# Routing Protocols Performance on 6 LoWPAN IoT Networks
## 1 Introduction  
According to a previous study, 24 billion IoT devices were available globally in the year 2020. This forecast suggested that, on average, there would be approximately four Internet of Things (IoT) devices for every individual [1]. IoT devices typically constitute low-power and lossy networks (LLNs), characterized by numerous motes that operate under strict constraints, especially on energy consumption. Due to the hardware limitations, the performance of an LLN is tied to the efficiency with which routing protocols are used. The radio transmission activity significantly influences the energy consumption of individual devices within a wireless sensor network (WSN). The selection of appropriate routing protocols can directly impact the overall energy consumption level. In other words, the protocol selection and control packet management can optimize energy efficiency and enhance the performance of WSNs [2]. Data redundancyoccurs when the WSN sensor nodes are densely clustered due to the effort to improve the probability of obtaining a suitable neighbor to transmit the data [3]. The rise in packet size transmitted across nodes and the concurrent goal of reducing power consumption within routing protocols poses significant challenges. Routing protocols for low-power networks must effectively manage packet delivery while minimizing energy consumption. As packet sizes increase, the complexity of managing these packets also grows, leading to greater processing demands on sensor nodes with limited computational capabilities. This increased complexity can adversely affect the performance of energy-efficient routing algorithms. This prompts a critical examination of routing protocols to determine whether they can effectively operate within the low constraints inherent in the IoT concept, particularly in the context of IPv6 over Low-Power Wireless Personal Area Networks (6 LoWPAN). Evaluating the effectiveness of other routing protocols in the context of 6 LoWPAN presents challenges, in part because the routing protocol for low power and lossy networks (RPL) has received a lot of attention from the academic and research communities. The understanding of IoT vulnerabilities, like rank attacks and blackhole attacks is expanded from previous studies, mainly by RPL. Through the assessment of standardized protocols such as RPL, Ad hoc On-Demand Distance Vector (AODV), and Lightweight On-Demand Ad hoc Distance Vector Routing Protocol--Next Generation (LOADng), a benchmark between modified protocols from previous research can be established. Additionally, analyzing recognized protocols thoroughly can help identify potential shortcomings that will lead to future improvements. This iterative process is especially helpful in addressing common issues, like energy consumption, in a variety of scenarios, which will promote advancements and optimize routing protocols within the 6 LoWPAN. A variety of performance metrics have been reported for assessing routing protocol effectiveness in the context of 6 LoWPAN. A certain amount of the academic literature emphasizes the use of Powertrace extension, especially when it comes to simulations with Cooja. This preference derives from the inherent characteristics of the Powertrace dataset, which contains essential parameters, most notably overall CPU power usage and energy dissipation in the low power mode (LPM). Specifically, this dataset represents an extensive collection of information relevant to the artificially created normal IoT network environment, outlining complex aspects of energy dynamics present in the motes [4]. Apart from that, [PERSON] et al. [5] presents exhaustive data on power utilization which was extracted from the Powertrace output. The output delineates power consumption metrics for individual motes, with a focus on incremental motes and transmission ranges of 50 and 100 m. [PERSON] et al. [6] proposed that energy estimate is a critical factor in the LLN and a surrogate for the detector lifetime.