2021 - 2022 : Top 10 Read articles in Computer Networks and Communication

Top10 Cited Articles in
Computer Networks&
Communications
2021-2022
International Journal of Computer
Networks& Communications (IJCNC)
http://airccse.org/journal/ijcnc.html
(Scopus, ERA Listed, WJCI Indexed)Scopus Cite Score 2022—1.7
ISSN 0974 - 9322 (Online); 0975 - 2293 (Print)
Citations, h-index, i10-index
Citations 6814 h-index 35 i10-index 194

DEVELOPING AN ADAPTIVE CHANNEL MODELLING USING A
GENETIC ALGORITHM TECHNIQUE TO ENHANCE AERIAL
VEHICLE-TO-EVERYTHING WIRELESS COMMUNICATIONS
Faris. A. Almalki
Department of Computer Engineering, College of Computers and Information Technology, Taif
University, Kingdom of Saudi Arabia
March 2021 | Cited by 12
ABSTRACT
In this digital era, Internet of Everything (IoE) has a potential to bring out drastic changes to how we live
today, where billions of people and devices require wireless connectivity. Where Unmanned Aerial
Vehicles contribute positively in paving the way for IoE and Fifth Generation technologies, and tackle
some of their comms challenges. Thus, this paper aims to provide an adaptive approach using a Genetic
Algorithm (GA) technique by combining indoor and outdoor propagation models to enhance aerial
vehicle-to-everything wireless connectivity. The proposed adaptive approach uses a GA multi-objective
function that yield optimum values of UAV altitude, elevation angles, and type of building for indoor
environment. The proposed GA optimization technique has met the demand of a typical dense-populated
urban environment, as well as empowering the IoE with greater coverage footprint, high Quality of
Service benchmark, and line-of-sight adaptability. The output results emphasized that the proposed
adaptive approach using the GA technique can help in smart decision-making and selecting a proper
setup and find the optimum parameters to provide seamless wireless connections from aerial vehicle-to-
everything.
KEYWORDS
Unmanned Aerial Vehicles, Internet of Everything, Channel Modelling, Propagation Model,
Fifth Generation
For More Details : https://aircconline.com/ijcnc/V13N2/13221cnc03.pdf
Volume Link : https://airccse.org/journal/ijc2021.html
Google scholar citations
https://scholar.google.co.in/citations?view_op=view_citation&hl=en&user=YnJ2pwkAAAAJ&cstart=20
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:nWoA1JPTheMC

UTILIZING XAI TECHNIQUE TO IMPROVE AUTOENCODER BASED
MODEL FOR COMPUTER NETWORK ANOMALY DETECTION WITH
SHAPLEY ADDITIVE EXPLANATION (SHAP)
Khushnaseeb Roshan and Aasim Zafar
Department of Computer Science, Aligarh Muslim University, Aligarh-202002, India
November 2021 | Cited by 6
ABSTRACT
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in
computer network security, such as fraud detection, network anomaly detection, intrusion detection, and
much more. However, the lack of transparency of ML and DL based models is a major obstacle to their
implementation and criticized due to its black-box nature, even with such tremendous results.
Explainable Artificial Intelligence (XAI) is a promising area that can improve the trustworthiness of
these models by giving explanations and interpreting its output. If the internal working of the ML and
DL based models is understandable, then it can further help to improve its performance. The objective of
this paper is to show that how XAI can be used to interpret the results of the DL model, the autoencoder
in this case. And, based on the interpretation, we improved its performance for computer network
anomaly detection. The kernel SHAP method, which is based on the shapley values, is used as a novel
feature selection technique. This method is used to identify only those features that are actually causing
the anomalous behaviour of the set of attack/anomaly instances. Later, these feature sets are used to train
and validate the autoencoderbut on benign data only. Finally, the built SHAP_Model outperformed the
other two models proposed based on the feature selection method. This whole experiment is conducted
on the subset of the latest CICIDS2017 network dataset. The overall accuracy and AUC of
SHAP_Model is 94% and 0.969, respectively.
KEYWORDS
Network Anomaly Detection, Network Security, Autoencoder, Shapley Additive Explanation,
Explainable AI (XAI), Machine Learning
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PRIVACY-PRESERVING MACHINE AUTHENTICATED KEY
AGREEMENT FOR INTERNET OF THINGS
Beaton Kapito1,3, Mwawi Nyirenda1 and Hyunsung Kim1,2
1Department of Mathematical Sciences, University of Malawi, Zomba, Malawi
2 School of Computer Science, Kyungil University, Kyungbuk, Korea 3Malawi Adventist
University, Ntcheu, Malawi
ABSTRACT
Internet of things (IoT) is the integration of computer-based systems and the physical world in which
things interact with each other. Due to heterogeneity and resource-constrained feature of IoT devices,
there are many privacy and security challenges resulting in many threat vulnerabilities in IoT
environments. After reviewing and analyzing the recent IoT security, privacy, and authentication
protocols, we will withdraw research gaps focused on the elimination of human factors in IoT
authentication. In order to fill these research gaps, this paper proposes a privacy-preserving machine
authenticated key agreement based on IoT, denoted as IoTMAKA. IoTMAKA uses dynamic identity and
machine fingerprint to provide security and privacy. Security analysis shows that IoTMAKA provides
anonymity and untraceability, provides freshness, and is secure against passive and active attacks.
IoTMAKA reduces communication overheads by 20% and computational overheads by 25% on average
as compared to the previous related works.
KEYWORDS
Internet of Things, Authenticated Key Agreement, Privacy, Machine Authentication,
Cryptography
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:Tfl4UtY-dJUC

A NOVEL ROUTING STRATEGY TOWARDS ACHIEVING ULTRA-
LOW END-TO-END LATENCY IN 6G NETWORKS
Satya R. Das1, Sayan Sen Sarma2, Mitrabinda Khuntia1, Indranil Roy3,Koushik Sinha3, and
Bhabani P. Sinha1
1 Dept. of Computer Science & Engg., SOA University, Bhubaneswar, India.
2 Dept. of Computer Science & Engg., University of Calcutta, West Bengal, India.
3 School of Computing, Southern Illinois University, Carbondale, USA.
January 2022 | Cited by 5
ABSTRACT
Compared to 5G, 6G networks will demand even more ambitious reduction in endto-end latency for
packet communication. Recent attempts at breaking the barrier of end-to-end millisecond latencies have
focused on re-engineering networks using a hybrid approach consisting of an optical-fiber based
backbone network architecture coupled with high-speed wireless networks to connect end-devices to the
backbone network. In our approach, a wide area network (WAN) is considered with a high-speed optical
fiber grid network as its backbone. After messages from a source node enter the backbone network
through a local wireless network, these are delivered very fast to an access point in the backbone
network closest to the destination node, followed by its transfer to the local wireless network for delivery
to the destination node. We propose a novel routing strategy which is based on distributing the messages
in the network in such a way that the average queuing delay of the messages through the backbone
network is minimized, and also the route discovery time at each router in the backbone network is
drastically reduced. Also, multiple messages destined towards a particular destination router in the
backbone network are packed together to form a mailbag, allowing further reductions in processing
overheads at intermediate routers and pipelining of mailbag formation and route discovery operations in
each router. The performance of the proposed approach green based on these ideas has been theoretically
analyzed and then simulated using the ns-3 simulator. Our results show that the average end-to-end
latency is less than 380 µs (with only 46-79 µs within the backbone network under varying traffic
conditions) for a 1 KB packet size, when using a 500 Gbps optical fiber based backbone network laid
over a 15 Km × 15 Km area, a 50 Mbps uplink channel from the source to the backbone network, and a 1
Gbps downlink channel from the backbone network to the destination. The significant reduction in end-
to-end latency as compared to existing routing solutions clearly demonstrates the potential of our
proposed routing strategy for meeting the ultra-low latency requirements of current 5G and future 6G
networks, particularly for mobile edge computing (MEC) application scenarios.
KEYWORDS
6G, Beyond 5G, 5G, Routing, Ultra-low latency, Network architecture, Queuing delay
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:pUxgyZctzPYC

FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION
METHOD TO PROLONG THE NETWORK LIFETIME IN WSNS
Jungsub Ahn1 and Sanghyeok Lim2 and Taeho Cho3*
1Department of Electrical and Computer Engineering, Sungkyunkwan University, Republic of
Korea
2Amorepacific Republic of Korea
3*Department of Computer Science and Engineering, Sungkyunkwan University, Republic of
Korea
November 2021 | Cited by 4
ABSTRACT
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The
sensor network communicates between nodes in a configured network through self-organization. An
energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy
consumption by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the
bottleneck problem through an efficient message route selection method. The proposed method selects
an efficient messaging path using GA and fuzzy logic composed of multiple rules. Message route
selection plays an important role in controlling the load balancing of nodes. A principal benefit of the
proposed scheme is the potential portability of the clustering-based protocol. In addition, the proposed
method is updated to find the optimal path through the genetic algorithm to respond to various
environments. We demonstrated the effectiveness of the proposed method through an experiment in
which the proposed method is applied to a probabilistic voting-based filtering scheme that is one of the
cluster-based security schemes.
KEYWORDS
Wireless sensor network, Fuzzy logic, Load balancing, Genetic algorithm.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:1EqfMoDn7-AC

SELF-PRUNING BASED PROBABILISTIC APPROACH TO MINIMIZE
REDUNDANCY OVERHEAD FOR PERFORMANCE IMPROVEMENT
IN MANET
Gyanendra Kumar Pallai1, Meenakshi Sankaran2 and Amiya Kumar Rath3
1Department of Computer Science & Engineering,SOA Deemed-to-be University,
Bhubaneswar, India,
2VIT Business School, VIT Bhopal University, Bhopal, India
3Department of Computer Science & Engineering, Veer Surendra Sai University of
Technology, Burla. Deputed as adviser to National Assessment & Accreditation Council,
Bengaluru, India
ABSTRACT
The Broadcast storm problem causes severe interference, intense collision and channel contention, which
greatly degrades the QoS performance metrics of the routing protocols. So, we suggest a neighbourhood
coverage knowledge probabilistic broadcasting model (NCKPB) integrating with AODV protocol with
knowledge on 2-hop neighbourhood coverage; a connectivity function to control a node’s forwarding
probability of retransmission to alleviate significant overhead redundancy. Our objective is to minimize
the broadcast RREQ overhead while ensuring fair retransmission bandwidth. We considered two more
important measures called Saved Rebroadcast and Reachability. The outcomes of NCKPB, Fixed
probability (FP) and Flooding (FL) routing schemes are examined under three major operating
conditions, such as node density, mobility and traffic load. The NS-2 results demonstrate the efficacy of
the proposed NCKPB model by illustrating its performance superiority over all key metrics such as
redundancy overhead, end to end latency, throughput, reachability, saved rebroadcast and collision
contrast to FP and FL.
KEYWORDS
Broadcasting, Flooding, Self-pruning, Neighbour Coverage, Forwarding Probability,
Connectivity Metric.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:Oo1CbQkBAzEC

AN EFFICIENT AND STABLE ROUTING ALGORITHM IN MOBILE AD
HOC NETWORK
Priyanka Pandey and Raghuraj Singh
Department of Computer Science and Engineering, Harcourt Butler Technical University,
Kanpur, India
July 2021 | Cited by 3
ABSTRACT
Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in
infrastructure-less wireless communication network. Routing in this kind of communication network is
highly affected by its restricted characteristics such as frequent topological changes and limited battery
power. Several research works have been carried out to improve routing performance in MANET.
However, the overall performance enhancement in terms of packet delivery, delay and control message
overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient
and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over
AODV to establish a better quality route between source and destination. In this method, we have
modified the route request and route reply phase. During the route request phase, cost metric of a route is
calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase,
average residual energy and average delay of overall path is calculated and the data forwarding decision
is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives
better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control
message overhead as compared to AODV.
KEYWORDS
Mobile Ad hoc Network, Energy, AODV, Routing, Random Waypoint Model.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:rFyVMFCKTwsC

CONTEXT INFORMATION AGGREGATION MECHANISM BASED ON
BLOOM FILTERS (CIA-BF) FOR HIGH PERFORMANCE
MONITORING APPLICATIONS OF INTERNET OF THINGS
Fawaz Alassery and Maha M. Althobaiti
College of Computers and Information Technology, Taif University, Taif, Saudi Arabia
January 2021 | Cited by 3
ABSTRACT
Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications
such as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators,
edge routers, and Base Stations (BS) which communicate with each other and send millions of data
packets that need to be delivered to their destination nodes successfully to ensure the High-performance
communication networks. IoT devices connect to the Internet using wired or wireless communication
channels where most of the devices are wearable, which means people slowly move from one point to
another or fast-moving using vehicles. How to ensure high performance of IoT data networks is an
important research challenge while considering the limitation of some IoT devices that may have limited
power resources or limited coverage areas. Many Kinds of research focus on how to customize routing
protocols to be efficient for IoT devices. The traditional routing mechanisms utilized specific IP
addresses to identify users while in IoT it is more beneficial to identify a group of users (things) based on
any contexts, status, or values of their resources such as the level of their batteries (e.g., low, medium or
high). While IoT devices have different characteristics, a multicasting mechanism to send one message
to various groups of devices will not be efficient in IoT communication networks since the aggregation
of packets is very difficult. Thus, it is useful to propose a mechanism that able to filter data packets that
need to be sent to a specific group of devices. In this paper, we propose efficient context-aware
addressing mechanism, which is based on bloom filters to increase the performance of IoT
communication networks. A routing architecture is built based on bloom filters which store routing
information. In our works, we reduce the size of routing information using a proposed aggregation
mechanism which is based on connecting each group of IoT devices with an edge router which is
hierarchically connected to an upper router after operating its bloom filter. Our simulation results show a
significant improvement in the IoT performance metrics such as packets transmission delay, jitter the
throughput, packets dropping ratio, and the energy consumption in comparison with well-known routing
protocols of IoT such as Destination Sequenced Distance Vector routing protocol (DSDV), and Ad hoc
On-demand Distance Vector routing protocol (AODV).
KEYWORDS
Internet of Things, context-aware addressing, bloom filters, High-performance IoT, routing in
IoT. Packets aggregation mechanism.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:d4tt_xEv1X8C

EVOLUTIONARY COMPUTING BASED NEURON-COMPUTATIONAL
MODEL FOR MICROSTRIP PATCH ANTENNA DESIGN
OPTIMIZATION
Rohini Saxena, Mukesh Kumar and Shadman Aslam
Department of Electronics and communication, University of Allahabad, U.P., India
May 2021 | Cited by 2
ABSTRACT
In this paper, a novel Evolutionary Computing named Adaptive Genetic Algorithm (AGA) based ANN
model is developed for rectangular MPA (Microstrip patch antenna). Considering at-hand and
Nextgeneration Ultra wideband application demands, the emphasis has been made on retaining optimal
lowcost design with desired cut-off frequency. The proposed method employs multiple sets of
theoreticallydriven training instances or patch antenna design parameters which have been processed for
normalization and sub-sampling to achieve a justifiable and reliable sample size for further design
parameter prediction. Procedurally, the input design parameters were processed for normalization
followed by sub-sampling to give rise to a sufficient set of inputs to perform knowledge-driven
(designparameter) prediction. Considering limitations of the major at-hand machine learning methods
which often undergo local minima and convergence while training, we designed a state-of-art new
Adaptive Genetic Algorithm based neuro-computing model (AGA-ANN), which helped to predict the
set of optimal design parameters for rectangular microstrip patch antenna. The predicted patch antenna
length and width values were later used for verification which achieved the expected frequency. The
depth analysis revealed that a rectangular patch antenna with width 14.78 mm, length 11.08mm, feed-
line 50 Ω can achieve the cut-off frequency of 8.273 GHz, which can be of great significance for
numerous UWB applications.
KEYWORDS
Microstrip Patch Antenna, Design Optimization, Evolutionary Computing, Neural Network,
UltraWideband.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:qPeb-qHga9sC

ABOUT DIGITAL COMMUNICATION METHODS FOR VISIBLE
LIGHT COMMUNICATION
Wataru Uemura, Yasuhiro Fukumori and Takato Hayama
Department of Electronics and Informatics, Ryukoku University, Shiga, Japan
May 2021 | Cited by 2
ABSTRACT
The visible light communication (VLC) by LED is one of the important communication methods
because LED can work as high speed and VLC sends the information by high flushing LED. We use the
pulse wave modulation for the VLC with LED because LED can be controlled easily by the
microcontroller, which has the digital output pins. At the pulse wave modulation, deciding the high and
low voltage by the middle voltage when the receiving signal level is amplified is equal to deciding it by
the threshold voltage without amplification. In this paper, we proposed two methods that adjust the
threshold value using counting the slot number and measuring the signal level. The number of signal
slots is constant per one symbol when we use Pulse Position Modulation (PPM). If the number of
received signal slots per one symbol time is less than the theoretical value, that means the threshold
value is higher than the optimal value. If it is more than the theoretical value, that means the threshold
value is lower. So, we can adjust the threshold value using the number of received signal slots. At the
second proposed method, the average received signal level is not equal to the signal level because there
is a ratio between the number of high slots and low slots. So, we can calculate the threshold value from
the average received signal level and the slot ratio. Unfortunately, the first proposed method adjusts the
threshold value after receiving the data, once the distance between the sender and the receiver is
changed, then the performance becomes worse. And after adjusting the threshold, the performance
becomes better. Therefore, this method should be used in stable environments. The second proposed
method can change the threshold value during the signal is received. That means this method can work
very quickly. So, this method can show good performance for the wide range. We show these
performances as real experiments.
KEYWORDS
Visible Light Communication, Digital Communication, Pulse Position Modulation.
&pagesize=80&sortby=pubdate&citation_for_view=YnJ2pwkAAAAJ:G36d5HCDkJYC

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2021 - 2022 : Top 10 Read articles in Computer Networks and Communication