A Green and Reliable Internet of Things

doi:10.4236/cn.2013.51B011

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Communications and Network, 2013, 5, 44-48

doi:10.4236/cn.2013.51B011 Published Online February 2013 (http://www.scirp.org/journal/cn)

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

Email: [email protected], [email protected]

Received 2012

ABSTRACT

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

Architecture

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

S. S. PRASAD, C. KUMAR 45

sink

Node

Gate way

Wireless

Applica tionDomain

NetworkDomain

M2MNode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-

terns.

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

Communication

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.

S. S. PRASAD, C. KUMAR

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 :j∈NB(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

S. S. PRASAD, C. KUMAR 47

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

(1)

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-

ploration.

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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