Efficient Data Collection for IoT Services in Edge Computing Environment

Abstract

The Internet of Things (IoT) represents a major change in sensor data collection. It is predicted that 50 billion devices will produce a large amount of data by 2020. This data needs to be stored efficiently so that it can be efficiently retrieved on demand for real-time application. Most of the Cloud-IoT solutions focus on centralized data collection and storage which is not appropriate for efficient data collection and utilization. For addressing such diverse set of requirements,resources are placed near to the data sources for processing and fast real-time decision making instead of sending all the data to the Cloud. The gateway is such a type of edge device that collects data from smart sensors, but it does not have any pre-processing or decision-making capabilities. Therefore, the gateway has to be made smarter with Fog capabilities and named as Fog Smart Gateway(FSG). We represent the distributed Cloud-IoT solution where data optimally distributed among mini-clouds/Fog nodes. The processing of IoT traffic is taken care of by Virtual Machines(VMs) facilitated by distributed mini-clouds/Fog nodes and located within the edge devices. We optimized the number of mini-clouds placement to reduce the total latency and power consumption induced by traffic aggregation and processing. However, there has been little research on fog node placement. Our results show that the optimal distribution of mini-clouds in the IoT network could yield a total energy saving and reduction in latency compared to processing IoT data in a conventional cloud system.