Abstract:
The rapid evolution of the Internet of Things (IoT)
facilitates the development of IoT applications in domains such as
manufacturing, smart cities, retail, agriculture, etc. Such IoT applications collect data, analyze, and extract insightful information
to enable decision-making and actuation. There is an unprecedented growth of IoT applications that automate decision-making
and actuation without requiring human intervention, which we
term autonomic IoT applications. The increasing scale of such
applications necessitates holistic measurement and evaluation of
application quality. Existing literature has evaluated quality from
an end-user perspective, which may be unsuitable when dealing
with the complexity of modern IoT applications, especially when
they are autonomic. In this paper, we refer to IoT application
quality as the aggregate quantitative value of various IoT quality
metrics measured at each stage of the autonomic IoT application
life cycle. We present an in-depth survey of current state-ofthe-art techniques and approaches for evaluating quality of
IoT applications. In particular, we survey various definitions
to identify the factors that contribute to understanding and
evaluating quality in IoT. Furthermore, we present open issues
and identify future research directions towards realizing finegrained quality evaluation of IoT applications. We envision that
the identified research directions will, in turn, enable real-time
diagnostics of IoT applications and make them quality- aware.
This survey can serve as the basis for designing and developing
modern, resilient quality-aware autonomic IoT applications.
