Omar Nooh Almotiry¹, Mohemmed Sha^2,*, Mohamudha Parveen Rahamathulla³, Omer Salih Dawood Omer²

Computer Systems Science and Engineering, Vol.36, No.1, pp. 1-12, 2021, DOI:10.32604/csse.2021.014267

Abstract As technology improves, several modernization efforts are taken in the process of teaching and learning. An effective education system should maintain global connectivity, federate security and deliver self-access to its services. The cloud computing services transform the current education system to an advanced one. There exist several tools and services to make teaching and learning more interesting. In the higher education system, the data flow and basic operations are almost the same. These systems need to access cloud-based applications and services for their operational advancement and flexibility. Architecting a suitable cloud-based education system will leverage all the benefits of the… More >

Haisheng Yu¹, Heng Qi¹, Keqiu Li¹, Jianhui Zhang¹,Peng Xiao², Xun Wang¹

Computer Systems Science and Engineering, Vol.33, No.4, pp. 251-258, 2018, DOI:10.32604/csse.2018.33.251

Abstract The routing mechanism in Data Center networks can affect network performance and latency significantly. Hash-based method, such as ECMP (Equal-Cost Multi-Path), has been widely used in Data Center networks to fulfill the requirement of load balance. However, ECMP statically maps one flow to a path by a hash method, which results in some paths overloaded while others remain underutilized. Some dynamic flow scheduling schemes choose the most underutilized link as the next hop to better utilize the network bandwidth, while these schemes lacks of utilizing the global state of the network. To achieve high bandwidth utilization and low latency, we… More >

Yang Yang^1,*, Jing Dong¹, Chao Fang², Ping Xie³, Na An³

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1015-1031, 2020, DOI:10.32604/cmes.2020.09404

Abstract The development of cloud computing and virtualization technology has brought great challenges to the reliability of data center services. Data centers typically contain a large number of compute and storage nodes which may fail and affect the quality of service. Failure prediction is an important means of ensuring service availability. Predicting node failure in cloud-based data centers is challenging because the failure symptoms reflected have complex characteristics, and the distribution imbalance between the failure sample and the normal sample is widespread, resulting in inaccurate failure prediction. Targeting these challenges, this paper proposes a novel failure prediction method FP-STE (Failure Prediction… More >

Xiaojun Shi¹, Yangyang Li^{2, *}, Haiyong Xie^{2, 3}, Tengfei Yang², Linchao Zhang², Panyu Liu⁴, Heng Zhang⁴, Zhiyao Liang⁵

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 385-398, 2020, DOI:10.32604/cmc.2020.06418

Abstract In today’s datacenter network, the quantity growth and complexity increment of traffic is unprecedented, which brings not only the booming of network development, but also the problem of network performance degradation, such as more chance of network congestion and serious load imbalance. Due to the dynamically changing traffic patterns, the state-of the-art approaches that do this all require forklift changes to data center networking gear. The root of problem is lack of distinct strategies for elephant and mice flows. Under this condition, it is essential to enforce accurate elephant flow detection and come up with a novel load balancing solution… More >