Abstract
In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.
Highlights
With the fast development of Internet of Things (IoT) [1] and the coming fifth generation mobile communication systems (5G) [2,3], we are arriving in the post-Cloud era, where a large quality of data are generated by things and many applications will be deployed at the edge of the network to consume these data
We focus on the data storage and information discovery technologies, which are the core technologies of the wireless sensor and actuator networks (WSANs)-based Edge computing systems, in WSANs and conduct a survey of the existing related schemes
From the analysis presented above, we can see that it is non-trivial to migrate the data-storage and information-discovery schemes developed for Wireless SensorNetworks (WSNs) directly to WSANs, and specially designed novel schemes need to be developed for the WSANs-based Edge computing systems
Summary
With the fast development of Internet of Things (IoT) [1] and the coming fifth generation mobile communication systems (5G) [2,3], we are arriving in the post-Cloud era, where a large quality of data are generated by things and many applications will be deployed at the edge of the network to consume these data. It is impossible to design the moving paths and the time duration to stay in each of the locations for the actuators to collect data, as the mobile elements typically do in WSNs. From the analysis presented above, we can see that it is non-trivial to migrate the data-storage and information-discovery schemes developed for WSNs directly to WSANs, and specially designed novel schemes need to be developed for the WSANs-based Edge computing systems. To the best of our knowledge, the WSANs-based Edge computing systems on data storage and information discovery are emerging research areas, and not much research has to date been carried out [42,43,44,45,46,47,48,49,50,51,52,53,54] Those existing schemes mainly follow two basic models: the query-driven model and the event-driven model. We describe these two models separately and analyze the related schemes based on them
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