Internet of Things (IoT) integrates diverse types of sensors, mobiles and other technologies to physical world and IoT technology is used in a wide range of applications. Compressive sensing based in-network compression is an efficient technique to reduce communication cost and accurately recover sensory data at the base station. In this paper, we investigate how compressive sensing can be combined with routing protocols for energy efficient data gathering in IoT-based wireless sensor networks. We propose a new compressive sensing routing scheme that includes the following new algorithms: (1) seed estimation algorithm to find the best measurement matrix by selecting the best-estimated seed, (2) chain construction algorithm to organize the network nodes during transmitting and receiving process, (3) compression approach to reduce the energy consumption and prolong the network lifetime by reducing the local data traffic, and (4) reconstruction algorithm to reconstruct the original data with minimum reconstruction error. The simulation results reveal that the proposed scheme outperforms existing baseline algorithms in terms of energy consumption, network lifetime and reconstruction error.

物联网（IoT）将各种类型的传感器，移动设备和其他技术集成到物理世界中，并且IoT技术被广泛应用于各种应用中。基于压缩感测的网络内压缩是一种有效的技术，可降低通信成本并准确恢复基站的传感数据。在本文中，我们研究了如何将压缩感测与路由协议相结合，以在基于IoT的无线传感器网络中收集节能数据。我们提出了一种新的压缩感知路由方案，该方案包括以下新算法：（1）种子估计算法，通过选择最佳估计种子来找到最佳测量矩阵；（2）链构建算法，以在发送和接收期间组织网络节点处理，（3）压缩方法通过减少本地数据流量来减少能耗并延长网络寿命，以及（4）重构算法以最小的重构误差重构原始数据。仿真结果表明，该方案在能耗，网络寿命和重构误差方面均优于现有的基线算法。