THE ROLE OF DEPENDABILITY IN IOT SYSTEMS

Abstract

The advances in the Internet of Things (IoT) have contributed to the automation of various industries by enabling devices and systems to effectively connect and collect data remotely over the internet. This progress has led to the creation of an intelligent society where physical things are becoming increasingly innovative and undoubtedly, the IoT systems will continue to impact real life by providing efficient data collection and sharing. The successful implementation of IoT systems relies on their dependability, which is closely tied to several factors such as their reliability, resilience, and security. This paper explores the crucial role of dependability in IoT system, emphasizing challenges such as real-time analysis, resource constrains, connection redundancy, and quick fault recovery. The paper also provides some strategies for overcoming dependability challenges, such as efficient algorithms, edge computing, prioritization of resources, and AI techniques integration. Additionally, the paper presents a case study of an IoT system that faced dependability problems, highlighting the importance of rigorous testing and redundancy in ensuring reliable IoT deployments. As a result of this research, we suggest that by addressing the challenges related to dependability aspects, stakeholders can unlock the full potential of IoT, empowering industries and individuals with transformative, efficient, and reliable technologies. For future work, a frame work for evaluating and enhancing the IoT dependability will be developed. Several factors will be considered in developing this framework, such as reliability, availability, safety, security, resilience, and fault management. The framework will define a quantifiable metrics to measure these factors.

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THE ROLE OF DEPENDABILITY IN IOT SYSTEMS
Mohammad Ibraigheeth1*
1Department of Software Engineering, Bethlehem University, Bethlehem, Palestine
ABSTRACT
The advances in the Internet of Things (IoT) have contributed to the automation of various industries by
enabling devices and systems to effectively connect and collect data remotely over the internet. This progress has
led to the creation of an intelligent society where physical things are becoming increasingly innovative and
undoubtedly, the IoT systems will continue to impact real life by providing efficient data collection and sharing.
The successful implementation of IoT systems relies on their dependability, which is closely tied to several factors
such as their reliability, resilience, and security. This paper explores the crucial role of dependability in IoT
system, emphasizing challenges such as real-time analysis, resource constrains, connection redundancy, and quick
fault recovery. The paper also provides some strategies for overcoming dependability challenges, such as efficient
algorithms, edge computing, prioritization of resources, and AI techniques integration. Additionally, the paper
presents a case study of an IoT system that faced dependability problems, highlighting the importance of rigorous
testing and redundancy in ensuring reliable IoT deployments. As a result of this research, we suggest that by
addressing the challenges related to dependability aspects, stakeholders can unlock the full potential of IoT,
empowering industries and individuals with transformative, efficient, and reliable technologies. For future work,
a frame work for evaluating and enhancing the IoT dependability will be developed. Several factors will be
considered in developing this framework, such as reliability, availability, safety, security, resilience, and fault
management. The framework will define a quantifiable metrics to measure these factors.
Keywords: internet of things (IoT), dependability, reliability, resource constrains, failure recovery.
1. INTRODUCTION
Nowadays, the rapid advancement of smart sensor
applications enables objects or things in various fields of
our life to be addressed, connected, and to collect data
about the environment around them. In this context, the
“Internet of Things” (IoT) is a paradigm that emerged to
manage and organize practical and technical issues [1].
Therefore, IoT deals with different technologies and
protocols, such as Internet, mobile communication, and
wireless sensor protocols [2]. The evolution of IoT has
led to use this paradigm by different applications such as
smart home, smart payment, smart lighting, fire detection,
monitoring safety, and many other fields [3]. Central to
the successful implementation and widespread adoption of
IoT systems is the concept of dependability [4].
Dependability in general is a combination of several
attributes such as reliability, availability, security,
confidentiality, and resilience. Having these attributes
enables a user to put trust into and rely on a system [5].
The dependability of an IoT device refers to ability of this
device to consistently deliver trusted, accurate and
reliable data, while maintaining the integrity and security
of data in the face of various challenges and uncertainties.
In IoT, dealing with vulnerabilities of a huge number of
heterogeneous devices is a challenge [6,7]. Enhancing
dependability enables IoT system to handle several
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challenges.
A way to realize dependability requirements in IoT
systems is by using fog computing [8,9]. Fog computing
enables real-time data processing and analysis at the
edge [10], which mean that the massive volume of data
generated by IoT devices can be processed and analyzed
locally and closer to the source of this data (network
edges) rather than sending data to centralized cloud or
data center. This reduces the data transmission and
allows faster decision-making at the edge, enhancing the
overall performance of IoT system [11]. Fog computing
provides a platform that supports data communication
between users, IoT devices and data centers, as well as
storage and processing devices. Therefore, a fog-based
IoT system can has dependability challenges, such as
managing data flow of IoT devices, memory limitation
and power constrains [12].
This paper studies the crucial rule of dependability
of IoT systems and its implications in different
applications. In the following sections, first some factors
that affect the IoT system's dependability will be
identified, then the challenges that can impact the
dependability as well as some solutions for overcoming
these challenges will be explored. Then a case study
related to IoT system that faced dependability problems
will be presented. Finally, a conclusion and future work
are described.
2. FACTORS AFFECTING
DEPENDABILITY IN IOT SYSTEMS
Dependability allows for continuity (uninterrupted)
of system services [13]. In other words, a dependable
system should provide mechanisms to tolerate any
condition throughout its life cycle. The dependability can
be achieved through different factors including
reliability, availability, safety and security, resilience,
fault management methods, scalability, and other factors
[14].
2.1 Reliability
We begin by considering the traditional IoT
architecture, characterized by centralized data processing
and decision-making. This framework emphasizes the
limitations of this approach, particularly in terms of
latency and scalability [1].
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System reliability is the probability that system will
behave as expected (without failure) over a given period
of time (t). The system reliability can be measured
through two metrics: mean time between failures
(MTBF) and mean time to failure (MTTF). The reliability
is measured by MTBF if the system has failure recovery
mechanism, while MTTF is used to measure the
reliability if there is no failure recovery mechanism [15].
Given R(t) is the reliability function of time:
󰇛󰇜   (1)
where λ=1/ MTBF if there is recovery mechanism,
otherwise λ=1/ MTTF.
Reliability is critical in IoT environment because
unreliable data collection, processing, and transmission
can cause long delay and data loss which can lead to a
loss of confidence in the IoT systems, and therefore
reliability is essential for the widespread of these systems
[16].
2.2 Availability
The availability attribute in IoT system is directly
related to reliability. The availability of an IoT system
can be defined as its ability to deliver the required
service as long as possible to ensure continuous
operation. There are methods that can help to keep the
system available, like maintaining a mechanism for faults
management [17], and apply some approaches to manage
hardware redundancy [18]. The availability can be
calculated as follows:
  
 (2)
where MTTF is mean time to failure, and MTTR is
mean time to repair.
2.3 Safety and Security
Safety and security are essential non-functional
requirements (NFR) for any IoT system and are
considered critical attributes for its dependability [19].
Safety is key attributes in IoT systems to prevent harm to
their users or to the IoT environment [20]. IoT's security
is related to avoiding security threats [21]. The two
attributes are both source of risks and there are affected by
each other [22]. Many IoT applications are integrated into
safety critical environment, such as smart transportation
and medical healthcare devices. It is essential to mitigate
potential risks associated with these situations. Similarly,

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security protection against unauthorized access and cyber-
attacks can help to preserve user privacy and sensitive
information
One of major requirements of an IoT system is that
safety and security issues are designed to support the
dependability of the system. Many attributes could affect
the safety and security of IoT systems, such as hardware
faults and, human errors, and security attacks [23]. These
impediments need to be identified and mitigated.
2.4 Resilience
Resilience is the property of preserving the system's
dependability when it encounters changes; thus, it is the
ability to deal with failure, predict, tolerate and prevent it
[24]. In an IoT system, the devices are connected through
a network, and resilience is responsible for keeping the
system connected regardless any failure that could affect
the network [25]. The IoT system must deal with some
constraints related to resources, such as network, memory
and battery constraints, to recover from faults and failures
as quickly as possible. Therefore, for the IoT system to be
resilient, it should provide a fault (and failure)
management mechanism. In addition, the system should
be survivable in which it should offer continuity
throughout managing and recovering the faults.
2.5 Fault and Failure Management
In IoT systems, a failure represents an unexpected
behavior, such as data loss due to network connection
problems or due memory overflow. To deal with faults,
there are four strategies: detection, prediction, mitigation
and prevention. Fault detection is the process of verifying
the unexpected behavior using various methods, such as
statistical machine learning methods [26], while fault
prediction applies different techniques to predict probable
failure, such as classification and regression techniques.
Fault mitigation aim to recover the IoT system from
failure, such as applying node load balancing [27] and
redundancy techniques [28]. Fault preventions aims to
prevent fault occurrence using different approach,
replicating data on more than one node.
2.6 Assuring Data Quality and integrity
In IoT system, the collected data should represent
the actual system context. For example, in an
environment such as Polar Regions, where the climate is
always cold, data from temperature sensors with a warm
temperature is likely wrong. Therefore, an IoT system
should previously know the context and related domain
to provide meaningful and trustworthy results that are
suitable for accurate decision -making [29].
2.7 Scalability
The IoT system should be scalable to accommodate
thousands or even millions of sensors in terms of data
transfer, storage, and real time processing [30]. The
scalable system needs to provide more computing
devices as well as the required hardware infrastructure
[31].
2.8 Heterogeneity
The IoT system includes different heterogeneous
devices that have different technologies and hardware
implementations [32]. The IoT system provides the
needed protocols to enable devices to communicate and
understand each other. Each communication protocol has
its own characteristics and application scenarios. For
example, low- power wide- area network (LPWAN)
technologies provide low power consumption and long
transmission ranges. Examples of LPWAN technologies:
Sigfox and NB-IoT [33]. Other examples of IoT
communications technologies are: Bluetooth [34], Z-
Wave [35], and Zigbee [36]. Furthermore, IEEE 802.11
standards can be adopted in an IoT environment for
devices with no battery constraints and for data
transmission over short distances [34].
3. CHALLENGES TO DEPENDABILITY
IN IOT SYSTEMS
This section presents some of most important
challenges of dependability in IoT systems:
3.1 Real-Time Analysis and Resource
Constrains
In the IoT environment, dealing with real-time
analysis and resource constrains is major challenge.
Real-time analysis involves processing data immediately
as it received from sensors without significant delay.
Furthermore, there is a need address resource constraints
such as limited availability of memory and power. IoT
devices may have limited resources compared to other
traditional devices, as they often designed to be small,
inexpensive, and power-efficient. As a result,
implementing complex real-time IoT system given some
resource constraints can be challenging.
Energy consumption is a major challenge, and more
research is needed to implement IoT systems with low
power consumption [38]. The IoT requires mechanism of
minimizing the power to be spent during the system
operation.

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3.2 Connection Redundancy
Connection redundancy is a crucial aspect of ensuring
dependable and continuous communication in IoT
deployments. The IoT system may involve numerous
interconnected devices with different data formats. IoT
nodes can be deployed with more than one communication
protocol [37]. Disconnections can be prevented using
monitoring mechanism that make automatic switching
between connection technologies. In other words, each
node can transmit and receive data using two or more
communication protocols and it can select a protocol with
better performance. However, in scenarios with huge
number of nodes and connection redundancy mechanisms,
it is challenge to deploy without the cost of hardware.
3.3 Quick Fault-Recovery
IoT system needs to detect and recover faults that may
occur in its components. It is critical to ensure that the
system can detect and recover from faults in real-time.
Faults can arise due to hardware failure, software error,
human error, or environmental factors.
4. STRATEGIES FOR OVERCOMING
IOT DEPENDABILITY CHALLENGES
Some strategies can help to overcome IoT
challenges. For example, using efficient and lightweight
algorithms can be used to optimize the computational
burden on IoT devices.
Other approach that can help to optimize IoT devices
communication is applying edge computing to perform
data processing near the IoT devices themselves, rather
than sending all data to centralized server. The edge
devices such as edge or gateway servers can perform data
analysis and filtering locally reducing the need for
continuous high-bandwidth communication.
Applying prioritization task mechanism allocate
resources based on tasks importance as well as scheduling
mechanisms that ensure critical tasks get the resources
promptly. Furthermore, enable the IoT system to
dynamically adjust resource allocation based on task
priority and available resources will help the system to
respond any changing condition
To overcome the limited-power challenges, it is
recommended to use hardware components that are
designed for low-power operational environment. For
example, using energy-efficient microcontrollers that
offer needed computational capabilities will help to
minimize power consumption during the IoT system
operation. Using energy harvesting techniques (such as
solar panels) to power IoT devices can help can help to
extend battery life or even eliminate the need for
batteries.
Using artificial intelligent (AI) techniques can play
vital role in enhancing IoT system dependability. AI
techniques can analyze massive amount of data, predict
probable failures, and detect security threats, aiding in
system optimization and predictive maintenance. Using
AI techniques can help in developing decision-making
system that can be used to enhance system reliability,
ensuring that IoT system can adapt to changes and
provide consistent performance.
By combining these strategies, many challenges can
be resolved, enabling a more robust and efficient IoT
system.
5. CASE STUDY: NEST THERMOSTAT
GLITCH
One example of an IoT system that faced problems
that affect its dependability is the "Nest Thermostat
Glitch" incident that occurred in January 2016 [39]. Nest
Labs, a company owned by Google, and specializing in
home automation and WiFi-enabled products that can
controlled remotely, such as smart thermostats, sensor-
driven and smoke detectors [40]. This company
experienced a service outage that impacted a large
number of their smart thermostats [41].
Nest's smart thermostats allow their users to
remotely control their home heating and cooling systems
through web service or mobile app. The smart thermostat
aims to provide personalized comfort to users and
optimized energy usage. This thermostat collects data
from sensors and use machine learning techniques to
adjust the temperature [42].
On January 13, 2016, an unexpected glitch
happened On Nest's servers during a scheduled
maintenance update. As a result of this glitch, many Nest
thermostats became inaccessible for users. Some
thermostats also provide wrong temperature readings,
causing problems in heating and cooling systems. This
accident affected the dependability of Nest thermostats
and led to user dissatisfaction and inconvenience as many
users were unable to control their thermostat, and the
wrong temperature reading caused energy inefficiency
and discomfort in their homes [41].
Nest engineers investigate and address the root

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cause of the glitch and developed solutions to prevent
occurring similar incident in the future to ensure the
dependability of their smart system. The nest lab
implemented more extensive testing procedures before
final deploying their final system. Additionally, they
improve the communication protocols to promptly
response to any incident and keep user updated related to
issues related to their service.
The Nest Thermostat Glitch incident illustrates how
even well-established IoT companies can face
dependability challenges. This incident showed the
importance of rigorous testing, quality assurance, and
redundancy in IoT systems. Furthermore, it highlights the
necessity of having backup solutions in place to ensure
reliable system functionality.
6. CONCLUSION AND FUTURE WORK
The role of dependability in IoT systems is essential
to ensure a reliable and secure system. Dependability
plays a critical role in building trust, ensuring safety, and
enabling the successful implementation of IoT solutions.
By addressing the challenges related to reliability,
resilience, security, and other dependability aspects,
stakeholders can unlock the full potential of IoT,
empowering industries and individuals with
transformative, efficient, and reliable technologies.
This paper identified factors affecting IoT system
dependability, including reliability, availability, safety,
security, resilience, fault management, data quality,
scalability, and heterogeneity. There are several
dependability challenges including real- time processing,
limited resources, continuous communication and quick
fault recovery. This paper addressed some strategies to
overcome these challenges and enhance the
dependability such as efficient algorithms, edge
computing, prioritization/ scheduling of resources, and
using AI techniques. This paper also identified one case
study that faced problems that affect its dependability,
which is the "Nest Thermostat Glitch" incident. This
incident showed how it is necessary to perform rigorous
testing, quality assurance, and redundancy before final
deployment of the IoT systems, and how it is important
to have backup solutions in place to ensure reliable
system functionality.
As future work, a framework to evaluate IoT
dependability can be developed. This framework should
consider several factors to assess the dependability of an
IoT system. The framework will define a quantifiable
metrics to measure different factors, such as reliability,
availability, safety, security, resilience, and fault
management. These metrics can be used for evaluating
the system's performance. By developing such
framework, the IoT system decision makers can assess
the dependability, and can take enhancing steps that will
lead to more reliable and successful IoT solutions.
In comparison to previous works in the realm of the
Internet of Things (IoT), our study delves into the
paramount role of dependability in IoT systems. While
past research has acknowledged the significance of some
factors such as reliability and security in IoT [20-23], our
paper extends the discussion to emphasize resilience,
real-time analysis, connection redundancy, and swift
fault recovery as critical factors influencing
dependability. We build upon existing literature by
proposing strategic solutions to overcome these
challenges, including the integration of efficient
algorithms, edge computing, resource prioritization, and
the incorporation of artificial intelligence techniques.
Notably, our work contributes a valuable case study
highlighting the practical implications of dependability
issues in an IoT system. This case underscores the
necessity for rigorous testing and redundancy measures
to ensure the reliability of IoT deployments, an aspect
that has not been extensively explored in prior studies.
Furthermore, we advocate for the development of a
comprehensive framework for evaluating and enhancing
IoT dependability in future work. This proposed
framework will consider a spectrum of factors including
reliability, availability, safety, security, resilience, and
fault management, providing quantifiable metrics for a
holistic assessment of IoT systems. Our research
contends that by addressing these dependability
challenges, stakeholders can unlock the full potential of
IoT, fostering transformative, efficient, and reliable
technologies for both industries and individuals.
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