Quality of Information in Wireless Sensor Networks: A Survey 1 (Completed paper)

Abstract: In Wireless Sensor Networks (WSNs) the operating conditions and/or user requirements are often desired to be evolvable, whether driven by changes of the monitored parameters or WSN properties of configuration, structure, communication capacities, node density, and energy among many others. While considering evolvability, delivering the required information with the specified quality (accuracy, timeliness, reliability etc) defined by the user constitutes a key objective of WSNs. Most existing research efforts handle fluctuations of operation conditions in order to deliver information with the highest possible specified quality. In this paper, we take these aspects into consideration and survey existing work on Quality of Information (QoI). As a contribution, we categorize WSN information into a set of abstract classes for generality across varied application types. Our survey shows that currently QoI is usually addressed in isolation by focusing on discrete data processing operations/building blocks such as raw data collection, in-network processing (compression, aggregation), information transport and sink operations for decision making. This survey comprehensively explains the different views of QoI on attributes, metrics and WSN functional operations mapped with existing approaches. The survey also forms the basis for specifying needed QoI research issues

A Generic Framework for Quality-based Autonomic Adaptation within Sensor-based Systems

With the growth of the Internet of Things (IoT), sensor-based systems deal with heterogeneous sources, which produce heterogeneous observations of disparate quality. Since network QoS is rarely sufficient to expertise Quality of Observation (QoO), managing such diversity at the application level is a very complex task and requires high levels of experience from application developers. Given this statement, this paper proposes a generic framework for QoO-based autonomic adaptation within sensor-based systems. An abstract architecture is first introduced, intended to bridge the gap between sensors capabilities and application needs thanks to the Autonomic Computing paradigm. Then, the framework is instantiated and practical considerations when implementing an autonomous sensor-based system are given. We illustrate this instantiation with concrete examples of sensor middlewares and IoT platforms