Context-free dynamic service clustering of IoT-based services

The Internet of Things (IoT) is made up of many linked devices that are dispersed across multiple areas and provide IoT services to service consumers (SCs). These services are heterogeneous in nature and growing very fast with time. The IoT devices generate a huge amount of raw data, which is meaningless or useless. Thus, the contextualisation of these raw data plays a vital role in improving its meaning. Further, context-based IoT services can increase the execution time and memory size in the service domain. There is a lack of an efficient mechanism to extract useful information to achieve different SCs objectives. Therefore, this article presents a service meta-store (SMS) layer between the device and application level. The atomic service at the device layer is moved toward the upper layer based on context. These atomic services establish different groups based on context. These groups have interacted with the help of the service interface. A service clustering algorithm is designed to capture such a scenario. These services are used in different applications to fulfil the SCs requirements. That means the contextual information is only associated at the lower or device level. This information is unnecessary for other service mechanisms and forms a full phased service system. Various parameters and algorithms are expressed for service clustering. A quality-based service clustering approach enable to reduce the service cluster load. The proposed method is mapped into the real-life scenario. Various characteristics are considered to show the efficiency of the proposed approach. The experimental results proved that the execution time and memory size of context-free are much less than the context-based service clustering mechanism.