Datalink streaming in wireless sensor networks

Abstract

Datalink layer framing in wireless sensor networks usually faces a trade-off between large frame sizes for high channel bandwidth utilization and small frame sizes for effective error recovery. Given the high error rates of intermote communications, TinyOS opts in favor of small frame sizes at the cost of extremely low channel bandwidth utilization. In this paper, we describe Seda: a streaming datalink layer that resolves the above dilemma by decoupling framing from error recovery. Seda treats the packets from the upper layer as a continuous stream of bytes. It breaks the data stream into blocks, and retransmits erroneous blocks only (as opposed to the entire erroneous frame). Consequently, the frame-error-rate (FER), the main factor that bounds the frame size in the current design, becomes irrelevant to error recovery. A frame can therefore be sufficiently large in great favor of high utilization of the wireless channel bandwidth, without compromising the effectiveness of error recovery. Meanwhile, the size of each block is configured according to the error characteristics of the wireless channel to optimize the performance of error recovery. Seda has been implemented as a new datalink layer in the TinyOS, and evaluated through both simulations and experiments in a testbed of 48 MicaZ motes. Our results show that, by increasing the TinyOS frame size from the default 29 bytes to 100 bytes (limited by the buffer space at MicaZ firmware), Seda improves the throughput around 25% under typical wireless channel conditions. Seda also reduces the retransmission traffic volume by more than 50%, compared to a frame-based retransmission scheme. Our analysis also exposes that future sensor motes should be equipped with radios with more packet buffer space on the radio firmware to achieve optimal utilization of the channel capacity.

ACR: Active Collision Recovery in Dense Wireless Sensor Networks

“…In order to exploit PCP in WSNs, an adaptive FEC scheme is proposed in [5] to help receivers recover such partial corrupted packets by sending packets with redundant bits. In [11], packets are divided into blocks, and each block is attached with CRC codes. When packets are corrupted, only erroneous blocks are retransmitted.…”

“…The size of blocks also depends on the method to identify erroneous blocks. As in [11], one extra byte of checksum is attached to each block for error detection. With smaller sizes of blocks, more blocks introduce more overhead.…”

Buffer Coding for Reliable Transmissions over Wireless Networks

“…The error model is therefore defined by a set of transition probabilities and the BER of the bad state. Equivalently, the interleaving good and bad states can also be characterized by the mean and standard deviation of the error cluster size and inter-cluster size, where the size is defined as the number of bits transmitted in each state [23].…”

“…To see the impact of coding distance in a real setting, we first assume that the size of the sender buffer is unbounded, and calculate the recovery probabilities of lost packets for the five loss models derived in Seda [23] based on real experiments (see table 2). …”

“…An optimal coding degree is then founded using Equation (2). If the potential performance gain is high enough, the new coding degree is applied (see line [18][19][20][21][22][23]. However, since the new coding degree is computed based on the theoretical model with several assumptions, and the measurements of the parameters may not be accurate enough, it is possible that the new degree is not better than the old one.…”