Browsing by Author "Savitha, S."

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Effectiveness of micro health insurance on financial protection: Evidence from India
(2015) Savitha, S.; Kiran, K.B.
Iatrogenic poverty caused by inadequate public expenditure on health, lack of social health insurance and low penetration of private health insurance can be mitigated by micro health insurance (MHI) schemes that provide financial protection. The empirical evidence on the impact of MHI on financial protection is limited in India. This paper elucidates the effect of Sampoorna Suraksha Programme (SSP), a MHI scheme in Karnataka on financial protection. Cross-sectional study was undertaken in Karnataka and the data was gathered from 416 insured, 366 newly insured and 364 uninsured households. The impact of SSP on out of pocket expenses (OOPE), catastrophic health expenditure (CHE), non-medical consumption expenditure, hardship financing and labour supply was analysed using linear and logistic regression methods. Results of the study demonstrate that insured members incurred lower OOPE, CHE and hardship finance. There was no effect on consumption expenditure and no direct impact on labour supply measured in terms of withdrawal from workforce and substitution of labour. We advocate a larger role of MHI in health financing in India since it curtails impoverishment of households in informal sector by reducing OOPE and hardship financing. 2014, Springer Science+Business Media New York.
Health seeking behavior in Karnataka: Does micro-health insurance matter?
(2013) Savitha, S.; Kiran, K.
Background: Health seeking behaviour in the event of illness is influenced by the availability of good health care facilities and health care financing mechanisms. Micro health insurance not only promotes formal health care utilization at private providers but also reduces the cost of care by providing the insurance coverage. Objectives: This paper explores the impact of Sampoorna Suraksha Programme, a micro health insurance scheme on the health seeking behaviour of households during illness in Karnataka, India. Materials and Methods: The study was conducted in three randomly selected districts in Karnataka, India in the first half of the year 2011. The hypothesis was tested using binary logistic regression analysis on the data collected from randomly selected 1146 households consisting of 4961 individuals. Results: Insured individuals were seeking care at private hospitals than public hospitals due to the reduction in financial barrier. Moreover, equity in health seeking behaviour among insured individuals was observed. Conclusion : Our finding does represent a desirable result for health policy makers and micro finance institutions to advocate for the inclusion of health insurance in their portfolio, at least from the HSB perspective.
Multilayer Technique to Secure Data Transfer in Private Cloud for SaaS Applications
(Institute of Electrical and Electronics Engineers Inc., 2020) Ghuge, S.; Kumar, N.; Savitha, S.; Suraj, V.
In recent times Cloud Computing[CC] has emanated as a substitute paradigm for hosting and providing services over the Internet. Software as a Service (Saas) is one among such services that deliver services to the end-users on pay-as-you-go manner. In spite of all its advantages, security always seems to be major drawback. For securing the users' data on the cloud, this paper proposes an application model for any SaaS application hosted on a private cloud environment. The application is divided into two micro-services, where the first one is Application Layer Firewall and second one is a secured application to login and send sensitive data. The application layer firewall checks for any malicious activity and prevents the intruder to access the features present in the application. Subsequently, a Hidden Markov Model layer is implemented which is a probability-based intrusion detection technique. The second micro-service uses Advanced Encryption Standard (AES) encryption algorithm to encrypt documents having sensitive data, which have to be transferred within the private cloud. Further security is provided by proposing a novel Video Steganography approach using the Least Significant Bit (LSB) technique. This paper gives a detailed structure of hiding the data using multiple levels of security. Thus, this paper provides a holistic approach to implement a high level of security in SaaS applications. Â© 2020 IEEE.
Perceptive VM Allocation in Cloud Data Centers for Effective Resource Management
(Institute of Electrical and Electronics Engineers Inc., 2021) Savitha, S.; Salvi, S.
Virtual Machine allocation in cloud computing centers has become an important research area. Efficient VM allocation can reduce power consumption and average response time which can benefit both the end users as well as the cloud vendors. This work presents a perceptive priority aware VM allocation policy named P-PAVA algorithm, which takes into account the priority of an application along with its compute, memory and bandwidth requirement. The algorithm performs allocation of the applications based on the priority it gets using a machine learning based prediction model. Furthermore, to reduce the overhead of the allocation algorithm, parallelization is employed before assigning various workloads. To achieve this, the algorithm employs the First fit technique as a baseline for the requests allocation with a criteria as low priority. When compared to the state of the art algorithm for VM allocation for priority aware applications, P-PAVA performs better on several criteria such as average response time, execution time and power consumption. Â© 2021 IEEE.
Virtual Machine Migration in Heterogeneous Clouds - A Practical Approach
(Institute of Electrical and Electronics Engineers Inc., 2020) Raj, S.; Mangal, N.; Savitha, S.; Salvi, S.S.
In modern times, Cloud Computing is viewed as more promising technology than any other traditional Information Technology Computing paradigms. It basically serves as an on-demand resource provisioning platform without any active intervention by its user. The resource provisioning strategies require appropriate load distribution management across the cloud network, without which the cloud would face biased workload performance. Virtualization is the backbone of Cloud Computing, which enables the distribution and management of data by initiating the Virtual Machines (VMs). Furthermore, a Cloud Service Provider(CSP) has to monitor, analyze, and manage the workload distribution for servers when VMs are migrated. It presents the need to consider VM migration as an important activity that would unload the cloud server that is overloaded to migrate it to the server that can handle the workload. This paper proposes a technique that initiates the migration of VMs between heterogeneous cloud environments that would lead to a stable and well-balanced cloud network. The process of VM migration is very intensive in terms of resources, and hence intelligent approaches are required. It should effectively reduce the utilization of network bandwidth by minimizing the downtime of the server. However, the migration of VMs between the heterogeneous cloud would be challenging, but the right solution would benefit the cloud network managers on a large scale. Our proposed technique demonstrates heterogeneous VM migration between various cloud platforms built on different architectures. Various parameters have to be technically tuned for the conversion of VM images according to the Cloud Architecture. The performance of the proposed technique is evaluated based on the time taken for migration. Â© 2020 IEEE.