Edge Cloud Placement with Traffic Load Alleviation for Cloud Computing

• Main Authors: Kun-Yu Lyu, 呂昆育
• Other Authors: Tai-Lin Chin
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/k3kk38

碩士 === 國立臺灣科技大學 === 資訊工程系 === 107 === In the modern world, the Internet is very widespread. People ask the Internet to provide kinds of services. The user sends a request message to the cloud server on the Internet. Then, the cloud server provides service to the user. Hence, between the user and the server, a traffic is generated as the user is served. However, if there a large traffic be generated and it is a long distance between the user and the cloud server, not only the data transmission time is longer, but also the data flow has more chance to compete with other data flow for the bandwidth, which leads to increase of traffic load. A solution is to deploy edge clouds in the networks. The user requests are served in edge clouds. Due to the cost of deploying an edge cloud is lower than setting up a cloud server, the more edge clouds can be deployed in the networks under the same budget. The deployment of edge cloud is resilient. The edge cloud is close to the user so the influence of data flow generated by service is small, the traffic load of the networks is alleviated. Locations of edge clouds influence data transmission time and traffic load of the networks. This thesis investigates the problem of selecting the locations of edge clouds in a cloud network and allocating user requests to appropriate edge clouds to share the workload of the cloud server while minimizing the traffic originally generated between the user and the cloud server. The problem is formally defined in an integer programming problem. The thesis proposed novel schemes to select the locations of edge clouds and allocate user requests to appropriate edge clouds. User requests are preferred to be processed locally in the nearby edge cloud such that the traffic load in the network could be minimized. Simulation results show that the proposed scheme outperforms other schemes in the recent literature. It is shown to be effective in reducing the traffic load in the network.