TY - JOUR
T1 - Green partial packet recovery in wireless sensor networks
AU - Daghistani, Anas H.
AU - Ben Khalifa, Abderrahman
AU - Showail, Ahmad
AU - Shihada, Basem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2015/8/18
Y1 - 2015/8/18
N2 - Partial packet recovery is well known for increasing network throughput and reducing frame retransmissions. However, partial packet recovery methods in the literature are not energy-aware and hence they are not suitable for the battery powered wireless sensor motes. We propose Green-Frag, a novel adaptive partial packet recovery mechanism that is energy friendly. It can help prolonging the battery life of wireless sensor motes that are usually resource constrained. It dynamically partitions the frame into smaller blocks to avoid dropping the whole frame due to a single bit error. Also, Green-Frag is able to tolerate high interference and save energy by varying the transmit power based on channel quality and interference pattern. We experimentally evaluate the energy efficiency as well as goodput and delay of Green-Frag using our TelosB sensor mote testbed. We find that Green-Frag reduces energy consumption by 33% on average compared to the state of the art partial packet recovery scheme in the literature in the presence of Wi-Fi interference. In the worst case, this reduction in energy consumption comes at the cost of 10% reduction in goodput. Finally, Green-Frag reduces the latency by 22% on average compared to other static frame fragmentation schemes.
AB - Partial packet recovery is well known for increasing network throughput and reducing frame retransmissions. However, partial packet recovery methods in the literature are not energy-aware and hence they are not suitable for the battery powered wireless sensor motes. We propose Green-Frag, a novel adaptive partial packet recovery mechanism that is energy friendly. It can help prolonging the battery life of wireless sensor motes that are usually resource constrained. It dynamically partitions the frame into smaller blocks to avoid dropping the whole frame due to a single bit error. Also, Green-Frag is able to tolerate high interference and save energy by varying the transmit power based on channel quality and interference pattern. We experimentally evaluate the energy efficiency as well as goodput and delay of Green-Frag using our TelosB sensor mote testbed. We find that Green-Frag reduces energy consumption by 33% on average compared to the state of the art partial packet recovery scheme in the literature in the presence of Wi-Fi interference. In the worst case, this reduction in energy consumption comes at the cost of 10% reduction in goodput. Finally, Green-Frag reduces the latency by 22% on average compared to other static frame fragmentation schemes.
UR - http://hdl.handle.net/10754/575500
UR - http://linkinghub.elsevier.com/retrieve/pii/S1084804515001915
UR - http://www.scopus.com/inward/record.url?scp=84940062992&partnerID=8YFLogxK
U2 - 10.1016/j.jnca.2015.08.006
DO - 10.1016/j.jnca.2015.08.006
M3 - Article
SN - 1084-8045
VL - 58
SP - 267
EP - 279
JO - Journal of Network and Computer Applications
JF - Journal of Network and Computer Applications
ER -