BMS: Bandwidth-aware Multi-interface Scheduling for energy-efficient and delay-constrained gateway-to-device communications in IoT
Computer Networks(2023)
Abstract
With the rapid growth of Internet of Things (IoT), gateways are being widely deployed and constantly deliver data traffic to their surrounding IoT devices, referred to as gateway-to-device or G2D communications. As the most commonly-accepted wireless technology, WiFi has been recommended for G2D communications due to its high data rate, high reliability, native IP compatibility, and good reusability of existing infrastructures. However, WiFi is inherently energy-hungry and thus could potentially shorten the lifetime of battery-powered IoT devices. Although numerous schemes have been designed to reduce the energy consumption of WiFi devices, they often suffer from long latency due to untimely wake-ups of the WiFi interface, especially under dynamic traffic. To address this, multi-interface protocols have been proposed to leverage the coexisting low-power ZigBee to enable timely wake-ups of the high-power WiFi interface. Despite high energy efficiency and low delay, these protocols have the silent assumption of unlimited ZigBee bandwidth, thus overlooking the optimization of ZigBee bandwidth efficiency. Hence, their performance is limited, when device density is high and/or ZigBee concurrently performs some other data transmission tasks. In this paper, we propose a Bandwidth-aware Multi-interface Scheduling (BMS) scheme, aiming to make efficient use of the limited ZigBee bandwidth to minimize IoT device’s WiFi energy consumption with constrained transmission delay in G2D communications. With BMS, the gateway utilizes the limited ZigBee bandwidth to dynamically alternate each device between two WiFi transmission modes for minimized energy consumption and bounded delay. A prototype of the proposed system is implemented and evaluated, and the testbed results show that under moderate traffic and delay bound, the energy consumption of BMS is 95.1% and 44.8% lower than those of the standard 802.11 power saving management and a state-of-the-art multi-interface scheme, respectively.
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Key words
Multi-interface,Bandwidth,Energy,IoT
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