IEEE Consumer Electronics Magazine - May/June 2023 - 66

Blockchain Technology to Combat COVID-19
FIGURE 3. Overall process in the proposed framework.
tracking under a smart home environment is
then demonstrated in Figure 3.
BLOCKCHAIN IMPLEMENTATION
The real-time blockchain simulation has been
executed over a system configuration considered
as a CS setting with the environment:
" Ubuntu 20.04 LTS, Intel Core i5-8400 CPU 3855 U
@ 1.60 GHz, Memory 4 GB, OS type 64-bit, disk
size 152.6 GB. "
We set up a distributed CS system for blockchain
execution, which forms a P2P CS network.
The P2P CS network consists of the number of distributed
servers as 12, which are participated for
blockchain simulation purpose. The communication
between the peer nodes aremade by the message-passing
process, where themessages may be
transactions or a block. The script for this simulation
is written in node.js language with VS CODE
2019. In this simulation, we consider the genesis
block (first block in the blockchain) to have all
peer nodes before adding new block into their
database. We have then implemented the votingbased
" PBFT consensus algorithm " discussed previously
for block verification and addition into the
blockchain. The simulation results are based on
the number of blocksmined versus computational
time (in seconds) (the time required to add the
block into blockchain) and transactions with
computational time. The details of these two cases
are elaborated as follows.
66
Case I: In this case, we consider the number
of blockchain versus the computational time
(in seconds), where " a fixed number of transactions
for each block in the blockchain " is
taken as 34. This means the chain of block is
varied but the loaded transaction in each
block in varied chain is fixed and the simulation
outcomes are reported in Figure 4(a).
The results imply whenever the blocks are
increased, the computational time also
increases in proportion. The graph of this
result is a straight line, which implies a linear
type. Therefore, " when the number of blocks
mined is increased, the total computational
time increases linearly. "
Case II: In this case, we have presented the
simulation results in Figure 4(b), where we
have considered a fixed number of blocks to
be mined in each blockchain as 40, and only
varied the number of transactions. It is
observed that the outcome trends show that
the total computational time (in seconds)
increases linearly (based on the linear type
graph, that is, the graph represents a single
straight line) when the number of transactions
per block also increases.
EXPERIMENTAL RESULTS FOR AIENABLED
BIG DATA ANALYTICS
In this section, we provide the comprehensive
experimental results under two circumstances:
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