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Journal Articles Internet of Things Year : 2023

Nearby connections strategies: Features, usage, and empirical performance evaluation

Marcelo Dias de Amorim
Serge Fdida

Abstract

The Device-to-Device (D2D) communications involve a direct, peer-to-peer link between devices that operates independently of fixed network infrastructures. It can either complement existing network infrastructures or be used as a standalone network to provide services, such as distributing content, supporting emergency services during natural disasters, and enabling smartphone applications like AirDrop (iOS) and Nearby Share (Android). However, the behavior of D2D communication is not always predictable, and there are many challenges to implementing and deploying D2D communication systems in real-world situations. In particular, it is hard to know what throughput one can obtain, as nominal numbers provided by the documentation are seldom observed in practice. This paper focuses on Nearby Connections Application Programming Interface (API) provided by Google. This API offers distinct strategies in function of the network's topology, and choosing the right one for an application is a challenging task as they perform differently. In this paper, we contribute to the research community in two ways. Firstly, we investigate the real-time performance of throughput of two strategies (STAR and POINT-TO-POINT, as they are the only ones to use Bluetooth and Wi-Fi Direct to transfer data). Our study shows that the POINT-TO-POINT strategy generally achieves high throughput performance and is suitable for use cases involving high network traffic. In contrast, the STAR performs poorly in throughput, which can result in link instability and slow transfers in some cases. Secondly, we disclose a tool to help network designers evaluate their networks and fine-tune their protocols and algorithms according to their specificities.
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hal-04225102 , version 1 (02-10-2023)

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Tomas Lagos Jenschke, Marcelo Dias de Amorim, Serge Fdida. Nearby connections strategies: Features, usage, and empirical performance evaluation. Internet of Things, 2023, 23, pp.100895. ⟨10.1016/j.iot.2023.100895⟩. ⟨hal-04225102⟩
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