An Improved Ant Colony Algorithm for Virtual Resource Scheduling in Cloud Computing

Abstract

In order to solve the problems of uneven spatial distribution of data nodes and unclear weight relationship of virtual scheduling features in cloud computing platform, a virtual resource scheduling method based on improved ant colony algorithm is studied and designed to improve the performance of virtual resource scheduling in cloud computing platform by this method. After analyzing the information resource sequence change of the cloud computing platform, according to the STR -Tree partition graph, a simulated annealing-based algorithm is employed to classify the resource types after optimal scheduling into IO types, middle types and CPU types, and the time span and load balance are set as the measurement indexes. The simulation results show that after applying this method, the occupied resources of the main platform are 535 MB, which are much lower than the other two comparison algorithms, and the method has improved the allocation rationality, resource balance, maximum queue length and energy consumption. This result indicates that applying this virtual resource scheduling method can effectively improve the intelligent scheduling of virtual resources in the cloud computing platform.

A Novel Low-Cost System for Remote Health Monitoring Using Smartwatches

“…The healthcare sector is quickly advancing in both technology and services. One recent advancement with numerous benefits is the remote monitoring of patients [1], [2], [3], [4], [5], [6], [7], [8], [9]. Through modern communication and sensor technologies, patients can be monitored while participating in their usual daily activities.…”