Semantic-based topic multicast aggregated routing algorithm for resource optimization of pub/sub systems in wireless sensor network

With the rapid advancement of communication technology, the IoT (Internet of Things) has emerged as a leading trend. As a key technology and infrastructure for realizing IoT, Wireless Sensor Networks (WSNs) are also evolving towards greater interconnection and interoperability. In this context, the current study applies topic-based publish/subscribe (pub/sub) systems to WSNs, proposing a solution optimized for resource use in addressing the multi-source multicast routing problem within actual bandwidth-limited environments. The pub/sub systems link data-producing publishers in the network with subscribers interested in specific topics. However, establishing and maintaining links between network switches or routers incurs costs. To minimize the consumption of link resources, this study incorporate the semantics of messages into communication. Recent semantic communication research has primarily focused on semantic representation to reduce information volume for more efficient transmission. Similarly, semantic-related research within pub/sub systems has concentrated on semantic publication/subscription, semantic summarization, and semantic extraction or compression, all aimed at enhancing user experience or reducing resource consumption. Considering the unique characteristics of topic-based pub/sub systems, this study introduces the concept of semantic aggregation for routing and forwarding. This concept aggregates the routing and forwarding of messages with different topics based on their semantic relationships, thereby optimizing resources and efficiency. The paper specifically focuses on semantic aggregation in routing and introduces the Semantic-Based Topic Multicast Aggregated Routing Algorithm. Compared to traditional routing architectures, our approach results in fewer multicast routes and reduced resource consumption for links. Ultimately, we experimentally determine the resource consumption of the algorithm across various scenarios, demonstrating its effectiveness in optimizing link resources.