Abstract
This paper presents a rapid response system architecture for the distributed management of warehouses in logistics by applying the concept of tiered edge computing. A tiered edge node architecture is proposed for the system to process computing tasks of different complexity, and a corresponding rapid response algorithm is introduced. The paper emphasizes the classification of abstracted outlier sensing data which could better match different sensing types and transplant to various application fields. A software-defined simulation is used to evaluate the system performance on response time and response accuracy, from which it can be concluded that common predefined emergency cases can be detected and responded to, rapidly.
Highlights
Wireless Sensor Networks (WSNs) [1] have been widely applied to transport [2], agriculture [3], smart cities [4] and smart homes [5] domains as the critical environmental sensing infrastructure in Internet of Things (IoT) systems
Instead of the standard approach of an integrated single edge layer in the WSN-Edge-Cloud architecture, this paper proposes a novel approach of a hierarchical edge layer with cooperated edge nodes in each of the different tiers
This paper has proposed a rapid response system architecture designed for data outlier detection, related to the errors and exceeding the threshold could be 100% detected by the system
Summary
Wireless Sensor Networks (WSNs) [1] have been widely applied to transport [2], agriculture [3], smart cities [4] and smart homes [5] domains as the critical environmental sensing infrastructure in Internet of Things (IoT) systems. On the node-to-cloud direction, edge nodes focus on local functionality to support geographically closer sensing with the additional feature of data preprocessing and rapid reaction time This aggregated, filtered and preprocessed data is sent to the cloud selectively according to application requirements. In this paper we propose a hierarchical structure for the edge layer in the WSN-Edge-Cloud architecture to meet the requirements of rapid response in the intelligent warehouse scenario. General functions that loosely coupled with concrete applications such as data formatting are achieved on low-level edge nodes while the application-specific functions are allocated to high-level edge nodes Such grading strategy keeps the advantages of edge computing with low latency and enhances the reconfiguration of hierarchical modules at the edge of the network. This paper is organized as follows: Section 2 presents the architecture and methodology of the proposed hierarchical structure in the rapid response system, Section 3 depicts the simulations and analyses the outcomes and Section 4 gives some conclusions and discusses potential future work
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