International Journal of Information Technology

The Montage project of NASA introduces an efficient astronomical image mosaic processing service with the help of Montage workflow applications. These workflow applications contain a set of input astronomical images that are able to produce custom mosaics of the sky to understand the universe’s activities. In the last 2 decades, extensive research has been done for processing Montage application in the various distributed computing paradigms such as Grids and Clusters but fails to achieve the required performance in terms of makespan. Recently, Cloud computing is the latest computing paradigm that provides online computing resources for efficiently processing these applications. In this article, we introduce an efficient astronomical image processing technique (EAIPT) for Montage workflow application in the cloud environment that shows notable improvements in terms of minimization of makespan without increasing the time complexity with the help of an advance dynamic scheduler. The proposed dynamic scheduler tries to schedule the current workflow task on the virtual machine that already processed its last parent task based on proposed scheduling constraints. In this way, it bypasses the communication time among different VMs. The performance of the proposed algorithm is compared with the existing state of art algorithms. The experimental results prove that our proposed technique has significant performance over compared algorithms in terms of schedule length ratio (SLR), the percentage of best results, and average running time metrics.

The study of antennas has taken a leap in the past few decades. On the contrast to the traditional large size antennas, Microstrip patch antennas have come to the picture and have found their application in mobile phones, defense instruments, wireless wearable devices, etc. The Microstrip patch antenna have more advantages and provides better results as compared to the traditional antennas. Being lighter, foldable, easy to fabricate, multiple frequency operations, small in size, Microstrip patch antennas have replaced almost all the traditional antennas in almost all the wireless applications. The paper presents a review of different Microstrip antennas with different feeding techniques and its application over the traditional antennas.

Facial Emotion Recognition (FER) has gained popularity in recent years due to its many applications, including biometrics, detection of mental illness, understanding of human behavior, and psychological profiling. However, developing an accurate and robust FER pipeline is still challenging because multiple factors make it difficult to generalize across different emotions. The factors that challenge a promising FER pipeline include pose variation, heterogeneity of the facial structure, illumination, occlusion, low resolution, and aging factors. Many approaches were developed to overcome the above problems, such as the Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) histogram. However, these methods require manual feature selection. Convolutional Neural Networks (CNN) overcame this manual feature selection problem. CNN has shown great potential in FER tasks due to its unique feature extraction strategy compared to regular FER models. In this paper, we propose a novel CNN architecture by interfacing U-Net segmentation layers in-between Visual Geometry Group (VGG) layers to allow the network to emphasize more critical features from the feature map, which also controls the flow of redundant information through the VGG layers. Our model achieves state-of-the-art (SOTA) single network accuracy compared with other well-known FER models on the FER-2013 dataset.

5G-distinctive network control systems of the existing automated guided vehicles are likely to bring immense improvement in the performance using fifth generation of mobile communication (5G) technology. Recent days 5G communication systems are having requirement of FIR Filter having auto-adjustment of bandwidth. In the conventional finite impulse response filters, once the design is completed, we cannot change the frequency band. Thus, in auto adjustment frequency selective FIR filters to get desired bandwidth many filter coefficients are required. For implementation of field programmable gate array (FPGA). This generates a huge amount of slice. In this paper a control logic to choose different finite impulse response filters with set of coefficients based on clock signal, selects a finite impulse response filter resulting in frequency selectivity. The proposed design is to implement RFIR filter based on partial product having control logic to achieve better bandwidth needs with auto adjustment of frequencies. Filter order is used as 16. Area of overall designs is reduced by use of partial product in the FIR filter. The overall power consumed is 155 mw. Power consumption is reduced by 12.4%. Utilized area is reduced as compared to folded as well as unfolded direct form of FIR filter. Also, delay is reduced by 27.2% having value as 1.409 ns. The simulation outcomes of the design are validated through Xilinx ISE on virtex-7 FPGA.

Security is the major concern in mobile or portable devices because the internet community can do their work at any time at any place at anywhere. Today various cryptographic algorithms like RSA, Elliptic Curve Cryptography (ECC), etc., can be used to protect the information in mobile devices. But, they have some limitations viz., energy, battery power, processing speed, operating systems, screen size, resolution, memory size, etc. Providing security for limited power mobile devices is a challenging task. RSA and ECC are normally used in mobile devices. In RSA, both encryption and decryption are of the form xe mod n and in ECC, the scalar point k[P] where k is a scalar and P is a point in EC plays a vital role in performing encryption and decryption. The point arithmetic involved in ECC is a power starving process. To speed up the operations in both cryptographic algorithms, addition chains (AC) are normally used. If the encryption and decryption time get reduced, it ultimately reduces the power consumption. There are several AC algorithms exist in the literature. But, ACs are generated using Particle Swarm Optimization and Simplified Swarm Optimization are proposed in this paper and they are used in the said processes of RSA and ECC with two android and window emulators. The processing time, power consumption taken for encryption, decryption process and security of the said algorithms are also analysed.

Internet of Things is one of the prevalent and inevitable trends of the current era where data is found to be scattered among sensing devices. This paper addresses about preserving the privacy and security of the data that is distributed among the sensors collected by the users in Industrial Internet of Things infrastructure domain. This work adopts a dynamic authentication key agreement strategy which permits authenticated users to access the data which is distributed among various IoT sensing devices. In the proposed work an efficient Key Agreement and Authentication Scheme is designed to ensure the establishment of secure data communication. The model called Real-or-Random and tool named Automated Validation of Internet Security Protocols are deployed to ensure the secured transmission of data collected by innumerous sensors deployed across the network. Scaling of the network is done by addition of new nodes followed by pre-deployment phase and restoration of the transmission route is done effectively if any intrusion is found. The performance of the scheme is validated by measuring the parameters such as throughput, residual energy, packet dropping rate and delay analysis and it is found that the proposed scheme is superior compared with existing schemes.