A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway
نویسندگان
چکیده
As an important component of China’s transportation data sharing system, high-speed railway data sharing is a typical application of data-intensive computing. Currently, most high-speed railway data is shared in cloud computing environment. Thus, there is an urgent need for an effective cloud-computing-based data placement strategy in high-speed railway. In this paper, a new data placement strategy named hierarchical structure data placement strategy is proposed. The proposed method combines the semidefinite programming algorithm with the dynamic interval mapping algorithm. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices, while the dynamic interval mapping algorithm ensures better self-adaptability of the data storage system. A hierarchical data placement strategy is proposed for large-scale networks. In this paper, a new theoretical analysis is provided, which is put in comparison with several other previous data placement approaches, showing the efficacy of the new analysis in several experiments.
منابع مشابه
Communication-Aware Traffic Stream Optimization for Virtual Machine Placement in Cloud Datacenters with VL2 Topology
By pervasiveness of cloud computing, a colossal amount of applications from gigantic organizations increasingly tend to rely on cloud services. These demands caused a great number of applications in form of couple of virtual machines (VMs) requests to be executed on data centers’ servers. Some of applications are as big as not possible to be processed upon a single VM. Also, there exists severa...
متن کاملGreen Energy-aware task scheduling using the DVFS technique in Cloud Computing
Nowdays, energy consumption as a critical issue in distributed computing systems with high performance has become so green computing tries to energy consumption, carbon footprint and CO2 emissions in high performance computing systems (HPCs) such as clusters, Grid and Cloud that a large number of parallel. Reducing energy consumption for high end computing can bring various benefits such as red...
متن کاملTask Scheduling Algorithm Using Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in Cloud Computing
The cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user's jobs has emerged as an important challenge in the field of cloud computing. It is mainly due to several reasons, including ever-increasing advancements of information technology and an increase of applications and...
متن کاملData Replication-Based Scheduling in Cloud Computing Environment
Abstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes...
متن کاملReduction of Energy Consumption in Mobile Cloud Computing by Classification of Demands and Executing in Different Data Centers
In recent years, mobile networks have faced with the increase of traffic demand. By emerging mobile applications and cloud computing, Mobile Cloud Computing (MCC) has been introduced. In this research, we focus on the 4th and 5th generation of mobile networks. Data Centers (DCs) are connected to each other by high-speed links in order to minimize delay and energy consumption. By considering a ...
متن کامل