ISSN (Print): 2210-3279
ISSN (Online): 2210-3287
Volume 11, 9 Issues, 2021
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Special Issue Submission
Blockchain Technologies for Internet of Things (IoT)
Guest Editor(s): Mohammad Tabrez Quasim, Mohammad Ayoub Khan, Prashant Johri
Submit Abstract via Email
It was a pleasure for me to submit my research work to be published by Bentham Science. You have got a professional team who always keeps me updated with my paper progress.
I wish you all the best with such a team, and keep it up.
The current era is evolving with the synergy between the physical systems, components and the computational technologies.
A Cyber-Physical System is a collection of physical world systems or devices interacting and communicating with each other
for their operations. CPS integrates the concepts of computation, communication and control for operations and monitoring of
physical systems. The cyber-physical systems can have dynamic and distributed subsystems that have the auto-connection and
self-operating capability. Engineered cyber-physical systems are booming and have been studied in robotic networks, power
grids, communication networks, and sensor networks. Those systems have proven their excellence and are encouraged for its
use in industrial automation, rescue mission, robotic surgeries, robotic surveillance, environmental monitoring and sensing, etc.
The CPS integrates physical systems in applications used in almost all the areas such as industrial manufacturing systems,
transportation systems, medical devices, military networks, home area networks, smart grid, smart buildings, etc. The thematic
issue on “Internet of Things (IoT) and Cyber Physical Systems (CPS) for Smart Applications “discusses on the recent advances
and literature survey of various designing, modeling, specification, analysis and verification of IoT and CPS applications.
The technical aspects in the thematic issue cover the interdisciplinary fields of science covering wide range of topics and
applications. The first article titled “Detection of Obstructive Sleep Apnea using Internet of Things: A Review” authored by
MK Sandhya, S Sathya Priya and S. Prasidh demonstrates the various non-invasive schemes using sensors and Internet-of-
Things to detect Obstructive Sleep Apnea . Further, the open research issues and challenges in detecting Obstructive Sleep
Apnea are also presented in the paper. The second article is authored by M. Durga Rao and I. Srinivasa Rao entitled “Design
and Development of Wide Beam width Antenna for Ionosphere Wireless Remote Sensing Applications” in the issue puts
forward the study of a designed wide beam width antenna for ionosphere wireless remote sensing applications. The article also
discusses the new approach devised for the first time to design the two element, wide beam width tilted Yagi antenna, where
folded dipole acts as active driver element and reflector as parasitic element . The peak power handling capability of up to
1kW by the system shows the reliable system design can be used continuously for long term use. The third article authored by
T.S Pradeep Kumar, and P. Venkata Krishna entitled “A Survey of Energy Modeling and Efficiency Techniques of Sensors for
IoT Systems” discusses on a survey of the power modeling techniques of sensors in IoT systems. Some of the techniques that
are studied and surveyed in the paper are transmission power modeling, power modeling of the sensor for sensor subsystems
and IoT systems, clustered approach, energy harvesting models and transmission distance modeling .
I acknowledge all the contributors such as authors and reviewers who have given immense efforts in bringing the qualitative
articles of the scope in the issue. I also thank the editorial board of International Journal of Sensors, Wireless Communications
and Control, Bentham Science for their support and approval for the publications.
I am delighted to write a foreword for this special issue on “Advances in wireless Communication, network and
Automation” for International Journal of Sensors, Wireless Communications and Control. The recent trends and emerging
advance in the field of wireless communications, network technology, automation and control of the systems are playing a
pivotal role in the field of engineering and opening up plethora of applications in diverse and promising areas. The wider areas
of applications encompass cellular communications, LTE, 4G and 5G, satellite communications, wireless communication
networks, social networks, delay tolerant networks, wireless sensor networks, vehicular networks, smart antennas,
beamforming, molecular communications, and other new trend topics about wireless communications and networking.
Recently, the advances in various wireless communication protocols in technologies such as 5G, RFID, Wi-Fi-Direct, Li-Fi,
LTE, and 6LoWPAN have greatly boosted the potential capabilities of networking and communication and made it become
more prevalent than ever, with emerging technologies in other areas such as sensing, wireless recharging, data exchanging, and
In the paper “Pre-deployment Strategy for Maximizing Barrier Coverage in Wireless Sensor Network” authors have
proposed a novel Minimum Radius Algorithm for maximizing the barrier coverage and increasing the operating life of the
network by reducing the energy consumption of sensor nodes.
In the paper “Piezoelectric Energy Harvesting Methodologies using Ambient Mechanical Vibration: Design perspective and
challenges”, the major advancement made in the field of micro-electromechanical systems based piezoelectric energy harvester
to extract ambient vibrations and convert them into usable electric power have been discussed. Increasing power generation of
piezoelectric energy harvesting and development of low power CMOS technology has brought the supplied power requirements
and required power level adjacent to one another.
In the next research article “Circular Slotted Antenna with CPW feed for GSM and UWB Applications” a study is supported
out to design a planar, cost-effective, dual-band, small and manufacture compatible unified GSM-UWB band antenna for
applications using these UWB antennas such as modern civil and military applications, wireless and radar communications, etc
In the research paper “An Efficient 4X4 Mesh Structure with a Combination of Two NoC Router Architecture”, a new
combination of two routers is used i.e. conventional and proposed router architecture and analyzed, which shows significant
area reduction as compared to the conventional model and there is no effect on delay and power requirement.
In the coming era it will become central to emerging technologies including robots, drones, self-driving vehicles and new
medical devices over the next five years. Considering the manifold and wide ranging applications of this field, the objective of
this special session is to provide the researchers a platform to present the state of the art innovations, researches, design and
implement methodological and algorithmic solutions for wireless communication, and network control systems.
The editor would like to express her sincere gratitude to all the editorial board members and reviewers for their generous
contribution towards publication of this issue.
The rapid expansion of network technologies, IoT, cloud computing, and big data promotes unprecedented advances in
signal processing and information system. Such advances support the development of sensing technologies, as well as softwaredefined
networks. The purpose of this special issue is to solicit manuscripts on the emerging trends, issues, and challenges in
sensor, cloud, and wireless technologies. It also aims to bring together researchers, practitioners, and decision‐makers from
academia, industry, the non-profit sectors, and the government who have expertise in the field of network computing and
systems in order to share their knowledge.
This thematic special issue on “Innovations in Network Technologies” incorporates eight (8) articles identified with the
field. A short review about the commitments for this thematic special issue is as follows:
1. Substrate Integrated Waveguide Based Leaky Wave Antenna for High-Frequency Applications and IoT by Manvinder
Sharma, Harjinder Singh. They claimed that the Internet of Things devices are managed by wireless networks so that higher
data rates can be achieved. There is an increase in the usage and demand of the Internet, and microwave signals are capable of
delivering that demand. However, these high-frequency waves need a waveguide to propagate. Otherwise, they get affected due
to atmospheric attenuation and rain fade. A modified structure of rectangular waveguide named as Substrate Integrated
Waveguide (SIW) is used. In this paper, work has been carried out taking SIW and Leaky Wave Antenna. The dielectric
substrate was taken as carbon. Modelling of SIW Leaky Wave Antenna is done by making C shaped slots. Design steps for
modelling LWA were orderly pursued and optimized with various equations followed by Finite Element Method based
modelling. A range of frequency as input is taken from 7 GHz to 11 GHz to analyze the design modelled .
2. An Adaptive Fault-Tolerant and Congestion Controlled Selection Strategy for Network-on-Chip by Ashima
Arora, Neeraj K Shukla, Shaloo Kikan. They claimed that network-on-chip is being developed as a communication
infrastructure in the design of multiprocessor SOCs. With the reduction in feature size, transient faults on the links are
becoming a major issue in the performance of NOCs. In this paper, two fault-tolerant algorithms are proposed. In the
first algorithm, a faulty link tolerant algorithm is designed, which by measuring network loads on the links will reduce
transient faults and balance the load. To address the effect of hardware faults, a fault and congestion-controlled
algorithm is designed that controls the congestion and the faults on both links and the nodes .
3. Performance Analysis of Energy-Efficient Opportunistic Routing Protocols in Wireless Sensor Network by
Premkumar Chithaluru, Rajeev Tiwari, Kamal Kumar. They claimed that energy-efficient wireless routing had been an
area of research particularly to mitigate challenges surrounding performance in the category of wireless networks. The
Opportunistic Routing (OR) technique was explored in recent times. It exhibited benefits over many existing protocols
and could significantly reduce energy consumption during data communication with limited compromise on performance.
Using the broadcasting nature of the wireless medium, OR practices to discourse two foremost issues of variable link
quality and unpredictable node agility in constrained WSNs. OR has a potential to reduce delay in order to increase the
consistency of data delivery in network. Various OR-based routing protocols have shown varying performances .
4. Survey of Radio Propagation Models for Acoustic Applications in Underwater Wireless Sensor Network by
Preeti Saini, Rishi Pal Singh, Adwitiya Sinha. They claimed that acoustic waves offer communication opportunities to a
large number of acoustic applications, including underwater monitoring, disaster management, military surveillance,
assisted navigation, etc. Acoustic waves are used primarily for underwater wireless communication owing to their unique
features. Hence, the need for a suitable propagation model arises that requires effective design compatibility with the
underwater sensor network. Generically, the propagation model predicts the average received signal strength at a given
distance from the transmitter and the variability of the signal strength in close spatial proximity to a particular location.
Various radio propagation models are developed for air. The characteristics of EM waves in water are not the same as
those in the air. Many parameters that are real-valued in the air become complex-valued in seawater. Thus, propagation
models for air have to be modified to calculate propagation loss underwater. Various radio propagation models are
developed for water by Al-Shamaa’a et al., Uribe and Grote, Jiang et al., Elrashidi et al., Hattab et al. The paper presents
a comparative analysis of these various radio propagation models developed for underwater. Among these models, the
radio propagation model by Hattab et al. is more realistic and covers both propagation loss and interface loss. According
to the authors, it is the first radio propagation model developed for UWSNs .
5. Performance analysis of Cluster-based DDoS Defense System with different Reactive Routing Protocols by
Deepa Nehra, Kanwalvir Singh Dhindsa, Bharat Bhushan. They claimed that DDoS attack poses a considerable threat
to communication and security of mobile nodes in MANETs. The number of approaches proposed for defense against
DDoS attacks in MANETs is much less as compared to those for the wire-based networks. The scheme proposed here
is a clustering-based DDoS defense mechanism, in which cluster heads perform the task to identify and filters the
attack-related traffic. In each cluster, cluster heads use flow-based attack detection algorithm to identify the presence
of DDoS attacks. The attack detection algorithm performs various tasks like monitoring, characterization, and
identification of attack traffic from the incoming flow with the help neighbouring cluster heads .6. A Hybrid Approach For Automatic Licence Plate Recognition System by Nitin Sharma, Pawan Kumar Dahiya,
Baldev Raj Marwah. They claimed that automatic license plate recognition systems are used for various applications
such as traffic monitoring, toll collection, car parking, and law enforcement. In this paper, a convolutional neural
network and support vector machine-based automatic license plate recognition system is proposed. Firstly, the
characters are extracted from the input image of the vehicle. Then characters are segmented, and their features are
extracted. The extracted features are classified using a convolutional neural network and support vector machine for
the final recognition of the license plate. The obtained recognition rate by the hybridization of the convolutional neural
network and the support vector machine is 96.5%. The recognition rate obtained for the proposed hybrid automatic
license plate system is compared with three other automatic license plate systems based on neural network, support
vector machine, and convolutional neural network .
7. An Energy-efficient and Reliable Opportunistic Routing for Wireless Sensor Networks by Nagesh Kumar,
Yashwant Singh. They claimed that routing protocols in wireless sensor networks (WSN) are of major concern because
of energy efficiency and reliability as important factors. Opportunistic routing (OR) is the simplest and most reliable
routing technique for all ad-hoc networks like WSN. OR also guarantee the data delivery in the network. As WSN
need energy-efficient routing, energy-efficient OR protocols gained popularity in the last three years. Opportunistic
routing improves the performance of the network by utilizing the broadcasting abilities of wireless channels. In this
paper, new energy-efficient and reliable routing protocol has been proposed which is based on the opportunistic
routing technique. The proposed protocol is based on the energy-efficient routing metric. The proposed OR protocol is
prioritized among the candidate forwarders on the basis of energy-efficient routing metric .
8. Brain Segmentation Using Deep Neural Networks by Vandana Mohindru, Ashutosh Sharma, Apurv Mathur, Anuj
Kumar Gupta. They presented a fully functional automatic brain segmentation method in this paper, which uses the
Deep Neural Networks (DNNs). The offered network is customized to glioblastoma sarcoma and metastatic
bronchogenic carcinoma  tumors pictured in MRI images. Tumors can be of various sizes and shapes. They can
also contrast anywhere in the brain. These causes inspire our investigation of machine learning, i.e., using a deep
neural networks solution that utilizes a bendable, high capability DNN  while being outstandingly effective. We are
using a 3‐D image segmentation approach in our paper for the totally computerized recognition and description of the
gross anatomical shape of the human brain based on their look in magnetic resonance images (MRI). A 3D digital
method of human brain anatomy and general hierarchical non-linear registration procedure approach is used to contain
the volumetric intensity-based data. We are using a fuzzy c-mean algorithm for brain tumor segmentation because it is
faster than the k-mean algorithm or any other algorithm .
Internet of Things (IoT), Cloud, Big Data and AI-Machine Learning are topics of contemporary research interest. They
cover not only information and communication technology, but also all kinds of systems in our society, including business,
finance, industry, manufacture, management, and environment. IoT connects the physical world to the Internet and generates
big amount of data. Cloud computing environment facilitates the processing of large data and makes intelligent decisions based
on large data analyses and machine learning. This Thematic Special Issue on IoT, Cloud, Big Data and Machine Learning:
Recent Advances and Future Trends of the Journal International Journal of Sensors, Wireless Communications and Control
incorporate thirteen (13) articles identified with the field. A short review about the commitments for this Thematic Special
Issue is as follows:
1. P. Chandrashaker Reddy and A. Suresh Babu contribute an article entitled “An Enhanced Multiple Linear Regression Model
for Seasonal Rainfall Prediction”. The main goal of this project is early and proper rainfall forecasting, that helpful to people
who live in regions which are inclined natural calamities such as floods and it helps agriculturists for decision making in
their crop and water management using big data analytics which produces high in terms of profit and production for farmers.
In this project, we proposed an advanced automated framework called Enhanced Multiple Linear Regression Model
(EMLRM) with MapReduce algorithm and Hadoop file system. We used climate data from IMD (Indian Metrological
Department, Hyderabad) in 1901 to 2002 period.
2. Nguyen Thi Ngoc Anh, Nguyen Danh Tu, Vijender Kumar Solanki, Nguyen Linh Giang, Vu Hoai Thu, Luong Ngoc Son,
Nguyen Duc Loc, Vu Thanh Nam contribute an article entitled “Integrating Employee Value Model with Churn Prediction”.
The process of prediction integrating Churn, value of employee and machine learning are described detail in 6 steps. The
pros of integrating model gives the more necessary results for company than Churn prediction model but the cons is
complexity of model and algorithms and speed of computing. A case study of an organization with 1470 employee positions
is carried out to demonstrate the whole integrating churn predict, EVM and machine learning process. The accuracy of the
integrating model is high from 82% to 85%. Moreover, the some results of Churn and value employee are analyzed.
3. Charu Bhardwaj, Shruti Jain and Meenakshi Sood contribute an article entitled “Automated Diagnostic Hybrid Lesion
Detection System for Diabetic Retinopathy Abnormalities”. In this research paper, an automated lesion detection diagnostic
scheme has been proposed for early detection of retinal abnormalities of red and yellow pathological lesions. The algorithm
of the proposed Hybrid Lesion Detection (HLD) includes retinal image pre-processing, blood vessel extraction, optical disc
localization and detection stages for detecting the presence of diabetic retinopathy lesions. Automated diagnostic systems
assist the ophthalmologists practice manual lesion detection techniques which are tedious and time-consuming. Detailed
statistical analysis is performed on the extracted shape, intensity and GLCM features and the optimal features are selected to
classify DR abnormalities. Exhaustive statistical investigation of the proposed approach using visual and empirical analysis
resulted in 31 significant features. The results show that the HLD approach achieved good classification results in terms of
three statistical indices: accuracy, 98.9%; sensitivity, 97.8%; and specificity, 100% with significantly less complexity.
4. Anurag Satpathy, Ganapati Panda, Rajasekhar Gogula and Renu Sharma contribute an article entitled “Low Complexity
Adaptive Nonlinear Models for the Diagnosis of Periodontal Disease”. The paper addresses a specific clinical problem of
diagnosis of periodontal disease with an objective to develop and evaluate the performance of low complexity adaptive
nonlinear models (ANM) using nonlinear expansion schemes and describes the basic structure and development of ANMs in
detail. Diagnostic data pertaining to periodontal findings of teeth obtained from patients have been used as inputs to train and
validate the proposed models.
5. Sarat Chandra Nayak, Subhranginee Das and Mohd Dilsad Ansari contribute an article entitled “TLBO-FLN: Teachinglearning
Based Optimization of Functional Link Neural Networks for Stock Closing Price Prediction”. Stock closing price
prediction is enormously complicated. Artificial neural networks (ANN) are excellent approximation algorithms applied to
this area. Several nature-inspired evolutionary optimization techniques are proposed and used in the literature to search the
optimum parameters of ANN based forecasting models. However, most of them need fine-tuning of several control
parameters as well as algorithm specific parameters to achieve optimal performance. Improper tuning of such parameters
either leads toward additional computational cost or land at local optima. Teaching learning based optimization (TLBO) is a
newly proposed algorithm which does not necessitate any parameters specific to it. The intrinsic capability of functional link
artificial neural network (FLANN) to recognize the multifaceted nonlinear relationship present in the historical stock data
made it popular and got wide applications to stock market prediction. This article presents a hybrid model termed as teaching
learning based optimization of functional neural networks (TLBO-FLN) by combining the advantages of both TLBO and
6. Sonal Agrawal and Pradeep Tripathi contribute an article entitled “Intuitionistic Fuzzy Score Function based Multi-Criteria
Decision Making Method for Selection of Cloud Service Provider”. Cloud computing (CC) has received great attention from
the scholarly researchers and IT companies. CC is a standard that offers services through the Internet. The standard has been
manipulated by existing skills (such as collect, peer-to-peer and grid computing) and currently accepted by approximately all
major associations. Various associations like as Microsoft and Facebook have revealed momentous investments in CC and
currently offer services with top levels of reliability. The well-organized and precise evaluation of cloud-based
communication network is an essential step in assurance both the business constancy and the continuous open services.
7. Syed Rameem Zahra and Mohammad Ahsan Chishti an article entitled “A Collaborative Edge-Cloud Internet of Things
based Framework for Securing the Indian Healthcare System”. Today, 73 years after the independence and twenty years after
the turn of the century, “Health for All” which should have been accomplished by now, remains a far-fetched and an elusive
dream. Instead, the people of India are bequeathed a triple burden of disease: sustaining the weight of transmittable
infections, expanding burden of nontransferable illnesses, and a healthcare system not efficient enough to handle them both.
At present, India is home to one-third of the poor population around the world. After a high population growth rate,
unregulated and inefficient healthcare is the major cause for this abjection and poverty. The global position of India vis-à-vis
the health indicators like Infant Mortality Rate (IMR), Crude Birth Rate (CBR), Crude Death Rate (CDR) and life
expectancy is shocking, shameful and on a downward trend. The objective of this paper was to identify the major issues in
the Indian healthcare system and offer Internet of Things (IoT) based solutions.
8. Tausifa Jan Saleem and Mohammad Ahsan Chishti contribute an article entitled “Exploring the Applications of Machine
Learning in Healthcare”. The objective of the research is to help the researchers in this field to get a comprehensive overview
of the machine learning applications in healthcare. Apart from revealing the potential of machine learning in healthcare, this
paper will serve as a motivation to foster advanced research in the domain of machine intelligence-driven healthcare.
9. Cerene Mariam Abraham, M. Sudheep Elayidom and T. Santhanakrishnan contribute an article entitled “Big Data Analysis
for Trend Recognition using Machine Learning Techniques”. This paper performs big data analytics on the Indian derivative
market and identifies a trend with the help of interdisciplinary areas such as cloud computing, machine learning and
10. Mohammad Irfan Bala and Mohammad Ahsan Chishti contribute an article entitled “Comparative Analysis of Load
Balancing Algorithms for Cloud Computing in IoT”. This work focuses on multiple load balancing algorithms whose
performance has been analysed and compared under varying load conditions. Cloud computing is a widely adopted
computing paradigm and its importance has increased multi-folds in the recent past due to the inception of Internet of Things
11. Ravinder Ahuja, Vineet Maheshwari, Siddhant Manglik, Abiha Kazmi, Rishika Arora and Anuradha Gupta contribute an
article entitled “Malicious apps Identification in Android Devices Using Machine Learning Algorithms”. In this paper,
malicious apps detection system is implemented using machine learning algorithms. For this 330 permission based features
of 558 android applications are taken into consideration. The main motto of this work is to develop a model which can
effectively detect the malicious and benign apps. In this we have used six feature selection techniques which will extract
important features from 330 permission based features of 558 apps and further fourteen classification algorithms are applied
using Python language.
12. Mohammad Khalid Pandit, Roohie Naaz Mir and Mohammad Ahsan Chishti contribute an article entitled “Adaptive Deep
Neural Networks for the Internet of Things”. Deep neural networks have become the state of art technology for real world
classification tasks due to their ability to learn better feature representations at each layer. However, the added accuracy that
is associated with the deeper layers comes at a huge cost of computation, energy and added latency. The implementation of
such architectures in resource constraint IoT devices is computationally prohibitive due to its computational and memory
requirements. These factors are particularly severe in IoT domain. In this paper we propose adaptive deep neural network
(ADNN) which gets split across the compute hierarchical layers i.e. edge, fog and cloud with all splits having one or more
exit locations. At every location the data sample adaptively chooses to exit from the NN (based on confidence criteria) or get
fed into deeper layers housed across different compute layers.
13. Midde Veenkateswarlu Naik, D. Vasumathi and A.P. Siva Kumar contribute an article entitled “An Improved Intelligent
Approach to Enhance the Sentiment Classifier for Knowledge Discovery Using Machine Learning”. The objective of the
research issue sentiment classifier accuracy has been hiked with the help of Kernel-based Support Vector Machine (SVM)
based on parameter optimization is applied. The optimal feature selections to classify sentiment or opinion towards about
review documents have been determined with the help of particle swarm optimization approach. The proposed method
utilized three datasets to simulate the results such as airline sentiment data, weather sentiment data, and global warming data
that are freely available datasets.
We hope that the quality research work published in this special issue will be able to serve the concerned humanity, science
Welcome to the special issue on “Recent research in network security analytics” in
International Journal of Sensors, Wireless Communications and Control. With the ripeness
of network data and encroachment of security technologies, data analytics now-adays
plays a very significant role in our day-to-day lives. Internet is one of the leading
accomplishment of this epoch thus securing it is also a precedence.
International Journal of Sensors, Wireless Communications and Control is a peer reviewed
journal considers both theoretical and implementation based papers. Network
security and Data analytics is an important call for present society where information
technology and services pass through each facet of our lives. However, this is demanding to achieve, as technology
is changing at a rapid speed and our systems turn into ever more complex. We are gradually more dependent
upon such information and communications infrastructures, and the threats we face are organized and
exploit our dependency by the attackers or cyber criminals. Moreover, cyber space is considered as fifth battlefield
after land, air, water and space.
The aim of this issue is to provide insight mechanisms while handling data; provide conceptual understanding
of network security issues, challenges and mechanisms; develop basic skills of secure network architecture
and explain the theory behind the security of networks, analytics and different cryptographic algorithms.
It is to present the most recent challenges and developments in data analytics and networks. It also
provides a forum for researchers, practitioners and educators to present and discuss the most recent innovations,
trends, and concerns, practical challenges encountered and the solutions adopted in these fields. Original
research papers and state of the art reviews will be accepted. We anticipate that the special issue will open
new entrance for further research and technology improvements in this important area.
In this regard, the first article is devoted to investigate that current wireless networks are based on unicast
routing protocol derived from wired networks. The purpose of this paper is to implement and evaluate opportunistic
routing protocols in new generation’s wireless network. This is a comparative study between two opportunistic
protocols, which are ExOR (Extremely Opportunistic Routing protocol) and SOAR (Simple Opportunistic
Adaptive Routing protocol). The main goal of this survey is to show the benefits required by using
opportunistic approach to optimize the new generation’s wireless networks operations and implemented the
most used protocols under MATLAB framework .
The second article proposed a defense model for wireless sensor network against worms attack based on
the concept of epidemic theory. This model basically focused on mechanism which can be used for protection
of sensor network against malware attack. They derived an expression for basic reproduction number this
helps in study of worm dynamics and development of control mechanism. The stability of network depends
on the value of basic reproduction number explained the worm free and endemic equilibrium. They also find
the threshold value of communication radius and node density. Correlate the basic reproduction number and
threshold value of communication radius and study its impact in the design of wireless sensor network. Explain
the effect of quarantine and recovery on the infectious nodes with the variation of parameters and
showed that if the rate of recovery increases the number of infected nodes decreases. The quarantine class of
nodes helps in controlling of worm spread in the wireless sensor network. The proposed model is efficient in
comparison to existing model proved by simulation. This is a good idea for the development of an antivirus
for wireless sensor network against worm attack .
The third article focuses on the infrastructure less operating mechanism of MANETs is leading to their
popularity and extending their role in the operations of certain real-time applications as well as certain multi- media applications. For MANETs being able to support such applications, the prime requirement is to support
efficient routing as well as to incorporate efficient QOS mechanisms. This guides multiple research trends
towards MANET for categories like: QOS (Quality of Service), efficient Routing etc. The approach proposed
in this paper centers on the methods that can overcome the limitations faced by the Zone Routing Protocol
when used for large networks and improve QOS thus making the use of MANET in real time applications
feasible. The proffered scheme combines the advantages provided by aggregation of routes, introduce a central
entity and optimize QOS based network performance. The algorithm divides the zones into bigger zones
within the network and appoints a Zone Head node for each newly formed bigger zone which is a collection
of nodes bigger than a ZRP zone with Zone Head as the central administrator. It then aggregates the routes at
the Zone Head which works as a central entity and routes the traffic into the cluster by the help of Route aggregation
mechanism thus, enhancing ZRP performance .
In the ever evolving field of software engineering the quality and predictability of success for a project has
been of concern for Project Managers. The next article focused on this concern by proposing certain mathematical
models, designated as process performance models (PPMs), which enhance the process improvement
and improves predictability factor for a project success. Mathematical model selected can be like Queuing
Theory, Time Series, Fuzzy logic etc. based on problem specified and nature of industry data. This PPMs approach
can lead to solution for similar problems and avoids rebuilding solution every time.
The benefit which accrues with design of PPM is the ability to predict and tune the parameters affecting
performance of the project to achieve desired result. The building of these PPMs for various real life project
situations has not been attempted by industry on a large scale. In case a model does not achieve the performance
levels as specified by the project or baselines for similar projects, the model is rejected. In the real life
problem discussed, authors work out Success of a given project based on Bayesian solution for a given network
problem. Also, the authors demonstrate how to assess process capability. The solution shows that it is
possible to display a network problem with non-numeric data by a relationship among variables as parentchild
in a tree structure. The solution is based on developing conditional probability tables. PPMs can be developed
for different emerging application areas like Cloud computing, e-Governance, Application Service
Maintenance etc. and a library of models can be created by an IT company. The relevant model can be selected
by a Manager from this Library. The authors opine that in future, building PPMs may become a necessity
in High Maturity IT Organizations.
The last article explored that RF energy harvesting is getting popular in research community because it
provides useful electrical energy source for wireless sensor network applications. Its popularity is due to its
physically separated power transmitter and power receiver topology. Although the energy received using the
RF energy transfer has its own limitation of distance from the RF power transmitter but this technology provides
enough power and energy to run an ultra-low power electronics circuits. Ambient RF sources (e.g. BTS
towers, TV towers, Radio towers, Wi-Fi sources etc.) also motivate the researchers to develop RF energy
harvesters which easily match with RF sources and starts to convert RF energy into useful electrical energy.
In this article, multiple experiments have been performed over the RF energy harvesters on the base of number
of stages of multiplier, matching networks, and equivalent practical resistive load. Different stages of RF
energy harvester have been implemented and optimized. The optimization of the RF energy harvester has
been performed using the inductor and capacitor circuit used in matching network .The circuit is optimized
in terms of return power loss (S11) and total overall efficiency. In this article, the voltage multiplier is investigated
without inductor and capacitor matching network due to which maximum efficiency of 60% at 12dBm
is achieved at 9th stage of voltage multiplier and only 5% at -15dBm. Matching network with inductor (L) and
capacitor (C) has been developed to achieve better S11 and efficiency. The maximum S11 of -49dB achieved
for 3rd stage voltage multiplier while the efficiency at this value is less than 30% for -20dBm to 20dBm input
RF power range. The value of L and C for such case is 21.24nH and 6.9pF respectively. In the next experiment,
the efficiency is tried to get improved and the maximum efficiency of 3rd stage was 68% but this is
found that for this case the value of S11 is -2.4dB. For improved efficiency the value of L and C is 26.5nH
and 6.3pF, respectively. These results hold same theory for all stages of voltage multipliers. There is scope of
research by finding the value of efficiency and S11 by using fabricated modules of simulated RF energy har- vesters. The comparison with the simulated values may provide more authenticate results and new dimension
of designing of RF energy harvesters. The research helps the research community to design the more appropriate
RF energy harvester for their applications.
Finally, we would like to thank all the reviewers for their excellent work and the authors for their contribution.
We expect that International Journal of Sensors, Wireless Communications and Control will provide
the best platform for the authors and the readers, with a comprehensive overview of the most recent developments
in information management research.
In this special issue of “International Journal of Sensors, Wireless Communications and Control”, the
projection is to publish research contributions that significantly advance the state-of-the-art research, and
six research articles explore new designing techniques, methodologies, concepts and protocols.
Singh et al, presents a cloud based environment parameter monitoring system. Wireless Sensor Area
Network is developed using ZigBee and NodeMCU.
Mehta et al, analysed the benefits of Clustering when it comes to scalability and proposes an algorithm
using the clustering mechanism.
Sharma et al, examined the dataset PIDD (Pima Indian Diabetes dataset) for the model. Dataset was
trained offline using the predictive techniques SVM, Naive Bayes and K-NN. Performance analysis was
performed on the basis of response time and waiting time of a request.
Gerg et al, validated and analyzed the performance of our algorithm by using the CloudSim toolkit to
simulate the cloud environment.
Verma, focused on the second option to design an efficient RSA variant. An improved RSA variant is
designed by adding MultiPrime feature to Dual RSA on the decryption side to increase the decryption
Bazaz and Zafar, presented a technique of using GA based approach in cloud network for QOS optimization
of parameters like packet drop rate and hop count.
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