A Survey on Live Virtual Machine Migrations and its Techniques

Today’s world is internet world. Almost all the people uses internet for accessing different services. In Cloud Computing various cloud consumers demand variety of services as per their dynamically changing needs over the internet. So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But due to the availability of finite resources it is very difficult for cloud providers to provide all the demanded services in time. From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So, it’s a vital issue to meet cloud consumers’ QoS requirements and satisfaction. Virtualization mainly abstracts the resources like CPU and Memory through Virtual Machine for efficient resource utilization. Virtual Machine Migration is one of the key technique for dynamic resource management in cloud computing. This paper mainly addresses key performance issues, challenges and techniques for live virtual machine migration in cloud computing. It also focuses on the key issues related to these existing live virtual machine migration techniques and summarizes them. Keywords: Cloud Computing, Migration, Virtualization, Virtual Machine, Physical Machine, Resource Management, Live Virtual Machine Migration

A Mathematical Appraisal: Evolution of Distributed File System and Hadoop

The  fast  growing  technology   has  left  a  great   impact  on  the  human  life. Many traditional systems are either replaced or running in parallel with their electronic counterpart. As for example: - the traditional postal system is now nearly replaced by mobile phones and emails. The electronic system is providing more functionalities than their traditional counterparts. Due to social media, peoples may communicate with each other, share their thoughts and moments of life in form of texts, images or videos. On the  other  hand,  to enhance  technologies  and  knowledge many research  activities  are propelled  and data from  different sources  are  gathered in large  volume for further  analysis. In short today’s world is surrounded with large volume of data in different form. This put a requirement for effective management of these billions of terabytes of electronic data generally called BIG DATA.  The effective management must be based on proven mathematical concepts so that chance of casualties may be reduced. This  paper  presents  a mathematical  appraisal for evolution   of  distribution of  file data   and  explains some basic  solution  of primitive  problems  based  on probability theory. Keywords: BIG DATA,   Distributed System, DFS, Commodity Hardware, Hadoop, Hadoop File System, HDF

Power Reduction Sleep Scheduling Technique for Cloud Integrated Green Social Sensor Network

The wireless sensor network is the maximum appropriate technology nowadays with such awesome applications and areas including Infrastructure tracking, environment tracking, health care tracking, etc. Cloud Computing has fantastic data collecting skills and effective data processing ability. Social Network is a group of People or organizations of human beings with similar intentions. Social Sensor Cloud is one type of expertise-sharing mechanism wherein similar types of human beings can connect. Energy Consumption is nowadays the largest challenge as far as the concern with green environment. Because the battery life of the sensor is so limited, the Social Sensor Cloud must be energy efficient. As a result, this article will concentrate on Energy-Efficient Techniques for the Social Sensor Cloud. According to our findings, findings, the majority of energy-saving measures will cope with not unusual place Parameters including Network Lifetime, Network Work rate, Throughput, Energy, Bandwidth, etc. We will Summarize current Technology and we Will Provide Our Architecture for Energy Reduction in Social Sensor Cloud

Location Based Power Reduction Cloud Integrated Social Sensor Network

It is great to hear about the advancements in wireless sensor networks and their applications, as well as the integration of cloud computing to enhance data analysis and storage capabilities. Indeed, these technologies have opened up numerous possibilities across various fields, including infrastructure tracking, environmental monitoring, healthcare, and more. The concept of a social sensor cloud, as you mentioned, brings an interesting dimension to this technology landscape by focusing on knowledge-sharing and connecting like-minded individuals or organizations. This could potentially lead to more collaborative and efficient solutions across a wide range of domains. Energy efficiency is a critical consideration in the design and operation of wireless sensor networks and the cloud infrastructure that supports them. The limited battery life of sensors necessitates careful management of energy consumption to ensure optimal functionality and longevity. Sleep scheduling methods are a common technique used to manage energy consumption in these networks. By coordinating when sensors are active and when they are in a low-power sleep mode, energy consumption can be significantly reduced without compromising the network's overall effectiveness. In the context of the Social Sensor Cloud, managing energy efficiency becomes even more crucial due to the shorter battery life of the sensors involved. This is particularly relevant given the growing concerns about environmental sustainability and the need to reduce energy consumption across technological systems. It's clear that your research paper addresses these challenges head-on, by exploring energy-efficient techniques for the Social Sensor Cloud. Sleep scheduling is just one of the many strategies that researchers and engineers are working on to strike a balance between functionality and energy consumption. Other methods might include optimizing data transfer protocols, developing energy-harvesting mechanisms, and enhancing sensor hardware efficiency. As technology continues to evolve, the integration of wireless sensor networks, cloud computing, and social networks will likely pave the way for innovative solutions and transformative applications. Addressing energy efficiency concerns will undoubtedly play a crucial role in ensuring the long-term viability and positive impact of these technologies