Metadata-based measurements transmission verified by a Merkle Tree

Abstract

The Data Stream Processing Strategy (DSPS) is focused on the automatization of measurement projects based on a measurement framework. The measurement adapter (MA) is an architecture component located on mobile devices aims to integrate heterogeneous data sources (i.e., sensors). The Gathering Function (GF) is the component responsible for interacting and receiving measures from the MAs, and it resides on the Stream Processing Engine (SPE). MA and GF share the project definition based on a measurement framework to foster data interoperability, while MA regulates the frequency, size, and route related to data transmission. As contributions (i) The brief data message is introduced to optimize the data transmission keeping immutable the hierarchical data organization based on the project definition, and (ii) The integrity record for mobile and SPE environments is described based on a Merkle Tree. This allows optimizing each data transaction, incorporating a historical integrity record both MA and SPE. The proposals and simulations have been implemented on the cincamimis, cincamipd, mair, and pabmmcommons libraries, which are freely available on GitHub under the terms of the Apache 2.0 licence. Four simulations are explained to detail how to measures were obtained. Interesting results show that the brief data message consumes 17.50 KB to transmit 1000 measures (2.4 times smaller than JSON), while a message with 200 measures could be generated and compressed using GZIP in 25.12 ms (2.43 times faster than JSON). 196 KB is required to keep 17 min of the integrity history in a MA, being created in 4.85 ms.