Adaptive Approximate Data Collection for Wireless Sensor Networks

Wireless sensor networks (WSNs) are used to collect large amounts of data over a wide area. However, the sensor nodes used in WSNs have a short lifespan because they are generally battery-operated. Research is actively underway to increase the lifespan of WSNs via techniques such as energy harvesting and wireless power transfer (WPT). This study proposes a scheme for clustering and adjusting the WSN data collection rate to alleviate the hotspot problem and improve network connectivity. The proposed scheme is targeted at WSNs in which the sensor nodes harvest solar energy. In addition, an unmanned aerial vehicle (UAV) traverses along a given path and delivers energy to sensor nodes using WPT, while collecting data as a sink node. In this scheme, the number of cluster heads is determined by considering the number of nodes at each hop distance and the maximum amount of data that can be transferred with the available energy. Further, sensor nodes limit the amount of data they collect to reduce the relay load on intermediate nodes. To achieve this, nodes consider the amount of data transferred by parent nodes, especially nodes in the hotspot, and the number of child nodes. The sink node traverses along a given path, and collects the data accumulated in the cluster head while supplying its remaining energy to the cluster head. The amount of energy it transfers is determined by considering the number of cluster heads. Consequently, nodes in the hotspot are prevented from becoming blacked out from a lack of energy, and the energy harvesting efficiency is increased. Simulation results indicate that the proposed scheme reduces the number of blackout nodes in the hotspot areas near cluster heads. Furthermore, the data collection and monitoring performance increases with the increase in network connectivity.

Distributed audio sensing with homeostasis-inspired autonomous communication

This chapter presents a combined approach to visualize the IoT and cyber-physical system in any wireless communication networks. The brief overview of IoT and its applications in wireless sensor network (WSN) are elaborated in current era. In today’s present situation and the challenges faced during COVID-19 pandemic how the things can be monitored through IoT is being focused in this chapter. Also, the threats challenges and monitoring of cyber-physical system for security is presented in analysis form. WSN provides a bridge between the physical and virtual world and finds use in numerous applications like environmental monitoring, civil structural health monitoring and industrial process monitoring. Lately, it has found much use in the latest technology called Internet of Things (IoT). It seems that IoT has a great potential in shaping our future where everything will be connected together all the time. The major challenges faced by WSN include energy-efficiency, heterogeneity, and systematic design. WSN comprise of autonomous sensors which are capable of wirelessly transmitting their sensed parameter-values (also called packets) to remotely 188located sink node. The sink node is a WSN node which has the capability to assemble the data from all the nodes and forward it to farther distances to the remote base station through wired connections. The data transmission from source node to sink node is done by taking multi-hops which means that data is not sent directly to the destination node but through jumping from one intermediate node to another until the sink is reached. The sensor nodes also act as wireless routers which transmit data to other sensor-routers. So, sensor devices are very useful in deployment, collection of data, act as a IoT sensor devices as an application in technology. IoT is a device which can be used as application while a cyber-physical system is a collection of various mechanical components which are controlled and managed by different devices and algorithms. An IFM (Information Flow Monitor) is an application to backtrack queries and find the culprit in an error that has occurred in the cyber system. However, while backtracking and flow monitoring is not always guaranteed in terms of secure and efficient transaction. In some cases, the sender may deny the authority of the data so the information flow monitors may fail to provide a trustful and authentic source of data. Thus, the chapter focuses on both the issues of IoT integration with cyber-physical security (CPS) system. The key challenges and some solutions are proposed for the researchers for future work.

One of the main applications in Wireless Sensor Networks (WSNs) is the accurate monitoring of extensive areas. However, due to the high density of nodes, redundant and correlated data are usually sensed by nearby nodes over time. Since saving energy is a key aspect of these networks, it is important to take advantage of these correlations to decrease communication and data exchange. However, current proposals usually results in high delays and outdated data arriving at the sink node. In this work, we go further and fully exploit both spatial and temporal correlations to perform near real-time data collection in WSNs. Also, in our proposal, called Efficient Data Collection Aware of Space-Time Correlation (EAST), obtained results clearly indicate that an event can be sensed with a high accuracy of more than 99.7% while still saving the residual energy of the nodes in more than 14 times when compared to the accurate data collection strategy.

A UAV-assisted CH election framework for secure data collection in wireless sensor networks

Security problems have become obstacles in the practical application of wireless sensor networks (WSNs), and intrusion detection is the second line of defense. In this paper, an intrusion detection based on dynamic state context and hierarchical trust in WSNs is proposed, which is flexible and suitable for constantly changing WSNs characterized by changes in the perceptual environment, transitions of states of nodes, and variations in trust value. A multidimensional two-tier hierarchical trust mechanism in the level of sensor nodes (SNs) and cluster heads (CHs) considering interactive trust, honesty trust, and content trust is put forward, which combines direct evaluation and feedback-based evaluation in the fixed hop range. This means that the trust of SNs is evaluated by CHs, and the trust of CHs is evaluated by neighbor CHs and BS; in this way, the complexity of evaluation is reduced without evaluations by all other CHs in networks. Meanwhile, the intrusion detection mechanism based on a self-adaptive dynamic trust threshold is described, which improves the flexibility and applicability and is suitable for cluster-based WSNs. The experiment simulation and evaluation indicate that the mechanism we proposed outperforms the existing typical system in malicious detection and resource overhead.

Recently, the use of wireless sensor networks has spread to applications areas that are not viable or costefficient to be run on other types of networks. Due to some critical tasks done in these types of networks, the majority of sensor networks applications should be dependable and should be run continuously and reliably without interruption. Hence, the two more significant dependability factors that should be nowadays taken into account in developing wireless sensor networks applications are ‘availability’ and ‘reliability’ of application services. The specific characteristics and constraints of wireless sensor networks require a different interpretation of these two factors when developing applications for such networks. In this paper, we propose a middleware layer mechanism for satisfying these two factors as more important dependability issues in sensor networks applications. We propose an event-based middleware service that is specifically designed for wireless sensor networks in which a group of sensor nodes forms a cluster and a replicated service is run on each cluster head. The communication model among cluster members and cluster head is based on the publish/subscribe scheme. We show how the replicated services and communication model in cluster nodes satisfy dependability issues and increase the availability and reliability of applications running under the proposed middleware.

But, as the energy-efficiency is critical for periodical data gathering applications in wireless sensor networks, it has the highest priority in algorithms design; also the latency, packet loss, and throughput are important factors and should be addressed. This chapter proposes a routing protocol inspired by an energy-efficient cluster-based routing protocol called Energy-Aware Routing Protocol (EAP). The new enhanced protocol that is called Low Loss Energy-Aware Routing Protocol (LLEAP) enhances the performance of EAP in terms of some quality of service parameters by adding a second iteration for constructing the tree structure for multi-hop communication among cluster heads, by modifying the used weights of the cluster heads and parent node selection, and finally by selecting suitable aggregation method to decrease losses and delay. Simulation results showed that LLEAP significantly outperforms EAP in terms of packet loss percentage by on average 93.4%.

Wireless sensor networks (WSNs) comprise nodes with restricted battery power that are deployed to observe some physical event within the sensor field. Information gathering is typical, but an important operation in several applications of WSNs. It is important to control the sensor network for longer period of time in an energy-efficient manner for gathering information. Hence, it is perpetually fascinating to design protocols that are energy efficient, have prolonged lifetime and can support event-driven applications. This paper proposes a protocol referred to as distance-based residual energy-efficient stable election protocol (DRESEP) that is nearly optimal for event-driven information gathering applications in sensor networks. The key idea of DRESEP is moving gathered information from sensor nodes to cluster head (CH) depending upon perceived changes. Dual-hop communication between CHs and base station is introduced to achieve energy minimization. Further, the results demonstrate that the proposed algorithm significantly outperforms existing algorithms in terms of energy optimization and system lifetime.

In real-life applications of wireless sensor networks (WSNs), optimization of the network operation is required to extend its lifetime. A framework is proposed that enables practical development of centralized cluster-based protocols supported by optimization methods for the WSNs. Based on this framework, a protocol using harmony search algorithm (HSA), a music-based meta-heuristic optimization method, is designed and implemented in real time for the WSNs. It is expected to minimize the intra-cluster distances between the cluster members and their cluster heads (CHs) and optimize the energy distribution of the WSNs. The study of HSA cluster-based protocol is carried out in a real case where the WSNs equipped with the proposed protocol are deployed in an indoor environment to monitor the ambient temperature for fire detection. A comparison is made with the well-known cluster-based protocols developed for WSNs such as low-energy adaptive clustering hierarchy-centralized (LEACH-C) and a cluster-based protocol using Fuzzy C-Means (FCM) clustering algorithm. Experimental results demonstrate that the proposed protocol using HSA can be realized in centralized cluster-based WSNs for safety and surveillance applications in building environments. From the obtained experimental test results, it can be seen that the WSNs lifetime has been extended using the proposed HSA protocol in comparison with that of LEACH-C and FCM protocols.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

A staggering number of applications rely on the network architecture to carry out their tasks, which has led to a fast growth in wireless sensor networks (WSN). The possibility of harmful activity and data theft is growing as a result of the growth in devices and data. Thus, the network’s regular users have an impact on legitimate data delivery, which lowers customer happiness and worsens network standards. The data have been saved using a variety of security procedures that have been developed in past research studies. However, harmful activity continues to engage in its illegal operations despite their efforts to safeguard data transmission in the network. As a result, a number of recent research projects have concentrated on predicting innovative techniques and processes to offer security in WSN. In comparison to existing methods, this work attempted to offer an effective tighter security for WSN and suggested an ML‐Based Secured Routing Protocol (MLSRP) for WSN with improved energy efficiency and overall performance. Energy efficiency is the main requirement of WSNs, hence a clustered network is proposed where the data are routed through the cluster head nodes. In this paper, a multicriteria based decision‐making (MCDM) model is used by the MLSRP to perform data routing, clustering, and cluster head election while also analyzing a number of network characteristics that might affect the quality of a node, route, and data. In NS2 software, the suggested framework is put into practice and simulated. The results are then validated to gauge performance. The observed quantitative results reveal that the proposed MLSRP method attains an improved network lifetime by 5% and network throughput of 6%. It reduces energy consumption by 40%, curtails overhead to 37%, and minimizes end‐to‐end delay by 30% than the other conventional methods. The suggested framework performs better than others when its total performance is compared to that of older methods.

Resource Management Approach to an Efficient Wireless Sensor Network

The applications of Wireless Sensor Networks (WSNs) are massive in the range that starts from the defense, civil, military to our day to day routine life. Energy conservation in WSNs is a crucial issue to make the network operational for a long time. It is entirely worth noting that most of the energy consumption occurs during the data transmission. Routing protocol plays a significant role in carrying and forwarding the data to the destination. Clustering is one such branch of routing technique that increases the Network Lifetime unexpectedly through minimal energy consumption. In this regard, this research paper aims to formulate an exciting clustering problem in WSNs where the coordinates of patterns are random variables. The clustering problem is solved using the CENTROID approach, such as Cluster Head (CH) selection is done with an optimization interpretation. The proposed protocol is verified through the ns-2 simulator, and the results obtained from the simulations show that the proposed constrained clustering LEACH (CC-LEACH) offers its superiority over the existing protocols such as LEACH and LEACH-C in terms of various performance parameters.

In most wireless sensor network (WSN) applications, data are typically gathered by the sensor nodes and reported to a data collection point, called the sink. In order to support such data collection, a tree structure rooted at the sink is usually defined. Based on different aspects, including the actual WSN topology and the available energy budget, the energy consumption of nodes belonging to different paths in the data collection tree may vary significantly. This affects the overall network lifetime, defined in terms of when the first node in the network runs out of energy. In this paper, we address the problem of lifetime maximization of WSNs in the context of data collection trees. In particular, we propose a novel and efficient algorithm, called Randomized Switching for Maximizing Lifetime (RaSMaLai) that aims at maximizing the lifetime of WSNs through load balancing with a low time complexity. We further design a distributed version of our algorithm, called D-RaSMaLai. Simulation results show that both the proposed algorithms outperform several existing approaches in terms of network lifetime. Moreover, RaSMaLai offers lower time complexity while the distributed version, D-RaSMaLai, is very efficient in terms of energy expenditure.