Internet of nano-things healthcare applications: Requirements, opportunities, and challenges

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Internet of Nano-Things Healthcare Applications:
Requirements, Opportunities, and Challenges
Najah Abu Ali
Faculty of Information Technology
United Arab Emirates University
Al Ain, UAE
najah@uaeu.ac.ae
Mervat Abu-Elkheir
Faculty of Computer and Information Sciences
Mansoura University
Mansoura, Egypt
mfahmy78@mans.edu.eg
Abstract—Ubiquitous healthcare is becoming a reality thanks
to the advances in sensing and communication technologies, which
make it possible to provide monitoring and diagnosis services
outside the premises of healthcare providers. The Internet of
Things (IoT) is the main paradigm through which medical devices
will be connected to the Internet, thereby empowering near-real-
time health services and transforming a patient’s physical space
into a smart space. Recent developments in nanotechnology are
giving rise to the Internet of Nano-Things, with a new set of fine-
grained and highly sophisticated healthcare applications that can
be run inside the human body. In this paper, we outline a vision of
the ubiquitous healthcare ecosystem and its architectural
requirements in order to incorporate nanonetworks. We identify
some of the envisioned IoNT healthcare applications and the IoNT
requirements that are necessary to support the different
application categories, as well as the underlying healthcare service
opportunities. In order to understand the current status of
implementation, we provide a brief analysis of the major efforts
targeted at IoNT performance analysis and evaluation. We finally
discuss the most pressing challenges that the IoNT paradigm poses
for healthcare applications and services.
Keywords— Internet of Nano-Things; healthcare applications;
nanonetworks.
I. INTRODUCTION
Recent advances in wireless communication and networking
paradigms made it possible to envision and design innovative
healthcare services that were not feasible before. Body area
networks (BANs) can support the near-real-time sensing and
reporting of patients’ vital signs and health conditions [1].
Mobile health (mHealth) and wearable health systems can
support the provision of health services through smartphones as
well as mobile and wearable devices [2]. Environmental sensor
networks can provide alerts related to environmental elements
that are related to health. The integration and collaboration
between the different smart devices and the sensor networks,
which is the backbone of the Internet of Things (IoT), is
projected to provide more sophisticated and integrated health
services. However, the medical applications that are currently
enabled and supported by the aforementioned networking
paradigms are still bound to basic health monitoring and
reporting, assisted and ambient living, and offline diagnostics.
Furthermore, those networking paradigms have limited
deployment options because of the underlying health concerns
and precautions that must be taken into consideration. In order
to bring health and medical services to the next level and provide
sophisticated and fine-grained applications, we need networking
paradigms with design primitives that facilitate seamless and
noninvasive deployment in different contexts; a human’s
environment, on the human body, and inside the human body.
Bolstered by the breakthroughs that are being made in
nanotechnology, a novel networking paradigm that promises to
extend medical applications beyond basic monitoring, is
nanonetworks [3]. Example applications that can be supported
by nanonetworks are smart drug administration, nanoscale
surgeries, and epidemic spread detection and management. The
principal structural unit in a nanonetwork is the nanomachines
or nano-devices, which are devices that have a size scale ranging
from one to a few hundred nanometers. Nanomachines can
perform sensing and actuation, and report biological data to
other nano-devices called nano-routers, which act as data sinks
that will forward data to a micro-device, a smartphone, or an
access point. Multiple nanonetworks can be deployed inside the
human body to perform specialized tasks. Two main
technologies are envisioned to enable the nano-devices to
communicate with each other: molecular communication and
Terahertz electromagnetic communication. Molecular
communication involves releasing and reacting to specific
molecules to mirror the transmission and reception of
information. This communication mode can be easily integrated
into nano-devices due to their size and domain of operation.
Nano-electromagnetic communication involves the
transmission and reception of electromagnetic radio frequency
waves at the Terahertz band. The nanomaterials that will be used
for antenna design will determine the bandwidth and the power
magnitude for a given input energy [4].
Due to their nanoscale size, nanomachines can be deployed
on a massive scale and in a non-invasive way, both inside
biological systems such as the human body and across a variety
of environmental contexts. However, the nanoscale imposes
severe restrictions on nanomachines, such as severely limited
energy and memory resources and limited communication
range, which translate to the ability to perform only simple
computations [4]. To extend the limited communication range,
nanonetworks can interconnect nanomachines and thus enable
cooperation and information sharing. However, the design of
communication technologies that empower such cooperation
and provide access to contexts that are otherwise challenging for
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standard sensing devices needs to be overhauled to account for
the different contexts and size scales and facilitate
interconnection of nanomachines to the Internet, in what is
becoming recognized as the Internet of Nano-Things (IoNT).
Recent work has called for the nanonetworks to rely solely on
molecular communication, coining the term Internet of Bio-
Nano-Things [5].
In this paper, we identify the architectural requirements
necessary for IoNT-based healthcare applications, and the
networking requirements entailed by those applications. Rather
than address specific applications, we provide a basic
classification of requirements which is linked to the generic
application functionalities supported by IoNT. We also highlight
the opportunities that can be realized for IoNT healthcare
applications. We discuss the IoNT implementation and
performance evaluation issues, especially those related to
deployment, communication, and co-existence with other
networking paradigms. We finally outline the major challenges
of realizing healthcare applications at the nanoscale in each of
the networking stack layers, as well as some general challenges.
This paper is organized as follows. Section II will provide a
general overview of the ubiquitous healthcare ecosystem and the
architectural requirements that will incorporate nanonetworks.
The IoNT projected healthcare applications and their
characteristics are highlighted in Section III. The current status
of performance analysis and evaluation is discussed in Section
IV. Section V outlines the IoNT networking requirements and
challenges that need to be addressed in order to realize novel
healthcare applications. Finally, Section VI concludes the paper.
II. HEALTHCARE ECOSYSTEM: ARCHITECTURAL
REQUIREMENTS
In order to provide a comprehensive and dynamic set of
services and applications for ubiquitous healthcare, the
fragmented technologies that support health services need to be
brought together in a holistic and integrated ecosystem. This is
essentially the IoT vision, in which multiple systems can
collaborate together in order to provide a service. Three main
networking paradigms are designed to provide various forms of
health services. Off-body networks are deployed within a
person’s context; home, vehicle, street, or hospital. These
networks can provide generic health and environment
monitoring services as well as support applications related to
ambient living. On-body networks are manifested in body area
networks and wearable devices that enable the mass
customization of health monitoring and alert applications, and
bring health services closer to the patient’s personal space.
Finally, intra-body networks are expected to be deployed at
different locations inside the human body, either as connected,
embedded smart monitoring devices, or as internetworked nano-
devices. Nanonetworks are expected to provide sensing health
services such as monitoring of the functions of a specific organ
or tissue, or actuation services such as smart drug delivery and
tissue engineering. However, the deployment of nanonetworks
will not be restricted to the human body. Nanonetworks can be
deployed on the patient’s body or within the patient’s external
contextual environment. A number of proposed systems already
deploy nanosensors in wearable garments [6] [7] or in mobile
phones [8]. This anticipated pervasive deployment of
internetworked nanomachines constitutes the vision of what is
now termed the Internet of Nano-Things.
The typical deployment of each of the networking paradigms
for health services follows a three-tier architecture, in which a
set of sensors and smart devices are connected to a gateway or
sink module that provides backhaul connection to the Internet.
Gateways can be WiFi access points that serve a certain location
in which a patient is located, or the patient’s own smartphone.
For nanonetworks, each nanomachine will be associated with a
nano-router, which will relay data to a designated gateway,
possibly deployed externally on the body. Data sensed and
collected by the sensors, smart devices, and nanomachines for a
patient are sent via the nearest gateway or via the patient’s
smartphone to servers residing on the premises of the healthcare
service provider with which the patient is associated. In the case
of sensors deployed by public entities, such as those that provide
environmental monitoring, data is sent to the servers owned by
these public entities.
The three-tier hierarchical deployment may work for BANs
and smart spaces, but nanonetworks deployment may not enjoy
the same fixed structure, and may instead exhibit random
behavior. Smart spaces and BANs usually involve static node
deployment, with no mobility issues and therefore no problems
in association with a network. Nanonetworks, on the other hand,
can move around the human body for certain health applications,
and therefore may need to be associated with a different nano-
router at different times. If nanonetworks are deployed for
environment monitoring, then wind movement will affect their
location, and therefore they may associate with different
gateways along their path. Furthermore, nanomachines have
severely limited communication range due to their size and the
communication technology they will use (molecular or
electromagnetic).
The limited communication range, in addition to the limited
processing capacity, dictates that IoNT maintain a multi-tiered,
dynamic, and opportunistic hierarchical architecture [9]. Aside
from the obvious hierarchy between the nanomachines and the
nano-router, nanomachines themselves can be further clustered
so that each group that serves a certain body area or a certain
purpose is managed by a cluster head that will handle data
propagation to the nano-router [4]. The hierarchy tree from
nanomachines to backend servers needs to be dynamic;
connectivity from nanomachines to cluster heads and from
cluster heads to gateways can change according to context and
availability. This way, nano-routers can opportunistically
connect to the nearest gateway in order to send data.
The different networking systems are usually isolated from
each other, with little seamless integration both on the
communication level and on the data level. This fragmentation
hinders the development of integrated and cutting edge health
services and applications, and leads to redundancy and
inconsistency of information at the respective systems that
receive and manage the data. To support ubiquitous healthcare,
the different networking systems involved in providing and
supporting health services need to be integrated at three levels:
the connectivity level, the data level, and the services level. On
the connectivity level, health networking systems can
opportunistically share gateways as their context changes. A
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BAN can use the patient’s smartphone to report health data, but
if the patient is driving their connected car, data can be
transmitted via the car’s transceiver. A nanonetwork deployed
inside the patient’s body can use different nano-routers
depending on its mobility pattern inside the body. On the data
level, data generated for the same patient by different
networking systems should be uniquely associated with that
patient, regardless of format, granularity, and context.
Redundancy and inconsistency of data should be kept at a
minimum, and data integration techniques should be deployed
where data is to be stored for further analysis, whether storage
takes place at the patient’s personal devices or at the healthcare
provider’s servers. On the services level, it should be possible to
perform service composition and orchestration of the services
provided by the different networking systems in order to build
more advanced services, instead of designing novel services
from scratch.
A generic architecture of the healthcare ecosystem is
illustrated in Fig. 1. Different nanonetwork clusters, both inside
the body and in the external environment, have cluster heads that
connect them to respective nano-routers. Nano-routers connect
nanonetworks to the nearest gateway, and the gateway can be an
access point, a smartphone, or a dedicated sink module that can
connect the network to a WiFi access point or smartphone.
Smartphones can perform basic analysis functionality to support
basic monitoring and alert services, as well as data aggregation
and data fusion for transmission to remote servers which can
perform more advanced data analysis. The three-level
integration of the different networking systems in an IoT/IoNT
system requires some form of coordination between different
networks deployed across a patient’s changing context, as well
coordination between networks/nanonetworks within the human
body, in order to perform cooperative tasks that may be required
by some healthcare applications, and correlate data collected
from the different networks. The IoT/IoNT network systems
will need to opportunistically share their resources in order to
facilitate constant connectivity to the backbone via a hierarchy
path that is optimized for the collective energy and processing
status of each network. This means that a unified interface
through which transmitted data is received and processed is
needed to facilitate such coordination and co-existence [3].
III. IONT-SUPPORTED HEALTHCARE APPLICATIONS
The main goals of nanoscale healthcare applications are to
diagnose, treat, monitor, and prevent health conditions and
diseases on the molecule, cell, or DNA level. Current healthcare
applications are implemented in two contextual domains: the
patient’s surrounding environment, and the patient’s body area.
Sensors and actuators can be installed in a patient’s surrounding
environment to monitor the patient’s daily activities and alert
healthcare providers and emergency units of abnormal changes
in patient activity behavior. Nanoscale healthcare applications
will serve certain therapeutic purposes. The nanonetworks can
periodically sense biological properties of the tissues or organs
they monitor and send readings to gateways. Nanonetworks can
also detect the presence of certain molecules, chemicals, or
viruses and send alerts. Detection can be more sophisticated and
focus on abnormalities in the tissues or organs being monitored,
such as indications of the onset of a heart attack. Nanonetworks
can be used to actively perform therapeutic actions inside the
body, such as administering medications, regenerative tissue
Fig. 1. Generic IoT/IoNT architecture for ubiquitous healthcare.
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engineering, and nanoscale or Intracellular surgery. There are
also applications that are enabled by the IoNT that are not
strictly related to health condition monitoring but contribute
indirectly to healthcare, such as bacteria detection in food
industries [10].
We categorize nanoscale healthcare applications and
services into three major domains based on the functionality
they need, whether it is monitoring, detection, or therapy. In
physiological signal monitoring or sensing (e.g. ECG
monitoring), applications center mainly on the capturing
periodical readings that reflect the status of a certain organ or
tissue, or the level of a certain chemical or substance in the blood
stream. Applications that involve detection of chemicals and
viruses, or detection of certain abnormalities in the functioning
of an organ or the composition of a tissue, usually require careful
design of thresholds and flags that will trigger alerts.
Deployment of nanonetworks that will serve detection
functionalities can take place inside the body as well as outside
in crowded spaces, such as hospitals and schools. This can help
with the detection of viral infections and how they spread, as
well as help support environmental monitoring of pollens,
allergens, and radiation. Nanosensor-integrated textiles were
used also to monitor driver alertness and detect when a driver is
experiencing drowsiness [11]. Therapeutic applications involve
the direct interaction with biological phenomena.
Nanomachines can respond to commands instructing them to
administer a certain drug, destroy tumors via tissue
reengineering, or restore the glucose feedback loop of diabetics.
A health service can be layered using any combination of the
three major functionalities discussed above. Detection of
abnormal phenomena may depend on the constant monitoring of
the biological systems that may exhibit these phenomena.
Therapy may be triggered upon the detection of a serious health
condition, without having to be physically present at a
healthcare facility. To better understand the requirements of the
different healthcare applications, we provide a preliminary
characterization of the founding functionalities for these
applications, summarized in Table I. Applications that will
incorporate detection and therapy elements will have to follow
stringent design principles when it comes to delay, data loss, and
reliability. However, they may not need a high level of
connectivity throughout the tiered hierarchy up to the servers
since they can be designed to support autonomous operation.
Analysis, especially for detection-based applications, will need
extensive resources, and therefore is better offloaded to servers.
This, however, will interfere will real-time requirements that are
mandatory for many detection-based applications. In this case,
real-time basic analysis at the gateway can be performed with a
lower level of accuracy for emergencies.
IV. PERFORMANCE EVALUATION OF IONT SYSTEMS
Even though nanonetworks are relatively a new field of
study, many simulation platforms exist to help evaluate the
performance of certain aspects of molecular communication,
such as NanoNS and N3Sim [12]. A High Level Architecture-
based simulator design was recently proposed to provide a
comprehensive and scalable platform for molecular
communication performance evaluation [13].
The only significant effort to build a simulator for a wireless
nanosensor network based on electromagnetic communication
is Nano-Sim [14]. The simulator models the three basic types of
nodes in a nanosensor network: nanomachines, nanorouters, and
nanointerfaces. Pulse-based communication protocols are
implemented for the PHY/MAC layer, and a routing protocol
based on selective forwarding is implemented at the network
layer. Major features are still missing from the simulator. There
are no robust channel models for in-body signal propagation,
and only transmission range information is used for channel
behavior modeling. It is not clear if efficient deployment
strategies that are driven by application needs and body shape as
opposed to network coverage are supported. Furthermore, there
is little support for mobility of nanomachines and routers as the
monitoring and sensing needs of the corresponding healthcare
applications evolve. In addition, integration with other types of
health monitoring networks that are deployed outside of the
body is not yet addressed.
In order to provide an accurate characterization of
electromagnetic wave propagation inside the body, design of 3D
tissue models that address tissue permittivity and heterogeneity
TABLE I. HEALTHCARE APPLICATION REQUIREMENTS FOR IONT.
Function
Example
Traffic
Volume
Reliability
Deployment
Connectivity
Nanonetwork
size
Latency
Mobility
Data Loss
Processing
/Analysis
Processing
Location
Monitoring
Vital signs
monitoring
Pathogens and
allergens
High
Medium
In-/on-
body/
environment
High
Large
Medium
Limited
Tolerant
Basic
End system
Detection
Detection of
cardio-
vascular
abnormalities
Detection of
drivers
drowsiness
Medium
High
In-/on-
body/
environment
Medium
Medium
Low
Moderate
Nontolerant
Advanced
Gateway/
end system
Therapy
Smart drug
delivery
Tissue
engineering
Low
High
In-body
Low to
Medium
Medium
Low
Moderate
to High
Nontolerant
Moderate
Localized
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are needed for accurate simulation of signal propagation and
path loss at the terahertz frequencies [15] [16].
The properties of ultrasound communication for
nanonetworks were evaluated via a simulation study with
detailed channel modeling and network protocols [17]. The
simulation study incorporates three components; a wave-level
component, a bit-level component, and a packet-level
component. The wave-level component is implemented in
Matlab and is based on acoustic propagation modeling tools.
The channel models produced by this component are fed to the
bit-level component, which analyzes the bit error rate (BER)
performance of transmission schemes over ultrasonic channels.
The resulting empirical models can be used by the packet-level
component, which can be based on NS2 or NS3 as well as any
discrete event-based simulator.
V. IONT HEALTH APPLICATION REQUIREMENTS,
OPPORTUNITIES, AND CHALLENGES
IoNT holds an exciting potential for advanced health
services and applications, and integration of IoNT with other
healthcare network systems and the IoT will expand the array of
services that can be provided to patients as well as healthcare
decision makers. For this potential to be realized, many
requirements that stem from IoNT’s unique features need to be
incorporated into its protocol design. Many design challenges
are still being investigated with no mature solutions. In the
following sections, we follow a networking layered approach to
identify and discuss the requirements and challenges of IoNT
healthcare applications and services.
1) The Application Layer
Application design for healthcare services needs to address
requirements for real-time, reliable, and context-aware
operation. The criticality of health services makes real-time or
near-real-time operation a fundamental requirement. However,
due to the unpredictable transmission medium and the very short
range of intra-body communication, random delay is to be
expected. In addition, the heterogeneous nature of
nanomachines because of their use for different medical
purposes inside the body will result in different data
representations and formats. Therefore, data fusion needs to be
optimal, dynamic, and delay-tolerant [9] for applications that
rely on the integration of diverse data sources. Applications that
involve periodic monitoring can be designed to operate on
sliding-window-based data aggregation in order to cater for
delay-tolerance. However, data aggregation and fusion are not
always suitable for healthcare applications, because of the real-
time requirements, and since many of those applications depend
on fine-grained variations in the temporal domain that are lost in
the aggregation/fusion process.
Context awareness is another challenging aspect for
nanonetworks. Networks deployed outside of the body can be
geographically tagged and can communicate with the external
environment in order to determine and update their context.
Nanonetworks deployed inside the human body need a
noninvasive mechanism to recognize their context, especially
for deployments that depend on node mobility. Furthermore,
applications need to coordinate multiple contexts for specific
services that can benefit from the integration of intra-body
networks and on-body networks as well as external networks.
For example, an on-body network can detect the change of
context for a patient and be alerted by an environmental network
about the presence of a certain allergen to which the patient is
sensitive. The intra-body network is then notified and the proper
drug is released in the body to control the allergic reaction.
2) The Transport Layer
Nanomachines suffer from unreliable transmission due to
the high level of biological noise [9]. However, the projected
dense deployment of nanomachines can make the nanonetwork
as a whole more reliable. Dense deployment will also make up
for the potential packet loss, since more nanomachines with the
same functionality can report the same data.
The nanoscale of the IoNT makes it impractical to have
individual network addresses for the individual nanomachines.
Instead, addressing can be cluster-based instead of node-based.
This makes it possible to address a group of nodes based on the
health functionality they perform or the biological organ or
phenomena they monitor [18].
One challenge that is not addressed in the literature is control
of congestion, especially in a dense nanomachines deployment
scenario. Although some techniques from electromagnetic
communication may be adapted for the Terahertz band, it is not
yet clear how congestion will be avoided in molecular
communication, since the molecules are the medium that carries
the information.
3) The Network Layer
The communication range for the IoNT systems is expected
to be between 1 cm and 1 m for terahertz-based communication
and 1 nm to 1 cm for molecular communication [18]. This means
that the transmission range is extremely limited, which makes
multi-hop communication and routing a critical aspect for
nanonetworks. Furthermore, the direction of a communication
route is not deterministic and is dependent on the drift velocity
of nanomachines inside the body, which can lead to
communication delay. Mobility of nanomachines can be utilized
for routing to reduce the delay incurred due to biological
propagation limitations. However, this will require efficient
schemes for multi-hop path creation and management.
The limited processing and storage capabilities of
nanomachines means that routing design should not assume that
nodes have knowledge about the network topology. Network
topology inside the body can be random and dynamic due to the
uncontrolled properties of the biological communication
medium. This also affects cooperation between nanomachines,
which needs to be kept at a minimum. Node mobility inside the
body and proximity-based opportunistic routing can be suitable
solutions. Topology information can be maintained by cluster
heads and gateways [9].
4) The MAC/PHY Layer
Three main requirements are needed by health application at
the PHY/MAC layer: a channel capacity that guarantees reliable
data delivery, an accurate channel model that accounts for the
unique biological transmission medium and its associated noise,
and efficient coding schemes that are resilient to errors.
Channel capacity is dependent on the end-to-end
communication path between the transmitter and the receiver.
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Since the transmission range for nanonetworks is severely
limited, dense deployment of nanomachines are required,
coupled with multi-hop communication support, in order to be
support reliable data delivery [3].
Channel models that incorporate path loss, thermal noise,
and channel capacity for both molecular and electromagnetic
nano-communication are needed [19]. For molecular
communication, the channel medium is the molecules, which
have to propagate through biological tissue and are subject to
Brownian motion [3]. This makes it challenging to predict how
the data will propagate through the biological channel. Since the
body is composed of 65% water, even EM radio frequency
propagation will be challenging to model. Ultrasonic
communication was proposed as a more reliable and already
operational paradigm to achieve internetworking of
nanomachines for intra-body communication [20]. Channel
characteristics for intra-body nanonetworks may vary with
health conditions and from person to person, so it is not clear
how this variation can be incorporated into channel modeling.
Efficient coding is affected by the ability to accurately
characterize and model the sources of error both in molecular
and electromagnetic communication. Coding at the nanoscale
needs to have extremely low complexity due to the limited
processing capacity of nanomachines [21].
VI. CONCLUDING REMARKS
The Internet of Nano-Things holds many promises for
ubiquitous healthcare, due to the relative ease of mass
deployment and the nanoscale operational mode. However, the
unique characteristics of nanoscale devices need to be
incorporated into the design of the network architecture, and the
challenges of nano-communication paradigms need to be
addressed in the networking protocols. The most pressing
challenges that the IoNT paradigm pose for healthcare
applications and services are the design of efficient information
dissemination and routing schemes, and the accurate channel
and signal propagation modeling for intra-body communication.
A bigger challenge is the seamless integration of IoNT with
current health-based IoT systems and networks, and the efficient
and dynamic orchestration of health services across the
heterogeneous networking and data governance domains.
ACKNOWLEDGEMENT
This work was made possible by NRF-UAEU grant
#31T005- from United Arab Emirates University, NRF.
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2015 The First International Workshop on Advances in Body-Centric Wireless Communications and Networks and Their
Applications
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