Statistical reliability for energy efficient data transport in wireless sensor networks

Abstract

Typical wireless sensor network deployments are expected to be in unattended terrains where link packet error rate may be as high as 70% and path length could be up to tens of hops. In coping with such harsh conditions, we introduce a new notion of statistical reliability to achieve a balance between data reliability and energy consumption. Under this new paradigm, the energy efficiency of a comprehensive set of statistically reliable data delivery protocols are analyzed. Based on the insight gained, we propose a hybrid system which combines the energy efficient and statistically reliable transport (eESRT) protocol with the implicit and explicit ARQ (ieARQ) protocol. This hybrid system adaptively switches between eESRT and ieARQ machanisms according to a dynamic hop threshold H_sw proposed in this work. Simulation and experiment results confirm our theoretical findings and demonstrate the advantages the hybrid system in boosting energy efficiency, reducing end to end delay, and in overcoming the ''avalanche'' effect.

Reliability Improved Cooperative Communication over Wireless Sensor Networks

“…Automatic Repeat-Request can improve reliability of data transmission compared with traditions scheme [32]. The main strategy of an ARQ protocol is as follows: once node transmits a data packet, it waits for an acknowledgement (ACK, a message sent by the receiver) indicating that its data packet was correctly received.…”

“…The sender does not send any additional packets until it receives an ACK signal or a timeout. In contrast, with GBN and SR, the nodes transmit packets continuously without the need to wait for individual ACKs from the receiver; only the ACK for the last packet is required [32]. In WSNs, an ACK could possibly be lost, which results in the transmitter resending a packet that was already successfully transmitted but an ACK was not received correctly or in time.…”

“…Additional ACK transmissions will not cause significant increases in energy consumption but can further improve the lifetime of the WSN [33]. The advantage of the retransmission-based mechanism is that it improves the network reliability at a low energy cost, so it is quite suitable for WSNs whose energy is extremely limited [4,32]. However, the unfavorable is that the network delay is usually long due to the repeat transmissions of data packets, especially in a link with high packet error rate [32] because the retransmission-based mechanism sends several data packets to the sink until the nodes receive ACK signals in response.…”

“…The advantage of the retransmission-based mechanism is that it improves the network reliability at a low energy cost, so it is quite suitable for WSNs whose energy is extremely limited [4,32]. However, the unfavorable is that the network delay is usually long due to the repeat transmissions of data packets, especially in a link with high packet error rate [32] because the retransmission-based mechanism sends several data packets to the sink until the nodes receive ACK signals in response. If the ACK is dropped, nodes cannot receive the ACK and will send data packets to the sink, thereby increasing the transmission delay.…”

A Survey on Modeling and Enhancing Reliability of Wireless Sensor Network

“…Nodes in WSNs are prone to be failure due to energy depletion, hardware failure, communication link errors, malicious attack etc [6] can be tolerated by hardware and software redundancy, which in turn improves the inherent reliability, and information redundancy and time redundancy will improve the operational redundancy. In general statistical reliability with level β [8] of WSN is a QoS (Quality of Service) level where during every predetermined time window, a predetermined size of random sensed data are delivered to the sink node from every source, each with a probability of at least β. But studying the characteristics, and considering constraints of WSN, it is understood that the overall reliability depends on many aspects spans from reliable sensing to receiving information in the sink and application underlying.…”