# Modified Echo State Network Enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs
## 1 Introduction  
Wireless sensor networks (WSNs) comprise a number of tiny sensor nodes for sensing and computation, transmission and reception for smart applications [1]. In WSNs, sensor nodes collect data about some targets and transmit sensed data to the sink node (or base station) via multiple hops [2]. Due to the ease of deployment, WSNs are utilized in many smart applications, such as security surveillance [3], disaster relief [4], IoT use cases [5], medical care [6], E-mobility [7], traffic management [8] and precision agriculture [9]. Enhancing the network lifetime and minimizing the packet delivery delays are some of the challenging tasks for WSNs based smart applications [10]. The size of the sensor nodes is small, and need regular power from a tiny size battery. However, it is unfeasible to recharge or alter the battery in case of hostile environments centric applications. In wireless sensor networks, we can extend the operating lifetime of nodes by energy harvesting mechanism and therefore enhancing the network lifetime [11]. Furthermore, this technology decreases the operation cost of WSNs, thus making it very essential for a sustainable \"near-perpetual\" WSNs operability. Therefore, energy harvesting in WSNs (EH-WSNs) is crucial for the sustainable operations of WSNs [12]. Various challenges exist in improving the environment of EH-WSNs. Further, there is a need for enhancing the performance of various applications for uplifting the ecosystem and human life by using EH-WSNs [13]. Efficient energy regulating schemes are required to make the nodes working proficiently without hurdles and thereby making the network more efficient [14]. Some mechanism is needed to address the issue of energy scarcity in EH-WSNs [15]. There are still various unresolved problems and to effectively manage the harvested energy, EH-WSNs should use a customized packet forwarding scheme. This minimizes the energy consumption and maximizes the lifetime of the network [16]. Opportunistic packet forwarding schemes (OPEH) are broadly used in WSNs, and usually yield high packet delivery ratio (PDR) and low end-to-end delay (EED). In EH-WSNs, the packet-transmission method acknowledges multistage relay set optimization mechanisms and renders an exact estimation to the cost of transmission. The relay nodes can be optimally chosen either by prioritization of the relay nodes or clustering the relay nodes in WSNs [17]. Likewise, in WSNs, nodes are generally duty-cycled to prolong the network lifetime. According to the duty cycle method, the nodes periodically switches among active and sleep mode and it is a most commonly applied scheme for energy saving. A node can transmit or receive packets while in active mode, but cannot communicate while in sleep mode. Thus, raising the duty cycle results in higher energy consumption and lower delay, while it produces the opposite effect by reducing the duty cycle. Furthermore, sensor nodes usually work with sleep-wake up schedules to save power by using the duty cycle scheme. [18; 19] discusses the duty cycle adjustment scheme that is based on residual energy aware and changing the wake-up interval as per the harvested energy. In EH-WSNs, the concept of dynamic and heterogeneous duty cycle (DC) of nodes helps in improving the energy acquisition. This approach would make the nodes working proficiently for a longer time. The reason belongs to the fact that the energy acquisition is typically insufficient, time-shifted and uneven in static duty cycle centric EH-WSNs. The opportunistic packet forwarding methods do not acknowledge the effect of the dynamic and heterogeneous DC. [PERSON] et al. [20] have improved the dynamic and heterogeneous DC methods with the assistance of the energy consumption calculation and utilized ESN [21] for predicting energy acquisition for next time slot, however only the traditional ESN model was used. In conventional ESN, the weight choice methodology is time-consuming making it non-scalable for WSNs.