On the performance, availability and energy consumption modelling of clustered IoT systems

• Published in: Computing 2019-12, Vol.101 (12), p.1935-1970
• Main Authors: Ever, Enver, Shah, Purav, Mostarda, Leonardo, Omondi, Fredrick, Gemikonakli, Orhan
• Format: Article
• Language: English
• Subjects: Access control; Artificial Intelligence; Availability; Clustering; Computer Appl. in Administrative Data Processing; Computer Communication Networks; Computer Science; Computer simulation; Data transmission; Domains; Energy consumption; Failure analysis; Information Systems Applications (incl.Internet); Internet of Things; Mathematical analysis; Mathematical models; Performance degradation; Queues; Remote sensors; Software Engineering; Wireless sensor networks
• ISSN: 0010-485X; 1436-5057
• DOI: 10.1007/s00607-019-00720-9

Wireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics.