Distributed cloud resources allocation for fair utilization using multi-objective bin packing algorithm

PurposeCloud computing services gained huge attention in recent years and many organizations started moving their business data traditional server to the cloud storage providers. However, increased data storage introduces challenges like inefficient usage of resources in the cloud storage, in order to meet the demands of users and maintain the service level agreement with the clients, the cloud server has to allocate the physical machine to the virtual machines as requested, but the random resource allocations procedures lead to inefficient utilization of resources.Design/methodology/approachThis thesis focuses on resource allocation for reasonable utilization of resources. The overall framework comprises of cloudlets, broker, cloud information system, virtual machines, virtual machine manager, and data center. Existing first fit and best fit algorithms consider the minimization of the number of bins but do not consider leftover bins.FindingsThe proposed algorithm effectively utilizes the resources compared to first, best and worst fit algorithms. The effect of this utilization efficiency can be seen in metrics where central processing unit (CPU), bandwidth (BW), random access memory (RAM) and power consumption outperformed very well than other algorithms by saving 15 kHz of CPU, 92.6kbps of BW, 6GB of RAM and saved 3kW of power compared to first and best fit algorithms.Originality/valueThe proposed multi-objective bin packing algorithm is better for packing VMs on physical servers in order to better utilize different parameters such as memory availability, CPU speed, power and bandwidth availability in the physical machine.

FPGA Implementation of Image Ordering and Packing Algorithm for TuMag Camera

The TuMag instrument is a Tunable Magnetograph that has been designed to measure the magnetic field of the sun. This instrument and others will be connected to a telescope that will be sent into the stratosphere using a balloon for an uninterrupted observation of the sun for four days in the summer of 2022. The TuMag camera is a new development for implementing the image detector of the instrument. It is based on the GPIXEL GSENSE400-BSI scientific CMOS image sensor and an FPGA device in charge of controlling the image sensor, configuring it and grabbing images. FPGA device consists of an array of Configurable Logic Blocks. However, the sensor does not supply the image data in a row-by-column format. This task has to be done in the FPGA that controls the sensor because the frame grabber has a significant workload with the control of all the instruments, the telescope, the refrigeration, the navigation, and so on. This work describes the FPGA implementation of Image Ordering and Packing algorithm for TuMag Camera concerning the real-time ordering of the images before grabbing and sending to the Data Processing Unit.