Adaptive Deep Rider LSTM-Enabled Objective Functions for RPL Routing in IoT Applications

Adaptive Deep Rider LSTM-Enabled Objective Functions for RPL Routing in IoT Applications

Chaudhari D. A., Dipalee A. Chaudhari, Umamaheswari E., E. Umamaheswari
Copyright: © 2022 |Pages: 17
DOI: 10.4018/IJISP.285583
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Abstract

This paper presents a proposed Objective Function (OF) design using various routing metrics for improving the performance of IoT applications. The most important idea of the proposed design is the selection of the routing metrics with respect to the application requirements. The various metrics, such as Energy, Distance, Delay, Link quality, Trust (EDDLT) are used for improving the objective function design of the RPL in various IoT applications. Here, the Adaptive Deep rider LSTM is newly employed for the energy prediction where the Adaptive Deep Rider LSTM is devised by the combination of the adaptive theory with the Rider Adam Algorithm (RAA), and the Deep-Long Short Memory (Deep-LSTM). However, the evaluation of the proposed method is carried out energy dissipation, throughput, and delay by achieving a minimum energy dissipation of 0.549, maximum throughput of 1, and a minimum delay of 0.191, respectively.
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1. Introduction

Barriers and distances are eliminated using the IoT by way of connecting the devices to devices, humans to devices, and humans to humans. IoT is considered a promising area in computing functionalities, which has attained considerable attraction because of its general applications in numerous domains, like constructions, medical fields (Lombardo et al., 2013), (Manfredini et al., 2016), (Michele et al., 2016), farms, surroundings (Safaei, et al., 2020). Recently, IoT has emerged as an attractive topic among researchers all over the world. This technology paved its way into various opportunities like agriculture, industry, transportation, and health because of its capability to function in an IP-driven network and also the capability to handle millions of nodes (Al-Fuqaha, et al., 2015; Taghizadeh, et al., 2018). On the whole, the construction and development of an IoT framework rely on the communication of several constrained embedded devices regarding the processing power, data rate, energy, memory, and the range of transmission over the wireless mediums (Safaei, et al., 2020). Every IoT layer consists of a precise set of tasks, which may affect the utilization of the resources in the IoT nodes (Safaei, et al., 2020). The sensor nodes in the IoT framework are power-constrained with some inadequate resources, and hence it is necessary to optimize the resource utilization performance. Several communication technologies such as Zigbee, Wifi, and Bluetooth are employed for establishing the IoT concepts in various network circumstances. In addition, the consistency features of the communication protocols are capable of gathering and transmitting the data from the real-time smart systems over the Internet Protocol (IP)-enabled framework. The association of smart devices and their interoperability with large-scale communications serves as a major function in the IoT network systems (Alameri, 2018).

In the Low and the Lossy Networks (LLN), certain power-constrained nodes and pair of border routers (Kim, et al., 2015; Taghizadeh, et al., 2018). The border router is also called as the Gateway. If the nodes cannot be able to communicate with the border router directly, it exploits some other nodes as the intermediary nodes in the track of the border router (Kim, et al., 2014). This kind of communication practice is managed based on the routing-enabled network protocols in the surrounding. Hence, routing protocols enables a significant role in sending the data packets to the border router from the main nodes of the IoT network (Yang, et al., 2016; Taghizadeh, et al., 2018). The primary services of the IoT framework is routing and networking, which facilitates communication among the IoT devices (Miorandi, et al., 2012; Airehrour, et al., 2019). A most important consideration throughout the routing process of IoT is scalability, autonomy and protected communication and energy efficiency (Hui, et al., 2017; Airehrour, et al., 2019). However, searching for an appropriate route for communication with certain constraints poses a great challenge for analysts. The routing devises the most widespread RPL protocol for the IoT-enabled routing applications over Low Power Lossy Network collection (ROLL). RPL can be used in automotive applications due to the descriptive and elastic nature of RPL. The IoT applications can further utilize the flexible nature of the RPL by considering the OFs along with the proper selection of the routing metrics (Solapure & Kenchannavar, 2020). RPL routing protocol enables the users to describe routing approaches with respect to their metrics and routing needs (Mayzaud, et al., 2017; Taghizadeh, et al., 2018). On the other hand, the IPv6 RPL was developed to supply flexible routing and less-power routing for the IoT environment (Winter, et al., 2012; Safaei, et al., 2020). OF is the element to provide flexibility for the RPL (Safaei, et al., 2020). OF defines the decisions for selecting the appropriate nodes for the operations in order to achieve the network goals (Hassan, et al., 2016; Taghizadeh, et al., 2018).

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