Cost Control and Efficiency Optimization in Maintainability Implementation of Wireless Sensor Networks based on Serverless Computing

TL;DR

This paper proposes a serverless computing framework for wireless sensor networks to improve maintainability, reduce costs, and enhance resource utilization across the entire lifecycle, supported by a case study in smart city scenarios.

Contribution

It introduces a novel serverless computing-based maintainability implementation for WSN, decoupling device operation from development to optimize resources and costs.

Findings

Significantly reduces design and operational costs.

Enhances resource reuse and system maintainability.

Supports efficient data collection and management.

Abstract

Wireless sensor network (WSN) has been developed for decades and have performed well in the performance, power consumption, and congestion control. However, the following problems have not been addressed, such as inaccurate cost estimation of device's lifecycle, highly-coupled engineering development, and low utilization of hardware and software resources during the life cycle of WSN. Therefore, we first propose the conceptual view of maintainability implementation for WSN based on Serverless Computing. The maintainability implementation refers to the ability to meet the WSN product to consume the minimum resources with a higher probability in configuration, trial production, debugging, batch production, deployment, operation, and maintenance phases. And then, we discuss that Serverless Computing can be realized at the software functional level of WSN to decouple the device operation and functional development, greatly improve the reuse of resources and exclude the hardware interference. From the perspective of maintainability and cost control, the concept of Serverless Computing can be used to build WSN platforms, which can support the functions of data collection and data management into functional development that may benefit from exploration through upfront expenditures, thereby significantly reducing design, manufacturing, and operational costs. Finally, based on existing technologies and smart city scenarios, the idea of a WSN platform for Serverless Computing is given with a case study.