Abstract
In industrial wireless sensors networks (IWSNs), the sensor lifetime predictability is critical for ensuring continuous system availability, cost efficiency and suitability for safety applications. When deployed in a real-world dynamic and centralised network, the sensor lifetime is highly dependent on the network topology, deployment configuration and application requirements. (In the absence of an energy-aware mechanism, there is no guarantee for the sensor lifetime). This research defines a conceptual model for enhancing the energy predictability and efficiency of IWSNs. A particularization of this model is the predictive energy-aware routing (PEAR) solution that assures network lifetime predictability through energy-aware routing, energy balancing and profiling. The PEAR solution considers the requirements and constraints of the industrial ISA100.11a communication standard and the VR950 IIoT Gateway hardware platform. The results demonstrate the PEAR ability to ensure predictable energy consumption for one or multiple network clusters. The PEAR solution is capable of intracluster energy balancing, reducing the overconsumption 10.4 times after 210 routing changes as well as intercluster energy balancing, increasing the cluster lifetime 2.3 times on average and up to 3.2 times, while reducing the average consumption by 23.6%. The PEAR solution validates the feasibility and effectiveness of the energy-aware conceptual indicating its suitability within IWSNs having real world applications and requirements.
Highlights
Industrial wireless sensor networks (IWSN) are deployed in harsh, hardly accessible environments to serve as control and monitoring infrastructure solutions
While the battery capacity is known and the acquisition rate is configurable in a dynamic mesh network, the energy consumption is dependent on the network topology
The results of the test cases where the energy balancing support is not enabled are labelled as NonPEAR and will be used to evaluate the improvements provided by the predictive energy-aware routing (PEAR) algorithm.test cases the be balancing support is notprovided enabled by arethe labelled
Summary
Industrial wireless sensor networks (IWSN) are deployed in harsh, hardly accessible environments to serve as control and monitoring infrastructure solutions. We propose the predictive energy-aware routing (PEAR) solution to enhance the network lifetime in terms of prediction, sensor node energy consumption profiles, and flexible energy balancing. The particularities of this solution closely reflect the requirements and constraints of the Industrial WSN applications. Considering industrial IoT application, the expected maximum network uptime is typically related to sensor specifications (i.e., battery capacity, consumption rate) and data update period. The senor nodes are grouped into homogeneous consumption clusters based on the adoption of energy profiles This approach allows for lifetime prediction and battery replacement scheduling on a per cluster basis.
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