Fog-assisted hierarchical data routing strategy for IoT-enabled WSN: Forest fire detection

Peer-to-Peer Networking and Applications(2022)

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摘要
Clustering and routing are among the key techniques to enhance energy-efficiency and, consequently, network lifetime in Wireless Sensor Networks (WSNs). In addition to the network lifetime requirement, some critical event-driven applications (e.g., forest fire detection) have other requirements such as response time and reliability to be met to avoid serious damage. A plethora of cluster-based routing protocols have been proposed in the literature. However, none of the existing protocols address these three issues jointly. In this paper, we propose a Hierarchical Data Routing Strategy (thereafter called HDRS) for fog-enabled WSNs. Firstly, we propose an energy-efficient multi-Fog Nodes (FNs)-based clustered network model. Secondly, we devise a novel approach aimed at separating the routing decision and data forwarding to reduce the communication cost and preserve the limited energy of sensor nodes. In this approach, the ordinary sensor nodes and Cluster Heads (CHs) concentrate only on data forwarding while the routing decision is taken at the FN level, owing to its high ability in terms of storage, energy, and computation. Thirdly, we propose to properly adjusting the network topology by considering the addition and removal of faulty nodes. Interestingly, we put proper node fault-handling rules, which guarantee high-level reliability without any loss of data or causing disruption to the network services. Finally, the proposed protocol is evaluated using the forest fire detection application. The simulations results reveal that HDRS outperforms quality of service-based routing protocol for software-defined WSNs with an improvement of 8.23 % in network lifetime and 19.02 % in network response time. The other main advantages of HDRS are ease of implementation, and low time and message complexities. Also, the HDRS is more suitable for forest fire detection than its peers.
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关键词
Software-defined wireless sensor networks, Fog computing, Clustering, Routing, Forest fire detection
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