Adaptive-Compression Based Congestion Control Technique for Wireless Sensor Networks

Abstract

Congestion in a wireless sensor network causes an increase in the amount of data loss and delays in data transmission. In this paper, we propose a new congestion control technique (ACT, Adaptive Compression-based congestion control Technique) based on an adaptive compression scheme for packet reduction in case of congestion. The compression techniques used in the ACT are Discrete Wavelet Transform (DWT), Adaptive Differential Pulse Code Modulation (ADPCM), and Run-Length Coding (RLC). The ACT first transforms the data from the time domain to the frequency domain, reduces the range of data by using ADPCM, and then reduces the number of packets with the help of RLC before transferring the data to the source node. It introduces the DWT for priority-based congestion control because the DWT classifies the data into four groups with different frequencies. The ACT assigns priorities to these data groups in an inverse proportion to the respective frequencies of the data groups and defines the quantization step size of ADPCM in an inverse proportion to the priorities. RLC generates a smaller number of packets for a data group with a low priority. In the relaying node, the ACT reduces the amount of packets by increasing the quantization step size of ADPCM in case of congestion. Moreover, in order to facilitate the back pressure, the queue is controlled adaptively according to the congestion state. We experimentally demonstrate that the ACT increases the network efficiency and guarantees fairness to sensor nodes, as compared with the existing methods. Moreover, it exhibits a very high ratio of the available data in the sink.

Compression in wireless sensor networks

“…when the statistics of the data do not change with time. In contrast, adaptive or dynamic compression methods monitor the raw data statistics and modify their operation and/or parameters in order to improve performance [Lee and Jung 2010]. This approach is more complex but provides better performance for non-stationary data.…”

Delay-aware DWT-based image transmission in wireless visual sensor networks

“…The idea is that intermediate nodes may silently drop low relevant packets according to the current energy level of the node and the relevance of the packets' payloads, saving energy with some quality loss of the received images. In [19], authors exploit DWT coding to reduce the total amount of information to be transmitted by source nodes when transmission paths face congestion. The relevancies of DWT subbands are considered by intermediate nodes when deciding if packets must be silently dropped, where low relevant packets are the first to be dropped.…”

Congestion Prediction and Adaptive Rate Adjustment Technique for Wireless Sensor Networks

“…Joa-Hyoung Lee and In-Bum Jung [12] have proposed a new congestion control technique, named ACT. Their scheme is proposed based on an adaptive compression scheme for packet reduction in case of congestion.…”