TY - GEN
T1 - Online algorithms for wireless sensor networks dynamic optimization
AU - Munir, Arslan
AU - Gordon-Ross, Ann
AU - Lysecky, Susan
AU - Lysecky, Roman
PY - 2012
Y1 - 2012
N2 - Technological advancements in wireless communications and embedded systems have led to the proliferation of wireless sensor network (WSN) applications, each with varying application requirements (i.e., lifetime, throughput, reliability, etc.). Sensor node tunable parameters enable WSN designers to specialize/tune a sensor node to meet application requirements, but however, parameter tuning is a challenging process that requires designer expertise to consider sensor node complexities and changing environmental stimuli. In this paper, we develop lightweight, online optimization algorithms for sensor node parameter tuning, which enables dynamic optimizations to meet application requirements and adapt to changing environmental stimuli. Results reveal that our online optimizations quickly converge to a near optimal solution using minimal computational and storage resources, and are thus amenable for implementation on resource and energy-constrained sensor nodes.
AB - Technological advancements in wireless communications and embedded systems have led to the proliferation of wireless sensor network (WSN) applications, each with varying application requirements (i.e., lifetime, throughput, reliability, etc.). Sensor node tunable parameters enable WSN designers to specialize/tune a sensor node to meet application requirements, but however, parameter tuning is a challenging process that requires designer expertise to consider sensor node complexities and changing environmental stimuli. In this paper, we develop lightweight, online optimization algorithms for sensor node parameter tuning, which enables dynamic optimizations to meet application requirements and adapt to changing environmental stimuli. Results reveal that our online optimizations quickly converge to a near optimal solution using minimal computational and storage resources, and are thus amenable for implementation on resource and energy-constrained sensor nodes.
KW - dynamic optimization
KW - lightweight
KW - low-power
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=84860674697&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860674697&partnerID=8YFLogxK
U2 - 10.1109/CCNC.2012.6181082
DO - 10.1109/CCNC.2012.6181082
M3 - Conference contribution
AN - SCOPUS:84860674697
SN - 9781457720710
T3 - 2012 IEEE Consumer Communications and Networking Conference, CCNC'2012
SP - 180
EP - 187
BT - 2012 IEEE Consumer Communications and Networking Conference, CCNC'2012
T2 - 2012 IEEE Consumer Communications and Networking Conference, CCNC'2012
Y2 - 14 January 2012 through 17 January 2012
ER -