P. Prakash

Big Data and Cloud: A Survey

Today, the world has become closer due to the development of Internet. More people communicate via Internet, and the volume of data to be handled also grows. Nowadays, we talk about peta- and zettabytes of data and this volume of data needs to be processed and analyzed further which had led to the research field of big data storage and analysis. Cloud computing is another emerging area in which the services such as infrastructure, storage, and software are provided to the consumers on demand basis. In this paper, we discuss about the big data, cloud computing, and how big data are handled in cloud computing environment.

A Study on Security Issues in Cloud Computing

Cloud computing focuses on maximizing the effectiveness of shared resources. It is also cost-effective, flexible, quick data storage, and is one of the most successful services in the internet. Cloud services are often outsourced to a third party, increasing the security threats. They are also delivered through the traditional network protocols and so a threat to the protocols is a threat to the cloud as well. In this paper, the major security issues are analyzed and sufficient countermeasures are provided, in order to minimize the security threats concerning cloud computing.

DISTRIBUTIVE POWER MIGRATION AND MANAGEMENT ALGORITHM FOR CLOUD ENVIRONMENT

In cloud computing, the resources are provided as service over the internet on demand basis. The resources such as servers, networks, storage, applications are dynamically scaled and virtualized. The demand grows gradually for each virtual machine in a cloud computing environment over time. So, it is necessary to manage the resources under each cluster to match the demand in order to maximize total returns by minimizing the power consumption cost. It can be minimized by applying minimal virtual design, live migration and variable resource management. But, the traditional way of scheduling doesn’t meet our expected requirements. So we introduce the distributive power migration and management algorithm for cloud environment that uses the resources in an effective and efficient manner ensuring minimal use of power. The proposed algorithm performs computation more efficiently in a scalable cloud computing environment. The results indicate that the algorithm reduces up to 30% of the power consumption to execute services.

Mobile controlled door locking system with two-factor authentication

In spite of the availability of digital password lockers and advanced door locks, hacking the lock code by an unauthorized person has become a plain-sailing task. Thus, the main goal of this paper is to design a highly advanced and secured home security system using mobile technology, video messaging, and electronic technology with two-factor authentication. The designed system directly communicates to the owner of the house when someone arrives at his door-step by sending a video along with a notification message. The owner sends a one-time password to the visitor’s mobile for him to enter in the keypad placed near the door.

Green Algorithm for Virtualized Cloud Systems to Optimize the Energy Consumption

In recent days, most of the cloud users request data center in the cloud environment by applying an exhaustive data-centric workflows which leads to the major energy consumption. The major energy breaks out from the data center and makes way to CO2 emission which impacts the global warming. In this paper, we introduce optimized energy utilization in deployment and forecast (OEUDF) for data-intensive workflows in virtualized cloud systems which help to reduce the energy in the cloud workflow environment. In this approach, initially, we compute the optimal data-accessing energy path (ODEP) which helps us to deploy and configure the virtual machines; secondly, it computes the rank, according to that it will schedule the workflow activities in the cloud environment. If any unscheduled activities are in the submission pool, then OEUDF finds the suitable virtual machine and reconfigures the data center by minimizing the energy utilization. The experiment result indicates that the proposed algorithm gradually reduces the energy consumption.

Hardware Based Distributive Power Migration and Management Algorithm for Cloud Environment

In cloud computing setup of computers power consumption among the distributed computers needs to be minimal with every server running increases the power cost by an average of 50w-100w. A real time implementation of an algorithm to minimize the power consumed in a setup of a parent computer a PIC microprocessor and connected servers is needed to manage the unwanted waste in energy. The usual traditional scheduler doesn’t meet the requirements. We program the Microcontroller to implement our algorithm which ensured that minimum number of servers run for a given numbers of virtual machines. The Distributive Power Migration & Management Algorithm for Cloud Environment that uses the resources in an effective and efficient manner ensuring minimal use of power. The proposed algorithm performs computation more efficiently in a scalable cloud computing environment. The results indicate that the algorithm reduces up to 28% of the power consumption to execute services.