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. [1]. 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. [2]. 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. [3]. 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. [4]. 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. [5]. 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. [6]. 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. [7]. 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
cells.
IMSM: An Interval Migration Based Approach for Skew Mitigation in MAPREDUCE, written by Singh et al. [8]. 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. [9]. 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 [10]. 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. [11]. 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 [12]. 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 [13]. 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. [14].
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 [15]. 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.
