An Efficient Design of RPL Objective Function for Routing in Internet of Things using Fuzzy Logic

Abstract

The nature of the Low power and lossy networks (LLNs) requires having efficient protocols capable of handling the resource constraints. LLNs consist of networks that connect different type of devices which has constraints resources such as energy, memory and battery life. Using the standard routing protocols such as Open Shortest Path First (OSPF) is inefficient for LLNs due to the constraints that LLNs need. So, IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was developed to accommodate these constraints. RPL is a distance vector protocol that used the object functions (OF) to define the best tree path. However, choosing a single metric for the OF found to be unable to accommodate applications requirements. In this paper, an enhanced (OF) is proposed namely; OFRRT-FUZZY relying on several metrics combined using Fuzzy Logic. In order to overcome the limitations of using a single metric, the proposed OFRRT-FUZZY considers node and link metrics. Namely, Received Signal Strength Indicator (RSSI), Remaining Energy (RE) and Throughput (TH). The proposed OFRRT-FUZZY is implemented under Cooja simulator and then results were compared with OF0, MHROF in order to find which OF provides more satisfactory results. And simulation results show that OFRRT-FUZZY outperformed OF0 and MHROF.

DCRL‐RPL: Dual context‐based routing and load balancing in RPL for IoT networks

“…ℛ n = P ℛ + ETX (14) where P ℛ defines the parent rank and ETX defines the expected transmission count. This metric describes the number of transmissions it requires to reach the root node.…”

“…Likewise, Safaei et al [13] have exploited the power delay product objective function to route the packets effectually to the root node. Some of the works have utilised the fuzzy logic to select the optimal path between the source and destination [14,15]. The context-aware objective function selection is introduced to enhance the routing performance in the RPL-based IoT network [16].…”

A Comprehensive Survey on Node Metrics of RPL Protocol for IoT

“…The traditional networks concern is limited support to traffic, scalability, network dynamicity, latency, manageability, convergence time stability, and support to mobility (Lamaazi et al 2016). In order to cover this limitation, a routing protocol has been proposed by the roll working group as a tree .This routing protocol of LLN is RPL (Lamaazi et al 2016;Saaidah et al 2019).…”

“…It only keeps an optimal routing at a time. Moreover, it just selects one of the parent nodes that are considered to be the best among the rest (Lamaazi&Benamar 2018; Saaidah et al 2019). The OFs seeks choosing and optimizing the route that is between nodes.…”

DDSLA-RPL: Dynamic Decision System Based on Learning Automata in the RPL Protocol for Achieving QoS

“…OFRRT-FUZZY [35] In this method, three parameters of RSSI, residual energy, and throughput rate have been implemented as fuzzy inputs in the network.…”