Blockchain Based Multi-hop Routing and Cost-Effective Decentralized Storage System for Wireless Sensor Networks

Abstract

In Wireless Sensor Networks, nodes have resource constraints such as storage capacity, low energy, and computational power, etc. Due to which it directly affects the lifetime, security, and performance of WSN. Improved-Low energy adaptive clustering hierarchy (I- LEACH) is one of the most famous clustering protocols and is employed to maximize the lifetime of the WSN network. In this paper, a blockchain based multi-hop routing protocol and clustering in Wireless Sensor Networks (WSNs) have been proposed. In our proposed model, for cluster head (CH) selections, three parameters have been deployed for CH selection i.e., residual energy of the ordinary node (ON), distance of an ON from the base station (BS) and value of the packet delivery ratio (PDR). After selection of an ON as a CH, an Energy-Efficient Adhoc On-demand Distance Vector EEAODV based routing protocol is employed to send data from CH to the BS in an energy-efficient way. Cloud storage is used to store the credentials and other data. The simulation results show that our proposed I-LEACH protocol performs better than the benchmark ALEACH.

Full text

Vol.:(0123456789)
Wireless Personal Communications
https://doi.org/10.1007/s11277-023-10597-9
1 3
Blockchain Based Multi‑hop Routing andCost‑Effective
Decentralized Storage System forWireless Sensor Networks
MuhammadFaisal1· GhassanHusnain1
Accepted: 28 June 2023
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023
Abstract
In Wireless Sensor Networks, nodes have resource constraints such as storage capacity,
low energy, and computational power, etc. Due to which it directly affects the lifetime,
security, and performance of WSN. Improved-Low energy adaptive clustering hierarchy (I-
LEACH) is one of the most famous clustering protocols and is employed to maximize the
lifetime of the WSN network. In this paper, a blockchain based multi-hop routing protocol
and clustering in Wireless Sensor Networks (WSNs) have been proposed. In our proposed
model, for cluster head (CH) selections, three parameters have been deployed for CH selec-
tion i.e., residual energy of the ordinary node (ON), distance of an ON from the base sta-
tion (BS) and value of the packet delivery ratio (PDR). After selection of an ON as a CH,
an Energy-Efficient Adhoc On-demand Distance Vector EEAODV based routing protocol
is employed to send data from CH to the BS in an energy-efficient way. Cloud storage is
used to store the credentials and other data. The simulation results show that our proposed
I-LEACH protocol performs better than the benchmark ALEACH.
Keywords Blockchain· Wireless Sensor Network· Improved LEACH· EEAODV· Cloud
Storage
1 Introduction
The wireless sensor network is one of the dominant technologies of today [1]. It is self-
organized with no infrastructure to control the physical environment. The main purpose
of the WSN is to collect information from the physical world. Usually, we deployed WSN
networks in those areas where it is difficult for the wired-base network to work efficiently.
The monetary cost of sensor nodes in WSN is very low, gives accurate results, and has
high performance. However. WSN sensors have limited energy, low transmission range,
and small size which forces the sensors to cooperate for the transfer of data. Also, WSNs
* Ghassan Husnain
ghusnain.mct@uetpeshawar.edu.pk
Muhammad Faisal
mfaisal5751@gmail.com
1 Department ofComputer Science, IQRA National University, Hayatabad,Peshawar25100,
Pakistan

M.Faisal, G.Husnain
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are less secure as compared to wired networks. Battery life is very low, and it needs to be
charged after a specific amount of time. Due to its wireless infrastructure, it faces envi-
ronmental resistance, and as a result communication speed of the sensor nodes is slow as
compared to the wired network. However, there are some positive aspects of WSN too, like
it does not need any physical infrastructure as we deployed in wired base networks. WSN
has many Applications like it can be used for surveillance, weather forecast, health care,
agriculture, industries, [2–4], etc.
Blockchain technology became popular day by day. Unlike a centralized system, block-
chain technology did not depend on the central authority [5]. It is a distributed ledger tech-
nology that Keeps records of the transaction between two entities in a secure and immu-
table way. Once a transaction is stored in the blockchain. It is impossible to alter that
information because the information is stored not only on the central point. However, it
is distributed. If someone wants to change the information stored on the blockchain must
take permission from all the nodes on which a copy of that ledger is saved. Each block in
the blockchain consists of two things, one is the blocking header and the other is the block
body. Block header further consists of a nonce value, timestamp and difficulty target, etc.
The second part of the block is the block body which consists of a transaction record.
The main feature of blockchain technology that makes it more reliable is as follows,
motivated from [6].
1.1 Decentralization
As we know that in the traditional system, there was a central authority (CA) on which the
whole network depends. However, in a blockchain, there is no CA. The information stored
in the blockchain is distributed. No single entity can change it. Change in the information
can only be made when all the entities in the network agreed.
1.2 Transparency
The transactions done through blockchain are transparent and every entity of the block-
chain network could see the transaction and its related details.
1.3 Immutability
Blockchain technology uses cryptographic hash functions. By using this, it is impossible to
alter the information once it is stored on the chain.
1.4 Non‑Repudiation
It means that once the transaction is held and stored on the blockchain, then no one can
refuse the transaction. There are two aspects of non-repudiation. Suppose we have two
nodes A and B. A want to send some information to B. After sending the information, A
cannot deny his behavior. The other aspect is that B cannot claim that he did not receive the
information. As digital signatures are used in blockchain to guarantee the non-repudiation
of information.
Similarly, there are mainly three types of blockchain technology which are:

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1.5 Public Blockchain
It is the type of blockchain that is publicly available and anyone can join the network. All
the participants are capable to read and write or participate in the network. Once the data is
validated on the blockchain, no one can change it. This type of blockchain is considered to
be fully decentralized. Examples are Bitcoin and Ethereum.
1.6 Private Blockchain
It is also called consortium blockchain. It is not available publicly and only preselected
nodes are capable to control the consensus process. This type of blockchain is considered
partially decentralized. It is usually designed for private businesses.
1.7 Hybrid Blockchain
It is a combination of both public and private blockchain [7]. However, a private block-
chain has been proposed in this work.
Today, blockchain is used in many areas like Finance [8], Hospitality, Tourism [9],
Healthcare [10], etc. To make the transaction secure on the blockchain, it uses a one-way
encryption scheme called a hash function. There are different families of hash functions
like secure hash functions SHA, MD5, and Blake, etc. Besides this, blockchain has also
some disadvantages it required more computation power while adding a transaction to the
chain. Different consensus mechanisms are used for this purpose i.e., Proof of Work, Proof
of Authority, Proof of stack, etc. Similarly, the monetary cost of blockchain is very high.
As in a traditional system, the whole network relies on a central entity, due to which it
faces a central point of failure, needing high computational cost and trust issues. However,
when we are talking about blockchain-based WSNs, it makes our communication more
secure and reliable. Besides this WSN using blockchain also face some critical problems.
Like in WSN storage capacity and lifetime is very low. On the other hand, storing data on
the blockchain is very costly and it needs more computational power to add transactions.
An energy-efficient routing is also a need of WSN. Many researches have been done on
these issues. However, no one can get the appropriate result [11].
To resolve the above-mentioned issues, we proposed a multi-hop routing and a cost-
effective decentralized storage station, cluster head, and ordinary nodes. Blockchain layer,
composed of the private blockchain. And cloud layer, consist of Fog computing and Cloud
computing. After deploying nodes, we will choose the cluster head based on three parame-
ters i.e., residual energy, degree of a node, and distance from the base station. After choos-
ing the cluster head, a pseudonym name will be assigned to all the nodes for communi-
cation. A private Blockchain is used for transaction records. Fog computing is used as a
medium between the base station and cloud computing. It is also responsible to store data.
For routing, we will use a routing protocol capable to find the route from the source to the
destination when it is needed. Cloud computing will store the data and send the hash of
that data to the base station for future use. The contributions of the paper are as follows.
• To improve the lifetime of the network, the ILEACH protocol is proposed.
• A blockchain-based multi-hop routing scheme is proposed to send data in a convenient
way to the base station.
• For reliable and efficient data storage, fog and cloud computing is utilized.

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2 RELATED WORK
2.1 Single Point ofFailure inWSN
As we know that traditional IoT authentication protocols purely depend on a trusted third
party or centralized system which may cause sometimes a single point of failure problem,
as a result, the whole network collapse. Also, in [12], as we know that traditional routing
protocols completely depend upon the central authority CA. The central authority is used
to identify and authenticate each device in the network. Many challenges are faced while
using any CA i.e., trust, single point of failure. While using CA it also faces many attacks.
The main disadvantages of using CA are the single point of failure. Besides this, in [13],
the authors addressed that IoT plays a very dominant role in today’s world and provides
many services in our daily life. Many mechanisms have been proposed previously for secu-
rity attack detection that merely relies on a distributed and centralized architecture. How-
ever, due to their distributed and centralized structure, they tend to face some problems like
high computation cost, single point of failure, storage constraints, and high latency. It also
faces problems in collecting and monitoring important data throughout the network.
2.2 Cost inTerms ofComputational Power
Industrial IoT has had a great impact on the revolution of IoT. It provides an ease to the
industrial zone in terms of security, cost, time, etc. with the combination of IoT and block-
chain has gained relatively research interest in the past few decades. However, the high
demand for resources for blockchain and insufficient performance of IoT modes has not
been tackled well. Furthermore, due to the involvement of the Merkle tree, public key
infrastructure PKI and Proof of work PoW, blockchain required a huge amount of com-
putation power. Due to all these factors in [14–16], it makes the blockchain very costly to
collaborate with IoT devices. In [17], blockchain technology is developing technology and
is used in distributed systems because of its capabilities i.e., trustworthiness. Different con-
sensus mechanisms are used to add transactions to the chain. However, it also faces a major
challenge by using PoW. Because PoW is very expensive in terms of computation power,
which is a very crucial issue in the blockchain. IoT has a great role in the development
of modern industries. IoT sensors can easily reduce the cost and human efforts with the
increase in production. However, IoT devices have also security concerns due to their low
computational power. The attackers can easily attack these devices and mitigate the perfor-
mance of the whole network [18]. Also, in [19], PoW is considered to be the original con-
sensus mechanism of blockchain technology. It is responsible for solving different math-
ematical puzzles. If we talk about the WSN environment, we know that nodes of WSN are
resource constraints. So, if we use PoW as a consensus mechanism in WSN, it will directly
affect the overall performance and lifetime of the network, because PoW required a large
amount of energy to solve the puzzles.
2.3 Data Storage ontheBlockchain
In [20], the development of smart cities is directly proportional to the development of
IoT. With the increase in IoT devices and data volume, issues are also increased such as
bandwidth bottleneck, privacy, high latency, and security. Security, computational power,
and storage resources are the basic need of IoT in a smart city. However, still, there is no

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security architecture made for smart cities to have more computational power and storage
capacity. Also, in [21], the nodes in the IoT network are not rich in resources, and their
monitoring, computational, and storage capabilities are very small. Deploying blockchain
on IoT networks leads to very serious storage problems. All the entities must save the same
ledger (record of a transaction) and this ledger keeps on increasing as transactions happen
in the network. And after a certain number of transactions, the IoT nodes become unable to
save the same repeated ledger. This issue is solved by saving only important information on
IoT devices and rather of the data is stored on some external storage. This leads to the syn-
chronization of data with mature blockchain. Synchronization of data demands large efforts
and IoT devices are not able to do such synchronization. Furthermore, in [22], data storage
is a very important factor. However, WSN nodes have very limited storage capacity, due to
which they can face many problems.
2.4 Detection ofMalicious Nodes
A wireless sensor network is considered to be a core technology that supports IoT opera-
tions. The fairness and traceability of malicious node detection cannot be guaranteed in
WSN. Similarly, in [23], the wireless sensor network is used everywhere in the world today
due to its specialties. However, it has also a lot of limitations like trustworthiness between
nodes, energy consumption, authentication, etc. In this paper, the author’s main focus is
trustworthiness among different nodes. The trust may be evaluated in terms of behavior or
data-based. To compute the behavior of a node in terms of trust, we calculate some met-
rics e.g., intimacy, closeness, frequency of interaction, and honesty. Also, in [24], with the
advancement in WSN technology, it also faces some challenges. During the communica-
tion between different sensor nodes, the network services are badly affected by malicious
nodes.
2.5 Authentication andOther Security Concerns
The lifetime of IoT devices is very low due to their small physical structure. So, it’s stor-
age capacity and computational power are very low. As a result, these devices are vulner-
able to many security attacks. Many solutions have been proposed to overcome the secu-
rity threats in IoT devices. However, no solution is proposed yet to get the desired result
against vulnerability [25]. Similarly, in [26], the wireless sensor network trustworthiness
of the routing is very important to ensure efficiency and routing security. A lot of studies
have been done to improve the route between different nodes by using trust management,
cryptographic system, etc. However, none of these have achieved the desired results. It is
also a very difficult task to identify the non-trusted behavior of the routing nodes in a real
environment. So, still, there is no effective way to overcome malicious node attacks. Also,
in [27], trustworthiness between the nodes is considered to be the foundation for success-
ful localization and secure communication in WSN. Besides this, in [28, 29], sensor net-
works SN and WSN play a very major role in the development of IoT. As we know that
authentication and trustworthiness are the most important factors for reliable communica-
tion between sensor nodes in an IoT environment. Many types of research have been done
to solve this crucial problem. However, none of them meet the desired solution for reli-
able communication. IoT environments also face some other problems like computational
power and energy consumption. Similarly, in [30], nodes are deployed in the environment
to monitor environmental changes. However, the privacy and security of these nodes are

M.Faisal, G.Husnain
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still big issues. Both the sensor nodes and their sensed data are vulnerable to many internal
and external attacks. Many studies are done to solve these issues. However, they do not
completely describe the behavior and constraints of caching schemes in Information- cen-
tric networks. Also, in [28], IoT nodes are not rich in terms of resources and ability to do
simple processing. For complex processing and aggregation of data, they send data to base
stations and other authorities, which are rich in resources, for further processing. After pro-
cessing, these high authorities store this data, these storage platforms are centralized hav-
ing the issue of a single point of failure. Therefore, in centralized platforms (e.g. clouds),
the data is vulnerable to security threats.
3 Method
In this section, we design a WSN network. Then clustering protocol is used to select a
cluster head. After cluster head selection, a multi-hop scheme routing scheme is used to
send data to the base station. In the end, data is stored in fog and the cloud. Before going to
discuss the network model, this paper has some assumptions.
3.1 Assumptions
• The MAC address of every node is unique.
• Every node in the subnet must trust the base station.
• Sensor nodes are deployed uniformly randomly
• All sensor nodes are homogenous
• All the sensor nodes have unique Ethernet address
• The base station is a trustable entity in the network
• The BS station has enough computational and storage power to serve the network for a
long time and cannot be died because of low power.
3.2 Network Model
WSN networks consist of thousands of nodes. Based on their capabilities these nodes are
divided into the base station, cluster head, and ordinary nodes.
• Base station: The base station has abundant resources and it is considered to be the
most powerful entity of WSN networks in terms of storage capacity and computational
power. The base station is responsible to manage incoming and outcoming data. It is
directly connected to the private blockchain and fog computing. All nodes in the subnet
of the base station need to be registered. before joining the network, every new node
must register with the base station.
• Cluster head: After the base station, the cluster head is the second most abundant
resource entity in the WSN environment. It is directly connected with the base station
and ordinary nodes. The main function of the cluster head is to receive sensing data
from the sensor nodes, process it and send it to the base station. Many sensor nodes are
connected to each cluster head. Similarly, many cluster heads are connected to the base
station directly.
• Sensor nodes: These nodes are located at the edge of the network. Each sensor node
is connected to a single cluster head at a time. Sensor nodes can only sense data from

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the physical environment and send it to the cluster head. Due to its low computational
power, it could not perform other operations and processing as the cluster head and
base station do.
3.3 Proposed Model
3.3.1 Registration ofNodes
After deploying nodes in the network, the first step is to register all the nodes with the base
station. To do so, all thenodes send their MAC address to the base station. The base station
hashes the MAC address of each node by using keccak 256 and generates a unique id for
each node. This unique id is assigned to the concerned node. Also, these credentials are
stored in the fog for future purposes.
3.3.2 Cluster Head Selection
As we know that the work of the cluster head is to receive data from the sensor nodes and
send it to the base station. By receiving and sending data to the base station its energy is
depleted respectively. A time is reached when the cluster head energy becomes zero and is
unable to receive sensing data from sensor nodes, process it, and send it to the base station.
Due to this, the whole network will collapse. To mitigate this issue, we have proposed an
I-LEACH-based clustering protocol.
The proposed clustering scheme selects random clusters in the first round as the energy
of the total energy is the same in the starting. After cluster head selection, it sends an
advertisement message to all sensor nodes. By receiving an advertisement message, the
sensor nodes decided to which cluster it belongs. this decision will be taken based on min-
imum distance. After sensor nodes decide to which cluster it belongs, the sensor nodes
send their credentials to the cluster head. The cluster head updates its database and sends
all these credentials to the base station for further process. We assume that all the sensor
nodes send data to the cluster head.
We have set a threshold, when the energy of the cluster head becomes low from that
threshold, the new cluster head selection process will start. We have set three parameters
for new cluster head selection, residual energy a value of PDR, and the distance of an ON
from the base station, as shown in algorithm 1. In the first iteration, residual energy is
checked, if two nodes have the same residual energy, then the distance will be checked for
both nodes from the base station. The nodes having a minimum distance from the base sta-
tion should be considered a new cluster head. We have considered the minimum distance
of CHs with BS because the energy of CH is depleted rapidly when there is a large distance
between CH and BS.
When a sensor node sense data from the physical environment and sends it to the con-
cerned CH, the energy of both the sensor node and CH will be depleted while sending
and receiving the data. The depleted energy in sending the data packet to CH is calculated
below Eq.(1).
where ET X is the transmitting energy, m shows the packet size, Eelec represents the elec-
tronic energy, εfs shows the transmit amplifier type and d is the distance. Similarly, the
(1)
ETX
=
m
∗
Eelec
+
m
∗𝜀
fs
∗
d2

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energy of the CH also depletes while receiving data from the sensor nodes as depicted in
Eq.(2).
where ERX is the CH energy consumed while receiving data from the sensor node. Besides
this, the energy depletion of CH depends on the number of sensor nodes connected to
it. The more data received from the sensor node; the more energy will be depleted, as in
Eq.(3)
where ERX is the CH consumed energy while receiving data packet m from sensor node n
connected to CH. The proposed system model of cost-effective and efficient routing based
on blockchain in WSN is shown in Fig.1:
3.3.3 Authentication
The authentication of nodes is an important factor. If two nodes want to communicate with
each other. It must be authenticated first. Suppose we have two nodes A and B, and they
want to communicate with each other. For this purpose, node A sends its credentials to the
CH to which it is attached. The credentials are node A id, the CH id to which it belongs,
and id of the node B to which it wants to communicate. CH verifies its authenticity and
sends these credentials to the BS. The BS compares these credentials with the information
stored on the private blockchain. The process will return an error if the credentials did not
match. A few other things are also verified. The BS also verifies that the existing node is
operational or dead. If it is found dead, the process will end at this stage. If both credentials
are the same then the BS executes the smart contract and sends a verification message to
(2)
ERX
=
m
∗
Eelec
(3)
ERX
∝
m
∗
n

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the concerned node through CH. The same process is repeated at node B. Mutual authenti-
cation is needed only when both of the nodes belong to a different cluster. However, if they
belong to the same CH, they can communicate with each other directly. The process of
cluster formation and nomination of CH is presented in Fig.2.
3.3.4 Routing
As AODV is an on-demand routing protocol so it is suitable for the WSN environment
because WSN has limited energy, computational power, bandwidth, etc. We proposed an
Fig. 1 Proposed System Model

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energy-efficient AODV (EEAODV) routing protocol. The route discovery and route main-
tenance are the same as in AODV. Suppose we have several routes from source to destina-
tion, we will choose the best route based on two parameters i.e., minimum hop count and
residual energy of the intermediate nodes. Using these parameters can help in the enhance-
ment of the lifetime of the network.
3.3.4.1 Route Discovery When a source node wants to send data to the destination. It will
first check its routing table information. If the path is available to the desired destination,
the source node will the data to the destination. However, if the path does not exist, then
the source node floods a route request (RREQ) message to its neighbor nodes. The RREQ
contains the source id, request-id, and destination id. These parameters make the RREQ
unique. After receiving RREQ, the neighbor nodes first verify request-id and source id. If
the request with the same parameters is already available, then the node discarded the new
RREQ. Otherwise, the RREQ will be forwarded to the destination. Upon receiving at the
destination end, a request-reply (RREP) message is generated and sent back to the source
node. At the same time both, the source node and other intermediate nodes can update their
routing table and then the source node can send data to the destination node.
3.3.4.2 Route Maintenance After finding a suitable route to the destination by route
discovery method. Failure of links may happen due to the WSN environment. Therefore,
intermediate nodes send Hello packets to the neighbor nodes to ensure that they are
Fig. 2 Clustering workflow

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active. Upon receiving this hello message, every intermediate node confirms the informa-
tion in the table regarding routing. If an invalid route is detected, it will delete the routing
information of that route and send a route error packet RERR to the source node. After
receiving RERR, the source node begins a new route discovery with new broadcasting.
In the proposed model, we have proposed an energy-efficient AODV (EEAODV) routing
protocol, motivated by [28].
3.3.4.3 Storing ofData Cloud storage is an emerging technology. We use both cloud and
fog storage to overcome the deficiencies of the cloud. Due to the high distance from the end-
user, the cloud faces some critical problems like high latency, high usage of bandwidth, high
consumption of energy, etc. Fog is used to mitigate the abovementioned issues faced by the
cloud as it is deployed near the end-user. It is a transient storage system. Which is capable
to receive data from the BS and perform some important tasks on the data like aggregation,
hashing, etc., and forwarding that data to the cloud for further processing and storage. There
are a few steps performed by fog, which are given below. Step 1: Calculate the Hash of data
d. In the very first step, when the BS sends data to the fog, the fog will first hash hi1 that data
using Keccak 256 hash algorithm. Step 2: Storing hash hi1 and data d. By hashing data di1,
it will generate a unique address. The hash of the data is sent to the BS and the data is sent
to the cloud for storage. Step 3: BS sends a request to the cloud for data d. The BS sends a
request to the cloud for data d retrieving. Step 4: BS calculate the hash. The Cloud sends
data d to the BS. The BS will calculate the hash hi2 of the data d by using Keccak 256 hash-
ing algorithm. Step 5: Comparison of hi1 and hi2. The BS will compare hi1 and hi2. If both
the hashes are the same, it means that the BS receives the right data, otherwise, the data will
be discarded. Similarly, the cloud provides convenient and secure data storage. Moreover,
the cost of storing data on cloud servers is very low.
4 Results andDiscussion
This section contains all results and a discussion of our proposed model. Step by step we
complete shown results in the form of figures as well as complete results description. In the
last section, we briefly describe and compare our proposed work with the existing research
study.
4.1 Tools andLanguage
In the proposed model we have used different tools and language. For the deployment of
nodes and graphical results, we used MATLAB. For smart contract deployment, we use
Remix IDE and in the last python is used for hashing.
4.2 Nodes Deployment
100 nodes are randomly (uniform) deployed in a 100 x 100 m square meter area. Each
cluster head has directly connected sensor nodes. The function of these sensor nodes is just
to sense data from the environment and send it to the concerned cluster head. Each cluster

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has many sensor nodes and one cluster head. The simulation parameters for the proposed
system are presented in Table1:
4.3 Comparison ofProposed Model withALEACH
The simulation results in Fig.3 show that our proposed model is capable to survive the
network for a greater number of rounds as compared to the existing clustering protocol.
We used three parameters for the selection of cluster heads. i.e., residual energy, value
of PDR, and distance from the base station. In traditional ALEACH clustering protocol,
they used only energy as a parameter for CH selection. The ILEACH protocol outper-
forms ALEACH because ILEACH considers three parameters for new CH selection and
TABLE 1 Simulation parameters Parameters Values
Total Sensing Area 100 X 100 m2
Total number of Nodes 110
Total Base station 1
Total Cluster Heads 10
Total Ordinary Nodes 100
Nodes deployment Random
Number of iterations 25
Fig. 3 Comparative analysis of ILEACH vs ALEACH

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ALEACH considers only one. In the observation of Fig.3, the existing technique only
survives for 1000 rounds and our proposed model survives the network for 1400 rounds.
The reason is, that the existing clustering technique selects the CH only based on
energy, and we have used three parameters for CH selection, which is why our proposed
scheme serves the network for more rounds as compared to the benchmark scheme.
4.4 Comparison Between Different CHs
Figure4 shows the comparison of the average energy consumption of different clusters
of our proposed I-Leach protocol. The figure shows that different clusters have different
energy consumption. The reason is that the nodes in each cluster are randomly deployed
and each node has a different distance from its respective cluster head. In this way, the
data packet of each node has to cover different distances to reach the cluster. As we
know, the energy consumption directly depends upon the distance as shown in the fol-
lowing Eq.(4).
Because the ordinary nodes in each cluster head have different distances from their
respective cluster head, it is the reason that the average energy of cluster 1 and cluster 2
are different, as shown in the above figure. It is also depicted that the lifetime of cluster
1 is 500 rounds while cluster 2 has a lifetime of 450 rounds.
(4)
ETX
=m∗E
elec
+m∗𝜀fs ∗d
2
Fig. 4 Comparative analysis between two CHs

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4.5 Comparison ofPacket Delivery Ratio
Figure 5 shows the comparison between the PDR value of our proposed model and the
benchmark scheme [31]. The performance of our proposed model is better than the bench-
mark scheme. The reason is that nodes of the benchmark scheme die rapidly because of
inefficient energy consumption due to CH selection while only considering the residual
energy of the ON. On the other hand, in our proposed model the CHs are selected on the
bases of residual energy of ON, distance of ON from BS, and the value of PDR. Therefore,
our proposed model has a high PDR as compared to the benchmark scheme.
4.6 Execution Time ofNodes duringAuthentication
Figure6 shows the execution time of nodes required during authentication. In the figure,
we can see that the time taken to authenticate five nodes will take 13s. And it increases
gradually when the number of nodes increases.
5 Conclusion andFuture Work
The proposed model aims to provide an energy-efficient mechanism and cost-effective
storage for WSNs. We use MATLAB for network deployment and clustering. For smart
contracts and hashing, we use Remix and Python. The purpose of this study is to pro-
vide an optimal solution for energy consumption. Similarly, it will also provide a cost-
effective way to store data. We enhance the lifetime of the network as shown in Fig.3.
Fig. 5 Comparison of Packet delivery ratio

Blockchain Based Multi‑hop Routing andCost‑Effective…
1 3
Our proposed model can serve the network for a greater number of rounds as compared
to the benchmark clustering scheme. Similarly, as we know that storage cost of data on
blockchain is very expensive. As Blockchain is a distributed technology, a copy of each
ledger must be stored on all the entities in the network. As a result, the storage cost
of data is very high. To overcome this issue, we have used fog and cloud as a storage
medium. As our main aim of the study is to increase the lifetime of the WSN. Thus, we
proposed an energy-efficient AODV routing protocol. In the future, we will work more
to improve the performance of the network and increase the lifetime of the network.
Furthermore, we will add some other parameters for the selection of CH, like the degree
of node and reputation of the node. Similarly, we will also work on PoS and PoA con-
sensus mechanisms to increase the performance of the network.
Funding The author(s) received no specific funding for this work.
Data Availability All the data is within the main manuscript.
Code availability All the data is within the main manuscript.
Declarations
Competing interests The authors have declared that no competing interests exist.
Execution Time (sec)
60
50
40
30
20
10
05 10 15 20 25 30 35 40 45 50 55 60 65 70 75
Numberof Nodes
Fig. 6 Nodes Authentication Execution Time

M.Faisal, G.Husnain
1 3
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law.
Muhammad Faisal (MS) has accomplished his M.S degree in Com-
puter Sciences (Blockchain Technologies) from Iqra National Univer-
sity, Peshawar, Pakistan and BSc in Computer Sciences (Networks &
Telecommunications) from COMSATS, Islamabad, Pakistan. His
research interests include intelligent systems, wireless sensor net-
works, blockchain technologies, route clustering and artificial
intelligence.
Ghassan Husnain , (PhD, BE) has accomplished his Ph.D. degree in
intelligent ad hoc networks and bio-inspired computation from the
University of Engineering and Technology at Peshawar, Pakistan, and
MSc in Network Systems from University of Sunderland, England. He
is also an Assistant Professor with IQRA National University Pesha-
war. His research interests include sensor networks, wireless personal
communications, intelligent systems, vehicular ad hoc networks, evo-
lutionary computation, bio-inspired algorithms and artificial intelli-
gence .