TY - JOUR
T1 - Extending the Lifetime of Dynamic Underwater Acoustic Sensor Networks Using Multi-Population Harmony Search Algorithm
AU - Lin, Chun-Cheng
AU - Deng, Der Jiunn
AU - Wang, Shang Bin
PY - 2016/6/1
Y1 - 2016/6/1
N2 - Like wireless sensor networks, lifetime of sensors is the main constraint for performance of underwater acoustic sensor networks (UASNs). Most previous works on UASNs did not consider dynamics of networks, i.e., as time goes by, in practice, part of sensors may be malfunctioned, deplete their battery power, or get lost due to violent underwater environment changes. Therefore, this paper considers a UASN in ocean and proposes a sleep scheduling scheme in which sensor nodes and autonomous underwater vehicles in this network can dynamically choose to sleep or work to adapt to the environmental change. The concerned problem is to dynamically determine a sufficient number of active nodes in the UASN at different times, such that the targets required to be detected are covered. A special static scenario of the problem has been shown to be NP-complete. Hence, this paper proposes an improved multi-population harmony search algorithm to solve this dynamic problem. By simulation, the proposed algorithm shows high performance in terms of extending network lifetime, robustness, and computing time.
AB - Like wireless sensor networks, lifetime of sensors is the main constraint for performance of underwater acoustic sensor networks (UASNs). Most previous works on UASNs did not consider dynamics of networks, i.e., as time goes by, in practice, part of sensors may be malfunctioned, deplete their battery power, or get lost due to violent underwater environment changes. Therefore, this paper considers a UASN in ocean and proposes a sleep scheduling scheme in which sensor nodes and autonomous underwater vehicles in this network can dynamically choose to sleep or work to adapt to the environmental change. The concerned problem is to dynamically determine a sufficient number of active nodes in the UASN at different times, such that the targets required to be detected are covered. A special static scenario of the problem has been shown to be NP-complete. Hence, this paper proposes an improved multi-population harmony search algorithm to solve this dynamic problem. By simulation, the proposed algorithm shows high performance in terms of extending network lifetime, robustness, and computing time.
KW - dynamic optimization
KW - harmony search algorithm
KW - multi-population
KW - Underwater acoustic sensor network
UR - http://www.scopus.com/inward/record.url?scp=84968547434&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2015.2440416
DO - 10.1109/JSEN.2015.2440416
M3 - Article
AN - SCOPUS:84968547434
VL - 16
SP - 4034
EP - 4042
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
IS - 11
M1 - 7116479
ER -