Engineering adaptive communication protocols for upcoming WSN applications

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With the advent of the Internet of Things (IoT), a growing number of devices start exchanging information. While this enables new interesting applications, it also places high demands on the underlying communications infrastructure, in particular, wireless sensor networks (WSNs), which facilitate interaction between IoT devices and the environment. These must enable reliable, energy-efficient and timely communication, which becomes increasingly complex as dynamics and heterogeneity of such networks increase. In this context, adaptive communication protocols seem to be an interesting solution, since these can automatically reconfigure themselves to meet specified performance goals under changing conditions. Unfortunately, existing solutions still have major drawbacks limiting their performance and applicability. For example, they only support single performance goals (e.g., reliability or energy, but not both) and do not account for heterogeneity among others. In this research work, to overcome this problem, a novel adaptive communication protocol is proposed. In contrast to existing solutions from the literature, the proposed approach is based on a specialized MAC (medium access control) protocol that intrinsically allows for adaptivity, which is extended by an ODA (observe, decide, act) loop for control and automation. In this context, different adaption techniques will be investigated such as control-theoretic approaches and machine learning (e.g., Q-Learning). The purpose is to assess their effectiveness as well as their impact on memory/computational performance of the embedded nodes. Effectiveness in this context is measured with respect to how good different adaption techniques are in finding a compromise between opposing performance goals. For example, reliability and energy consumption are two contradictory requirements, i.e., increasing one worsens the other. As a result, it is paramount to find suitable tradeoffs. In addition, considering that WSNs are distributed, embedded systems with heterogeneous (i.e., node-specific) limitations, this turns to be a very challenging task.Finally, the proposed adaptive communication protocol will be evaluated in simulation and on real hardware, e.g., on T-Mote Sky nodes. This provides valuable insights that help correct shortcomings by today's solutions and thus increase their applicability and performance – current adaptive protocols already achieve >80% higher performance than classic, non-adaptive ones, but this can be further increased. In summary, this research project thus contributes to the design and development of adaptive WSNs able to cope with the increasing complexity, dynamics and heterogeneity of modern and upcoming applications.