IoT-F2CDM-LB: IoT Based Fog-to-Cloud and Data-in-Motion Architectures with Load Balancing

Abstract

The work in this paper tries to enhance the performance of IoT by modifying the Cloud based architecture in terms of storage, processing, and Load Balancing (LB). The assumption is as follows: In a single Fog server, high traffic coming from Things may cause packet loss which in turn affect the overall IoT performance. To overcome such a situation, LB on Fog layer is proposed and implemented practically using virtualization technology. The proposed IoT based Fog-To-Cloud and Data-inMotion with LB (IoT-F2CDM-LB) architecture consists of two load balancers; HAProxy and Server Load Balancing (SLB), are used to distribute messages from Things to four virtualized Fog servers according to Least Connection technique. The implementation is carried out using VirtualBox and GNS3. Message Queue Telemetry Transport (MQTT) protocol is used to transfer messages between layers. Both load balancers result in packet loss reduction by 50%, lower response time and higher throughput.