ISSN (Print): 2666-2558
ISSN (Online): 2666-2566
Volume 14, 8 Issues, 2021
ISSN (Print): 2666-2558
ISSN (Online): 2666-2566
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12 Abstract Ahead of Print are available electronically
102 Articles Ahead of Print are available electronically
Over the past three decades, the Information Technology has been one of the most interesting fields for research and development.
From commerce, healthcare, education, entertainment, and environmental management, information technology has
played an indispensable role for sustainable development of these sectors, and hopefully will continue to fuel further advances
for the same.
The primary interest of this special issue is to provide the platform for state of art research in information technology for
sustainable development. The focus of this special issue is on real world problems and their prospective solutions through information
technology. The special issue titled "Recent advancement in information technology for sustainable development” is
an excellent collection of review and research articles. From a wide range of interesting 2 reviews & 13 research papers are
selected for this special issue after undergoing exhaustive peer-reviews with experienced and well-known reviewers.
The list of contributions in this special issue is as follows:
Mining of Closed High Utility Itemsets: A Survey, written by Singh et al. . Finding High Utility Itemsets (HUIs) is one of
the major problems in the area of frequent itemsets mining. However, HUIs mine lots of redundant itemsets which degrade the
performance and importance of high utility itemsets mining. For overcoming this limitation, closed HUIs mining has been proposed.
Closed high utility itemsets mining finds complete and nonredundant itemsets. The main goal of this survey is to provide
recent studies and future research opportunities. This paper provides a rough outline of the recent work and gives a general
view of closed high utility itemsets mining field.
Influence Maximization on Social Networks: A Study, written by Singh et al. . Influence Maximization, which selects a
set of k users (called seed set) from a social network to maximize the expected number of influenced users (called influence
spread), is a key algorithmic issue in social influence analysis. In this paper, we give recent studies on influence maximization
algorithms. The main goal of this survey is to provide recent studies and future research opportunities. We give taxonomy of
influence maximization algorithms with the comparative theoretical analysis.
A novel variant of bat algorithm inspired from ‘range determination’ feature of ‘bats’bats written by Sharma et al. . In
this work, many variants of Bat Algorithm are studied developed by various researchers. Despite its drawback of getting
trapped in local optima, it is preferred over other swarm intelligence techniques. Considering the performance of Bat Algorithm
and to extend the existing work, biological behavior of bats is explored in this research work.
Source redundancy management and host intrusion detection in wireless sensor networks, written by Singh et al. . Intrusion
Detection System (IDS) is a Software application which gives the facility to monitor the traffic of network, event or activities
on network and finds out any malicious operation if present. In this paper, a new protocol was developed that can detect the
Wireless Network Attack based on the reference of TCP/IP Model. In the proposed system, the new feature is integrated in the
IDS which is built in the router itself.
SVM-PCA based Handwritten Devanagari Digit Character Recognition written by Khamparia et al. . There is ample information
available on handwritten character recognition on Indian and Non-Indian scripts but very few articles emphasize the
recognition of Devanagari scripts. Therefore, this paper presents an efficient handwritten Devanagari character recognition system
based on block based feature extraction and PCA-SVM classifier. We have collected samples of handwritten Devanagari
characters from different handwritten experts for classification. For experimental work, total of 100 images having Devanagari
digit characters have been used for the purpose of training and testing. The proposed system achieves a maximum recognition
accuracy of 96.6 % and 96.5% for 5 & 10 fold validations with 70% training and 30% testing data using block based feature
and SVM classifier having different kernels.
Localization and Tracking of Mobile Jammer Sensor Node Detection in Multi-Hop Wireless Sensor Network, written by
Gianey et al. . The jammer in a wireless sensor network is located and tracked with open access and shared nature of the
wireless medium. The existing algorithms mainly track the stationary jammer. Mobile jammers often move from one place to
another becoming difficult to be tracked. Mobile jammer location tracker algorithm is proposed to find the location of a mobile
jammer with four steps selection i.e., initial examining node, determination of supporting node, trilateration localization and
examining group handover. The accurate location of the mobile jammer is predicted with the proposed algorithm. The effectiveness
of the proposed scheme is evaluated by conducting simulation experiments. It is observed that the proposed technique
outperforms the mobile jammer tracker effectively and accurately.
A Stack Autoencoders Based Deep Neural Network Approach for Cervical Cell Classification in Pap-Smear Images written
by Singh et al. . Early detection of cervical cancer may give life to women all over the world. Pap-smear test and Human
papillomavirus test are the techniques used for the detection and prevention of cervical cancer. In this paper, pap-smear images
are analysed and cells are classified using stacked autoencoder based deep neural network. Pap-smear cells are classified into 2
classes and 4 classes. Two class classification includes classification of cells in normal and abnormal cells while four-class
classification includes classification of cells in normal cells, mild dysplastic cells, moderate dysplastic cells and severe dysplastic
IMSM: An Interval Migration Based Approach for Skew Mitigation in MAPREDUCE, written by Singh et al. . This
paper proposes an algorithm for MapReduce to balance the load and eliminate the skew on Map tasks. It reduces the execution
time of job by lowering the completion time of the slowest task. Method: The proposed method performs one-time settlement
of load balancing among the Map tasks by analyzing the expected completion time of the Map tasks and redistributes the load.
It uses intervals to migrate the overloaded or slows tasks and appends them on the under loaded tasks.
Greedy Load Balancing Energy Efficient Routing Scheme for Wireless Sensor Networks written by Maratha et al. . Despite
so many constraints, the limited battery power of the sensor nodes is the core issue in Wireless Sensor Networks. This
compels how to extend the lifetime of the network as long as possible. One of the ways to solve the problem is to balance the
relay traffic load to extend the lifetime. In this paper, a load balancing algorithm is suggested that selects the best possible relay
node so that uniform consumption of the battery power of the sensor nodes can be ensured.
Graph-based Application Partitioning Approach for Computational Offloading in Mobile Cloud Computing, written by
Robin Prakash Mathur and Manmohan Sharma . Using the offloading concept, a mobile device can offload its computation
to the cloud servers and receives back the results on the device. An important question that arises in the offloading scenario is
which part of the application needs to be offloaded remotely. In order to identify that, the application needs to be partitioned. In
this paper, the graph partitioning approach is considered which is based upon the spectral graph partitioning with the Kernighan
Lin algorithm. Experimental results show that the proposed approach performs optimally in partitioning the application. The
proposed technique gave better results than the existing techniques in terms of edge cut which is less, concluding minimum
communication cost among components and thus save energy of the mobile device.
Big Data Analysis on Job Trends Using R written by Somula et al. . This work illustrates the use of data mining and
advanced data analysis techniques such as data aggregation, summarization along with data visualization using R tool to understand
and analyse the job trends in the United States of America (USA) and then drill down to analyse job trends for data science-
related job positions from year 2011 to 2016.
Role of Self Phase Modulation and Cross Phase Modulation on Quality of Signal in Optical Links written by Karamjit Kaur
and Anil Kumar . Among the different impairments, the present work focuses on phase modulations owing to the intensities
of signals themselves as well as the neighboring signals. It includes the influence of SPM, SPM and XPM, system parameters
like signal power, wavelength and fiber parameters like attenuation coefficient, dispersion coefficient and their influence on Qvalue
and BER. The analysis is done through a single and two-channel transmitter system with varied power, wavelengths and
system parameters. The corresponding optical spectrums are analysed.
Impact of System Parameters of Optical Fiber Link on Four Wave Mixing written by Kumar and Kaur . The present
work aims to identify and describe the role of FWM in optical networks. The mathematical model of FWM is studied to know
the parameters influencing the overall impact on system performance. The power of optical source, channel spacing, distance of
transmission and presence of dispersion are considered as key factors influencing FWM power being developed. Their impact
on FWM power and hence, FWM efficiency is calculated. In addition, the influence of FWM on Quality of transmission is
quantified in terms of BER and Q-factor.
TraCard: A Tool for Smart City Resource Management based on Novel Framework Algorithm written by Singh et al. .
The model proposed in the paper captures the necessity of development of an efficient method that considers the finiteness of
fossil fuels by monitoring the distribution of fuel and its consumption. The purpose of this project is to save energy with aim of
AI Engine managed logistics and goal of creating Energy-Efficient survival of the human species.
Resource Efficient Deployment and Data Aggregation in Pervasive IoT Applications (Smart Agriculture) written by Zahoor
and Naaz . For heterogeneous scenarios, we propose a clustering approach, Superior Aggregator Resource Efficient Clustering
(SAREC), to address the resource constraints in pervasive Edge-IoT applications. The comparison of homogeneous and
heterogeneous networks is based on LEACH and SAREC protocols, respectively. The results show that SAREC is 25% more
efficient in energy utilization and network lifetime than LEACH. The results also show that SAREC is more efficient in terms
of storage and processing time as compared to LEACH.
The special issue contains research papers exploring novel concepts and applications related to the Internet of Things. This
issue contains research papers elaborating and exploring novel concepts and practices involved in short-range and long-range
communication technologies, data collection, analysis, processing and visualization tools from big market giants and its multifaceted
advantages in network navigability, scalability, evaluation of objects’ trustworthiness, service composition, object discovery,
behavior classification and prediction, giving an accelerated momentum for becoming one of the most popular future
In this special issue, we aim to focus on recent research related to the Internet of Things methods and applications where we
selected research papers after a peer-review process conducted by a team of domain experts. These papers deal with applying SI
techniques in the area of Internet of Things, Cloud computing, Vehicle networks, intelligent networks and security.
SUMMARY OF ACCEPTED PAPERS
This Special issue contains 4 papers that are briefly discussed as follows:
The article by Sivakumar, Veeramani, Pandi and Ganesh Gopal  “A Novel Encryption of Text Messages using Two Fold
Approach” proposes that the amount of digital data created and shared via the internet has been increasing every day. Though
there are several cryptosystems to secure the information, in the proposed security framework, there is a necessity to introduce
new methods in order to protect information from the attackers. A simple encryption method using binary tree traversals and
XOR operation is developed. Encrypting data using binary tree traversals is a different way compared with other traditional
encryption methods. The proposed method is fast, secure and can be used to encrypt short messages in real-time applications.
The article by Bhavani and Srimathi , titled “Optimal adaptive data dissemination protocol for VANET road safety using
optimal congestion control algorithm” presents a vehicular ad-hoc network (VANET) to disseminate traffic information of the
data gathered, and road conditions are forwarded from source vehicle to many destination vehicles on the road. The process of
data dissemination plays an important role in VANET and is used to improve the quality of travelling to avoid unwanted accidents.
The suggested OAddP protocol performs very efficiently when compared with the existing protocols in terms of end-toend
delay, success ratio, redundancy rate, collision rate, number of control OH messages, propagation distance and dissemination
The article titled  “An Accomplished Energy Aware Approach for Server Load Balancing in Cloud Computing” by Alekhya
Orugonda and Dr. V. Kiran Kumar, represents a method for cloud computing, which is the consignment of on-demand
computing services from applications to storage and processing power consistently over the internet and on a pay-as-you-go
basis. The comforts of our day-to-day life almost depend on cloud efficiency. Cloud efficiency means ensuring the finest possible
use of cloud resources at minimum cost. The designed EACLBT (Energy-Aware Cloud Load Balancing Technique) deploys
the virtual machines for power saving purposes. The average power consumption is used as performance metrics and the
result of PALB is used as a baseline. The EACLBT can reduce the number of power-on physical machines and average power
consumption compared to other algorithms with power saving. It exhibited that an idle server consumes approximately 70% of
the power consumed by the server running at the full CPU speed.
The article titled, “Vedic Arithmetic based High Speed & Less Area MAC Unit for computing devices” by Selvakumar
Jayakumar, Prithiviraj Rajalingam, Rizwan Patan and Manikandan Ramachandran  presents some rapid improvements in the
technology that have enabled the design of high-speed devices, modified computational elements for FPGA implementation.
With complexity increasing day-to-day, there is a demand for modified VLSI computational elements. Basically, for the past
decade, an improvement in the basic VLSI Operators like adder, and multiplier is significant. The basic multiplication operator
is completely refined for FPGA implementation. Results were found very promising and a complete working tool for translation
Collectively, these 4 papers illustrate various issues related to the Internet of Things and Internet applications, which can be
dealt with using IoT processing, cloud computing processing, security, expert systems and network intelligence. It is expected
that these papers will help provide the prospective researchers with valuable resources and motivate them to work on advanced
and challenging issues related to similar research domain. With this special issue, there is strong, convincing evidence that the
Internet of Things and computing Intelligence can play a crucial role in proposing the solutions of multi-disciplinary challenging
problems with appreciable results.
Cognitive Computing focuses on mimicking human behavior and reasoning to solve complex problems where the answers
may be ambiguous and uncertain. AI augments  human thinking to solve complex problems. It focuses on providing accurate
results. The phrase cognitive computing is closely associated with IBM's cognitive computer system, Watson. The goal of cognitive
computing is to simulate human  thought processes in a computerized model. Using self-learning algorithms that use
data mining, pattern recognition and natural language processing, the computer can mimic the way the human brain works.
Cognitive tools are generalizable computer tools that are intended to engage and facilitate cognitive processing. Cognitive
computing systems can analyze and combine more information on a topic than any one person could ever be expected to
The special issue of the journal titled "Recent Advances in Computer Science and Communications" is an excellent collection
of review and research articles in the field of cognitive computing, its methodologies and applications. A call for the paper
was issued for this special issue. The guest editors feel happy to announce this special issue of the most reputed journal of Bentham
From a wide range of interesting research papers on various aspects of cognitive computing, the guest editors, after undergoing
exhaustive peer-reviews from experienced and well-known reviewers, have carefully selected 26 research papers out of
43 submitted papers. The final decision for the inclusion of 26 research papers has been strictly based on the outcome of the
rigorous peer-review process, shortlisting successful research papers by researchers as per reviewers' comments and guidelines.
Resilient, scalable and extensible mission-critical networks are used to interconnect datacenters, enterprise, customer sites
and mobile entities. Fault tolerance, reliability and availability are the important issues addressed by researchers to ensure the
smooth delivery of services by mission critical networks in emergency and disaster scenarios [1, 2]. In this special issue, we
aim to highlight the recent trends in fault-tolerance, reliability and availability for the design of mission-critical network and
services. The role of artificial intelligence based techniques have also been highlighted for the optimization and solving the
problems in developing mission-critical systems and services. All the 13 papers of the Special issue have been selected after an
exhaustive reviewing process conducted by the team of renowned experts in the field. These papers deal with the recent techniques
and trends in mission-critical systems with reference to fault-tolerance, reliability and availability.
In “Summary of Accepted Papers” section, we present a brief summation of the selected papers for this special issue and
“Conclusion” section provides concluding remarks.
SUMMARY OF PAPERS
The article “A Review of Cloud Computing Adoption Issues and Challenges” by A. Dhanapal and P. Nithyanandam 
covers the broad classification of the issues and challenges faced by the organization to adopt the cloud computing model.
The article “Malicious Route Detection in Vehicular Ad-hoc Network using Geographic Routing with Masked Data” by P.
Saravanan, R. Logesh, V. Vijayakumar, V. Subramaniyaswamy, and G. Xiao-Zhi  proposes Geographic Routing Protocol
for malicious route detection in Vehicular Ad-hoc Network with masked data.
The article “Cost-Aware Ant Colony Optimization for Resource Allocation in Cloud Infrastructure” by Punit Gupta, Ujjwal
and Vaishali  has proposed a novel a learning-based cost efficient algorithm for cloud infrastructure. The proposed algorithm
has been compared with existing Round Robin and ACO algorithm.
The article “Machine Learning Based Support System for Students to Select Stream (Subject)” by Kapil Sethi, Varun
Jaiswal and Mohd Dilshad Ansari  proposes different machine learning algorithms were developed to support the students to
The article “Performance Analysis of DCF-Two Way Handshake vs RTS/CTS During Train-Trackside Communication in
CBTC based on WLAN802.11b” by Bhupendra Singh and Rajesh Mishra  handles four-way handshake (FWH), request to
send (RTS) and clear to send (CTS) delay with better packet delay time.
The article “An Energy Efficient Routing Protocol Based On New Variable Data Packet (VDP) Algorithm for Wireless
Sensor Networks” by Veervrat Singh Chandrawanshi, Rajiv Kumar Tripathi, Rahul Pachauri and Nafis Uddin Khan  proposes
an energy-aware algorithm for the transmission of variable data packets from sensor nodes to the base station according to
the balanced energy consumption by all the nodes of a WSN.
The article “Brain Tumor Detection from MR Images Employing Fuzzy Graph Cut Technique” by Jyotsna Dogra, Shruti
Jain, Ashutosh Sharma, Rajiv Kumar and Meenakshi Sood  presents an approach for the automatic segmentation of brain
MRIs by selecting the seed points and employing fuzzy graph cut technique.
The article “SEGIN-Minus: A New Approach to Design Reliable and Fault-Tolerant MIN” by S. Gupta and G. L. Pahuja
 presents new reliable MIN named as a (Shuffle Exchange Gamma Interconnection Network Minus) SEGIN-Minus, which
provide reliability and fault tolerance with less number of stages.
The article “ANN-Based Relaying Algorithm for Protection of SVC- Compensated AC Transmission Line and Criticality
Analysis of a Digital Relay” by Farhana Fayaz and G.L. Pahuja  presents the protection of transmission line compensated
with static VAR compensator (SVC) and criticality ranking of different failure modes of a digital relay is carried out.
The article “An Intelligent Resource Manager Over Terrorism Knowledge Base” by Archana Patel, Abhisek Sharma and
Sarika Jain  makes an effort at creating the largest comprehensive knowledge base of terrorism and related activities, people
and agencies involved, and extremist movements; and providing a platform to the society, the government and the military
personnel in order to combat the threat of the global menace terrorism.
The article “Dimensionality Reduction Technique in Decision Making Using Pythagorean Fuzzy Soft Matrices” by Rakesh
Kumar Bajaj and Abhishek Guleria  presents a technique for finding a threshold element and value for the information provided
in the form of Pythagorean fuzzy soft matrix. A comparative analysis in contrast with the existing methodologies has also
The article “Optimization of PV Based Standalone Hybrid Energy System using Cuckoo Search Algorithm” by Vinay
Anand Tikkiwal, Sajai Vir Singh and Hariom Gupta  deals with the design and optimization of a stand-alone hybrid renewable
The article “Probabilistic and Fuzzy based Efficient Routing Protocol for Mobile Ad Hoc Networks” by M.M. Agarwal,
Hemraj Saini and M.C. Govil  proposes a new energy efficient routing protocol for best route selection using fuzzy logic
from multiple routes with efficiency in overheads and energy consumption.
Collectively, these 13 papers present the diverse range of issues regarding mission critical systems, network and services
with reference to the recent trends in artificial intelligence techniques for fault-tolerance, reliability and availability. With this
special issue, there is a strong convincing evidence that fault-tolerance, reliability and availability with artificial intelligence
techniques plays an important role towards solving mission critical problems with encouraging results. We hope that the quality
research work published in this special issue will be able to serve the concerned humanity, science and technology.
We would like to thank the Editor-in-Chief of the journal, for his continuous support for completing this issue. The Guest
Editors are thankful to the authors and reviewers who contributed to this special issue with their scientific work and useful
comments, respectively. Moreover, the guest editors also want to thank Mr. Ashutosh Sharma, Research Scholar, JUIT, India
for his back end support for publicizing and completing the SI.
The special issue contains research papers elaborating advancements in Swarm Intelligence for optimizing problems in the
Next Generation Networks. Swarm Intelligence [1-3], as demonstrated by natural biological swarms, exhibits numerous powerful
features that are desirable in many engineering systems, such as communication networks. In addition, new paradigms for
designing autonomous and scalable systems may results from analytically understanding and extending the design principles
and operations in intelligent biological swarms. The communication network management is becoming increasingly difficult
due to the increase in network size, topological changes, complexity and security. A new class of algorithms, inspired by swarm
intelligence, is currently developed that can solve numerous problems related to the communication networks, and these algorithms
are optimized enough to rely on the interaction of a multitude of simultaneously interacting agents.
In this special issue, we aim to highlight the importance of Swarm Intelligence based optimized algorithms for solving problems
and optimizing next generation communication networks.
The special issue contains 5 papers, selected after a vigorous reviewing process conducted by the team of renowned Swarm
Intelligence and Communication networks experts. These papers deal with applying the SI based techniques in the area of
In “Summary” section, we present a brief summation of the selected papers for this special issue (Part-3) and “Conclusion”
section provides concluding remarks.
This Part-3 of the Special issue contains 5 papers, that are briefly discussed as follows:
The article “Tree-based Ant Colony Optimization Algorithm for Effective Multicast Routing in Mobile Adhoc Network” by
Priyanka Sharma, Manish Kumar Nunia, Madhushree B and Sudeep Tanwar  proposes an ACO based approach for the optimization
of QoS based multicast routing algorithm for multimedia streaming applications. The routing protocol being proposed
is simulated as the tree structure where the nodes are stations and the edges are links. Simulation-based-results state that
proposed approach is better in performance as compared to AntNet due to trace maintenance, tree approach for path selection
and implementation of local and global update of pheromone values.
The article “Determining Network Communities based on Modular Density Optimization” by Seema Rani and Monica
Mehrotra  addresses the problem of the resolution limit posed by modularity as fitness function and novel algorithm is proposed
using discrete bat algorithm. To test the novelty of algorithm, experimentation was conducted on four real-world datasets
and it was observed that proposed algorithm is better as compared to the traditional and evolutionary community detection algorithms
in terms of number of communities, maximum modularity and average modularity.
The article “Learning-Based Task Scheduling Using Big Bang Big Crunch for Cloud Computing Environment” by Pradeep
Singh Rawat, Priti Dimri and Punit Gupta  proposes a meta-heuristic approach-based cost-aware algorithm using the Big-
Bang Big-Crunch for reducing the execution time and cost paid for resources in cloud computing. The results are compared
with Genetic Algorithm and it was found that proposed algorithm has better performance in terms of time and cost.
The article “Catechize Global Optimization through leading Edge Firefly based Zone Routing Protocol” by Neha Sharma,
Sherin Zafar and Usha Batra  proposes a novel protocol i.e. FRA-ZRP to improvise the performance of zone routing protocol
by reducing the amount of reactive traffic to provide solution to degraded network performance in case of large networks. In
addition to this, researchers have made use of Firefly algorithm to achieve global optimization. The proposed approach is tested
using simulation and it was observed that FRA-ZRP is better as compared to Traditional ZRP and RA-ZRP in terms of End-to-
End delay, route aggregation and overall QoS in MANETs.
The article “Into the World of Underwater Swarm Robotics: Architecture, Communication, Applications and Challenges”
by Keerthi K.S, Bandana Mahapatra and Varun G. Menon  provides comprehensive review of the Underwater Swarm Robotic
Technology and the paper outlines concepts, technical background, architecture and communication mediums and also
highlights the various issues and challenges surrounding underwater swarm robots.
Collectively, these 5 papers illustrate the diverse range of issues regarding Communication Networks which can be solved
via applying Swarm Intelligence techniques. It is expected that these papers can provide strong base to researchers with valuable
resources and motivation to work on more advanced challenging issues matching this research. With this special issue, there
is a strong convincing evidence that Swarm Intelligence plays a crucial role towards optimizing tremendous problems in Communication
Networks with encouraging results.
We would like to thank the previous Editor-in-Chief of the journal, Professor Hamid Mcheick for his huge support for this
issue. Our special thanks go to all the editorial staff, especially Wajeeha Syed, Wajeeha Ahmed and Raheela Anjum for their
valuable and prompt support throughout the preparation and publication of this special issue. We express our deep thanks to all
authors for their novel contributions to this special issue. We also extend our thanks to all reviewers for their time devotion,
hard work and on-time precision response to ensure high quality review of the accepted papers.
Over the past few decades, swarm intelligence has emerged as a powerful approach to solving optimization as well as other
complex problems in the real world. Swarm Intelligence models are inspired by social behaviours of simple agents interacting with
each other as well as with the environment, e.g., foraging behavior of ants and bees, flocking of birds, schooling of fish, etc. [1-3].
The collective behaviours that emerge out of the interactions at the colony level are useful in achieving complex goals.
Algorithms, applications and methodologies of the Swarm Intelligence approach explore the emerging realm of swarm intelligence
that finds its basis in the natural behaviour of animals.
The special issue of the Journal titled “Recent Advances in Computer Science and Communications” is an excellent collection
of review and research articles in the field of swarm intelligence-related algorithms, methodologies and applications. An
open call for paper was issued for this special issue. The guest editors feel happy to announce this special issue of the most reputed
journal of Bentham Science.
From a wide range of interesting research papers on various aspects of swarm intelligence, the guest editors, after undergoing
exhaustive peer-reviews from experienced and well-known reviewers, have carefully selected 6 research papers and 1 review.
The final decision for the inclusion of 6 research and 1 review papers has been strictly based on the outcome of the rigorous
peer-review process, shortlisting successful research papers by researchers as per reviewers’ comments and guidelines.
A brief summary of the research papers included in this special issue is enlisted as follows:
The first article by Ranjendra Singh, Anurag Singh and Arun Solanki  titled “A Binary Particle Swarm Optimization for IC
floorplanning” proposed a novel SI based algorithm “Binary Particle Swarm Optimization” combined with floor plan representation
to optimize the area and wire length for a fixed outline floorplan. The experimental results on the Microelectronic Center of
North Carolina (MCNC) validated the proposed BPSO algorithm towards better convergence for area and wire length optimization,
as compared to other meta-heuristic algorithms. The results obtained were compared with the solutions derived from other
meta-heuristic algorithms, and it was found that area is improvised up to 10% and the wire length is improvised up to 28%.
The second article by Amandeep Kaur Virk and Kawaljeet Singh  titled “On Performance of Binary Flower Pollination
Algorithm for Rectangular Packing Problem” assessed the performance of recent metaheuristic approach named “Binary Flower
Pollination Algorithm” for rectangle packing optimization problem, which was employed to search the optimal placement
order and optimal layout. The algorithm was tested on benchmark datasets and the simulation results proved that the performance
of binary flower pollination algorithms is the best as compared to other existing metaheuristic approaches.
The third article by Sandeep Kumar, Anand Nayyar, Nhu Gia Nguyen and Rajani Kumari titled  “Hyperbolic Spider
Monkey Optimization Algorithm” studied various perturbation techniques used in spider monkey optimization algorithms and
proposed a novel algorithm titled “Hyperbolic Spider Monkey Optimization Algorithm” inspired by hyperbolic growth function.
The proposed algorithm was tested over a set of 23 CEC 2005 benchmark problems and it was observed that the proposed
algorithm is better as compared to other approaches in terms of improved perturbation rate, desirable convergence precision,
rapid convergence rate and improved global search capability.
The fourth article by Avinash Kaur, Pooja Gupta and Manpreet Singh titled  “A Data Placement Strategy Based on Crow
Search Algorithm in Cloud Computing” proposed a novel data placement strategy based on Crow Search Algorithm (CSA) to
dynamically distribute the data sets to appropriate data center’s during the runtime stage of the workflow. Simulation-based
results proved that the CSA outperforms in locating the best data center for data placement for best workflow management as
compared to other algorithms.
The fifth article by Asima Kukkar and Rajni Mohana titled  “Bug Report Summarization by using Swarm Intelligence
Approaches” proposed a novel approach for the extraction of crucial information from extensive reports to summarize the problem
in short description. The objective of this paper was to generate an unsupervised extractive bug report summarization system
to apply on any dataset without much effort and high cost for creating manual summaries of dataset, to handle comments
and summaries in an effective manner, reduce data sparsity, information and redundancy for lengthy data set and to provide
accurate summary information. The proposed approach was tested with other supervised and unsupervised approaches and it
was concluded that the Hybrid swarm intelligence approach provides better results.
The sixth article by Soniya Lalwani, Harish Sharma and Kusum Deep titled  “An Implementation of Three-Level Multi-
Objective ABC Algorithm for RNA Multiple Structural Alignment” presented Artificial Bee Colony algorithm based threelevel
multi-objective approach for performing structural alignment of RNA sequences i.e. MO-3LABC. MO-3LABC algorithm
was compared with MO-TLPSO algorithm and results were compared for pairwise and multiple sequence alignment datasets for prediction accuracy and solution quality criteria. It was proved that MO-3LABC outperforms MO-TLPSO in all evaluation
The seventh article by Chinwe Igiri, Yudhveer Singh and Ramesh F.C. Poonia titled  “A Review Study of Modified
Swarm Intelligence: Particle Swarm Optimization, Firefly, Bat and Gray Wolf Optimizer Algorithms” explored the improvement
strategies of various swarm intelligence algorithms with regard to PSO, Firefly, Bat and Gray Wolf optimizer with a primary
objective to understand the trends and relationships among their performance.
The main aim of this special issue is to enlighten the researchers regarding the latest methodologies, algorithms and applications
with regard to Swarm Intelligence. It is expected that these papers can benefit students, researchers and academicians to
do advanced work in the area of swarm intelligence. With this special issue, there is a strong convincing evidence that Swarm
Intelligence plays a crucial role in optimizing tremendous problems in diverse areas of computer science.
We would like to thank the Editor-in-Chief of the journal, Professor Francesco Benedetto for his huge support for this issue.
Our special thanks go to all editorial staff, especially Wajeeha Syed, Wajeeha Ahmed and Raheela Anjum for their valuable
and prompt support throughout the preparation and publication of this special issue. We express our deep thanks to all authors
for their novel contributions to this special issue. We also extend our thanks to all the reviewers for their time, devotion, hard
work and on-time precision response to ensure the high-quality review of the accepted papers.