Edge Computing of Online Bounded-Error Query for Energy-Efficient IoT Sensors

Since the power of transmitting one-bit data is higher than that of computing one thousand lines of code in IoT (Internet of Things) applications, it is very important to reduce communication costs to save battery power and prolong system lifetime. In IoT sensors, the transformation of physical phenomena to data is usually with distortion (bounded-error tolerance). It introduces bounded-error data in IoT applications according to their required QoS² (quality-of-sensor service) or QoD (quality-of-decision making). In our previous work, we proposed a bounded-error data compression scheme called BESDC (Bounded-Error-pruned Sensor Data Compression) to reduce the point-to-point communication cost of WSNs (wireless sensor networks). Based on BESDC, this paper proposes an online bounded-error query (OBEQ) scheme with edge computing to handle the entire online query process. We propose a query filter scheme to reduce the query commands, which will inform WSN to return unnecessary queried data. It not only satisfies the QoS²/QoD requirements, but also reduces the communication cost to request sensing data. Our experiments use real data of WSN to demonstrate the query performance. Results show that an OBEQ with a query filter can reduce up to 88% of the communication cost when compared with the traditional online query process.