Dongyang Ou, Yongjian Ren, Congfeng Jiang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2043-2067, 2024, DOI:10.32604/cmes.2023.029987

Abstract Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents a quality of service (QoS) prediction-based scheduling model (QPSM) for co-located workloads. The performance prediction of QPSM consists of two parts: the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on random forest. On-line service… More >

Manar Ahmed Hamza^1,*, Shaha Al-Otaibi², Sami Althahabi³, Jaber S. Alzahrani⁴, Abdullah Mohamed⁵, Abdelwahed Motwakel¹, Abu Sarwar Zamani¹, Mohamed I. Eldesouki⁶

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1371-1383, 2023, DOI:10.32604/csse.2023.030232

Abstract Internet of things (IoT) and cloud computing (CC) becomes widespread in different application domains such as business, e-commerce, healthcare, etc. The recent developments of IoT technology have led to an increase in large amounts of data from various sources. In IoT enabled cloud environment, load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource utilization. The load scheduling problem was regarded as an optimization problem that is solved by metaheuristics. In this view, this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling (C3SOA-LS) technique for IoT enabled cloud environment. The… More >

R. Joshua Samuel Raj¹, V. Ilango², Prince Thomas³, V. R. Uma⁴, Fahd N. Al-Wesabi^5,6,*, Radwa Marzouk⁷, Anwer Mustafa Hilal⁸

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4101-4114, 2022, DOI:10.32604/cmc.2022.022063

Abstract Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of… More >