Communications and Network, 2013, 5, 44-48
doi:10.4236/cn.2013.51B011 Published Online February 2013 (
A Green and Reliable Internet of Things
Shyam Sundar Prasad1, Chanakya Kum ar2
1Deptment of ECE, National Institute of Technology, Jamshedpur, India
2Deptment of ECE, Sam Higginbottom Institute of Agriculture, Technology & Science, Allahabad, India
Received 2012
Internet of Things (IoT) is innovation in the field of Communication where a number of intelligent devices are involved
sharing information and making collaborative decision. IOT is going to be a market-changing force for a wide variety of
real-time monitoring applications, such as E-healthcare, homes automation system, environmental monitoring and in-
dustrial automation as it is supporting to a large number of characteristics and achieving better cost efficiency. This ar-
ticle explores the emerging IoT in terms of the potential Energy Efficiency Reliability (EER) issues. This paper dis-
cusses the potential EER barriers with examples and suggests remedies and techniques which are helpful in propelling
the development and deployment of IoT applications.
Keywords: Energy Efficiency Reliability; Internet of Things; Machine to Machine Communication
1. Introduction
Internet of Things is a new research in the field of Inter-
net. IoT is the advance version of Machine to Machine
(M2M) Communication, where each object connects
with another object, without human intervention.
In IoT, billions of objects can communicate, recognize
and respond without human intervention. IoT may be
explained with the following example: When a car goes
to a petrol pump station, it will refill petrol in the car. A
sensor at the pump will read the registration number of
the car, and pass the information to the credit card swap-
ping machine, which will deduct the amount for the pet-
rol filled, automatically. Similarly, plants in a field may
communicate to a sprinkler system, when they need to be
watered. A runner’s shoes may communicate time, speed
and distance to him or her. Current research projections
estimate that within 5-10 years, 100 billion devices will
be connected to the internet [1].
Previously, computers communicated via Electronic
Data Interchange (EDI). With the advent of internet, all
computers are now able to connect and communicate.
Their ability is not only limited to communication but
they can also control and monitor another device. Thus
devices start talking. With the revolution of wireless
communication, mobile devices can also be easily con-
nected. Evolution of Internet of Things has made it pos-
sible for objects to get information about their position in
the world, to interact with other objects, and to have ac-
cess to information for data gathered in their vicinity.
Internet of Things first started in the 1990s, with Indus-
trial automation systems. Slowly, internet and internet
protocols became widely used between embedded devices
and Back End Servers (BS). The vision behind Internet of
Things is that embedded devices, also called smart objects,
will universally become IP enabled with the help of IPV6.
Hence, they will also slowly become an integral part of
the internet. M2M serves as a base for IoT. The basic
components of internet of things are a node sensor and its
connection strategy – i.e. how this sensor will transfer
data to a collecting device. Gradually IoT will lead to all
objects surrounding us that are connected to the Internet
in some way or the other. Thus, Energy Efficiency Reli-
ability-EER becomes an issue of concern.
This paper technically discusses the energy efficiency
and reliability issues in emerging IoT communications,
and suggests introduction of efficient activity scheduling
schemes for providing an energy efficient and reliable
IoT communications environment.
2. Overview of IoT Communication
As shown in Figure 1, architecture of Internet of Things
consists of sensor nodes, network domain, and applica-
tion domains [2].
Sensor Node domain is same as M2M node domain in
M2M communication [2]. In the node domain, an area
network is potentially formed by a large number of IoT
nodes {N0, N1 …} and an IoT Gate Way (GW). Each
IoT node Ni is a very flexible and smart device equipped
with some specific sensing technology for real-time
monitoring. Once monitoring data are sensed, IoT nodes
Copyright © 2013 SciRes. CN
Gate way
Applica tionDomain
Figure 1. The structure of M2M communication.
will make intelligent decision and transmit the sensory
data packets to the GW in single-hop or multihop pat-
The Gateway GW is an integrated device. After col-
lecting the packets from nodes, it is able to intelligently
manage the packets and provide efficient paths for for-
warding these packets to the remote back-end server (BS)
via wired/wireless networks.
Network Network domain provides cost-effective and
reliable channels for transmitting sensory data packets
from the Sensor domain to the application domain.
Application domain is the last part of the architecture.
In the application domain, BS is the key component for
the whole IoT communication paradigm, which not only
forms the data integration point for storing all sensory
data from the IoT domain, but also provides these real-
time data to a variety of IoT applications for remote
monitoring management.
3. The EER Requirements in IoT
Despite the real –time application and lots of bene-
fits, research in M2M communication still in its in-
fancy and faces many technical challenges. These
challenges include M2M Architecture, M2M com-
munication’s Green issues, M2M cost effectiveness,
M2M reliability, M2M Privacy, Persistency, Secu-
rity [3].
Recently, much attention has been paid to the deploy-
ment of architecture and software challenges in M2M
communications not only from the IT industry but also
from academia [3].
However, the energy efficiency, reliability, and secu-
rity issues in M2M Communications have not been well
explored. According to a recent report on global carbon
emissions [4], information and communication technol-
ogy (ICT) accounts for 2–2.5 percent of all harmful
emissions, which is almost equal to the global aviation
industry. Therefore, to protect global environments,
green communication has been widely advocated for
achieving energy efficiency in communication networks.
All IoT communication systems may have unique fea-
tures in a rapidly growing environment, and they are
generally organized in an architecture similar to that
shown in Figure 2, with the following common charac-
teristic: a massive number of sensor nodes are deployed
in the IoT domain to collect useful monitoring data by
sensing technologies and real-time processes, and to
transmit sensory data to the BS in the application domain
without direct human intervention. This characteristic
can benefit users from fast growing IoT communications
in many promising applications; however, it also brings
new EER challenges.
To successfully deploy IoT communication systems
for the next generation, real-time monitoring applications
are required and Energy-efficiency and Reliability (EER)
requirements must be satisfied.
3.1. Efficient
Since a mass of Sensor nodes {N0, N1…} are deployed
in the IoT sensor domain, IoT communication should
focus on energy saving by optimizing sensor nodes-
sensing, processing, and transmissions, and ultimately
Figure 2. An example that node N0 may switch to sleep
mode because its sensing range is fully covered by the con-
nected neighbors N1… N4.
Copyright © 2013 SciRes. CN
prolong the lifetime of the whole IoT communication. In
addition, since the BS is also a power-con- suming com-
ponent in IoT communication, great efforts should also
be made on the BS to achieve environment friendly,
green IOT communication.
3.2. Reliability
Reliability is critical for Efficient IoT communication,
because unreliable sensing, processing, and transmission
can cause false monitoring data reports, long delays, and
even data loss, which would reduce people’s interest in
IoT communication. Therefore, the rapid growth of IoT
communication demands high reliability.
Now, let us discuss the EER issues in IoT communica-
tion by surveying several potentially useful solutions to
shed light on this research line.
4. Energy Efficiency in IoT Communication
IoT communication system is dependent upon the
massive sensor nodes to intelligently collect monitoring
data in the IoT domain. It is also dependent on the wired/
wireless network to relay the collected sensory data to
the BS in the network domain, and on the BS, to support
various IoT applications on the network in an application
domain. This is because a massive number of devices are
involved in IoT. The Energy Efficiency (green) becomes
a challenging issue especially in the IoT sensor domain.
IoT Communication dominates energy consumption.
Energy Efficiency can be increased by wisely adjusting
transmission power (to the minimal necessary level), and
carefully applying algorithms and distributing computing
techniques to design efficient communication protocols
(e.g., routing protocols) [5].
It can be further improved by activity scheduling, the
objective of which is to switch some nodes to low-power
operation (“sleeping”) mode so that only a subset of
connected nodes remain active while the functionality
(e.g., sensing and data gathering) of the original network
is preserved. In [6] an activity scheduling scheme is pro-
posed for sensing coverage, which appears to be the best
in the literature. This scheme requires time to be slotted,
and activity scheduling is then done in rounds. In each
round, a node selects a random timeout and listens to
messages from neighbors before it expires. These mes-
sages contain the activity decision (i.e., whether to be
active or not) of their senders.
When the timeout expires, which is solely based on the
received information, the node makes its own activity
decision and announces it to the neighbors by transmit-
ting a message. A node decides to be active if its sensing
range (coverage circle) is fully covered by the sensing
ranges of a connected set of active neighbors.
The decision on full coverage is in turn grounded on a
well-known geometric theorem (illustrated in Figure 2,
together with the connectivity consideration): if there are
at least two coverage circles, and any intersection point
of the two circles inside the sensing area is covered by a
third coverage circle, the sensing area is fully covered.
Some nodes may have announced themselves as active,
and later, after receiving new announcements from
neighbors, find that they are fully covered. In this case,
they may change their previous decisions and enter sleep
mode after announcing their new decisions.
The scheme involves local communication only and
generates a very small number of control messages, thus
being Energy Efficient. Simulations based on ideal and
realistic physical layers reveal its advantages over other
similar algorithms. Therefore, the scheme can be applied
to achieve Green communication in the IOT domain.
5. Reliability in IoT Communication
For achieving Green IoT, since not all sensor nodes are
expected to simultaneously be active in the IoT domain,
Reliability is a challenging issue. In order to improve the
Reliability of IoT communication, exploiting redundancy
technologies, including information redundancy, spatial
redundancy, and temporal redundancy, can be an effi-
cient approach for IoT communication. Below, let us
discuss three major Reliability issues in IoT communica-
tion with different redundancy technologies.
6. Reliability in Sensing and Processing
Due to component faults and so on, a single IoT node
may not be sufficient to accurately sense and process
monitoring data. Therefore, a majority vote in green IoT
communication is desirable to improve reliability. In [7],
a local vote decision fusion (LVDF) algorithm is pre-
sented, which can be directly applied in IoT communica-
tion. In LVDF, each IoT node Ni first independently
senses, processes, and makes an initial single-bit decision
di {0, 1} on some event in a specific IoT application,
and shares the decision di with its neighbors NB(i). Giv-
en a set of decisions {di :jNB(i)}, node Ni adjusts ini-
tial decision di zi{0, 1} based on the majority vot-
ing strategy. In the end, all updated decisions zi are
communicated to the GW, which again uses majority
voting to make a decision based on zi. Since LVDF is a
corrected decision strategy, it can improve the sensing
and processing reliability in IoT communication with
additional information and temporal redundancy.
7. Reliability in Transmission
Consider that there are n total positive monitoring data
on the same event in the IoT domain, and the GW will
report the decision to the BS only if it can collect more
Copyright © 2013 SciRes. CN
than k distinct monitoring data packets. These positive
monitoring data can first be aggregated and then for-
warded to the GW together for achieving communication
efficiency. However, in green IoT communication, not
all nodes are active, which may result in unreliable
transmission in the IoT domain.
To improve transmission reliability, spatial redun-
dancy technology can be adopted [7]. Specifically, each
monitoring data packet is independently transmitted to
the GW. Assume that each transmission has an equal
transmission reliability p in the IOT domain, where 0 < p
1. Then the reliability of more than k out of n packets
can reach the GW for making the correct decision,
. Obviously, at the cost of re-
dundant transmissions, the reliability in this strategy is
higher than that in the aggregation transmission.
8. Reliability at BS
The BS receives sensory and decisional data packets
from the GW. These are processed one by one in the ap-
plication domain and only one server is used to process
them as this saves energy (power). But when there is
considerable increase in the data packets, which may
happen during peak hours, one single server is not ade-
quate to deal with the situation. In such a case, reliability
and QoS degrade. Therefore, to solve this issue a pair of
servers, i.e. a primary and secondary server is deployed
at the application domain. (Shown in Figure 3) So, when
there are a large number of data packets, the second
server will automatically be activated [2].
We model both the primary and second servers as
M/M/1 queuing systems, where the means of service
time are 1/µp and 1/µs, respectively. Let λ be the arrival
rate at the BS. If λ is small, all packets will be served by
the primary server for energy saving. However, when λ
Figure 3. The deployments of primary and second servers
to achieve reliability [2].
increases, a fraction λ, where0 α <λ, of the packets will
be served by the second server, and the rest, 1–α packets,
will still be served by the primary server for guaranteeing
the QoS in terms of average service delay. Therefore, the
total average delay can be expressed as
where and
By calculating the derivative
We have
which indicates that, all packets are served by the pri-
mary server; when the second server will be adaptively
active, and serve a fraction α of packets. Therefore, the
reliability issues in IOT communication can be addressed
by redundancy technologies; however, they will incur
additional redundancy costs. How to balance greenness
and reliability in IOT communication needs further ex-
To transfer secure data with reliability and efficiently is
an important issue for IOT communication. To achieve
this there are many research paper has been published
-for example by using the optimal allocation method of
the message shares onto multiple paths in terms of secu-
rity, and the multipath discovery techniques in a mobile
ad hoc network [8].
9. Conclusions
In this article, we have studied the issues to achieve
green IoT communication by employing efficient activity
scheduling techniques for energy saving. We have also
offered several approaches to address the reliability is-
sues in IoT. Although we have discussed the EER issues
in the general IoT paradigm to shed light on this research
line, further efforts are needed to identify the EER issues
in specific IoT communication contexts.
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