Distributed Wireless Networks Research Articles

Resource Allocation of Distributed Wireless Network Based on Mobile Edge Computing

Resource Allocation of Distributed Wireless Network Based on Mobile Edge Computing

Study of Guard Interval Duration on the Operation Impact of IEEE 802.11 Network

Purpose. One of the new additions in the IEEE 802.11n standard amendment was the introduction of the short inter-symbol guard interval, which makes it possible to operate at slightly higher data rates. However, using a short guard interval is not always recommended. The fact is that on some types of sites where radio coverage is provided, the peculiarities of signal propagation with a short guard interval may give worse frame retry rate. In modern networks, this aspect remains more relevant than ever, and the task of correct guard interval configuration remains relevant for both the designer and the administrator of a wireless network. In order to conduct a comparative analysis of the measurement results with a short and long guard inter-symbol interval, it is necessary to conduct a full-scale radio site-survey of industrial WLAN site. As part of the present experiment, a WLAN was investigated at a site in one of the industrial zones of St. Petersburg. The main goal of the work is to experimentally determine the benefits that can be obtained from choosing a modulation and coding scheme with a long inter-symbol guard interval using the example of a distributed wireless network of the IEEE 802.11n/ac/ax standard. A related goal is to experimentally test the potential for reducing the radiation power of access points radios in order to improve network performance. Methods. Conducting a radio survey of a wireless network at a typical industrial site with subsequent analysis of its results. Novelty. The novelty of the presented solution includes a full-scale examination of an actually operated industrial network with simultaneous monitoring of characteristics at various levels of the OSI model: physical (spectrum analysis), channel (protocol analysis), application (control of application operation). Results. Analysis of the collected data shows a practically significant difference between the values of the frame retry rate for different values of the duration of the inter-symbol guard interval and the radiation power of the radio modules of the access points. Practical relevance. In is quantitatively shown that there is a reduction in frame retry rate by 8-10% in an production wireless network, achievable through correct control of the inter-symbol interval length for an industrial site.

IOT SYSTEM FOR CAR PARKING, STREET LIGHTS, AND AUTOMATIC IRRIGATION WITH REAL-TIME UPDATES ON MOBILE APP

In today's energy-conscious world, our foremost duty is to efficiently conserve energy. With advancing technology, automation systems have become the preferred choice over traditional manual methods. We've developed a user-friendly IoT application encompassing smart street lights, a smart parking system, and an automatic irrigation system to ensure effective energy conservation and water reduction. Our IoT-based smart street lights utilize external light sensing to automatically adjust illumination levels, offering 50% and 100% intensity as needed. This minimizes electricity waste and reduces the need for manual control, thus conserving energy. The saved energy can be redirected for residential, commercial, or other essential purposes, contributing to sustainable energy practices. The smart parking system offers convenience to users by allowing them to view available parking slots through the application. Users can make secure online payments, streamlining the parking experience. Additionally, the system aids in locating parked vehicles, enhancing efficiency. Automatic irrigation system employs a distributed wireless network of soil moisture sensors. A gateway unit manages sensor data, triggers, and actuators, transmitting real-time information to a web application. This innovation optimizes water usage in agriculture and landscaping, reducing water wastage and labor. A realtime data, conserving water and time spent on irrigation. This system's ability to adjust water distribution based on soil moisture content ensures efficient water management. Users receive soil moisture information on their mobile devices, promoting responsible water use. By automating processes, reducing waste, and enhancing user experience, we contribute to a more sustainable and energy-efficient future.

Review of Sustainable Irrigation Technological Practices in Agriculture

The paper focuses on the increasing demand for water and its impact on irrigated agriculture, emphasizing the importance of effective water management. It reviews the use of soil moisture sensors, IoT, big data analytics, and machine learning in agriculture, particularly in the context of Indian agriculture. The study explores the potential of IoT technologies, such as sensors, drones, and machine learning algorithms, to optimize water usage, minimize waste, and enhance crop yields. The role of big data analytics in sustainable water irrigation management and decision support systems is highlighted. The integration of IoT and sensory systems in smart agriculture is discussed, addressing both the challenges and benefits of implementing sensory-based irrigation systems. Additionally, the paper describes an automated irrigation system developed to optimize water use for crops, utilizing a distributed wireless network of sensors and a web application. The system, powered by photovoltaic panels, demonstrated significant water savings of up to 90% compared to traditional irrigation methods in a sage crop field. The system's energy autonomy and cost-effectiveness suggest its potential utility in water-limited and geographically isolated areas.

Study and Development of IOT based Smart Irrigation System using Soil Moisture and Weather Prediction

Abstract: The smart irrigation system was developed to optimize water use of crops. The system has a distributed wireless network of soil-moisture temperature sensors placed in the root zone of the plants. Also, a gateway unit handles sensor information, triggers, actuators, and transmits data to the web application. The intelligence of The proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web- services and a web-based information visualization and decision support system provides real-time information insights based on the analysis of sensor dataand weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging

Energy Efficient Routing Scheme for Performance Enhancement of MANET Through Dominating Set

Mobile Ad-Hoc network is a distributed wireless network that is self-organized and self-maintained and it doesn’t require a fixed framework or central administration. Wireless nodes in a mobile ad hoc network are transient and have a short lifespan. They combine to form a self-configured, infrastructure-free network where routing is a significant difficulty. The wireless nodes in the network must synchronize in order to decide connectivity and routing. Ad hoc network synchronization includes activities including node organization, neighborhood detection, and routing. The predetermined framework resulted in an increase in network control overhead. If a node can link to every other node in the network, it is referred to as a dominating node, and a set of dominating nodes make up the dominating set. The main purpose of this article is to lessen routing overhead in the wireless network with the dominating set based routing (DSBR). In order to discover routes, shorten reroute establishment times, and increase packet delivery rates, this research presents an energy-efficient routing algorithm (EERA) that considerably increases the network performance. The effectiveness of this technique is demonstrated by the simulation analysis of the outcome.

Opportunistic coding across on‐route dominating nodes in a flow‐orientedSDNenabledWSN

SummaryWith the aid of network coding, numerous packets can be mixed at intermediary nodes if any encoding opportunity exists. However, it is challenging to choose intermediate relay nodes of probable opportunistic coding in distributed wireless networks. In this work, a wireless sensor network (WSN) is employed with a software defined network (SDN) architecture along with a connected dominating set (CDS)‐based routing technique. The SDN offers a centrally managed architecture that lowers energy usage and network traffic by reducing the controlling and managing overheads in sensory networks. In addition, the CDS‐based routing and the potential for opportunistic coding at dominant nodes are coupled to enhance network performance. The proposed CDS‐based flow‐oriented coding‐aware energy‐efficient routing (CFCER) is contrasted with existing traditional wireless sensor networks and software‐defined sensor networks in terms of throughput, packet delay, and energy usage. CFCER increases network throughput by 15% more than SDN‐based WSN and by about 25% more than traditional WSN. However, compared to standard WSN, a significant improvement was made in packet delay and energy conservation. Over SDN‐WSN, packet delay is reduced by about 18%, and the energy consumption is cut by 10%.

Contrasting Journal on Agriculture Systems Using the Internet of Things

Agriculture is being rebuilt by the Internet of Everything (IoT) Temperature, humidity, and soil fertility are monitored using remote sensors. A field interruption, exact location, and wild plant species can all be found through an IOT-based investigation. The same wireless sensors may be used to monitor the soil's pH rate, temperature, and water level. A distributed wireless network of soil moisture and temperature sensors placed in plant root zones make up the implementation, of an automated watering system powered by solar panels. The Arduino board, which serves as an IoT gateway, receives data from these sensors, which continually monitor the settings, and processes it. A smartphone app gives customers access to live sensor data and enables farmers to take appropriate steps to meet the needs of the land. Farmers can use robotic systems for pesticide spraying, cultivating, and other such activities. Shows a block diagram of proposed concepts for an Internet of Things system.

Intra-Domain Knowledge Reuse Assisted Reinforcement Learning for Fast Anti-Jamming Communication

The novel technology based on reinforcement learning (RL) is considered as a promising direction to achieve cognitive and even intelligent anti-jamming communication. However, traditional RL converges slowly in the face of huge state-action space, while the performance improvement of deep RL depends on high-cost computing resources. Under unknown and dynamic malicious jamming attacks, it is still a major challenge to realize online anti-jamming communication through fast and autonomous learning. In this paper, we propose a fast anti-jamming scheme based on intra-domain knowledge reuse for distributed wireless networks. First, we introduce the Bisimulation Relation to measure the similarity of different state-action pairs in the communication anti-jamming problem, so as to build a bridge of knowledge reuse between state-action pairs. This similarity stems from the fact that the anti-jamming problem can be divided into two categories according to whether it successfully resists jamming attacks, in which different state-action pairs in the same category have similarities. Then, through the real-time update and reuse of state-action values, each node can independently learn the characteristics of dynamic environment and adjust the transmission strategy quickly, so as to avoid external malicious jamming and internal mutual interference. The simulation results show that our proposed scheme significantly accelerates the convergence speed and improves the network normalized throughput compared with the benchmark against unknown and dynamic jamming, and has remarkable agility and jamming memory.

Exploring Trust Modeling and Management Techniques in the Context of Distributed Wireless Networks: A Literature Review

Exploring Trust Modeling and Management Techniques in the Context of Distributed Wireless Networks: A Literature Review

Dynamic Multichannel Access Based on Deep Reinforcement Learning in Distributed Wireless Networks

With the emergence of innovative applications in vertical industries such as smart home and industrial automation, machine communication has shown a spurt of development. Different from the traditional human-oriented cellular communication, machine communication is characterized by strong uncertainty and abruptness, large-scale concurrent device connection as well as uneven and unsaturated data traffic. This article investigates the dynamic multiple-devices multiple-channels access for unsaturated traffic with retransmission mechanism, which is aimed at reducing the long-term data packet loss resulting from buffer overflows and transmission failure. The instant channel selection will lead to a non-negligible impact on the future decision, motivating us to model this problem as a Markov decision process. Limited by the unknown environment knowledge, we proposed a dynamic access policy based on deep reinforcement learning algorithm to optimally select the channel for transmission or keep silent for Internet-of-Things devices. Simulation results confirm that our proposed channel access strategy can reduce the collision and the packet loss of network. Furthermore, it can also work well when coexisting with the devices that adopt time division multiple access (TDMA) or ALOHA protocol.

Distributed wireless network resource optimisation method based on mobile edge computing

AbstractFor caching and forwarding problems in mobile networks, a new method of caching and forwarding in mobile networks based on boundary computing is proposed. Using Problem Optimisation to Transform Joint Optimal Problems into Linear Programming Problems and online algorithms, such as real‐time caching and forwarding, are designed. The network ranking leader, consumption amount, and network signal reception of the three algorithms are compared. The study found that in terms of network sort captain, there are significant differences between the CPLEX algorithm, the cell clustering for spatial transcriptomics (CCST) algorithm, and edge computing methods. The CCST algorithm and edge computing have little difference in queue length with small queue length and low latency. However, the CPLEX algorithm has a long queue, resulting in high latency. In terms of amount spent, at the beginning, the edge computing method requires more costly than the linear programming method. But as the beta value increases, so does its amount spent. Although the amount spent of the CPLEX algorithm is low, it is not accepted by users in terms of network delay. In terms of the network signal reception, the edge computing method is 18.3% higher than the linear programming method, and the network signal reception of the CPLEX algorithm is low. Under the premise of higher network signal reception and smaller queue length, higher delivery costs can be achieved and can be adjusted by the size. It can make the consumption amount and the network congestion level to be satisfied.

Statistical Evaluation of Power-Aware Routing Protocols for Wireless Networks

Distributed wireless networks use low-power nodes, battery-powered routers, and base-station nodes. Routing strategies lose energy due to distance-dependent transmission and reception. Researchers design low-power routing solutions for wireless networks. Each technique has unique advantages, restrictions, and research options. Protocols vary in energy consumption, throughput, latency, packet delivery ratio (PDR), scalability, and computational complexity. Researchers can't choose ideal context-aware network models due to diverse performance measurements. This article addresses application-specific deployment strengths to reduce uncertainty. This discussion may help researchers choose context-specific routing models. This article compares power-aware routing model performance measures. This comparison may be used to construct routing models for low-delay, high-throughput, high PDR installations, etc. This paper proposes an algorithm rank score (ARS) with performance metrics. Network designers may employ high-ARS routing models to achieve performance balance over numerous assessments.

An intelligent access algorithm for large scale multihop wireless networks based on mean field game

In a distributed wireless network with a large number of nodes, competitive access of nodes may result in the deterioration of throughput and energy. Therefore, in this paper we propose an intelligent access algorithm based on the mean field game (MFG). First, we formulate the competitive access process between nodes as a game Query ID="Q1" Text="Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary." process by a stochastic differential game model, which maximizes the energy efficiency of nodes and obtain the optimal behavior strategy while meeting the requirements of channel access. However, as the number of nodes increases, the dimension of the matrix used to characterize the interaction between nodes becomes too large, which increases the complexity of the solution procedure. Therefore, we introduce the MFG and the interaction between nodes can be approximately transformed into the interaction between nodes and the mean field, which not only reduces the complexity, but also reduces the computational overhead. In addition, the HJB-FPK equation is solved to obtain the Nash equilibrium of the MFG. Finally, a backoff strategy based on the Markov model is proposed, and the node obtains the corresponding backoff strategy according to the network situation and its own state. Simulation results show that the proposed algorithm has good performances on optimizing network throughput and energy efficiency for a large scale multi-hop wireless network.

Density Estimation in Randomly Distributed Wireless Networks

Networks of randomly distributed nodes appear in various fields, including forestry and wireless communications, and can often be modeled, using stochastic geometry theory, as Poisson point processs (PPPs). In these contexts, estimation of nodes density is important for monitoring and optimizing the network. Originally, this problem has been addressed in forestry where the trees are the nodes and, assuming these are distributed according to an infinite two-dimensional homogeneous PPP, the spatial density can be estimated by measuring the distances from one reference tree to its neighbors. However, in many other scenarios, nodes could result invisible with some probability, for example depending on distance. In this paper, we derive the Cramér-Rao bounds and new estimators for the node spatial density, taking into account a limited capability in sensing neighbors. As an example, we provide estimators of the spatial density of transmitting devices in wireless networks with links affected by thermal noise, path loss, and shadowing.

Comparative Analysis of Routing Algorithms to Enhance the Quality of Service in MANET

Mobile Ad hoc Network is a self-organizing, infrastructure-free, distributed wireless networks made up of various mobile devices. Quality-of-Service routing is most difficult task in MANET due to inherent characteristics–for example frequent dynamic topology, node mobility, resource scarcity, absence of centralized control, etc as well. The QoS variables of any MANET routing algorithms determine its performance. QoS routing is process of routing packets from source (S) to destination (D) based on QoS resource constraints such as bandwidth, delay, packet loss rate, cost, security, link stability, and so on. Swarm intelligence, which mimics the collective behaviour of biological organisms to handle routing problems and improve QoS in the network, has been one of most popular studies for network routing in recent years. Particle Swarm Optimization algorithm (PSO), Genetic Algorithm (GA) and Ant Colony Optimization algorithm (ACO) have all been shown to be effective for developing routing algorithms by improving QoS metrics in ad hoc networks using Swarm Intelligence (SI). The primary objective of this comparative study paper is to improve QoS parameters by applying swarm intelligence to MANET routing algorithms. Swarm intelligence-based routing algorithms will be more promising for the specific nature of adhoc networks, outperforming in real scenarios/constraints/environmental conditions and will be tuned and simulated to obtain an efficient and effective MANET routing protocol. This paper investigates four potential pre-existing approaches proposed for MANET routing problems. These routing algorithms are evaluated using various performance metrics such as packet delivery ratio, routing overhead, link failure prevention, energy consumption, accuracy, and throughput, among others.

Analysis and Design of Distributed MIMO Networks With a Wireless Fronthaul

We consider the analysis and design of distributed wireless networks wherein remote radio heads (RRHs) coordinate transmissions to serve multiple users on the same resource block (RB). Specifically, we analyze two possible multiple-input multiple-output wireless fronthaul solutions: multicast and zero forcing (ZF) beamforming. We develop a statistical model for the fronthaul rate and, coupled with an analysis of the user access rate, we optimize the placement of the RRHs. This model allows us to formulate the location optimization problem with a statistical constraint on fronthaul outage. Our results are cautionary, showing that the fronthaul requires considerable bandwidth to enable joint service to users. This requirement can be relaxed by serving a low number of users on the same RB. Additionally, we show that, with a fixed number of antennas, for the multicast fronthaul, it is prudent to concentrate these antennas on a few RRHs. However, for the ZF beamforming fronthaul, it is better to distribute the antennas on more RRHs. For the parameters chosen, using a ZF beamforming fronthaul improves the typical access rate by approximately 8% compared to multicast. Crucially, our work quantifies the effect of these fronthaul solutions and provides an effective tool for the design of distributed networks.

Robust Incremental Least Mean Square Algorithm With Dynamic Combiner

In distributed wireless networks, the adaptation process depends on the information being shared between various nodes. The global minimum, is therefore, likely to be affected when the information shared between the nodes gets corrupted. This could happen due to several reasons namely link failure, noisy environment and erroneous data etc. In this research, we propose a computationally efficient robust incremental least mean square (RILMS) algorithm to resolve the aforementioned issues. Essentially, a fusion step is introduced in the framework of the incremental least mean square (ILMS). Prior to adaptation at a node, the information shared by the neighbouring node is fused with the temporally preceding information of the node using an efficient combiner. An adaptive fusion strategy is proposed resulting in dynamic weight assignment for the fusion step. Closed form expression for the steady-state excess mean square error (EMSE) is derived and the performance of the proposed algorithm is evaluated for the noisy link environments and compared to the existing algorithms. Extensive experiments show the efficacy of the proposed approach compared to the contemporary methods. The proposed algorithm is found to be robust against the link failure and local node divergence problems. The improved performance of the proposed RILMS algorithm comes with a significant reduction in computational complexity compared to the convex combination based ILMS (CILMS) approach.

Security in IoT Mesh Networks Based on Trust Similarity

Internet of Things (IoT) Mesh networks are becoming very popular to enable IoT devices to communicate without relying on dedicated PC services. Internet of Things (IoT) implicitly uses mesh networks. IoT connectivity to cloud and edge computing is in vogue. A Wireless Mesh Network (WMN) is a multi-hop and distributed wireless network with mesh routers and mesh clients. Data originating from mesh clients are forwarded to destinations through mesh routers. In IoT Mesh networks, mesh clients are IoT devices. The crucial security issue with these networks is the lack of a trusted third party for validation. However, trust between nodes is required for the proper functioning of the network. WMNs are particularly vulnerable as they rely upon cooperative forwarding. In this research work, a secure and sustainable novel trust mechanism framework is proposed. This framework identifies the malicious nodes in WMNs and improves the nodes’ cooperation. The proposed framework or model differentiates between legitimate and malicious nodes using direct trust and indirect trust. Direct trust is computed based on the packet-forwarding behavior of a node. Mesh routers have multi radios, so the promiscuous mode may not work. A new two-hop mechanism is proposed to observe the neighbors’ packet forwarding behavior. Indirect trust is computed by aggregating the recommendations using the weighted D-S theory, where weight is computed using a novel similarity mechanism that correlates the recommendations received from different neighbors. Dynamic weight computation calculates the overall trust by using several interactions. We present the evaluations to show the effectiveness of the proposed approach in the presence of packet drop/modification attacks, bad-mouthing attacks, on-off attacks, and collusion attacks by using the ns-2 simulator.

Smart Irrigation System Using Intelligent Robotics

To optimize water use for agricultural crops while also verifying water scarcity in the field, an automated irrigation system was developed. Weed management and control are critical for high-yielding, high-quality crops, and developments in weed control technologies have had a significant impact on agricultural output. Any weed control method that is effective must be both durable and versatile. Despite the variety in field circumstances, robust weed control technologies will successfully manage weeds. Weed control technology that is adaptable can change its strategy in response to changing weed populations, genetics, and environmental conditions. The system includes a distributed wireless network of soil-moisture and temperature sensors, as well as conductive sensors in the plant's root zone. Agate way unit also manages sensor data, triggers actuators, and sends data to an Android mobile device. To control water quantity, an algorithm with temperature and soil moisture threshold values was developed and programmed into a microcontroller-based gateway. The added future of this research is that we are utilising a robot to monitor the condition of the crop to see if it is affected by insects or not. The robot will move around the field, and we will be able to track the crop's health on our device.