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An Energy-Efficient Object Tracking Algorithm in Sensor Networks

机译:传感器网络中的一种节能对象跟踪算法

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Object tracking needs to meet certain real-time and precision constraints, while limited power and storage of sensors issue challenges for it. This paper proposes an energy efficient tracking algorithm (EETA) that reduces energy consumption in sensor network by introducing an event-driven sleep scheduling mechanism. EETA gives tradeoffs between real time and energy efficiency by making a maximum number of sensor nodes outside tracing area stay asleep. EETA reduces the computation complexity on sensors to O(N) by formulating the location predication of an object as a state estimation problem of sensor node, instead of building a complex model of its trajectory. EETA locates the object using modified weighted centroid algorithm with the complexity of O(N). We evaluate our method with a network of 64 sensor nodes, as well as an analytical probabilistic model. The analytical and experimental results demonstrate the effectiveness of proposed methods.
机译:对象跟踪需要满足一定的实时性和精度约束,而有限的功率和传感器的存储为此提出了挑战。本文提出了一种节能跟踪算法(EETA),该算法通过引入事件驱动的睡眠调度机制来减少传感器网络中的能耗。 EETA通过使跟踪区域外的最大数量的传感器节点处于休眠状态,从而在实时性和能源效率之间进行权衡。 EETA通过将对象的位置预测公式化为传感器节点的状态估计问题,而不是建立其轨迹的复杂模型,将传感器的计算复杂度降低到O(N)。 EETA使用改进的加权质心算法以O(N)的复杂度来定位对象。我们通过一个由64个传感器节点组成的网络以及一个分析概率模型来评估我们的方法。分析和实验结果证明了所提出方法的有效性。

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