ISSN (Print): 2666-2558
ISSN (Online): 2666-2566
Volume 13, 6 Issues, 2020
ISSN (Print): 2666-2558
ISSN (Online): 2666-2566
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12 Abstract Ahead of Print are available electronically
242 Articles Ahead of Print are available electronically
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.