TY  - JOUR
T1  - An Adaptive Scheduling Algorithm for Collecting Data in Wireless Body Sensor Networks
AU - saba, Amirreza AU - Abdulnabi, Mohamed AU - Michelle Liu, Xiang 
JO  - Asian Journal of Information Technology
VL  - 20
IS  - 11
SP  - 210
EP  - 219
PY  - 2021
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2021.210.219
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2021.210.219
KW  - new data aggregation technique
KW  -Scheduling algorithm
KW  -data collection
KW  -wireless body sensor networks
AB  - Recent developments in the communications
and electronic industry have provided the stage for
producing multi-purpose, cost-effective sensor nodes with
low energy consumption in small dimensions and the
ability to communicate in short distances. This paper is
aimed at improving the efficiency of sensor networks in
the body sensor networks by using the learning automata
smart method and a new data aggregation technique. The
data is transmitted from clusters to the base station by a
data aggregation technique and a scheduling algorithm
(vital signs written in C++). Now automata data is sent
inside a random environment. According to the learning
algorithm with a variable structure LRI in which penalty
is zero and reward is given to the vital signs considering
their type, the random environment returns data to
automata so that automata uses it for selecting its next
action. If critical signs have received the maximum
reward after N repetition, it is determined as the best
action of automata. Then this data is sent to the physician
after being transmitted to the sink node (base station) via
the internet, and the physician diagnoses the disease and
returns the treatment result. To examine the performance
of the proposed protocol, we studied its behavior through
simulation. NS-2 simulator environment has been used for
simulating protocol. The scenario has been implemented
by OTCL, and we used files created by this language and
the C++ programming language in NS-2 space. The
results of the simulation show that the proposed protocol
has had a better performance.
ER  -