Wireless Body Sensor Network is a prominent research topic in the domain of WSN and has diversified healthcare applications. In real time application WBSN facing many problems i.e. WBSN system battery lifetime, the mobility of a person and delay time in recorded data communication. This paper proposed an energy and time efficient WBSN model by optimizing the sleep and awake period of microcontroller while recording the physiological parameters. EAT algorithm was designed to optimize the data buffering period and IEEE 802.11 superframe size to save the time consumed during biophysical data communication on the cloud. The results show that the proposed model was 16.04% energy efficient and 28.57% time efficient than previous models.
Volume 11 | 02-Special Issue
Pages: 1523-1532