A Hierarchical Energy-Efficient Service Selection Approach With QoS Constraints for Internet of Things

With the emergence of Service-oriented Architecture (SoA) technologies, service-defined Internet of Things (IoT) applications have been widely developed. However, IoT system is resource-constrained. Devices in IoT usually have limited storage, computation and especially limited energy. Unfortunately, traditional service selection technologies ignore the energy efficiency of services. Although a few studies address energy consumption in service selection or composition, they fail to pay more attention to the dynamic characteristic of IoT, which is not suitable for resource-constrained IoT. In order to resolve this issue, we propose a hierarchical energy efficient service selection approach for resource-constrained IoT. In our approach, a Quality of Service (QoS) guaranteed global constraints decomposition is performed to acquire a group of local QoS constraints. Then, based on the selected local QoS constraints, an energy efficient service selection scheme can be carried out independently according to the dynamic network state. Experimental evaluations demonstrate the capability of our proposed approach.

Automated summary

A hierarchical energy efficient service selection approach for resource-constrained IoT is proposed, which includes global constraints decomposition and selection of local QoS constraints to achieve an energy efficient service selection scheme based on dynamic network state. Experimental evaluations show the capability of the proposed approach.