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Data Storage and Precision of Dynamism-Efficient Fault-Tolerant in Mobile Cloud

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Data Storage and Precision of Dynamism-Efficient Fault-Tolerant in Mobile Cloud ISSN 2454-9924 Volume: 1 Issue: 1(2015) Data storage and Precision of Dynamism-Efficient Fault-Tolerant in Mobile Cloud B. Naseema Begum#1, S. Prasanna*1 Mailam Engineering College, Mailam#1 *1 [email protected] Abstract- Although the technology improvement in hardware for hand-held mobile devices, video and image storage devices requires large calculation or computation and storage capacity. Recent research has implemented to address these issues by deploying remote servers, such as clouds and peer mobile devices. Here the mobile devices has implemented on dynamic networks with frequent topology changes and mobility in mobile cloud. In existing work, challenges of reliability and energy efficiency are not unaddressed. In this proposed system, we provide the solution for addressing these issues. Here we implement a combined approach of k-out-of-n computing for both data storage and processing in mobile cloud. In our system, mobile devices successfully save or process data, in the most energy-efficient way, as long as k out of n remote servers are processed. From this proposed system we have also achieved feasibility of the system. Additionally this system performs the fault tolerance and energy efficiency performance in large scale networks. Keywords- K out of n, cloud, Topology, Peer I. Related Work II. Proposed Method Although the technology improvement in In this proposed system, we provide the hardware for hand-held mobile devices, solution for addressing these issues. Here we video and image storage devices requires implement a combined approach of k-out- large calculation or computation and storage of-n computing for both data storage and capacity. In existing work, challenges of processing in mobile cloud. In our system, reliability and energy efficiency are not mobile devices successfully save or process unaddressed. data, in the most energy-efficient way, as long as k out of n remote servers are 1.1 Drawback processed. In existing system provides less efficiency 2.1 Benefits and reliability when access the system. Copyright © 2015 IJARCSET. All rights reserved. ISSN 2454-9924 Volume: 1 Issue: 1(2015) In this proposed system, it provides dynamically changing topology. Serendipity enhanced efficiency and high reliability. and other VM-based solutions considered Additionally this system performs the fault the energy cost for processing a task on tolerance and energy efficiency performance mobile devices and offloading a task to the in large scale networks. remote servers, but they did not consider the scenario in a multi-hop and dynamic III. Introduction network where the energy cost for relaying/transmitting packets is significant. Personal mobile devices have gained Furthermore, remote servers are often enormous popularity in recent years. Due to inaccessible because of node failures, their limited resources (e.g., computation, unstable links, or node-mobility, raising a memory, energy), however, executing reliability issue. Although Serendipity sophisticated applications (e.g., video and considers intermittent connections, node image storage and processing, or map- failures are not taken into account; the VM- reduce type) on mobile devices remains based solution considers only static challenging. As a result, many applications networks and is difficult to deploy in rely on offloading all or part of their works dynamic environments. In this article, we to ―remote servers‖ such as clouds and peer propose the first framework to support fault- mobile devices. For instance, applications tolerant and energy-efficient remote storage such as Google Goggle and Siri process the & processing under a dynamic network locally collected data on clouds. Going topology, i.e., mobile cloud. Our framework beyond the traditional cloud based scheme, aims for applications that require energy- recent research has proposed to offload efficient and reliable distributed data storage processes on mobile devices by migrating a & processing in dynamic network E.g., Virtual Machine (VM) overlay to nearby military operation or disaster response. We infrastructures. This strategy essentially integrate the k-out of-n reliability allows offloading any process or application, mechanism into distributed computing in but it requires a complicated VM mobile cloud formed by only mobile mechanism and a stable network connection. devices. K-out-of n, a well-studied topic in Some systems (e.g., Serendipity) even reliability control, ensures that a system of n leverage peer mobile devices as remote components operates correctly as long as k servers to complete computation intensive or more components work. More job. In dynamic networks, e.g., mobile cloud specifically, we investigate how to store data for disaster response or military operations, as well as process the stored data in mobile when selecting remote servers, energy cloud with k-out-of-n reliability such that: 1) consumption for accessing them must be the energy consumption for retrieving minimized while taking into account the distributed data is minimized; 2) the energy Copyright © 2015 IJARCSET. All rights reserved. ISSN 2454-9924 Volume: 1 Issue: 1(2015) consumption for processing the distributed IV. Literature Review data is minimized; and 3) data and processing are distributed considering [6] Describes about, Mobile applications are dynamic topology changes. In our proposed becoming increasingly ubiquitous and framework, a data object is encoded and provide ever richer functionality on mobile partitioned into n fragments, and then stored devices. At the same time, such devices on n different nodes. As long as k or more of often enjoy strong connectivity with more the n nodes are available, the data object can powerful machines ranging from laptops and be successfully recovered. Similarly, another desktops to commercial clouds. This paper set of n nodes are assigned tasks for presents the design and implementation of processing the stored data and all tasks can Clone Cloud, a system that automatically be completed as long as k or more of the n transforms mobile applications to benefit processing nodes finish the assigned tasks. from the cloud. The system is a flexible The parameters k and n determine the application partitioned and execution degree of reliability and different (k, n) pairs runtime that enables unmodified mobile may be assigned to data storage and data applications running in an application-level processing. System administrators select virtual machine to seamlessly off-load part these parameters based on their reliability of their execution from mobile devices onto requirements. The contributions of this device clones operating in a computational article are as follows: • It presents a cloud. Clone Cloud uses a combination of mathematical model for both optimizing static analysis and dynamic profiling to energy consumption and meeting the fault partition applications automatically at a fine tolerance requirements of data storage and granularity while optimizing execution time processing under a dynamic network and energy use for a target computation and topology. • It presents an efficient algorithm communication environment. At runtime, for estimating the communication cost in a the application partitioning is effected by mobile cloud, where nodes fail or move, migrating a thread from the mobile device at joining/leaving the network. • It presents the a chosen point to the clone in the cloud, first process scheduling algorithm that is executing there for the remainder of the both fault-tolerant and energy efficient. • It partition, and re-integrating the migrated presents a distributed protocol for thread back to the mobile device. Our continually monitoring the network evaluation shows that Clone Cloud can topology, without requiring additional adapt application partitioning to different packet transmissions. • It presents the environments, and can help some evaluation of our proposed framework applications achieve as much as a 20x through a real hardware implementation and execution speed-up and a 20-fold decrease large scale simulations. of energy spent on the mobile device. [22] Copyright © 2015 IJARCSET. All rights reserved. ISSN 2454-9924 Volume: 1 Issue: 1(2015) Describes about Smartphones have exploded Describes about Mobile devices are in popularity in recent years, becoming ever increasingly being relied on for services that more sophisticated and capable. As a result, go beyond simple connectivity and require developers worldwide are building more complex processing. Fortunately, a increasingly complex applications that mobile device encounters, possibly require ever increasing amounts of intermittently, many entities capable of computational power and energy. In this lending it computational resources. At one paper we propose Think Air, a framework extreme is the traditional cloud-computing that makes it simple for developers to context where a mobile device is connected migrate their smartphone applications to the to remote cloud resources maintained by a cloud. Think Air exploits the concept of service provider with which it has an smartphone virtualization in the cloud and established relationship. In this paper we provides method-level computation consider the other extreme, where a mobile offloading. Advancing on previous work, it device’s contacts are only with other mobile focuses on the elasticity and scalability of devices, where both the computation the cloud and enhances the power of mobile initiator and the remote computational cloud computing
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