Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption

Un nuevo esquema de agrupación para redes sensoras inalámbricas de radio cognitivas heterogéneas

Introduction: This article is the product of the research “Learning-based Spectrum Analysis and Prediction in Cognitive Radio Sensor Networks”, developed at Sejong University in the year 2019. Problem: Most of the clustering schemes for distributed cognitive radio-enabled wireless sensor networks consider homogeneous cognitive radio-enabled wireless sensors. Many clustering schemes for such homogeneouscognitive radio-enabled wireless sensor networks waste resources and suffer from energy inefficiency because of the unnecessary overheads. Objective: The objective of the research is to propose a node clustering scheme that conserves energy and prolongs network lifetime. Methodology: A heterogeneous cognitive radio-enabled wireless sensor network in which only a few nodes have a cognitive radio module and the other nodes are normal sensor nodes. Along with the hardware cost, theproposed scheme is efficient in energy consumption. Results: We simulated the proposed scheme and compared it with the homogeneous cognitive radio-enabled wireless sensor networks. The results show that the proposed scheme is efficient in terms of energyconsumption. Conclusion: The proposed node clustering scheme performs better in terms of network energy conservation and network partition. Originality: There are heterogeneous node clustering schemes in the literature for cooperative spectrum sensing and energy efficiency, but to the best of our knowledge, there is no study that proposes a non-cognitiveradio-enabled sensor clustering for energy conservation along with cognitive radio-enabled wireless sensors. Limitations: The deployment of the proposed special device for cognitive radio-enabled wireless sensors is complicated and requires special hardware with better battery powered cognitive sensor nodes

Formal Probabilistic Analysis of a Wireless Sensor Network for Forest Fire Detection

Wireless Sensor Networks (WSNs) have been widely explored for forest fire detection, which is considered a fatal threat throughout the world. Energy conservation of sensor nodes is one of the biggest challenges in this context and random scheduling is frequently applied to overcome that. The performance analysis of these random scheduling approaches is traditionally done by paper-and-pencil proof methods or simulation. These traditional techniques cannot ascertain 100% accuracy, and thus are not suitable for analyzing a safety-critical application like forest fire detection using WSNs. In this paper, we propose to overcome this limitation by applying formal probabilistic analysis using theorem proving to verify scheduling performance of a real-world WSN for forest fire detection using a k-set randomized algorithm as an energy saving mechanism. In particular, we formally verify the expected values of coverage intensity, the upper bound on the total number of disjoint subsets, for a given coverage intensity, and the lower bound on the total number of nodes.Comment: In Proceedings SCSS 2012, arXiv:1307.802

Fuzzy enhanced Cluster based Energy Efficient Multicast Protocol for Increasing Network Lifetime in WSN

99–102Wireless Sensor Networks (CWSN) consists of sensor node which is mobile roaming inside and outside the network region. The difficulty in existing models observed is to identify the best routes for forwarding packets. If the balancing of packet arrivals and energy conservation is not achieved, it may lead to reduction of network lifetime. In our research work, Fuzzy enhanced Cluster based Energy Efficient Multicast Protocol (FCEEMP) is developed based on three aspects. First one, the establishment of multicast routing based on the calculation of best route metric and average reliability metric. Second, the cluster is formed based on node stability and route capability. Three set of nodes are formed in the cluster network model i.e. sensor node, cluster member and Cluster Head (CH) to estimate energy consumption. Third, enhancement of fuzzy model is implemented to produce optimal energy and the value of network lifetime. From the simulation analysis, proposed protocol achieves better improvement over existing schemes

Residual Energy Based Cluster-head Selection in WSNs for IoT Application

Wireless sensor networks (WSN) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. The paper focuses on an efficient cluster head election scheme that rotates the cluster head position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy and an optimum value of cluster heads to elect the next group of cluster heads for the network that suits for IoT applications such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the LEACH protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%

Reliable and Congestion Control Protocols for Wireless Sensor Networks

The objective of this paper is to analyze review and different congestion control protocols that are employed at the transport layer and some of them working at the medium access control layer in wireless sensor networks. Firstly, a brief introduction is given about wireless sensor networks and how congestion occurs in such networks. Secondly, the concept of congestion is discussed. Thirdly, the reason of occurrence of congestion in wireless sensor networks is analyzed. After that, congestion control and why it is needed in the wireless sensor networks is discussed. Then, a brief review of different congestion control and reliable data transport mechanisms are discussed. Finally, a comparative analysis of different protocols is made depending on their performance on various parameters such as - traffic direction, energy conservation characteristic, efficiency etc. and the paper is concluded

Energy-Efficient Data Acquisition in Wireless Sensor Networks through Spatial Correlation

The application of Wireless Sensor Networks (WSNs) is restrained by their often-limited lifetime. A sensor node's lifetime is fundamentally linked to the volume of data that it senses, processes and reports. Spatial correlation between sensor nodes is an inherent phenomenon to WSNs, induced by redundant nodes which report duplicated information. In this paper, we report on the design of a distributed sampling scheme referred to as the 'Virtual Sampling Scheme' (VSS). This scheme is formed from two components: an algorithm for forming virtual clusters, and a distributed sampling method. VSS primarily utilizes redundancy of sensor nodes to get only a subset to sense the environment at any one time. Sensor nodes that are not sensing the environment are in a low-power sleep state, thus conserving energy. Furthermore, VSS balances the energy consumption amongst nodes by using a round robin method

Secured Clustering in Wireless Sensor Networks

Wireless sensor networks are being increasingly used in a wide variety of applications such as the environment, nuclear power plants, military and transportation, to name a few. These sensors are fragile devices, with minimal energy, storage and computational resources. The phenomenon that is sensed is relayed to a powerful base station for further analysis. A key issue in the design of communication protocols for wireless sensor networks is energy conservation. Another important criterion for sensor networks is security. This is particularly important in military applications and national infrastructure such as power plants and transportation systems. As far as we are aware, no protocols have been proposed for energy efficient secure communications. In previous work both security and energy efficiency have been considered separately in the design of protocols for sensor networks. In this thesis we propose a secure energy efficient communication protocol for wireless sensor networks. A clustered protocol based on "A key-management scheme for distributed sensor networks" proposed by V.D. Gligor is developed and simulated in this thesis. To further improve energy efficiency we apply the concept of a force to improve the coverage of the sensor nodes. The properties of our proposed algorithm have been analyzed. We propose in this thesis a secure scheme with clustering, a balanced secure scheme with clustering and finally a balanced clustered secure scheme after the application of force. Results show that the proposed balanced clustered secure scheme after the application of force provides the best energy efficiency as well as security. The secure scheme with no clustering gave the worst results.Computer Science Departmen