Data transmission reduction formalization for cloud offloading-based IoT systems

Abstract

Computation offloading is the solution for IoT devices of limited resources and high-cost processing requirements. However, the network related issues such as latency and bandwidth consumption need to be considered. Data transmission reduction is one of the solutions aiming to solve network related problems by reducing the amount of data transmitted. In this paper, we propose a generalized formal data transmission reduction model independent of the system and the data type. This formalization is based on two main ideas: 1) Not sending data until a significant change occurs, 2) Sending a lighter size entity permitting the cloud to deduct the data captured by the IoT device without actually receiving it. This paper includes the mathematical representation of the model, general evaluation metrics formulas as well as detailed projections on real world use cases.

Towards Information Flows in Recognition and Prediction Tasks with Internet of Things

“…In the middle of systems, communication can also occur between different interfaces or parts by analogy, as it can be implemented in technological processes [5]. In the context of the Internet of Things [6,7], we considered reducing the load on cloud services through data grouping. This may mean that, in general, the concept of information flows and their interaction in the system occupies an integral part of effective functioning.…”