Autonomous Wireless Network Research Articles

A deep experimental analysis of energy‐proficient firewall policies and security practices for resource limited wireless networks

AbstractThe role of firewalls and security principles in resource‐limited wireless networks and Wireless Sensor Networks (WSN) is more expected than in any dedicated network environment. The advanced wireless technologies and emerging fashion of autonomous wireless network nodes are mostly expecting resilient firewall services with multi‐level security policies. Wireless networks are classified under sensor networks, Internet of Things (IoT) mobile networks, and so forth. According to the expectations, security frameworks are gradually invented around the communication platform using various ideologies. The novel ideology and respective implementation effort open better solutions against wireless network attacks. Anyhow, the minimal production of time complexity, energy complexity, and computation overhead from any novel security approach is always considered under the best practices. The complexity levels directly affect the wireless node's energy consumption ability and operational spans severely. The energy optimization techniques and load‐balancing techniques integrated into multi‐class firewall rules are extremely useful solutions for resource‐limited wireless networks. This article has been motivated to analyze the recent firewall techniques and secure data communication mechanisms used for securing wireless networks. Consequently, the practice of comparative literature analysis helps to improve the current limitations identified under the classified categories of security mechanisms such as energy‐optimized security principles and load‐balanced security principles. The establishment of secure and energy‐optimized multi‐class firewall rules in each wireless node assures a healthy focus on next‐generation networks. The experiment section shows the benefits of energy‐optimized secure network communication in terms of better accuracy and the benefits of load‐balanced secure network communication through minimal overhead in computing platforms.

Adaptive protocol of raft in wireless network

Original distributed consensus algorithms are typically engineered with wired communication networks in mind. However, when these algorithms are applied in wireless networks, the unique characteristics of wireless communication among nodes, including high error rates, variable latency, and dynamic network topology, present novel challenges that necessitate the development of adaptive protocols. This article aims to address these challenges by designing an adaptive protocol specifically for the implementation of the Raft consensus algorithm within wireless environments. We first outline the key stages of this adaptive protocol, focusing on enhancing robustness and efficiency in the state synchronization and routing processes, which are demonstrated through extensive simulations. The proposed adaptive protocol intends to ensure consistent states across nodes in wireless networks, which promote reliable and effective distributed systems for a variety of applications in autonomous wireless networks, including Vehicle-to-everything (V2X), Internet of Things (IoT), and edge computing.

A Naive Bayes-Driven Mechanism for Mitigating Packet-Dropping Attacks in Autonomous Wireless Networks

A Naive Bayes-Driven Mechanism for Mitigating Packet-Dropping Attacks in Autonomous Wireless Networks

From Massive IoT Toward IoE: Evolution of Energy Efficient Autonomous Wireless Networks

From Massive IoT Toward IoE: Evolution of Energy Efficient Autonomous Wireless Networks

Performance of Optimized Security Overhead Using Clustering Technique Based on Fuzzy Logic for Mobile ad hoc Network

Abstract MANET is an autonomous wireless network without any centralized authority, consisting of a dynamic topology with a multi-hop scenario. Clustering provides centralized authority within MANET and makes the network stable up to some extent. Security is one of the most challenging aspects, directly proportional to load and overhead over the network. The model being proposed uses a cluster-based technique and modified secure routing protocol, which minimizes the network’s load and overhead, improving the network’s security and performance. Two major factors are used as contribution level and stability factor for the choice of cluster head, which minimizes the method of re-selection for cluster head. The node addition using authentication and the Modified Secure Routing Protocol increases the security of the network. The Modified Secure Routing Protocol, based on limited and efficient use of the certificates with encryption and decryption of packets, minimizes the overhead and load over the network. Hence, it provides more efficiency and security.

Grounded coplanar waveguide microstrip array antenna for 6G wireless networks

This paper presents the three-stage design of a grounded coplanar waveguide (GCPW) microstrip array antenna with via-holes beyond 100 ​GHz. The design was with a time-domain solver at the Computer Simulation Technology Microwave Studio (CST MWS) simulator, while the comparison was with the frequency-domain solver at the CST MWS simulator. As a result, a good agreement was achieved, which validated the proposed antenna. Furthermore, simulated results of the proposed antenna showed a bandwidth (BW), working frequencies, peak gain, and peak directivity of 24.22 ​GHz, 107.41–133.54 ​GHz, 12.1 ​dB, and 12.98 dBi, respectively. Thus, this GCPW microstrip array antenna can be suitable for beyond 100 ​GHz integrated vehicular autonomous and next-generation wireless communication networks at the sixth generation (6G) after a suitable experimental verification.

Mitigating Traffic Remapping Attacks in Autonomous Multihop Wireless Networks

Multihop wireless networks with autonomous nodes are susceptible to selfish traffic remapping attacks (TRAs). Nodes launching TRAs leverage the underlying channel access function to receive an unduly high Quality of Service (QoS) for packet flows traversing source-to-destination routes. TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of honest nodes. Recognizing the need for providing QoS security, we use a novel network-oriented QoS metric to propose a self-enforcing game-theoretic mitigation approach. By switching between TRA and honest behavior, selfish nodes engage in a noncooperative multistage game in pursuit of high QoS. We analyze feasible node strategies and design a distributed signaling mechanism called DISTRESS, under which, given certain conditions, the game produces a desirable outcome: after an upper bounded play time, honesty tends to become a selfish node’s best reply behavior, while yielding acceptable QoS to most or all nodes. We verify these findings by Monte Carlo and ns-3 simulations of static and mobile nodes.

IRDFPR-CMDNN: An energy efficient and reliable routing protocol for improved data transmission in MANET

Mobile Ad hoc Networks (MANET) are structure less, autonomous wireless networks with mobile nodes that dynamically establish data transmission connections. Due to dynamic topological change, MANET routes are unbalanced and break repeatedly. Hence, providing efficient and reliable data delivery with effective utilization of network resources is a challenging issue to be considered in MANET. This paper proposes an instant-runoff Ranked Decision Forests Probit Regression-based Connectionist Multilayer Deep Neural Network (IRDFPR-CMDNN) for efficient data transmission and higher data delivery with a minimum end-to-end delay. This IRDFPR-CMDNN method performs route identification, data delivery, and route maintenance with more than three layers. Then the mobile nodes are sent to the input layer of the Connectionist Multilayer Deep Neural Network. In hidden layer 1, the Instant-runoff Ranked Decision Forests algorithm is applied for classifying the mobile nodes depending on the residual energy and load capacity. With selected mobile nodes, the Probit Regression is applied for finding the nearest neighboring nodes in the second hidden layer based on the link quality and received signal strength for route path establishment. Then multiple paths for routing are established from source to destination node and start to perform the data transmission. If link failure occurs during the data transmission, another alternative route with better link quality is selected for routing. In this way, energy-efficient data transmission is performed from source to destination with a higher data delivery rate and minimal time consumption. Experimental evaluation is carried out on energy consumption, packet delivery ratio, packet drop rate, throughput, and end-to-end delay with varying numbers of mobile nodes and data packets. Simulation results show that the IRDFPR-CMDNN technique effectively enhances data delivery, throughput and minimizes energy consumption, packet loss rate, delay with respect to conventional methods.

Adaptive Wireless Network Management with Multi-Agent Reinforcement Learning.

Wireless networks are trending towards large scale systems, containing thousands of nodes, with multiple co-existing applications. Congestion is an inevitable consequence of this scale and complexity, which leads to inefficient use of the network capacity. This paper proposes an autonomous and adaptive wireless network management framework, utilising multi-agent deep reinforcement learning, to achieve efficient use of the network. Its novel reward function incorporates application awareness and fairness to address both node and network level objectives. Our experimental results demonstrate the proposed approach’s ability to be optimised for application-specific requirements, while optimising the fairness of the network. The results reveal significant performance benefits in terms of adaptive data rate and an increase in responsiveness compared to a single-agent approach. Some significant qualitative benefits of the multi-agent approach—network size independence, node-led priorities, variable iteration length, and reduced search space—are also presented and discussed.

Route Discovery Using Hybrid Approach for Disaster Management in MANET

A disaster situation is an event that alters in the normal execution of activities. A mobile ad-hoc network (MANET) is a self-controlled, autonomous wireless network used in an uncertain environment with decentralized control. In disaster, when communication between nodes is not performed properly, MANET can impart an important role of communication between nodes in uncertain situations. In MANET, routing is considered one of the most salient aspects of data transfer in a disaster situation. Proactive and reactive protocols are used as standard in various applications of MANET owing to the simplicity in their design and performance. Combining three routing protocols makes a hybrid approach to get better performance inefficient route discovery and maintenance. This is because reactive routing protocols, sometimes, do not provide better performance in heavy traffic and load, especially in a disaster. This is because the hybrid approach is very useful for fast convergence with low memory and power management. This paper introduces an improved hybrid routing protocol (IHRP) approach that combines two reactive and one proactive routing protocol to provide efficient route discovery and maintenance mechanisms. The simulation environment is used for the proposed approach. Results after simulation illustrate that it provides better performance in data packet delivery, routing load, throughput, and end-to-end delay data packet delivery, routing load, throughput, and end-to-end delay than the Ad-hoc On-demand Distance Vector (AODV) and Zone-based Routing Protocol (ZRP). The contrasting results between the IHRP and existing protocol indicate that the IHRP outperforms and increases the performance from 9% to 12%.

Scintillation gamma radiation sensors based on solid-state photomultipliers in wireless industrial internet networks

The article examines the principles of developing wireless networks of autonomous gamma sensors in order to create systems for spatial environmental radiation monitoring. The main task of such systems is to control the level of gamma radiation in areas where potential sources of ionizing radiation are located. An autonomous gamma-ray spectrometer is used as a measuring sensor. The authors propose to apply measuring sensors based on a silicon photomultiplier to create autonomous wireless networks of the industrial Internet for radiation monitoring. To confirm the possibility of using this class of receivers as part of gamma spectrometers, the main structural elements of the system were modeled, and the experimental model of the gamma spectrometer was prototyped. The linearity and energy resolution of the experimental sample were also investigated. To test the model for constructing a gamma spectrometer, a CsI (Tl) scintillation crystal and a Sensl Array-60035-4P photomultiplier were used. The established range of recorded energies is in the range from 121 keV to 1332 keV, the relative energy resolution for the 137Cs peak is 11.07 %, the linearity of the transfer characteristic is 99.91 %. Based on this sensor, the architecture of an automated wireless system for monitoring the spatial distribution of gamma radiation has been developed. The results of the work allow the use of radiation monitoring systems in accordance with the requirements of Industry 4.0.

Binary Spray and wait routing Protocol with controlled replication for DTN based Multi-Layer UAV Ad-hoc network Assisting VANET

Unmanned Arial Vehicle (UAV) Network is an autonomous wireless communication network, mainly used for natural disaster recovery operations to forward the captured images or video information to the ground vehicle. The UAV network can be applied in various applications essentially, search and rescue operations. This work concentrates on Delay Tolerant Network DTN based Decentralized Multi-layer UAV ad-hoc network assisting VANET for post-disaster scenarios. Because of unbalanced links in highly dynamic UAV networks, packet forwarding is a challenge. This work proposes a Binary Spray and wait routing protocol (BSnW) with controlled replication for DTN based Decentralized Multi-layer UAV networks. The Next Layer UAVs are presented to empower a well-organized Store and carry forward (SCF), in Multi-Layer UAV ad-hoc networks. Next Layer UAVs expands the accessibility of connecting tracks among the all DTN UAVs and the ground vehicle, hence reducing end-to-end delays and growing the packet delivery ratio and drop the packet drop ratio. The proposed BSnW with controlled replication protocol enables a high packet delivery ratio, which enables, and guarantees single-copy data forwarding to evade duplication of every message. Proposed protocol has been experimented using Opportunistic Network Environment (ONE) Simulator. Our simulated experiment show that the proposed protocol outstrips the epidemic routing protocols reported in the literature in terms of the packet delivery ratio, average delay, throughput and the routing overhead.

ПРОГНОЗИРОВАНИЕ ВРЕМЕНИ РАБОТЫ БЕСПРОВОДНЫХ СЕНСОРНЫХ СЕТЕЙ НА ОСНОВЕ ТЕХНОЛОГИИ LORA С ИСПОЛЬЗОВАНИЕМ ВЕРОЯТНОСТНОЙ МОДЕЛИ МАРКОВСКИХ ЦЕПЕЙ

Real-time monitoring systems and sensors are not complete without wireless data transmission modules. Improving energy efficiency requires examining various system parameters that affect the power consumption of transmitting and receiving devices. The most important parameter of any autonomous wireless network is its uptime. In this work, we used LoRa wireless modules on the SX1278 chip manufactured by Semtech to determine their power consumption in various operating modes. The obtained data were used to build a consumption model of the device when connected to a receiver. Three operating modes are considered: transmit mode, receive mode and sleep mode. In an ideal communication channel, all transmitted data reaches the receiver with 100% probability. In a real situation, data reaches the receiver with a certain probability, depending on the communication channel, transmission power, distance to the addressee, and network parameters. In this work, the occurrence of an error is random. In this case, the occurrence of an error during reception entails a lack of confirmation of receipt or a request for re-sending data. Sending data again increases the power consumption of the device and, consequently, decreases the operating time of the wireless device. This paper shows the dependences of the operating time on various initial monitored parameters of the device, such as: confirmation timeout, packet length, time of one transmission cycle and the maximum number of retransmissions in one cycle. The developed model for predicting the consumption of the device can be used in the design of autonomous wireless sensor monitoring networks.

An AI-Based Incumbent Protection System for Collaborative Intelligent Radio Networks

Since the early days of wireless communication, wireless spectrum has been allocated according to a static frequency plan, whereby most of the spectrum is licensed for exclusive use by specific services or radio technologies. While some spectrum bands are overcrowded, many other bands are heavily underutilized. As a result, there is a shortage of available spectrum to deploy emerging technologies that require high demands on data like 5G. Several global efforts address this problem by providing multi-tier spectrum sharing frameworks, for example, the Citizens Broadband Radio Service (CBRS) and Licensed Shared Access (LSA) models, to increase spectrum reuse. In these frameworks, the incumbent (i.e., the technology that used the spectrum exclusively in the past) has to be protected against service disruptions caused by the transmissions of the new technologies that start using the same spectrum. However, these approaches suffer from two main problems. First, spectrum re-allocation to new uses is a slow process that may take years. Second, they do not scale fast since it requires a centralized infrastructure to protect the incumbent and coordinate and grant access to the shared spectrum. As a solution, the Spectrum Collaboration Challenge (SC2) has shown that the collaborative intelligent radio networks (CIRNs) -- artificial intelligence (AI)-based autonomous wireless networks that collaborate -- can share and reuse spectrum efficiently without any coordination and with the guarantee of incumbent protection. In this article, we present the architectural design and the experimental validation of an incumbent protection system for the next generation of spectrum sharing frameworks. The proposed system is a two-step AI-based algorithm that recognizes, learns, and proactively predicts the incumbent's transmission pattern with an accuracy above 95 percent in near real time (less than 300 ms). The proposed algorithm was validated in Colosseum, the RF channel emulator built for the SC2 competition, using up to two incumbents simultaneously with different transmission patterns and sharing spectrum with up to five additional CIRNs.

A Stochastic Geometry Analysis of Large-Scale Cooperative Wireless Networks Powered by Energy Harvesting

Energy harvesting is an emerging technology for enabling green, sustainable, and autonomous wireless networks. In this paper, a large-scale wireless network with energy harvesting transmitters is considered, where a group of transmitters forms a cluster to cooperatively serve a desired receiver amid interference and noise. To characterize the link-level performance, closed-form expressions are derived for the transmission success probability at a receiver in terms of key parameters such as node densities, energy harvesting parameters, channel parameters, and cluster size, for a given cluster geometry. The analysis is further extended to characterize a network-level performance metric, capturing the tradeoff between link quality and the fraction of receivers served. Numerical simulations validate the accuracy of the analytical model. Several useful insights are provided. For example, while more cooperation helps improve the link-level performance, the network-level performance might degrade with the cluster size. Numerical results show that a small cluster size (typically 3 or smaller) optimizes the network-level performance. Furthermore, substantial performance can be extracted with a relatively small energy buffer. Moreover, the utility of having a large energy buffer increases with the energy harvesting rate as well as with the cluster size in sufficiently dense networks.

Auction-Based Pricing Schemes for Distributed Partner Selection in Cooperative Wireless Networks

In autonomous wireless networks, distributed and efficient partner selection is critical for fully realizing the benefits of cooperative communications. However, the selfish nodes in the networks bring catastrophe for partner selection when implementing cooperative transmissions. In order to stimulate cooperation and achieve distributed partner selection for such systems, an auction-based pricing scheme that considering efficiency and fairness is proposed in this paper. Two most prevalent auction forms, i.e., the second-price auction and the first-price auction, are both considered and analyzed in the single- and multiple-relay networks. In the single-relay scenario, the Nash equilibrium strategy for each auction is characterized, based on which the expected payoff and revenue for the source and relay are derived, respectively. Conclusions show that the same expected payoff is charged for the source with different auction schemes, and so is the expected revenue for the relay. Nonetheless, things are different in the multi-relay networks. With the linear 0–1 integer programming models, it is concluded that the first-price auction is more efficient than the second-price auction. Numerical results and analysis present that the proposed auction scheme efficiently solve the noncooperation issues of selfish nodes in autonomous wireless networks.

Efficient and Scalable Distributed Autonomous Spatial Aloha Networks via Local Leader Election

This paper uses a spatial Aloha model to describe a distributed autonomous wireless network in which a group of transmit-receive pairs (users) shares a common collision channel via slotted-Aloha-like random access. The objective of this study is to develop an intelligent algorithm to be embedded into the transceivers so that all users know how to self-tune their medium access probability (MAP) to achieve overall Pareto optimality in terms of network throughput under spatial reuse while maintaining network stability. While the optimal solution requires each user to have complete information about the network, our proposed algorithm only requires users to have local information. The fundamental of our algorithm is that the users will first self-organize into a number of non-overlapping neighborhoods, and the user with the maximum node degree in each neighborhood is elected as the local leader (LL). Each LL then adjusts its MAP according to a parameter R which indicates the radio intensity level in its neighboring region, whereas the remaining users in the neighborhood simply follow the same MAP value. We show that by ensuring R less than or equal to 2 at the LLs, the stability of the entire network can be assured even when each user only has partial network information. For practical implementation, we propose each LL to use R=2 as the constant reference signal to its built-in proportional and integral controller. The settings of the control parameters are discussed and we validate through simulations that the proposed method is able to achieve close-to-Pareto-front throughput.

Detection and Removal of Gray, Black and Cooperative Black Hole Attacks in AODV Technique

Mobile ad hoc network (MANET) is an autonomous self-configuring infrastructure-less wireless network. MANET is vulnerable to a lot of routing security threats due to unreliability of its nodes that are highly involved in the routing process. In this paper, a new technique is proposed to enhance the security of one of the most popular MANET routing protocols that is called Ad hoc on Demand Distance Vector (AODV) with minimum routing overhead and high packet delivery ratio. The proposed technique intends to detect and remove black, gray, and cooperative black hole AODV attacks depending on a mobile backbone network constructed from randomly moving regular MANET nodes based on their trust value, location, and power. The backbone network monitors regular nodes as well as each other to periodically estimate monitoring trust values which represent the reliability of each node in the network. The drop in the monitoring trust value of any node is used as a clue to its malicious behavior. The backbone network also tries to bait the malicious nodes to reply to a request for a route to fake destination address. The proposed technique uses the control packets of the AODV to exchange its control information which highly reduces the overhead. The simulation results show that the performance of the proposed technique is more secure than AODV and the other recently introduced techniques.

Performance improvement of rectifiers for WPT exploiting thermal energy harvesting

This paper proposes a combined harvesting system to improve the efficiency and flexibility of autonomous wireless network nodes, supplied by means of wireless power transfer technique. In particular, a mixed system for electromagnetic (EM) and thermal energy harvesting (EH), conceived for passive nodes of wireless sensor networks and radio frequency (RF) identification tags, is described. The proposed system aims at increasing the effectiveness and the efficiency of the EH system by integrating an antenna and a rectifier with a thermo-electric generator (TEG) able to perform thermal EH. The energy provided by the thermal harvester is exploited twice: to increase the rectifier efficiency by providing a voltage usable to improve the bias condition of the rectifying diode, and to provide additional dc energy, harvested for free. Ultimately, a great efficiency improvement, especially at low incident RF power, has been observed. The design methodology and the EM performance of a quarter-wavelength patch antenna, integrated with the TEG are resumed. Then, a test campaign to evaluate the thermal EH performance has been carried out. Afterward, a rectifier with variable bias voltage, operating at the same frequency of the antenna, has been opportunely designed to exploit the harvested thermal energy to bias the diode. A measurement campaign has been then carried out to test the efficiency increment obtained and to validate the proposed solution.

Comparative Study of Dominant Routing Protocols in Ad Hoc Networks

An network is an autonomous self-organized wireless network. It consists of a collection of wireless nodes in which the communication paradigm is decentralized. The term ad hoc refers to the lack of any preexisting communication infrastructure such as routers in wired networks or access points in the traditional wireless networks. Instead, each node participates in routing by forwarding data for other nodes, so the determination of which nodes forward data is made dynamically on the basis of network connectivity. The network is an autonomous system in which mobile hosts connected by wireless links are free to move randomly and often act as routers at the same time. As a result, the routing task in such type of networks introduces several types of challenges which were never apparent in the traditional infrastructure-based networks. The main objective of this study is to investigate the routing problem in wireless networks. More specifically, the performance of the different routing protocols which are dominantly adopted in such types of network environments will be examined. A simulation model with MAC and physical layer models, based on the simulation tool ns-2, was used in studying the behavior of two different protocols, namely, Ad Hoc On-Demand Distance Vector Routing (AODV), and DestinationSequenced Distance-Vector Routing (DSDV). Two performance metrics were used to establish a comparison between these routing algorithms: Average End-to-End Delay, and Packet Delivery Ratio. Simulation results showed that On-Demand routing protocol, AODV, provides a higher Packet Delivery Ratio. However, Table-Driven routing protocol, DSDV outperformed AODV in minimizing the Endto-End Delay.