Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks

Abstract

Maintaining critical data access latency requirements is an important challenge of Industry 4.0. The traditional, centralized industrial networks, which transfer the data to a central network controller prior to delivery, might be incapable of meeting such strict requirements. In this paper, we exploit distributed data management to overcome this issue. Given a set of data, the set of consumer nodes and the maximum access latency that consumers can tolerate, we consider a method for identifying and selecting a limited set of proxies in the network where data needed by the consumer nodes can be cached. The method targets at balancing two requirements; data access latency within the given constraints and low numbers of selected proxies. We implement the method and evaluate its performance using a network of WSN430 IEEE 802.15.4-enabled open nodes. Additionally, we validate a simulation model and use it for performance evaluation in larger scales and more general topologies. We demonstrate that the proposed method (i) guarantees average access latency below the given threshold and (ii) outperforms traditional centralized and even distributed approaches.

Keywords: Industry 4.0; Internet of Things; data management; experimental evaluation; performance analysis.

Figure 1

A typical industrial IoT network for condition monitoring.

Figure 2

Example of data access latency. In this case, the data access latency is $L_{u,p}=l_{u,v_1}+l_{v_1,v_2}+l_{v_2,p}+l_{p,v_2}+l_{v_2,v_1}+l_{v_1,u}$ .

Figure 3

The Data Management Layer (DML): decoupling the data management plane from the network plane.

Figure 4

Experimental setup.

Figure 5

Euratech topology and ProxySelection+ output.

Figure 6

Experimental results in the IoT-LAB Euratech testbed. The validation of the simulation model is displayed in green.

Figure 6

Experimental results in the IoT-LAB Euratech testbed. The validation of the simulation model is displayed in green.

Figure 7

Network with $n=500$ , $m=0.4·\left|S\right|$ .

Figure 8

Comparison of the three methods.