# Blockchain-Assisted QoS-Aware Routing for Software-Defined Wide Area Network
## 2 Related Work
Using a newly designed multi-QoS link metric, the system selects optimal paths and applies local rerouting to handle link congestion efficiently. In the case of a congested scenario, their approach modifies only thelinks before and after the congested link (if found) instead of modifying the whole path from source to destination. Simulation results confirm the effectiveness of the approach in ensuring QoS before and after congestion events. [PERSON] et al. [13] introduced AQRA (Application-Aware QoS Routing Algorithm), which identifies multiple optimal paths based on adaptive weighting and current network conditions. AQRA selects the path with the highest available bandwidth while ensuring load balancing. It prioritizes flows and safeguards the QoS of high-priority IoT applications. Evaluation results show that AQRA outperforms existing approaches in satisfying QoS requirements for mission-critical applications. Similarly, [PERSON] et al. [14] presented the NSAF framework to ensure application-level QoS in SDN environments. NASF can identify QoS requirements, detect violations, and select appropriate network paths. NSAF supports 12 DiffServ application types, using measurable QoS metrics such as bandwidth, delay, jitter, and packet loss. It incorporates an application profile model and a topology model to monitor and manage QoS violations. [PERSON] et al. [3] addressed QoS challenges in video streaming over an SDN using ARVS (an adaptive routing scheme) that treats video packet flows on two levels: a base layer and an enhancement layer. The algorithm prioritizes rerouting based on delay variation and available bandwidth, where base layer packets are rerouted first to maintain video quality, while enhancement layer packets remain on the original path unless rerouting is necessary. This dynamic approach helps mitigate congestion on the shortest path. [PERSON] et al. [15] applied Smart-OSPF within a hybrid SDN environment, where Smart-OSPF is an enhanced version of the traditional OSPF protocol that improves data transmission by gathering distributed traffic at target nodes. Additionally, various heuristic algorithms, including ant colony optimization, simulated annealing, and genetic algorithms, have shown effectiveness in balancing network load and reducing packet loss, but those methods often come with high computational complexity, which can limit their scalability in large networks. [PERSON] et al. [4] proposed DCUR (Delay-Constrained Unicast Routing) as a distributed heuristic algorithm that maintains only a cost and delay vector for loop-free routing. They compared DCUR with traditional distance-vector and link-state protocols, and DCUR provided a low message overhead. [PERSON] et al. [5] presented BaProbSDN as a probabilistic QoS routing mechanism for an SDN to address the growing challenges of dynamic traffic patterns driven by cloud computing and distributed data services. They used [PERSON] theorem and a Bayesian network model based on bandwidth availability constraints. Simulation results show that it outperforms the widest-shortest path routing (WSR) algorithm [16] by reducing bandwidth blocking rate under conditions of link update inaccuracies and time delays. [PERSON] et al. [17] explored the use of bidirectional search to improve the efficiency of multi-constrained QoS routing. Their strategy addresses limitations in traditional unidirectional search methods that affect path success rates and quality. The authors also decompose routing problems into simpler subproblems and identify conditions under which bidirectional search can terminate without sacrificing accuracy. [PERSON] et al. [6] addressed the multi-criteria optimal path selection problem in QoS-aware routing that satisfies multiple constraints (e.g., bandwidth and delay) and optimizes a given metric (e.g., cost). Traditional approaches simplify the problem using a single weighted metric, but this requires predefining the relative importance of each criterion, which may not always be available in many real-world scenarios.