## Adaptive-Compression Based Congestion Control Technique for Wireless Sensor Networks  
**[PERSON] and [PERSON] *  
Department of Computer Science and Engineering, Kangwon National University, Chuncheon,  
Gangwondo, 200-701, Korea; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel. : +82-33-241-9793; Fax: +82-33-252-6390. _Received: 27 January 2010; in revised form: 22 February 2010 / Accepted: 16 March 2010 / Published: 29 March 2010_  
**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. Conventional congestion control protocols usually use a back-pressure scheme, which reduces congestion by reducing the transfer rate of child nodes of a congested node and by decreasing the packet generation rate of a sensor node that causes heavy traffic. However, packet drops might still occur because the back pressure is propagated slowly due to the collision among sensor nodes in case of serious congestion. Slow propagation of the back pressure may also cause fluctuation in packet flows because network state changes frequently with the back pressure. Moreover, a decrease in the packet generation rate leads to a reduction in the fidelity of an event because heavy traffic is generated by a sensor node that detects the specified event. Figure 1 shows the problem of congestion control with the back pressure [17-35]. In order to reduce congestion, the routing protocol should reduce the number of packets in the network; however, simply dropping overflowed packets will reduce the data fidelity and increase the energy dissipation. 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. 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 the data with the help of ADPCM, and then reduces the number of packets by means of RLC before transferring the data to the source node. It then introduces the DWT for priority-based congestion control because the DWT classifies the data into four groups with different frequencies.