# Context-Aware Trust and Reputation Routing Protocol for Opportunistic IoT Networks
## 2 Related Work
Through simulations, the effectiveness of the proposed protocol is demonstrated. The pruning and filtering processes may introduce computational overhead, potentially impacting the protocol's scalability in large networks. Additionally, the reliance on accurate trust evaluations might make the scheme vulnerable to scenarios with incomplete or inconsistent trust information, limiting its effectiveness in highly dynamic OppNet environments. In [PERSON] et al. (2019), [PERSON] et al. proposed a trust-based and secured opportunistic routing scheme for wireless sensor networks, in which the trust value of a node is calculated based on specific parameters, which are the sincerity of the node in forwarding the data packet, sincerity of the node in acknowledging the data packet receipt, and the node's energy depletion value. Based on this trust value calculation, a relay selection algorithm is invoked to determine the suitability of the considered to participate in the routing process. Through experiments, the performance of the proposed routing protocol is shown to be superior to that of selected trust-based routing schemes in terms of predefined metrics. The protocol's effectiveness depends on accurate trust evaluations, which could be compromised in the presence of incomplete or misleading data, potentially impacting its robustness in hostile environments. [PERSON] Xiao [PERSON] et al. address the communication security challenges in T-S fuzzy network control systems (NCSs) caused by network congestion and denial-of-service (DoS) attacks under a QoS framework. To ensure system stability, the authors propose an intelligent event-triggered controller (IETC) featuring an improved data compression mechanism and a mini-batch gradient descent algorithm to optimize trigger thresholds for bandwidthefficiency. The study also introduces asymmetric Lyapunov-Krasovskii functions (LKFs) to reduce decision variables and enhance control robustness. The effectiveness of the IETC is validated on a CarSim-Simulink platform in an autonomous vehicle system, demonstrating its practical applicability and reliability. The main limitation of this work lies in the reliance on the CarSim-Simulink platform for validation, which may not fully capture the complexities and variations of real-world autonomous vehicle systems or large-scale networks. Additionally, while the IETC approach improves bandwidth efficiency, its performance could degrade in highly dynamic or unpredictable network environments, where the assumptions of stable conditions or accurate model parameters might not hold. In [18], [PERSON] et al. proposed a social context-aware routing protocol for OppNets, in which a mapping technique to analyze the recent relationships among two encountered nodes is designed. Based on these, a dynamic intra-cluster mechanism is invoked to reduce the message copies, and an inter-cluster communication method is devised to route the data packets to their intended destinations while eliminating unnecessary message flooding in the network. Simulation experiments have shown the superiority of the proposed scheme against a few benchmark schemes in terms of predefined performance metrics, under varying practical scenarios. The limitation of this work lies in its reliance on the assumption that the social relationships between nodes can be accurately mapped and remain stable over time. In highly dynamic or unpredictable environments, such assumptions may not hold, leading to suboptimal routing decisions. Furthermore, the approach may not be scalable in large networks with a high number of nodes, as managing dynamic intra- and inter-cluster communications could incur significant overhead. In [19], the author proposed a probabilistic routing model for OppNets, which relies on the nodes' meeting probabilities, last meeting time, and acknowledgment tables to determine their likelihood to carry the data packets toward their intended destination.