Density Estimation in Randomly Distributed Wireless Networks

Recently, real-time Graphical Simulation and applications of mobile computing devices in wireless Environment have shown promising foreground in WMS system, as a result of the former gives a way to shifting data to another intuitive and easier understudied visualization, and the latter promote real-time data acquisition. But the B/S structure is a fat server and thin client architecture, most of the logic and computing are deployed on the server side. So that when the need for graphical simulation and applications of mobile computing devices in wireless network comes to B/S structure, server performance will decline distinctly. This paper presents an efficient architecture for semi-real-time graphical simulation based on mobile computing devices in wireless network. In the architecture, the real-time graphics generation will deployed not only the server but also the client, and graphical layers decomposed into three varieties according to the need for real-time refresh, the client will deal with them respectively. Experimental results demonstrate improvement of computation efficiency without performance degradation.

The next-generation wireless communication and networks are envisioned to become controllable, programmable, and intelligent by leveraging emerging technologies such as Intelligent Reflecting Surface (IRS) and Cognitive Radio. Reconfigurable wireless networks aim to enable “intelligence” into the existing system to perceive and assess the available resources, autonomously learn to adapt to the wireless environment’s dynamism and reconfigure its operating mode to maximize the utility of the available resources. Moreover, it needs to be energy efficient to support the technological limitations on energy supply and mitigate the effect of the information and communication technologies. Apart from that, the newly designed solutions need to be energy efficient to accommodate the power consumption of the numerous devices in wireless communication and Networks. This special issue aims to motivate the researchers to design novel schemes and architectures for the energy-efficient reconfigurable wireless communication and networks. This issue has 47 high-quality papers covering several aspects of reconfigurable wireless communication and networks. Among them, 17 papers with significant original contributions were eventually selected for publications in this special issue.

This paper reviews the expected wide and profound impact of nanotechnology for future wireless devices and communication technologies. This article points out the possibilities of overcoming the same problem set from a device perspective by taking advantage of the merits of nanotechnologies. At the same time, open research issues and challenges are identified to spark new interests and developments in this field. Devices that use wireless communication range from RFID tags to TV receivers, and satellites to mobile phones. The availability of internet access from tablets and mobile phones is growing at an exponential rate, causing increasing demands on the performance of wireless networks and mobile devices. Some passive components necessary in wireless devices, such as inductors and capacitors, cannot be minimized as quickly as transistors and integrated circuits. This imbalance makes it likely that the performance requirements of mobile handsets will exceed the capabilities of current RF technologies within the next 10 to 15 years. As well as the global growth in mobile internet access via tablets and smartphones, wireless sensors, health monitoring systems and other devices dependent on wireless communication are becoming more and more prevalent. Developing more compact, more efficient, and less expensive wireless communication devices will have significant impact on these areas and enable new solutions for healthcare services, logistics and environmental monitoring. The devices that use wireless communication ranges from RFID tags to television set receivers and satellites to mobile phones. The availability of internet access from mobile devices is growing at an exponential rate that causes rising demand on the wireless network and mobile devices' performance. As the type of activities that consumers are engaging in over the wireless connections is changing day in day out, it has been an increased need for the devices to change also. For instance in radios, the increasing quantity of mobile internet traffic there has been increased the need for additional frequency for support. The modern world is becoming an intelligent interactive environment that has needs novel autonomous sensors with wireless communication links that require to be incorporated into an everyday object. This is the reason why sensors that are nanoenabled integrated with small RF transceivers are useful in monitoring air quality, water pollution among other aspects. The main drivers of changing into nanotechnology in wireless devices are needed for high performance, reduced consumption of power as well as reduced compact size.

The recent development of high-speed data transmission over wireless networks enables multimedia broadcasting service to mobile users. Multimedia broadcasting service involves interactions among different system and network components, so it is crucial for the service provider to verify the correctness of system/service model and design, and their behaviors before a new type of service is deployed. However, due to limitations of using network simulations or scaled experimental testbeds, there has been none of research on such verification and simulation framework in 3G broadcasting networks. Therefore, we propose a simulation and analysis framework for multimedia broadcasting service over wireless networks. With concrete modeling of wireless physical channel, network, and data processing on a client device, it enables the prediction of various interesting system parameters and perceived quality of multimedia streams to users. Different models of system and network components can be plugged easily in our simulation framework for further extensions. Using this framework, we analyze the processing performance for decoding scalable videos on mobile devices in CDMA2000 wireless networks.

The benefits of cooperation among devices of wireless networks are potentially so rewarding that distributed processing has become a major research topic in recent years. Distributed protocols are designed to achieve a global task over a network of devices connected via wireless links for different applications in wireless networks such as statistical inference and decision making, optimization in radio access and interference management, fault-tolerant networking. Channel variability and fading, dynamic routing and battery-aware policy, are only few of the specific challenges that the design of any distributed algorithm over wireless links need to account for. Of the many problems that are still open in this fascinating area of research, this special JCN issue sheds some light on the following important issues.

The coexistence of heterogeneous devices in wireless networks brings a new topic on cross-technology communication (CTC) to improve the coexistence efficiency and boost collaboration among these devices. Current advances on CTC mainly fall into two categories, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">physical-layer CTC</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">packet-level energy modulation</i> (PLEM). The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">physical-layer CTC</i> achieves a high CTC data rate, but with channel incompatible to commercial devices, making it hard to be deployed in current wireless networks. PLEM is channel and physical layer compatible, but with two main drawbacks of the low CTC data rate and MAC incompatibility, which will induce severe interference to the other devices' normal data transmissions. In this paper, we propose symbol-level energy modulation (SLEM), the first CTC method that is fully compatible with current devices in both channel and the physical/MAC layer processes, having the ability to be deployed in commercial wireless networks smoothly. SLEM inserts extra bits to WiFi data bits to generate the transmitting bits, so as to adjust the energy levels of WiFi symbols to deliver CTC information. We make theoretical analysis to figure out the performance of both CTC and WiFi transmissions. We also conduct experiments to demonstrate the feasibility of SLEM and its performance under different network situations.

Rapid advances in wireless communications, hardware/software, and Internet technologies have contributed to an exponential growth in the number of users accessing the Internet using mobile, wearable or other Internet of Things devices. Identity-based signature schemes have been widely applied to enforce user authorization and validate user messages in mobile wireless networks. However, the user’s private key used to generate signatures is prone to leakage because the key is being stored on the mobile device. Several ( t, n ) threshold secret sharing schemes have been proposed to address the issue. One limitation is that the private keys in most of those schemes have to be recovered on a single device when generating signatures, so that the user who holds the device can sign any message without the participation of other users. To address the recovery limitation, we propose an efficient and secure two-party distributed signing protocol for the identity-based signature scheme in the IEEE P1363 Standard, where two users can generate a valid signature without recovering the whole private key. We formally prove its security under a nonstandard assumption. We also implemented our proposed protocol using the MIRACL Cryptographic software development kit. The experimental results obtained show that the time it takes for two general Android devices to generate a signature is about 709.53 ms.

Recently, Unmanned Aerial Vehicles (UAVs) are being utilized to ensure a better solution to a dependable and cost-effective wireless communication network from the sky. The adoption of UAVs has been considered as an alternative supplement of the existing cellular networks, to accomplish better transmission efficiency with enhanced coverage and network capacity. This article has represented some urban wireless communication scenarios where UAVs can be utilized to ensure better coverage, enhancement of efficiency and capacity. After that, to establish the effectiveness of UAVs in wireless communication, the paper has included several performance scenarios (path loss) after utilizing UAVs in the wireless network. This article might be informative to those who are engaged in research regarding UAV assisted wireless communication.

Location determination of devices in wireless networks has been around for some time. Due to the fact that most approaches are based on client collaboration, they are not suitable for being integrated in security related components as intrusion detection or access control systems. In this paper we propose an approach that works without any client collaboration and even awareness by the client. Further on, our architecture is intended to be deployed on standard state-of-the-art IEEE 802.11g access points which operate using open source firmware as OpenWRT. We use these modified access points to collect, process and relay received signal strength (RSS) values of all communicating clients. These values are then used for trilateration using a location determination algorithm on a centralized server. We also present a working prototype, its promising results and possible further enhancements of our approach.

This paper introduces an approach to select the bandwidth or smoothing parameter in multiresolution (MR) density estimation and nonparametric density estimation. It is based on the evolution of the second, third and fourth central moments and the shape of the estimated densities for different bandwidths and resolution levels. The proposed method has been applied to density estimation by means of multiresolution densities as well as kernel density estimation (MRDE and KDE respectively). The results of the simulations and the empirical application demonstrate that the level of resolution resulting from the moments method performs better with multimodal densities than the Bayesian Information Criterion (BIC) for multiresolution densities estimation and the plug-in for kernel densities estimation.

The expansion of wireless communication introduces security vulnerabilities, emphasizing the essential need for secure systems that prioritize confidentiality, integrity, and other key aspects of data protection. Since computational security acknowledges the possibility of breaches when adequate computational resources are available, that is why information-theoretic security is being explored, which suggests the existence of unbreakable cryptographic systems even in the presence of limitless processing power. Secret key exchange has traditionally relied on RSA or DH protocols, but researchers are now exploring innovative approaches for sharing secret keys among wireless network devices, leveraging physical or link layer characteristics. This research seeks to revolutionize secure multi-party key acquisition in wireless networks, capitalizing on information-theoretic security and collaborative data extraction. The proposed secret key generation framework comprehensively organizes and explains the information-theoretic aspects of secret key generation within the lower layers of wireless networks, especially the link layer, proposes a novel information-theoretic SKG framework for the dynamic acquisition of symmetric secret keys, and responds to contemporary information security challenges by relying on information-theory principles rather than vulnerable mathematical relationships in the post-quantum period. A new cryptographic key can be generated using a straightforward method, and when it is combined (XORed) with the previous key, it creates a continuously changing secret for encryption and decryption. This approach enhances security because, as attackers attempt to break the encryption, the system generates fresh, dynamic keys, making it progressively more challenging for them to succeed. The research work in question integrates key renewal, or how often keys are updated (dynamic keys), with a security off-period. It introduces a framework for determining the best key refresh rate based on the anticipated rate at which keys might be compromised. Furthermore, the proposed framework is scalable, allowing new nodes to quickly join the existing network. The system was tested with multiple nodes equipped with IEEE 802.11 interfaces, which were set in monitor mode to capture frames at the link layer. Nodes map their on-time frames onto their Bloom filters. Nodes exchange these Bloom filters in a feedback mechanism. Nodes extract those frames from their .pcap files, which are present in all Bloom filters; these are common frames among all nodes. These frames are used to form a shared secret that is passed to HMAC Key Derivation Function by each node to acquire the final encryption key of the required length. The validation of this encryption key is performed using a simple challenge-response protocol; upon successful validation, encrypted communication begins. Otherwise, the key generation process is restarted.

A great number of people and non-equalizing medical resources, in developing countries, have become a serious contradiction. Not only does it affects the person’s life, but also causes serious epidemic contagious, because patients can not get help with hospital on time. With the development of wireless communication network, patient may get medical information by wireless network device. It can alleviate contradictions between patients and medical resources. But in developing countries, population quantity is a big data. How to solve data packets in wireless communication network is a big problem when researchers face huge population. In order to solve some problems in big data communication, this paper founds availability data transmission routing algorithm. This algorithm can reduce energy consumption and overhead, then improve deliver ratio in big data communication. Compare with Spray and Wait algorithm, Binary spray and wait algorithm in opportunistic networks, this algorithm acquires good results by reduce energy consumption, overhead and deliver ratio.

Caching on the edge has been recognized as an effective solution to tackle the backhaul constraint of network densification. However, most related works ignored user mobility in wireless networks, which is unreasonable under the background of network densification. For a more flexible and context-aware caching decision, the concept of caching on the edge can be extended to mobile edge computing (MEC) that enables computation and storage resources at mobile edge networks. With MEC servers deployed on base stations, a huge amount of collected radio access network context data can be analyzed and utilized to render a caching scheme adaptive to user’s context-aware information. In this regard, a novel mobility-aware coded probabilistic caching scheme is proposed for MEC-enabled small cell networks (SCNs). Different from previous mobility-aware caching schemes, user mobility and distributed storage are incorporated into a conventional probabilistic caching scheme, with the aim of throughput maximization. Based on stochastic geometry theory and a modified mobility model of discrete random jumps, the explicit expression of throughput is derived. Due to the complexity of the expression, two light-weight heuristic algorithms are provided to numerically obtain the optimal solutions. Moreover, a significant trade-off among the gains of mobility diversity, content diversity, and channel selection diversity is discussed, and we further numerically analyze how such a trade-off is influenced by user mobility, content popularity, and backhaul capacity, with some fundamental insights into the application of the proposed scheme in MEC-enabled SCNs. The superiority of our proposed scheme is demonstrated by the comparisons with the classical M most popular caching scheme and the conventional probabilistic caching scheme. Numerical results show that our proposed caching scheme achieves higher throughput than those of the other two, especially when users of intense mobility request contents, of which the popularity profile is not skewed, in MEC-enabled SCNs with poor backhaul capacity, indicating that the proposed caching scheme is a promising solution for network densification.

Wireless networks can be easily attacked by jammers due to their shared nature and open access to the wireless medium. Jamming attack can degrade the network performance significantly by emitting useless signals to the wireless channel, i.e. the access delay of nodes’ packets will increase under jamming scenarios. In order to analyze the impact of jamming attack, this paper investigates the access delay of nodes’ packets in a string multi-hop wireless network. Specially, a ring-based model is put forward to calculate the existing probability of the jammer based on the stochastic geometry theory. Then, the collision probabilities of the nodes in different locations are derived while considering the impact of neighbor nodes and jammers. At last, the access delay of the packets under IEEE 802.11 protocols is obtained. A series of numerical tests are conducted to illustrate the impact of different jamming probabilities or jammer densities on the access delay.

A nonparametric density estimate that incorporates spatial dependency has not been studied in the literature. In this article, we propose a new spatial density estimator that depends on two kernels: one controls the distance between observations while the other controls the spatial dependence structure. The uniform almost sure convergence of the density estimate is established with the rate of convergence. The consistency of the mode of this kernel density is also studied. Then a spatial hierarchical unsupervised clustering algorithm based on the mode estimate is presented. Some simulations as well as an application to the Monsoon Asia Drought Atlas data illustrate the efficiency of our algorithm, and a comparison of the spatial structures of these data detected by the density estimate and clustering algorithm are done.