoint of humans. It is important to understand the behavior of deep neural networks so as to trust the decision made and improve the classification accuracy of deep neural networks. In this study, the information theoretical

Node localization is a basic research problem for wireless sensor networks (WSN), and many application implementations require accurate location of sensor nodes. Until now, a range-free algorithm, DV_Hop algorithm, one of the localization algorithms that relied on multi-hop connectivity information between sensor nodes, has become one of the most frequently used algorithms due to its simplicity to

The primary issue in Wireless Sensor Network (WSN) based monitoring applications is the preservation of the sensing coverage under the harsh physical environment. WSN forms the monitoring infrastructure, where a large set of energy-constrained sensor nodes are deployed to collect the physical parameters of the environment. The sensor nodes communicate their data to the nearby edge server (ES) where

LTE-V2X (also known as C-V2X or Cellular V2X) introduces direct or sidelink V2V (Vehicle to Vehicle) communications using the PC5 interface. LTE-V2X defines two modes (Mode 3 and Mode 4) for the management of radio resources. This study focuses on Mode 3 where the cellular network manages and allocates the radio resources for direct or sidelink V2V communications. Contrary to Mode 4, the 3GPP standards

This paper focuses on the migratable traffic risk estimation problem in intelligent transportation systems using the social sensing. The goal is to accurately estimate the traffic risk of a target area where the ground truth traffic accident reports are not available by leveraging an estimation model from a source area where such data is available. Two important challenges exist. The first challenge

To facilitate research in dynamic spectrum access, 5G, vehicular networks, underground wireless communications, and radio frequency machine learning, a city-wide experimental testbed is developed to provide realistic radio environment, standardized experimental configurations, reusable datasets, and advanced computational resources. The testbed contains 5 cognitive radio sites, and covers 1.1 square

In the past few decades, research related to concept drift learning has been increasing, and many concept drift learning algorithms have also been developed and applied to actual data stream processing. In general, concept drift research involves the development of methodologies and techniques for drift detection, understanding and adaptation. This paper focuses on concept drift detection, and proposes

Wireless Sensor Networks (WSNs) consist of a large number of spatially distributed sensor nodes connected through the wireless medium to monitor and record the physical information from the environment. The nodes of WSN are battery powered, so after a certain period it loose entire energy. This energy constraint affects the lifetime of the network. The objective of this study is to minimize the overall

Recently, blockchain trustless properties started to be investigated to design cooperation enforcement mechanisms in many systems. This paper presents a comprehensive and detailed review of works on blockchain-enabled data forwarding incentives for multi-hop MANETs. We contextualize the problem of selfish misbehavior in networks composed of routers that are property of different participants: community

With the development of 5G communication technology, the Internet of Things technology has ushered in the development opportunity. In the application of Internet of Things, spatial and social relations can be used to provide users with convenience in life and work, meanwhile there is also the risk of personal privacy disclosure. The data transmitted in the wireless network contains a large number of

In this paper, we propose a novel data augmentation method to dynamically learn occluded samples via adversarial learning for person re-identification (re-ID) in sensor networks. Specifically, we design two CNN models to learn original-image features and occluded-image features, respectively. As for occluded-image features, we extract the most salient region from the attention map to obtain the meaningful

Wireless rechargeable sensor networks are widely used in many fields. However, the limited battery capacity of sensor nodes hinders its development. With the help of wireless energy transfer technology, employing a mobile charger to charge sensor nodes wirelessly has become a promising technology for prolonging the lifetime of wireless sensor networks. Considering that the energy consumption rate varies

The interest in Mobile Wireless Sensor Networks (MWSN) has grown considerably due to its various applications in the fields of military, industrial infrastructure, automation, health, traffic, and many consumer areas. Hence, as the modern world shifting to the age of IoT with possibly new emerging technologies and applications, there will be a number of implications that influence the design and deployment

This paper aims to optimize the different network parameters in a distributed manner for delay-constrained flying ad hoc networks (FANETs) without the global network topology information. To this end, each Unmanned Aerial Vehicle (UAV) calculates the average interference level during a certain time period to indicate the channel states. Next, we formulate the distributed optimization problem as a utility

Multimedia transport over Wireless Sensor Networks (WSN) has been a challenging task due to the limited available resources of such networks. The capability of Multipath routing to balance and distribute the load of a given flow on different disjoint non correlated paths is a viable solution to ensure the required high throughput. Moreover, operating the WSN under a duty-cycle mode reinforces the challenge

The Constrained Application Protocol (CoAP) is gaining attention as a standardised RESTful interface for the Internet of Things (IoT). Recent studies have focused on different congestion control strategies for CoAP, in order to ensure proper operation of large-scale IoT deployments. In this paper, we carry out a performance evaluation of different congestion control policies for CoAP in a realistic

Spectrum sensing is a key technique for future intelligent networks, such as AdHoc network, wireless sensor networks. However, the existing works suffer from high computational complexity, which is a huge challenge for those networks composed of many nodes with the limited computing capabilities. In this paper, we propose a simple and novel method based on the generalized likelihood ratio test(GLRT)

High-efficiency Access network selection algorithms are crucial to ensure Quality of Service (QoS) and Quality of Experience (QoE) in heterogeneous networks environment. Hereby, an intelligent access network selection algorithm based on multiple attribute decision making (MADM) is proposed in this paper. First, considering the special characteristics of cognitive wireless networks, a cross-layer network

Multi-hop broadcasting in Vehicular Ad Hoc Network (VANET) is the basic building block for renovating on-road travel experiences because it supports message dissemination among a large number of travelers in real-time. In order to make forwarding decisions, 1-hop neighbor table is suggested to be maintained at each vehicle by exchanging beacon packets on a periodic basis. However, a network crowded

The Internet of Things (IoT) paradigm envisions billions of interconnected things. This high density of things generates a huge amount of data, which results in communication delays and increases the amount of contention. Thus, it is necessary to have efficient Medium Access Control (MAC) protocols to coordinate channel access. In this paper, we consider a network throughput maximization problem in

In this paper, a physical layer security based secure routing problem in a multi-hop cognitive radio enabled device-to-device (CRD2D) communication, under the threat of multiple randomly distributed eavesdroppers (EVEs), is studied. Delivery of confidential packets between a given legitimate D2D transmitter–receiver pair is targeted with the aid of multiple intermediate legitimate D2D nodes that share

The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message

Multi-hop and multi-sink wireless sensor networks have the potential to provide network performance through efficient data exchanges. In multi-sink phenomena, clusters of nodes are defined using distance vector and thereby specific node that lies at the center of the cluster is identified as a sink. The performance of multi-hop and multi-sink wireless networks is significantly affected by sink node