Modified Echo State Network-enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs

Minimizing energy consumption is one of the major challenges in wireless sensor networks (WSNs) due to the limited size of batteries and the resource constrained tiny sensor nodes. Energy harvesting in wireless sensor networks (EH-WSNs) is one of the promising solutions to minimize the energy consumption in wireless sensor networks for prolonging the overall network lifetime. However, static energy harvesting in individual sensor nodes is normally limited and unbalanced among the network nodes. In this context, this paper proposes a modified echo state network (MESN) based dynamic duty cycle with optimal opportunistic routing (OOR) for EH-WSNs. The proposed model is used to act as a predictor for finding the expected energy consumption of the next slot in dynamic duty cycle. The model has adapted a whale optimization algorithm (WOA) for optimally selecting the weights of the neurons in the reservoir layer of the echo state network towards minimizing energy consumption at each node as well as at the network level. The adapted WOA enabled energy harvesting model provides stable output from the MESN relying on optimal weight selection in the reservoir layer. The dynamic duty cycle is updated based on energy consumption and optimal threshold energy for transmission and reception at bit level. The proposed OOR scheme uses multiple energy centric parameters for selecting the relay set oriented forwarding paths for each neighbor nodes. The performance analysis of the proposed model in realistic environments attests the benefits in terms of energy centric metrics such as energy consumption, network lifetime, delay, packet delivery ratio and throughput as compared to the state-of-the-art-techniques

Several Categories of Energy Harvested Routing Protocols, Challenges, and Characteristics in WSN: A Review

The routing protocol is a technique for determining the most efficient channel for data transmission. The route selection procedure, which relies on the kind of network, channel conditions, and measurement systems, presents several challenges. Routing is essential in Wireless Sensor Networks (WSNs) for environmental monitoring, traffic monitoring, and other applications. WSNs are small nodes that can sense, interpret data, and communicate wirelessly. Many routing, power control, and data dissemination techniques have been developed specifically for WSNs, where energy efficiency is a crucial design factor. On the other hand, the focus has been on energy harvesting and standard routing methods, which can vary depending on the design and network architecture. In a Wireless Sensor Network (WSN), the data collected by the sensor nodes is typically transferred to the base station, which connects the sensor network to other networks (such as the internet), where it is processed and necessary action is taken. WSN has recently been developed to allow various applications, including traffic enforcement building automation, smart warfare, environmental sensing, and many more.WSN integrates several sensors or nodes deployed around a specific node to perform computational processes

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Optimization of the overall success probability of the energy harvesting cognitive wireless sensor networks

Wireless energy harvesting can improve the performance of cognitive wireless sensor networks (WSNs). This paper considers radio frequency (RF) energy harvesting from transmissions in the primary spectrum for cognitive WSNs. The overall success probability of the energy harvesting cognitive WSN depends on the transmission success probability and energy success probability. Using the tools from stochastic geometry, we show that the overall success probability can be optimized with respect to: 1) transmit power of the sensors; 2) transmit power of the primary transmitters; and 3) spatial density of the primary transmitters. In this context, an optimization algorithm is proposed to maximize the overall success probability of the WSNs. Simulation results show that the overall success probability and the throughput of the WSN can be significantly improved by optimizing the aforementioned three parameters. As RF energy harvesting can also be performed indoors, hence, our solution can be directly applied to the cognitive WSNs that are installed in smart buildings

Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer

Radio frequency (RF) energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service (QoS) requirement. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then, we present a case study of designing in the receiver operation policy, which is of paramount importance in the RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed by previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

[EN] Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.This work has also been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR.Qureshi, KN.; Bashir, MU.; Lloret, J.; León Fernández, A. (2020). Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision. Journal of Sensors. 2020:1-19. https://doi.org/10.1155/2020/9040395S1192020Sneha, K., Kamath, R., Balachandra, M., & Prabhu, S. (2019). New Gossiping Protocol for Routing Data in Sensor Networks for Precision Agriculture. 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A Novel Energy Harvesting Aware Routing Protocol for Underwater Wireless Sensor Networks

Underwater wireless sensor networks (UWSNs) have the potential to empower smart ocean applications. However, the widespread use of UWSN applications has been limited due to the many daunting challenges incurred in underwater wireless acoustic communication. Moreover, underwater wireless communication is energy-hungry, which confines UWSN deployment to small-scale due to the risks and costs of missions for at sea replacement of the nodes' batteries. The energy harvesting capability of underwater sensor nodes is an important characteristic that has been overlooked in the literature. In this thesis, we study the data routing process in UWSNs with energy harvesting capabilities. We proposed a novel opportunistic routing protocol, named RELOR, that is the first in the literature to consider the energy harvesting capability of underwater sensor nodes during routing decisions. RELOR implements a learning framework for the best selection of the forwarder nodes based on the observed environment conditions. We conduct extensive simulations to compare the performance of the proposed protocol to the state-of-the-art solution. Obtained results show that RELOR outperforms the related work in terms of packet delivery ratio, end-to-end latency, and nodes’ energy consumption