Wildfire Monitoring Based on Energy Efficient Clustering Approach for FANETS

Forest fires are a significant threat to the ecological system’s stability. Several attempts have been made to detect forest fires using a variety of approaches, including optical fire sensors, and satellite-based technologies, all of which have been unsuccessful. In today’s world, research on flying ad hoc networks (FANETs) is a thriving field and can be used successfully. This paper describes a unique clustering approach that identifies the presence of a fire zone in a forest and transfers all sensed data to a base station as soon as feasible via wireless communication. The fire department takes the required steps to prevent the spread of the fire. It is proposed in this study that an efficient clustering approach be used to deal with routing and energy challenges to extend the lifetime of an unmanned aerial vehicle (UAV) in case of forest fires. Due to the restricted energy and high mobility, this directly impacts the flying duration and routing of FANET nodes. As a result, it is vital to enhance the lifetime of wireless sensor networks (WSNs) to maintain high system availability. Our proposed algorithm EE-SS regulates the energy usage of nodes while taking into account the features of a disaster region and other factors. For firefighting, sensor nodes are placed throughout the forest zone to collect essential data points for identifying forest fires and dividing them into distinct clusters. All of the sensor nodes in the cluster communicate their packets to the base station continually through the cluster head. When FANET nodes communicate with one another, their transmission range is constantly adjusted to meet their operating requirements. This paper examines the existing clustering techniques for forest fire detection approaches restricted to wireless sensor networks and their limitations. Our newly designed algorithm chooses the most optimum cluster heads (CHs) based on their fitness, reducing the routing overhead and increasing the system’s efficiency. Our proposed method results from simulations are compared with the existing approaches such as LEACH, LEACH-C, PSO-HAS, and SEED. The evaluation is carried out concerning overall energy usage, residual energy, the count of live nodes, the network lifetime, and the time it takes to build a cluster compared to other approaches. As a result, our proposed EE-SS algorithm outperforms all the considered state-of-art algorithms.publishedVersio

A Hybrid Optimized Weighted Minimum Spanning Tree for the Shortest Intrapath Selection in Wireless Sensor Network

Wireless sensor network (WSN) consists of sensor nodes that need energy efficient routing techniques as they have limited battery power, computing, and storage resources. WSN routing protocols should enable reliable multihop communication with energy constraints. Clustering is an effective way to reduce overheads and when this is aided by effective resource allocation, it results in reduced energy consumption. In this work, a novel hybrid evolutionary algorithm called Bee Algorithm-Simulated Annealing Weighted Minimal Spanning Tree (BASA-WMST) routing is proposed in which randomly deployed sensor nodes are split into the best possible number of independent clusters with cluster head and optimal route. The former gathers data from sensors belonging to the cluster, forwarding them to the sink. The shortest intrapath selection for the cluster is selected using Weighted Minimum Spanning Tree (WMST). The proposed algorithm computes the distance-based Minimum Spanning Tree (MST) of the weighted graph for the multihop network. The weights are dynamically changed based on the energy level of each sensor during route selection and optimized using the proposed bee algorithm simulated annealing algorithm

Energy efficient scheme to Jointly Optimize Coverage and Connectivity in Large Scale Wireless Sensor Network

Efficient coverage and connectivity are two important factors that ensures better service quality especially during tracking targets or monitoring events in wireless sensor network. Although massive amount of studies has been carried out in the past to enhance coverage and connectivity issues, till date very few studies have witnessed a significant and standard outcomes that can opt further. Hence, this paper introduces a computationally efficient technique for jointly addressing both coverage and connectivity problems in large-scale wireless sensor network that ensures optimal network lifetime too. The proposed system has been empirically designed, and algorithms formulated to ensure energy efficient monitoring of event. The outcomes of the study are compared with standard energy efficient hierarchical protocol to benchmark the results

Performance analysis of self-organized Ad-Hoc sensor networks

This project deals with a Distributed Sensor Network (DSN). The main focus of this thesis is to deliver an OPNET simulation model for working DSN model. After building a model, various performance analysis techniques in terms of different parameters were used to verify the working model. Query Dominant Sets (QDS) are the main idea behind this thesis. The QDS node is in charge of the nodes for a specific region and its job is to assign the query tasks that it gets to the nodes in that region to help maximize the life of the network. If no user queries are being sent, the QDS nodes themselves go to sleep to conserve energy and just listen for special incoming control signals. QDS management (including the selection of QDS and the interaction of QDS nodes and other common nodes) is a challenging issue in DSN platforms. Our algorithm for QDS management attempts to limit the dead spots in the network that tend to disrupt the communication of the whole network. It has two phases and the first phase is the election phase. The second stage is the previously elected QDS nodes distribute the tasks to the other nodes. This algorithm turns out to be distributed which is good for sensor networks. There is no use of any global communication or long-range, high energy data communication, but just local communications. This also helps to save power and energy for long life of the sensors. This algorithm is also very scalable and fault tolerant. We have done significant simulations to verify our QDS concepts. There are some metrics that are used to evaluate our schemes such as the average energy values of all the nodes in the network, minimum energy of all the nodes in the network, total energy consumed in the awake, transmit, and receive states, maximum time spent by any node in electing a new QDS, number of elected QDSs, and so on. Our simulations have shown satisfactory energy-efficiency of our algorithms

Lifetime Estimation of Wireless Body Area Sensor Network for Patient Health Monitoring

Wireless Body Area Sensor Networks (WBASN) is an emerging technology which utilizes wireless sensors to implement real-time wearable health monitoring of patients to enhance independent living. These sensors can be worn externally to monitor multiple bio-parameters (such as blood oxygen saturation (SpO2), blood pressure and heart activity) of multiple patients at a central location in the hospital. In health monitoring, the loss of critical or emergency information is a serious issue so there is a concern for quality of service which needs to be addressed. It is important to have an estimate of the time the first node will fail in order to replace or recharge the battery. A common type of failure happens when a node runs out of energy and shuts down. In this work, Monte Carlo simulation is used to determine the lifetime of WBASN. The lifetime of the WBASN is defined in this work as the duration of time until the first sensor failure due to battery depletion. A parametric model of the health care network is created with sets of random input distributions. Probabilistic analysis is used to determine the timing and distributions of nodes\u27 failures in the health monitoring network

A Grey Wolf Optimization-Based Clustering Approach for Energy Efficiency in Wireless Sensor Networks

In the realm of Wireless Sensor Networks, the longevity of a sensor node's battery is pivotal, especially since these nodes are often deployed in locations where battery replacement is not feasible. Heterogeneous networks introduce additional challenges due to varying buffer capacities among nodes, necessitating timely data transmission to prevent loss from buffer overflows. Despite numerous attempts to address these issues, previous solutions have been deficient in significant respects. Our innovative strategy employs Grey Wolf Optimization for Cluster Head selection within heterogeneous networks, aiming to concurrently optimise energy efficiency and buffer capacity. We conducted comprehensive simulations using Network Simulator 2, with results analysed in MATLAB, focusing on metrics such as energy depletion rates, remaining energy, node-to-node distance, node count, packet delivery, and average energy in the cluster head selection process. Our approach was benchmarked against leading protocols like LEACH and PEGASIS, considering five key performance indicators: energy usage, network lifespan, the survival rate of nodes over time, data throughput, and remaining network energy. The simulations demonstrate that our Grey Wolf Optimisation method outperforms conventional protocols, showing a 9% reduction in energy usage, a 12% increase in node longevity, a 9.8% improvement in data packet delivery, and a 12.2% boost in data throughput

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime

Analysis and Ad-hoc Networking Solutions for Cooperative Relaying Systems

Users of mobile networks are increasingly demanding higher data rates from their service providers. To cater to this demand, various signal processing and networking algorithms have been proposed. Amongst them the multiple input multiple output (MIMO) scheme of wireless communications is one of the most promising options. However, due to certain physical restrictions, e.g., size, it is not possible for many devices to have multiple antennas on them. Also, most of the devices currently in use are single-antenna devices. Such devices can make use of the MIMO scheme by employing cooperative MIMO methods. This involves nearby nodes utilizing the antennas of each other to form virtual antenna arrays (VAAs). Nodes with limited communication ranges can further employ multi-hopping to be able to communicate with far away nodes. However, an ad-hoc communications scheme with cooperative MIMO multi-hopping can be challenging to implement because of its de-centralized nature and lack of a centralized controling entity such as a base-station. This thesis looks at methods to alleviate the problems faced by such networks.In the first part of this thesis, we look, analytically, at the relaying scheme under consideration and derive closed form expressions for certain performance measures (signal to noise ratio (SNR), symbol error rate (SER), bit error rate (BER), and capacity) for the co-located and cooperative multiple antenna schemes in different relaying configurations (amplify-and-forward and decode-and-forward) and different antenna configurations (single input single output (SISO), single input multiple output (SIMO) and MIMO). These expressions show the importance of reducing the number of hops in multi-hop communications to achieve a better performance. We can also see the impact of different antenna configurations and different transmit powers on the number of hops through these simplified expressions.We also look at the impact of synchronization errors on the cooperative MIMO communications scheme and derive a lower bound of the SINR and an expression for the BER in the high SNR regime. These expressions can help the network designers to ensure that the quality of service (QoS) is satisfied even in the worst-case scenarios. In the second part of the thesis we present some algorithms developed by us to help the set-up and functioning of cluster-based ad-hoc networks that employ cooperative relaying. We present a clustering algorithm that takes into account the battery status of nodes in order to ensure a longer network life-time. We also present a routing mechanism that is tailored for use in cooperative MIMO multi-hop relaying. The benefits of both schemes are shown through simulations.A method to handle data in ad-hoc networks using distributed hash tables (DHTs) is also presented. Moreover, we also present a physical layer security mechanism for multi-hop relaying. We also analyze the physical layer security mechanism for the cooperative MIMO scheme. This analysis shows that the cooperative MIMO scheme is more beneficial than co-located MIMO in terms of the information theoretic limits of the physical layer security.Nutzer mobiler Netzwerke fordern zunehmend höhere Datenraten von ihren Dienstleistern. Um diesem Bedarf gerecht zu werden, wurden verschiedene Signalverarbeitungsalgorithmen entwickelt. Dabei ist das "Multiple input multiple output" (MIMO)-Verfahren für die drahtlose Kommunikation eine der vielversprechendsten Techniken. Jedoch ist aufgrund bestimmter physikalischer Beschränkungen, wie zum Beispiel die Baugröße, die Verwendung von mehreren Antennen für viele Endgeräte nicht möglich. Dennoch können solche Ein-Antennen-Geräte durch den Einsatz kooperativer MIMO-Verfahren von den Vorteilen des MIMO-Prinzips profitieren. Dabei schließen sich naheliegende Knoten zusammen um ein sogenanntes virtuelles Antennen-Array zu bilden. Weiterhin können Knoten mit beschränktem Kommunikationsbereich durch mehrere Hops mit weiter entfernten Knoten kommunizieren. Allerdings stellt der Aufbau eines solchen Ad-hoc-Netzwerks mit kooperativen MIMO-Fähigkeiten aufgrund der dezentralen Natur und das Fehlen einer zentral-steuernden Einheit, wie einer Basisstation, eine große Herausforderung dar. Diese Arbeit befasst sich mit den Problemstellungen dieser Netzwerke und bietet verschiedene Lösungsansätze.Im ersten Teil dieser Arbeit werden analytisch in sich geschlossene Ausdrücke für ein kooperatives Relaying-System bezüglicher verschiedener Metriken, wie das Signal-Rausch-Verhältnis, die Symbolfehlerrate, die Bitfehlerrate und die Kapazität, hergeleitet. Dabei werden die "Amplify-and forward" und "Decode-and-forward" Relaying-Protokolle, sowie unterschiedliche Mehrantennen-Konfigurationen, wie "Single input single output" (SISO), "Single input multiple output" (SIMO) und MIMO betrachtet. Diese Ausdrücke zeigen die Bedeutung der Reduzierung der Hop-Anzahl in Mehr-Hop-Systemen, um eine höhere Leistung zu erzielen. Zudem werden die Auswirkungen verschiedener Antennen-Konfigurationen und Sendeleistungen auf die Anzahl der Hops analysiert.  Weiterhin wird der Einfluss von Synchronisationsfehlern auf das kooperative MIMO-Verfahren herausgestellt und daraus eine untere Grenze für das Signal-zu-Interferenz-und-Rausch-Verhältnis, sowie ein Ausdruck für die Bitfehlerrate bei hohem Signal-Rausch-Verhältnis entwickelt. Diese Zusammenhänge sollen Netzwerk-Designern helfen die Qualität des Services auch in den Worst-Case-Szenarien sicherzustellen. Im zweiten Teil der Arbeit werden einige innovative Algorithmen vorgestellt, die die Einrichtung und die Funktionsweise von Cluster-basierten Ad-hoc-Netzwerken, die kooperative Relays verwenden, erleichtern und verbessern. Darunter befinden sich ein Clustering-Algorithmus, der den Batteriestatus der Knoten berücksichtigt, um eine längere Lebensdauer des Netzwerks zu gewährleisten und ein Routing-Mechanismus, der auf den Einsatz in kooperativen MIMO Mehr-Hop-Systemen zugeschnitten ist. Die Vorteile beider Algorithmen werden durch Simulationen veranschaulicht. Eine Methode, die Daten in Ad-hoc-Netzwerken mit verteilten Hash-Tabellen behandelt wird ebenfalls vorgestellt. Darüber hinaus wird auch ein Sicherheitsmechanismus für die physikalische Schicht in Multi-Hop-Systemen und kooperativen MIMO-Systemen präsentiert. Eine Analyse zeigt, dass das kooperative MIMO-Verfahren deutliche Vorteile gegenüber dem konventionellen MIMO-Verfahren hinsichtlich der informationstheoretischen Grenzen der Sicherheit auf der physikalischen Schicht aufweist