A fundamental challenge in wireless networks is that radio links are subject to transmission power, fading, and interference, which degrade the data delivery performance. This challenge is exacerbated in wireless sensor networks (WSNs), where severe energy and resource constraints preclude the use of many sophisticated techniques that may be found in other wireless systems . Dynamic Packet Length Control in Wireless Sensor Networks In this paper, we consider a simple, cost-effective solution based on the technique of dynamic packet length control to improve the performance in these varying conditions. A tradeoff exists between the desire to reduce the header overhead by making packet large, and the need to reduce packet error rates (PER) in the noisy channel by using small packet length . Dynamic Packet Length Control in Wireless Sensor Networks Although there have been several studies on packet length optimizations in the literature , existing approaches usually require that a set of parameters to be carefully tuned such that it can better match the level of dynamics seen by any particular data trace. However, any fixed set of parameters will not adapt to the changing conditions since one parameter set does not fit all conditions. Furthermore, the update process would require user intervention, further data collection and Dynamic Packet Length Control in Wireless Sensor Networks reprogramming the parameters. This is precisely what we want to avoid in our case, and one of the strengths of using dynamic packet length optimization scheme. We design and implement DPLC based on TinyOS 2.1. The current implementation of DPLC Dynamic Packet Length Control in Wireless Sensor Networks on TelosB motes is lightweight. We evaluate DPLC in a testbed consisting of 20 TelosB nodes, running the CTP protocol, and compare its performance with a simple aggregation scheme and AIDA . Results show that DPLC achieves the best perform . The rest of this paper is structured as follows. Section II Dynamic Packet Length Control in Wireless Sensor Networks discusses related work. Section III describes the experimental observations that motivate our design. Section IV presents the design of DPLC. Section V presents an analysis the energy consumption and the convergence rate of DPLC. Section VI introduces the implementation details. Section VII shows the simulation results. Section VIII shows the evaluation results. Finally, Section IX concludes this paper.