A Hybrid AHP-TOPSIS Approach for Selecting Message Brokers in IoT Applications

Message brokers play a pivotal role in IoT systems by managing crucial functions such as message routing, storage, and reliable delivery. They enable IoT development teams to concentrate on core business functionality rather than communication infrastructure. Thus, the selection of a message broker is a critical architectural decision in IoT systems. While various comparative studies and benchmarks provide valuable insights into specific aspects of message brokers, there is a lack of comprehensive, decision-oriented frameworks that can support this complex selection process. This paper addresses this gap by introducing a multi-criteria decision analysis (MCDA) approach that supports the process of selecting message brokers. The approach uses the Analytic Hierarchy Process (AHP) for criteria weighting and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank alternative brokers. The approach was implemented as a configurable decision support tool facilitating systematic and transparent evaluation of five message brokers (Apache Kafka, Apache Pulsar, RabbitMQ, NATS, and EMQX). The approach and tool effectiveness were evaluated on three use cases.