An MSCN-Based Virtual Computing Cell-Oriented BSM Dissemination Mechanism

With the concept of multiaccess edge computing (MEC) being put forward, Roadside Unit (RSU) is considered as a valid application provider, which not only executes transmission resource allocation and data processing-related computing but also provides real-time applications to road vehicles. However, when fixed roadside nodes communicate with mobile vehicles, the high service migration rate could influence real-time feature of corresponding service. Moreover, vehicle density also affects service performance. Hence, in this paper, a two-processing layer architecture is constructed. A new concept, mobile secondary computing node (MSCN), which is used to compose mobile computing layer, is defined, and the number of MSCN changes dynamically with the vehicle density. Then, MSCN oriented virtual computing cell (VirCC), while corresponding to resource allocation approach and vehicle message dissemination mechanism, is designed. A network simulator (NS-3.28) is employed to investigate the performance of the proposed architecture. The simulation results show that the proposed architecture significantly improves both communication performance and computing efficiency.

Distributionin of Data Handling in Cloud Asset

In Cloud computing, task scheduling is one of the technique of specifying and assigning job to assets that finish the job. It may be virtual computing elements like threads & processors or data flows, which is planned on hardware resources like processors. The planning operation is performed by a scheduler. Schedulers are enabled various customers to properly communicate system funds or attain excellent service quality. Scheduling is essential for computing and the notion of planning allows multitasking computers with single CPU as inner portion of a computer system's execution model. Preference will be provided based on the requirements and goals of the user. Multiple computing parts comprise of many parallel applications while duties of execution are relied on other duties. We have studied few related articles in this paper, which is presented in the following section.

Enhhanced and Efficient Memory Model For Hadoop Mapreduce

Usage of high-performance computing (HPC) infrastructure adopting cloud-computing environment offers an efficient solution for executing data intensive application. MapReduce (MR) is the favored high performance parallel computing framework used in BigData study, scientific, and data intensive applications. Hadoop is one of the significantly used MR based parallel computing framework by various organization as it is freely available open source framework from Apache foundation. The existing Hadoop MapReduce (HMR) based makespan model incurs memory and I/O overhead. Thus, affecting makespan performance. For overcoming research issues and challenges, this manuscript presented an efficient parallel HMR (PHMR) makespan model. The PHMR includes a parallel execution scheme in virtual computing worker to reduce makespan times using cloud computing framework. The PHMR model provides efficient memory management design within the virtual computing workers to minimize memory allocation and transmission overheads. For evaluating performance of PHMR of over existing model experiment are conducted on public cloud environment using Azure HDInsight cloud platform. Different application such as bioinformatics, tex mining, stream, and nonstream application is considered. The overall result obtained shows superior performance is attained by PHMR over existing model in term of makespan time reduction and correlation among practical and theoretical makespan values.

CSCLab

This paper presents a platform to create and manage virtual computing laboratories using Cloud resources. Using this platform a professor can create a customized laboratory according to the class needs. The laboratory is composed of a set of virtual machines that students may use to get access to the necessary computing resources to attend the class. The platform aims at the creation of a solution to avoid proprietary lock in's, and it was designed to be agnostic to the cloud infrastructure. The machines of the lab can be accessed using some remote desktop protocol and managed by non-expert users.