- SHAJULIN BENEDICT graduated in 2001 from Manonmaniam Sunderanar University, India, with Distinction. In 2004, he rece... moreSHAJULIN BENEDICT graduated in 2001 from Manonmaniam Sunderanar University, India, with Distinction. In 2004, he received M.E Degree in Digital Communication and Computer Networking from A.K.C.E, Anna University, Chennai. He is the University second rank holder for his masters. He did his Ph.D degree in the area of Grid scheduling under Anna University, Chennai (Supervisor - Dr. V. Vasudevan, Director, Software Technologies Group of TIFAC Core in Network Engineering). He was affiliated towards the same group and published more papers in Int. Journals. After his Ph.D award, he joined a research team in Germany to pursue PostDoctorate under the guidance of Prof. Gerndt. He served as Professor at SXCCE Research Centre of Anna University-Chennai. Later, he visited TUM Germany for teaching Cloud Computing as Guest Professor of TUM-Germany. Now, he works at the Indian Institute of Information Technology Kottayam, Kerala, India, an institute of national importance of India. He serves as Director/PI/Representative Officer of AIC-IIITKottayam (Sec.8 Company) for nourishing young entrepreneurs of India. His research interests include HPC/Cloud/Grid scheduling, Performance Analysis of parallel applications (including exa-scale), CloudComputing, IIoT, Blockchain, parallel compilers, and so forth.edit
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High Performance Computing (HPC) is used for running advanced application programs efficiently, reliably, and quickly. HPC makes use of both parallel as well as distributed computing technologies. In earlier decades, performance analysis... more
High Performance Computing (HPC) is used for running advanced application programs efficiently, reliably, and quickly. HPC makes use of both parallel as well as distributed computing technologies. In earlier decades, performance analysis of HPC applications was evaluated based on speed, scalability of threads, memory hierarchy. Now, it is essential to consider the energy or the power consumed by the system while executing an application. There exist performance analysis tools, such as, Periscope, Scalasca, Vampir, TAU, and Paradyn, which consider hardware based performance bottlenecks and memory hierarchy issues including EnergyAnalyzer which is a dedicated tool for energy analysis purpose. Recently, these tools have focused on doing an automatic tuning of HPC applications which require a wide study of HPC applications in terms of power consumption. This paper aims at experimenting the most commonly used HPC applications and express the HPC application developers or tool developers that power consumption will be higher in certain conditions. We have done the experiments in HPCCLoud Research Laboratory, India. The experimental results were impressive when tested for the energy consumption of HPC applications.
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Performance issue, including energy consumption, is a primordial challenge for HPC application developers and HPC resource providers, including cloud providers. On the path to exa-scale computing, autotuning would find optimal solutions... more
Performance issue, including energy consumption, is a primordial challenge for HPC application developers and HPC resource providers, including cloud providers. On the path to exa-scale computing, autotuning would find optimal solutions considering performance parameters, such as, energy efficiency, load balance, memory access time, and so forth. This paper proposed Scalability-aware Energy AutoTuning (SCALE-EA), a dynamic runtime approach, that automatically identifies the suitable number of threads for individual parallel regions of OpenMP applications in a multi-core environment. The proposed approach was tested in a sandybridge processor machine using NAS-BT benchmark. SCALE-EA using random search provided 82.7 percentage performance improvement over exhaustive search mechanism; it manifested the need for such an autotuning mechanism when OpenMP-based HPC applications were executed on multi-core machines.
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IoT, Blockchain, Cloud, and other ICT technologies have more to offer to overcome the ongoing economic crisis of the rubber industry and reflect the adequate regard for boosting the economy of manufacturers. This paper proposes an... more
IoT, Blockchain, Cloud, and other ICT technologies have more to offer to overcome the ongoing economic crisis of the rubber industry and reflect the adequate regard for boosting the economy of manufacturers. This paper proposes an IoT-Blockchain enabled Yield Advisory System (IBEYAS) for natural rubber manufacturers. IBEYAS connects IoT-enabled sensors of agricultural land, assesses the yield value of rubber trees at different time intervals, and notifies the anomalies to rubber manufacturers and the associated involving participants. The anomaly record of IBEYAS advises manufacturers to opt for appropriate rubber yielding procedures. For experiments, sensors were mounted on three different agricultural locations and the blockchain network was set up at the IoT cloud research laboratory. Experimental results revealed how IBEYAS recorded the anomalies after the entries consented from i) rubber manufacturers, ii) landowners, iii) rubber board authorities, and iv) rubber tappers; the results showcased the yield opportunities suggested by IBEYAS to the rubber manufacturers.
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Internet of Things (IoT) based systems, most predominantly, the machine to machine communication based systems, have evolved in the recent past which helped to increase the efficiency of services offered without much necessity of human... more
Internet of Things (IoT) based systems, most predominantly, the machine to machine communication based systems, have evolved in the recent past which helped to increase the efficiency of services offered without much necessity of human interaction. In general, IoT cloud-assisted solutions could serve several applications, including the Smart Home Automation, due to the availability of high-speed mobile networks coupled with cost effective, accessible and fast embedded hardware. In fact, there exists a few smart home solutions in the market that aim at automating the basic operations of home appliances. However, most of these systems focus on mimicking the basic operations of the electrical switches. This paper attempts to unfold a Smart Home Automation system using Natural Language Processing (NLP) and IoT cloud solutions. The proposed system was able to remotely control smart homes in a secure and in a customized manner; the approach could precisely monitor home devices with the application of GoogleAPI for integrating devices. Experiments were carried out at the IoT Cloud research lab of IIIT Kottayam such that a mini-Smart Home environment was setup to remotely control the sensors such as humidity and temperatures of Smart Homes. The paper described a method to create an end user product using 3D modeling and 3D printing facilities. In addition, the paper has unfolded the state-of-the-art research works carried out in the field of smart home automation using NLPs.
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Purpose This paper aims to develop an architecture for 3D printers in an Industrial Internet of Things (IIoT) controlled automated manufacturing environment. An algorithm is proposed to estimate the electrical energy consumption of 3D... more
Purpose This paper aims to develop an architecture for 3D printers in an Industrial Internet of Things (IIoT) controlled automated manufacturing environment. An algorithm is proposed to estimate the electrical energy consumption of 3D printing jobs, which is used, 3D Printing, Sustainable Manufacturing, Industry 4.0, Electrical Energy Estimation, IIoT to schedule printing jobs on optimal electrical tariff rates. Design/methodology/approach An IIoT-enabled architecture with connected pools of 3D printers and an Electrical Energy Estimation System (EEES) are used to estimate the electrical energy requirement of 3D printing jobs. EEES applied the combination of Maximum Likelihood Estimation and a dynamic programming–based algorithm for estimating the electrical energy consumption of 3D printing jobs. Findings The proposed algorithm decently estimates the electrical energy required for 3D printing and able to obtain optimal accuracy measures. Experiment results show that the electrical ...
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IoT, Blockchain, Cloud, and other ICT technologies have more to offer to overcome the ongoing economic crisis of the rubber industry and reflect the adequate regard for boosting the economy of manufacturers. This paper proposes an... more
IoT, Blockchain, Cloud, and other ICT technologies have more to offer to overcome the ongoing economic crisis of the rubber industry and reflect the adequate regard for boosting the economy of manufacturers. This paper proposes an IoT-Blockchain enabled Yield Advisory System (IBEYAS) for natural rubber manufacturers. IBEYAS connects IoT-enabled sensors of agricultural land, assesses the yield value of rubber trees at different time intervals, and notifies the anomalies to rubber manufacturers and the associated involving participants. The anomaly record of IBEYAS advises manufacturers to opt for appropriate rubber yielding procedures. For experiments, sensors were mounted on three different agricultural locations and the blockchain network was set up at the IoT cloud research laboratory. Experimental results revealed how IBEYAS recorded the anomalies after the entries consented from i) rubber manufacturers, ii) landowners, iii) rubber board authorities, and iv) rubber tappers; the results showcased the yield opportunities suggested by IBEYAS to the rubber manufacturers.
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Function-as-a-Service (FaaS) is an attractive cloud computing model that simplifies application development and deployment. However, current serverless compute platforms do not consider data placement when scheduling functions. With the... more
Function-as-a-Service (FaaS) is an attractive cloud computing model that simplifies application development and deployment. However, current serverless compute platforms do not consider data placement when scheduling functions. With the growing demand for edge-cloud continuum, multi-cloud, and multi-serverless applications, this flaw means serverless technologies are still ill-suited to latency-sensitive operations like media streaming. This work proposes a solution by presenting a tool called FaDO: FaaS Functions and Data Orchestrator, designed to allow data-aware functions scheduling across multiserverless compute clusters present at different locations, such as at the edge and in the cloud. FaDO works through headerbased HTTP reverse proxying and uses three load-balancing algorithms: 1) The Least Connections, 2) Round Robin, and 3) Random for load balancing the invocations of the function across the suitable serverless compute clusters based on the set storage policies. FaDO further provides users with an abstraction of the serverless compute cluster's storage, allowing users to interact with data across different storage services through a unified interface. In addition, users can configure automatic and policy-aware granular data replications, causing FaDO to spread data across the clusters while respecting location constraints. Load testing results show that it is capable of load balancing high-throughput workloads, placing functions near their data without contributing any significant performance overhead.
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Additive Manufacturing or 3D printing based solutions are seen to have much potential for developing creative solutions in various domains such as health care, agriculture, industrial automation and so forth. In fact, the emergence of... more
Additive Manufacturing or 3D printing based solutions are seen to have much potential for developing creative solutions in various domains such as health care, agriculture, industrial automation and so forth. In fact, the emergence of Industry 4.0 has demanded the need for 3D printers as main production tools which are capable to do intelligent decisions. This paper proposes an energy aware architecture suitable for future industries with 3D printers as main production tools. The proposed architecture measures the energy consumption of 3D printers using IoT cloud technology by designing a non-invadable energy measurement device with At-mega328p for calculating the energy consumption of the 3D printers. In addition, analysis of the energy consumption pattern of 3D printers for various customized 3D printing jobs are carried out by exploring the impacting parameters. Experimental results show the relationship between energy consumption and printing parameters for various 3D printing jobs.
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Grid computing has emerged as a solution for handling the everyday increasing data usage and computation on the Internet by sharing the load among different nodes in it. The main challenge of grid computing is handling of node failures.... more
Grid computing has emerged as a solution for handling the everyday increasing data usage and computation on the Internet by sharing the load among different nodes in it. The main challenge of grid computing is handling of node failures. Vishwa is a two-layered peer-to-peer network for handling the failures by reconfiguring the application. In this article, the performance of Vishwa grid in virtual machines and ordinary computers is compared. The proposed method uses virtual machines as nodes of grid rather than physical systems, which reduces not only the hardware cost incurred in setting up and connecting individual systems, but also the communication delay between nodes and zonal server in the grid. Three models are proposed for forming grid in virtual environment that uses Oracle VirtualBox and VMware Workstation. The performances of the models have been evaluated by running firefly algorithm, using Ramanujan number, and finding the square of numbers in virtual machines and physical systems separately.
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The push for agile pandemic analytic solutions has attained development-stage software modules of applications instead of functioning as full-fledged production-stage applications – i.e., performance, scalability, and energy-related... more
The push for agile pandemic analytic solutions has attained development-stage software modules of applications instead of functioning as full-fledged production-stage applications – i.e., performance, scalability, and energy-related concerns are not optimized for the underlying computing domains. And while the research continues to support the idea that reducing the energy consumption of algorithms improves the lifetime of battery-operated machines, advisable tools in almost any developer setting, an energy analysis report for R-based analytic programs is indeed a valuable suggestion. This article proposes an energy analysis framework for R-programs that enables data analytic developers, including pandemic-related application developers, to analyze the programs. It reveals an energy analysis report for R programs written to predict the new cases of 215 countries using random forest variants. Experiments were carried out at the IoT cloud research lab and the energy efficiency aspects...
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The culpable cybersecurity practices that threaten leading organizations are logically prone to establishing countermeasures, including HoneyPots, and bestow research innovations in various dimensions such as ML-enabled threat... more
The culpable cybersecurity practices that threaten leading organizations are logically prone to establishing countermeasures, including HoneyPots, and bestow research innovations in various dimensions such as ML-enabled threat predictions. This article proposes an explainable AI-assisted permissioned blockchain framework named EA-POT for predicting potential defaulters' IP addresses. EA-POT registers the predicted defaulters based on the suggestions levied by explainable AI and the approval of IP authorizers to blockchain database to enhance immutability. Experiments were carried out at IoT Cloud Research laboratory using three prediction models such as Random Forest Modeling (RFM), Linear Regression Modeling (LRM), and Support Vector Machines (SVM); and, the observed experimental results for predicting the AWS HoneyPots were explored. The proposed EA-POT framework revealed the procedure to include interpretable knowledge while blacklisting IPs that reach HoneyPots.