Pankaj Deep Kaur

Cloud based intelligent system for delivering health care as a service

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity.

A resource elasticity framework for QoS-aware execution of cloud applications

Abstract Cloud infrastructures consisting of heterogeneous resources are increasingly being utilized for hosting large-scale distributed applications from diverse users with discrete needs. The multifarious cloud applications impose varied demands for computational resources along with multitude of performance implications. Successful hosting of cloud applications necessitates service providers to take into account the heterogeneity existing in the behavior of users, applications and system resources while respecting the user’s agreed Quality of Service (QoS) criteria. In this work, we propose a QoS-Aware Resource Elasticity (QRE) framework that allows service providers to make an assessment of the application behavior and develop mechanisms that enable dynamic scalability of cloud resources hosting the application components. Experimental results conducted on the Amazon EC2 cloud clearly demonstrate the effectiveness of our approach while complying with the agreed QoS attributes of users.

Unfolding the Distributed Computing Paradigms

Distributed computing combines multiple computers, geographically dispersed in a cost effective way and presents a single unified resource to the end user with huge storage and computational power. In the past few years, many overlying concepts of distributed computing eminently Cluster, Grid and Cloud Computing have appeared. This paper attempts to unfold these concepts and discusses their close alliance with other forms of computing like Service and Utility Computing. A qualitative comparison between these paradigms has been done. The key impediments to the successful adoption of Cloud Computing have been identified and directions for the future have been in-sighted.

Enhancing Grid Resource Scheduling Algorithms for Cloud Environments

Cloud computing is the latest evolution in the distributed computing paradigm and is being widely adopted by enterprises and organizations. The inherent benefits like instant scalability, pay for use, rapid elasticity, cost effectiveness, self-manageable service delivery and broader network access make cloud computing ‘the preferred platform’ for deploying applications and services. However, the technology being in nascent stage needs to be proven. The biggest challenge confronting service providers is effective provisioning and scheduling of cloud services to consumers leveraging the cost benefits of this computing paradigm. This paper attempts to investigate the key concerns for cloud resource management and explores possible alternatives that can be adapted from the existing Grid technology.

Effectiveness of web-based social sensing in health information dissemination-A review

Role and impact of social media in healthcare has moved to a centered-stage.Social media has been proved to be effective in disseminating health information.To foresee the impact of web-based tools on the outcome of healthcare interventions.To what extent ontology has been helpful in extracting relevant healthcare data. Social media has moved ahead of just being a tool for adolescent users to share their personal lives (messages, pictures) but has also been taken up by healthcare stakeholders to disseminate health information worldwide. The role of social media in healthcare industry and impact of patient engagement has moved to centered-stage and is continuously propelled by patient demand, mobile technology and mounting influence of the native digital generation. The pace with which the social activity is growing, it is important to foresee what impact these web-based platforms are having on the deliverance and outcome of healthcare interventions. This survey looks at how far social media has been prove to be effective in disseminating health information and to what extent ontological advancing approaches have been helpful in extracting relevant knowledge from sheer amount of healthcare data.

SQL injection: Study and augmentation

The Pervasive Adoption of the Web as an imminent means of information retrieval and other transactions, involving financial consequences like e-banking, online payment of bills, e-shopping etc, have made us more and more dependent on web applications. An unauthorized access to highly sensitive data by an attacker can threaten the Confidentiality, Integrity and Authorization of data. SQL injection attacks are the most perilous attacks to databases and web applications. It stands among top ten most threatening attacks to database security. Various techniques have been developed to curb SQLIA but still the rate of such attacks is increasing day by day. Although numerous techniques and methods have been devised to put an end to SQLI attacks, these methods either fail to discourse all the aspects of attack or have limitations, preventing their use. In this paper, various reasons accountable for such attacks have been identified, analyzed and the existing techniques have been extensively reviewed.

Evaluating Cloud Platforms- An Application Perspective

Cloud computing has gained tremendous consideration recently. In the ‘Era of Tera’ when data sizes are continuously escalating and traffic patterns have become unpredictable; Cloud is a viable alternative for enterprises to serve their consumers with quicker response times. The businesses can rely on service provider to host their applications and can thus focus on their core competencies. However, a large number of Cloud providers have spurred up with their offerings. As the number of Cloud Computing players grows, the run time services provided to the cloud consumers act as key differentiators. In this paper, traditional applications are compared with Cloud applications and metrics relevant to the Cloud services have been identified. Further, the services of five major Cloud providers are compared for fundamental differences that exist in their offerings on the basis of these metrics.

Cloud Resources Optimization for Air Pollution Monitoring Devices and Avoiding Post Pillar Problem

Cloud Computing is 21st century’s precious gem that is revolutionizing the computing world. Cloud computing is progressively transforming the world through its wide applicability in diverse fields. One such field is environment monitoring. Today cloud computing is being utilized for monitoring the air pollution levels in association with different sensory devices and aid the ecologists around the globe to derive subtle ways to lower down its impact factor. But the major problem with such noble application is the elasticity factor of resource provision in cloud for handling the gargantuan amount of data that is generated by sensors. This elasticity cause troublesome to the service provider as the need of resources are very erratic and spontaneous. In this paper we present an algorithmic technique that attempts to quash this problem and provide a way to optimally allocate and utilize the resources. The evaluated simulation results reveals a very positive side and suggest an increase in utilization factor by 25 %–40 %.

Optimization of Cloud Resources for Air Pollution Monitoring Devices

Cloud Computing has evolved out as one of the most advanced contrivance of the 21st century. It has integrated in almost every field and has now entered in such a stage where it is unfolding some new levels of usages that it can address. Air Pollution monitoring is one such application which is becoming prominent. Google, the face of the IT industry has integrated with Aclima to monitor air pollution with its street view application. But not everything meant to be perfect. The devices associated with monitoring part secretes out large and variable amount of data which makes its handling a vicious constraint for cloud providers as allocated resources are not used up to their potential. Researchers areleaving no stone unturned by coming at the rock bottom level to figure out certain approaches to make this vogue affordable to the providers. The major contributing factor for this forfeiture is the elasticity factor which enables users to scale up or scale down resources at any instant of time. To counter this problem, this paperpresents a dynamic algorithmic approach foroptimization of resources. Analysis of results achieved shows that the algorithm helps to improve optimization by 20% to 30%.

Subjective well-being prediction from social networks: A review

From the ancient times, every human being has been trying to improve themselves, either for personal or societal benefits. These benefits define the well-being of individuals. Well-being can be judged by outer and inner factors. The outer factors can be in the form of materials and it can measure by objective factors like GDP (Gross Development Product). The internal components are the feelings of a person which characterize how life is experienced by a person. The personal satisfaction (Quality of Life, QoL) is the detecting of people day by day life including all enthusiastic, social, and physical viewpoints. QoL is for the most part measured by requesting that individuals report their joy and life fulfillment. The measurement of emotions in the human behavior in terms of happiness is known as Subjective Well-Being (SWB). In this wireless age, people express their emotions on social networking sites (SNs). The expressions are largely in text form and the growing importance of linguistic text analysis of SNs gives a direction to predict the SWB of individuals. The paper presents the main findings from the literature on various determinants of happiness. The major theories have been studied and their parameters to measure the human behavior from the SWB perspective are defined. Also, this paper describes how these parameters have been used by researchers to predict SWB from SNs. The effectiveness in predicting the SWB from SNs has been elaborated and the positive, and negative effects of SNs usage on individual behavior have been discussed.