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 produce a large amount of data by 2020. That data needs to be stored efficiently so that it can be retrieved efficiently on demand for real-time application. Most of the Cloud-IoT solutions focusing on centralized data collection and storage which is not appropriate for efficient data collection and utilization. For addressing such diverse set of requirements, instead of sending all data to the Cloud, resources are placed near to the data sources for processing and fast real-time decision making. The gateway is such type of edge device that collects the data from smart sensors, but dont 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 optimally distribute data 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. To the best of our knowledge, this is the first work on mini-clouds placement. Our results show that the optimal distribution of mini-clouds in the IoT network could yield a total energy savings and latency reduced compared to processing IoT data in a conventional cloud system.