No abstract

cloud computing has become more powerful with the inclusion of software-defined networking (SDN) in its environment. In Cloud Data Centers (CDCs), an important research issue is how to forecast and allocate resources efficiently whilst achieving Quality of Service (QoS) of users request with minimal overall power consumption; taking into account the frequent changes in resource requirements. In this paper, we propose a Supervisor Controller-based Software-Defined Cloud Data Center (SC-boSD-CDC) framework for dynamic resource allocation and prediction of cloud computing-based SDN. In this proposed module, Genetic Algorithm (GA) is proposed to deal with the multi-objective problem of dynamically forecasting the utilization of resources in both compute nodes and links bandwidth of network as well as energy consumption in the Cloud Data Center (CDC).  Furthermore, a Virtual Machines (VMs) placement algorithm is also proposed to allocate computing resources and routing algorithms to choose the proper bandwidth links between switches; resulting in increased CPU and memory utilization and reduction in overall power consumption.

This study aimed to investigate the anticancer activity of Haplophyllum tuberculatum(Forsk.) aerial parts ethanol extract and fractions and reveal the potential anticancer targets, binding modes, pharmacokinetics, and toxicity properties of its phytoconstituents. MTT assay was used to investigate the anticancer activity. TargetNet, ChemProt version 2.0, and CLC-Pred web servers were used for virtual screening, and Cresset Flare software was used for molecular docking with the 26 predicted targets. Moreover, pkCSM, swiss ADME, and eMolTox web servers were used to predict pharmacokinetics and safety. Ethanolic extracts of H. tuberculatum on HepG2 and HeLa cell lines showed promising activities with IC50 values 54.12 and 48.1 µg/mL, respectively. Further, ethyl acetate fraction showed the highest cytotoxicity on HepG2 and HeLa cell lines with IC50 values 41.7 and 52.31 µg/mL. Of 70 compounds screened virtually, polygamain, justicidin A, justicidin B, haplotubine, kusunokinin, and flindersine were predicted as safe anticancer drugs candidates. They showed the highest binding scores with targets involved in cell growth, proliferation, survival, migration, tumor suppression, induction of apoptosis, metastasis, and drug resistance. Our findings revealed the potency of H. tuberculatum as a source of anticancer candidates that further studies should support.