One of the basic challenges in wireless sensor networks is energy conservation. Sensor nodes are energy constrained and prudent energy usage is of utmost importance. Data aggregation aims to reduce amount of data communicated across the network without loss in information, thereby reducing the energy costs, and increasing network lifetime. In this paper, we propose a novel, simple and easy to implement method to reduce the amount of periodic data transferred from the sensor nodes to the sink. Instead of sending a set of measures at the end of every time period, we propose sending the first measure, and for every subsequent measure in that time period, we send the difference with respect to first measure. Differences are represented by a group of binary bits. Differences are also chosen in an adaptive manner in order to maintain precision between the data measured at sensor nodes and data reconstructed from binary bit patterns at sink. We evaluated our technique against two real world data-sets with vastly different properties. Results indicate 85–88.5% reduction in amount of data sent and transmission energy.

节能是无线传感器网络的基本挑战之一。传感器节点受能量限制，谨慎的能源使用至关重要。数据聚合的目的是减少在不损失信息的情况下跨网络传输的数据量，从而降低能源成本并延长网络寿命。在本文中，我们提出了一种新颖，简单且易于实现的方法，以减少从传感器节点传输到接收器的周期性数据量。我们建议不要发送每个时间段末尾的一组度量，而是发送第一个度量，然后针对该时间段内的每个后续度量，发送与第一个度量的差。差异由一组二进制位表示。还以自适应方式选择差异，以保持在传感器节点处测量的数据与从接收器中的二进制位模式重构的数据之间的精度。我们根据两个性质迥异的现实世界数据集评估了我们的技术。结果表明，发送的数据量和传输能量减少了85–88.5％。