Research
The main objective of this project is to develop an energy efficient MTC deployment for diverse IoT applications and their specific requirements. To achieve this goal, we will analyze the communication deployment as a transparent part of a Cyber-Physical System (system of the future). In other words, the path from the sensed physical process to the end-application is a black-box that must achieve a pre-determined performance.
This project will open such a black-box and design the most energy efficient MTC wireless network that satisfies the specific application with its particular traffic regime. Our main hypothesis together with specific scientific objectives are given next.
Hypothesis: The most energy efficient communication deployment for any cyber-physical system depends on the specific application under consideration, which ultimately determines type of MTC needed and the traffic regime experienced by the communication network.
(H1) mMTC applications: The most energy efficient solution consists in data aggregation with event-based pre-processing for normal traffic conditions and time-based for high traffic conditions, both using short messages. Use of unlicensed frequencies are possible.
(H2) URLLC applications: The most energy efficient solution cross-layer design based on the communication effective capacity achieved by a direct link (without aggregation) between the pre-processing units (sensors) and the application (actuator). Use of licensed frequencies are preferable.
The optimal communication system setting depends on the specific application within these classes. A schematic of the proposed scenario is given next, where different physical processes and related applications co-exist. Our goal is to find the most energy efficient IoT deployment for this scenario.
Schematic of the cyber-physical system considered in this proposal. There are many physical processes happening at the same time. Sensors are deployed to acquire raw data about some specific processes. This data is pre-processed in the edge following a given strategy (e.g. time-based or event-.based sampling). The pre-processed data is aggregated/fused and then transmitted via wireless MTC. At this stage, depending on the application requirements, the transmissions must be related to mMTC or URLLC. The final step is processing of the received data to be used by the end-application. The ee-IoT goal is to design the most energy efficient IoT solution for every chain from acquisition to application.