Optimizing evaluation patterns and data acquisition for stream analytics in resource-constrained wireless environments

Abstract

Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.