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Kumar, Shishir
- Resource Cost Optimization for Dynamic Load Balancing on Web Server System
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Authors
Affiliations
1 Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
2 Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
1 Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
2 Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
Source
International Journal of Distributed and Cloud Computing, Vol 2, No 1 (2014), Pagination: 7-18Abstract
The growth of technology increases user expectations at a fast pace in terms of performance and efficiency of web servers. Such user's expectations are required the number of efficient and dynamic computational resources and mechanism. Several scheduling policies have been already working on multiple web servers, but still web servers get overloaded while the access of resources has been increased. Now-adays, to increase the number of resources gets costly for the organizations so there is a need for an efficient scheduling policy which can optimize the cost of the resources as per the user’s expectation. In this paper, an efficient dynamic load balancing policy based on the activity of the processes has been proposed for reducing the cost of Grid resources and simulated on the Grid-Sim simulator to compare with existing scheduling policies. Therefore, costs of resources have been optimized through the proposed dynamic load balancing policies on web servers.Keywords
Dynamic Load Balancing, Web Server, Grid, Grid-Sim, Scheduling Policy, Resource Costs, Condor Scheduler.
References
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- Artificial Neural Network Based Approach for Identification of Operating System Processes
Abstract Views :376 |
PDF Views:0
Authors
Amit Kumar
1,
Shishir Kumar
1
Affiliations
1 Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
1 Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, IN
Source
Journal of Applied Information Science, Vol 2, No 1 (2014), Pagination: 1-11Abstract
A computer system can be secured by using various methods like firewalls, anti-virus tools, network security tools, malware removal tools, monitoring tools etc. These tools and applications are being by most of the computer users. These computer security tools need to be updated and monitored regularly by the user. If any computer users fail to update the security tools, then the computer system may be infected by virus or may be attacked. Through this paper a learning system is being proposed to provide security by identify the operating system process as Self and Non-Self. Concepts of Artificial Neural Network (ANN) Learning have been used for the identification of processes. Initially, an Artificial Neural Network is created by using processes parameters with random weights. These weights are updated by using Gradient Descent Algorithm for various training examples, and then this Artificial Neural Network is tested with test data examples. It has been observed that the Artificial Neural Network Learning provides a better approach for identifying Self and Non-Self process and provides a better security.Keywords
Self and Non Self Process, Machine Learning, Artificial Neural Network, Gradient Descent, Perceptron.References
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- Perceptions on Risk Management Strategies in Software Development
Abstract Views :236 |
PDF Views:2
Authors
Affiliations
1 Bhagwant University, Ajmer, Rajasthan, IN
2 Jaypee University of Engineering & Technology, Guna, Madhya Pradesh, IN
1 Bhagwant University, Ajmer, Rajasthan, IN
2 Jaypee University of Engineering & Technology, Guna, Madhya Pradesh, IN
Source
International Journal of System & Software Engineering, Vol 2, No 1 (2014), Pagination: 20-27Abstract
According to CHAOS 2004, maximum projects were finished with overtime and overbudget, which cause project failure. Therefore this risk should be analyzed to understand software risk. Many authors have identified different risk factors like team risk, organisational and environmental risk, requirements risks, plan and control risk, etc. Solutions are not many, but simulation and case studies are some of the solutions to reduce risk. In this paper, open source architecture is discussed and also a solution is proposed, which makes the development more easy and secure towards risk.References
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- www.codeigniter.com, MVC framework
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- Evaluation of Adverse Drug Reactions and their Management in Psychiatric in-Patients
Abstract Views :312 |
PDF Views:0
Authors
Affiliations
1 Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences, Nitte (Deemed to be University), Mangalore, Karnataka- 575018, IN
2 Department of Psychiatry, Justice K.S. Hegde Charitable Hospital, Mangalore, Karnataka- 575018, IN
1 Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences, Nitte (Deemed to be University), Mangalore, Karnataka- 575018, IN
2 Department of Psychiatry, Justice K.S. Hegde Charitable Hospital, Mangalore, Karnataka- 575018, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 7 (2019), Pagination: 3455-3461Abstract
Objective: To identify the adverse drug reactions caused by psychotropic drugs and to evaluate the causality, severity, preventability and management of those Adverse Drug Reactions (ADRs). Methods: A prospective observational study was carried out in hospitalised patients with psychiatric disorders. All the in-patients prescribed with psychotropic drugs were enrolled in the study and followed regularly for the identification of ADRs. Identified ADRs were assessed for causality, severity and preventability using various scales. Approaches towards the management of the ADRs and the patient outcomes were analysed. Results: A total of 200 patients were monitored, of which 79 ADRs were identified from 56 patients. The most commonly reported ADRs were tremor (18.98%) followed by drowsiness (17.72%). Olanzapine was found to be associated with more number of ADRs (29.11%) followed by Clozapine (12.65%). Causality assessment using World Health Organisation- Uppsala Monitoring Centre (WHO-UMC) scale showed that most of the ADRs were probable (62.02%) and possible (37.97%). Severity assessment revealed that 54.42% of ADRs were found to be moderately severe. 48.10% of ADRs were definitely preventable and 44.30% were probably preventable. Assessment on the management of ADRs says that most of them were resolved by specific treatment approach to the reaction. Conclusion: The end results of the study created the evidence on the incidence of ADRs in patients prescribed with psychotropic drugs. The study emphasises on monitoring of those drugs that are considered to have high risk in developing ADRs. Thus, it can influence to a chance of preventing or reducing an unwanted reaction.Keywords
Adverse Drug Reaction, Psychiatry, Psychotropic Drugs.References
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