Zippy Random Access Protocol for Critical Data Transmission in Consumer Healthcare Applications

Nowadays, consumer electronic devices have transformed the healthcare industry from telemedicine to accurate remote patient monitoring. This digital transformation helps to monitor patients and provide timely diagnoses with minimum delay. In such time-sensitive healthcare applications, short-range communication protocols always play a crucial role from data collection to the data computation phase. However, the traditional protocols fail to handle concurrent transmissions of time-critical data from multiple sensor nodes. Due to an inefficient backoff algorithm with a predefined contention window size, these protocols could not simultaneously allocate the time slots to more than one critical sensor node over a common channel. Further, it can increase the delay when two or more sensor nodes with critical data choose the same random backoff counter values and try to access the medium along with other non-critical nodes. To mitigate all these issues, this work aims to design a novel Zippy Random Access Protocol (ZRAP) using an Emergency Lookup Table (ELT) to dynamically assign and adjust the backoff counter values and effectively minimize the backoff value conflicts among the sensor nodes. The extensive simulation results show that the proposed ZRAP outperforms the state-of-the-art random-access protocols in terms of delay, failure probability, collision rate, reliability, and throughput.