# Trust-Aware Routing Mechanism through an Edge Node for IoT-Enabled Sensor Networks
## 2 Related Works  
In this section, we provide an overview of the recently published trust-aware routing protocols with their advantages and limitations. We summarize these in Table 1. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Algorithm/Protocol** & **Advantages** & **Remarks** \\ \hline [PERSON] et al. [16] & TEM-MEN & Reliable because of efficient hostile attacks prevention & Failed to minimize the energy and costly due to multiple mobile edge nodes \\ \hline [PERSON] et al. [17] & TBSEER & Resolve the congestion and serious energy dissipation problems & Increasing the percentage of malicious nodes increases the number of rounds needed to exclude them. \\ \hline [PERSON] et al. [10] & VFDC & Overcomes limited storage capacity and weak computation power due to mobile edge data collector & The applications complying with the edge intelligence network have to be made more trustworthy \\ \hline [PERSON] et al. [18] & ITCM & Improves detection accuracy of malicious nodes and solves & Not suitable for resource constraint systems, convergence speed needs to be improved \\ \hline
[19; 20; 21] & Trustworthy nodes selection & Can be improved to encounter other external or internal attacks such as ballot stuffing, conflicting behavior, Sybil attacks, etc. & Security breach from distributed network threats, not cost effective \\ \hline [PERSON] et al. [8] & DRL & Intelligent trust nodes selection & High computational complexity and resource rich \\ \hline [PERSON] et al. [22] & ALO-K & Efficient hybrid clustering & Intra-cluster distance must be minimum and F-measure must be maximum for better cluster quality \\ \hline [PERSON] et al. [23] & Modified ECO with K-means & Low convergence time & Restricted to single-objective optimization functions \\ \hline [PERSON] et al. [24] & Modified ABC & Detects Sybil attacks in pervasive edge computing based IIOT & \\ \hline [PERSON] et al. [25] & ACO & Efficient data collection by minimizing delay and maximizing the network life & Hard to decide population size and initial parameters \\ \hline [PERSON] et al. [26] & PCA & \\ \hline [PERSON] et al. [27] & WOA-SA & Efficient selection of cluster heads & Energy consumption and security issues need to be addressed \\ \hline
**Our approach** & **TARM** & High convergence with no local optima problem & None \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of related work on recently published trust-aware protocols. There are many research contributions on trust-aware routing in the literature; we summarize the most recent ones in this section. [PERSON] et al. [16] proposed a trust evaluation scheme based on mobile edge nodes for IoT. In [17], the authors propose a routing protocol called trust-based secure and energy (TBSEER) routing protocol to resolve the congestion and serious energy dissipation problems. In this proposal, the nodes calculate the adaptive direct trust value, and the sink nodes take care of indirect trust computation. Here, the edge nodes efficiently identify the untrustworthy nodes, thereby reducing the risk of attacks. A virtual force data collection (VFDC) scheme is proposed in [10] that enables a mobile edge node to visit every trustworthy node and collect their data to ensure both energy-saving and security of the system. Another approach called Intelligent Trust Cloud (ITCM) [18] management is used to determine the untrustworthy devices in the Internet of Medical Things (IoMT). This approach works in three phases: firstly, the trust clouds are formed; then, they are established through the Fuzzy inference system; finally, the third phase deals with seeking untrustworthy nodes in it. In [19; 20; 21], the authors propose trust-based algorithms to select trustworthy nodes, and the data are collected from those nodes using edge node or edge intelligence. These approaches isolate the detected malicious nodes using different techniques. Deep reinforcement learning-based trustworthy target tracking is presented in [8].