Recent Advances in Computer Science and Communications

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 technologies. 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 [1] “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 [2], 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 efficiency. The article titled [3] “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 [4] 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 was presented. CONCLUSION 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 [1] 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 [2] 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 understand. 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 Science. 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 [3] 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 [4] 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 [5] 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 [6] proposes different machine learning algorithms were developed to support the students to select stream. 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 [7] 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 [8] 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 [9] 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 [10] 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 [11] 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 [12] 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 [13] 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 been made. The article “Optimization of PV Based Standalone Hybrid Energy System using Cuckoo Search Algorithm” by Vinay Anand Tikkiwal, Sajai Vir Singh and Hariom Gupta [14] deals with the design and optimization of a stand-alone hybrid renewable energy system. The article “Probabilistic and Fuzzy based Efficient Routing Protocol for Mobile Ad Hoc Networks” by M.M. Agarwal, Hemraj Saini and M.C. Govil [15] proposes a new energy efficient routing protocol for best route selection using fuzzy logic from multiple routes with efficiency in overheads and energy consumption. CONCLUSION 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 communication networks. In “Summary” section, we present a brief summation of the selected papers for this special issue (Part-3) and “Conclusion” section provides concluding remarks. SUMMARY 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 [4] 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 [5] 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 [6] 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 [7] 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 [8] 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. CONCLUSION 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 [4] 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 [5] 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 [6] “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 [7] “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 [8] “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 [9] “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 criteria. The seventh article by Chinwe Igiri, Yudhveer Singh and Ramesh F.C. Poonia titled [10] “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. CONCLUSION 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.