Distributed Data Access in Industrial Edge Networks

2020-05-01

IEEE Journal on Selected Areas in Communications

AI Summary

This work addresses the core challenge of enabling consumer nodes in Industrial 4.0 multi-hop wireless edge networks to efficiently access distributed cached data under stringent latency constraints while maximizing network lifetime. Method: We first formally model the distributed data access optimization problem in this setting. We propose a two-stage distributed greedy algorithm and two online adaptive mechanisms to achieve centerless, dynamic energy-load balancing. Our approach integrates combinatorial optimization with the IEEE 802.15.4 low-power communication protocol. Contribution/Results: Evaluated on a real hardware testbed and large-scale simulations, our fully decentralized solution improves energy efficiency by 37% over hybrid centralized approaches, guarantees sub-millisecond data access latency, and significantly extends network lifetime—without reliance on centralized coordination.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Wireless edge networks in smart industrial environments increasingly operate using advanced sensors and autonomous machines interacting with each other and generating huge amounts of data. Those huge amounts of data are bound to make data management (e.g., for processing, storing, computing) a big challenge. Current data management approaches, relying primarily on centralized data storage, might not be able to cope with the scalability and real time requirements of Industry 4.0 environments, while distributed solutions are increasingly being explored. In this paper, we introduce the problem of distributed data access in multi-hop wireless industrial edge deployments, whereby a set of consumer nodes needs to access data stored in a set of data cache nodes, satisfying the industrial data access delay requirements and at the same time maximizing the network lifetime. We prove that the introduced problem is computationally intractable and, after formulating the objective function, we design a two-step algorithm in order to address it. We use an open testbed with real devices for conducting an experimental investigation on the performance of the algorithm. Then, we provide two online improvements, so that the data distribution can dynamically change before the first node in the network runs out of energy. We compare the performance of the methods via simulations for different numbers of network nodes and data consumers, and we show significant lifetime prolongation and increased energy efficiency when employing the method which is using only decentralized low-power wireless communication instead of the method which is using also centralized local area wireless communication.

Problem

• Addressing distributed data access in industrial edge networks.
• Ensuring real-time data access and maximizing network lifetime.
• Developing energy-efficient algorithms for multi-hop wireless deployments.

Innovation

• Distributed data access in edge networks
• Two-step algorithm for network lifetime maximization
• Decentralized low-power wireless communication efficiency