Abstract
The Internet of Things (IoT) comprises a large number of sensor nodes with limited processing, storage, and battery abilities. The IoT has to operate in a constrained environment with specific challenges, such as hardware malfunctions, battery depletion, and harsh wireless environmental conditions. Deploying a reliable IoT is especially important for critical IoT applications such as smart cities. To ensure the quality of service requirements of these applications, the IoT needs to provide specific reliability guarantees. There are several strategies to ensure energy efficient and reliable transport of data in the IoT. However, there is an inherent conflict between power consumption and reliability: an increase in reliability usually leads to an increase in power consumption as in traditional retransmission-based reliability. To solve this problem, we present four scenarios of optimization using a mixed integer linear programming (MILP) model. First, we used a standby routes selection scheme (SBRS) to replace node failures and achieve reliability with minimum traffic power consumption. Second, we used a desired reliability level scheme (DRLS), which minimizes the traffic power consumption of the IoT devices while considering the desired reliability level as a key factor. We also propose a reliability-based sub-channel scheme (RBS) to avoid overhead on busy reliable routes while mitigating interference. Moreover, we present a reliability-based data compression scheme (RBDS) to overcome the capacity limits of the links. The results show that our proposed schemes reduce the negative effect between reliability and total traffic power consumption with an average power saving of 57% in SBRS and 60% in RBDS compared to DRLS.
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