Publication Date
Fall 2021
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Navrati Saxena
Second Advisor
Ben Reed
Third Advisor
Abhishek Roy
Keywords
Cloud-based computing networks, P2P cloud, social credits, task migration, cloud security
Abstract
Cloud-based computing networks have taken over the digital landscape. From small non-profits to large multinational corporations, more and more entities have been offloading computing effort to the cloud in order to take advantage of the increased cost-efficiency and scalability of cloud computing. One of the new types of cloud that have emerged is the P2P cloud, which disengages from a traditional datacenter setup by allowing users to instead share their own computing hardware into a cloud to take advantage of cloud computing’s advantages at an even lower cost. However, this new paradigm comes with a slew of challenges, notably, security when operating with the devices of strangers and fairness when not operating in a market-based system. This paper aims to address these two issues by proposing an algorithm based on social credits for a P2P cloud system that uses a social network to establish its security measures. The project implements the Social Credit algorithm along with two other task-migration based load balancing algorithms adapted for a P2P social cloud in Cloudsim Plus, and the results are compared in terms of general metrics and fairness.
Recommended Citation
Huang, Kaiyi, "Achieving Fairness through Load-Balancing in Social Cloud Computing Networks" (2021). Master's Projects. 1047.
DOI: https://doi.org/10.31979/etd.g46w-n6bq
https://scholarworks.sjsu.edu/etd_projects/1047