Resilient Edge: Building an adaptive and resilient multi-communication network for IoT Edge using LPWAN and WiFi

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Abstract

Edge computing has gained attention in recent years
due to the adoption of many Internet of Things (IoT) applications
in domestic, industrial and wild settings. The resiliency and
reliability requirements of these applications vary from noncritical
(best delivery efforts) to safety-critical with time-bounded
guarantees. The network connectivity of IoT edge devices remains
the central critical component that needs to meet the timebounded
Quality of Service (QoS) and fault-tolerance guarantees
of the applications. Therefore, in this work, we systematically
investigate how to meet IoT applications mixed-criticality QoS
requirements in multi-communication networks. We (i) present
the network resiliency requirements of IoT applications by
defining a system model (ii) analyse and evaluate the bandwidth,
latency, throughput, maximum packet size of many state-of-the art
LPWAN technologies, such as Sigfox, LoRa, and LTE (CATM1/
NB-IoT) and Wi-Fi, (iii) implement and evaluate an adaptive
system Resilient Edge and Criticality-Aware Best Fit (CABF)
resource allocation algorithm to meet the application resiliency
requirements using Raspberry Pi 4 and Pycom FiPy development
board having five multi-communication networks.We present our
findings on how to achieve 100% of the best-effort high criticality
level message delivery using multi-communication networks.
Original languageEnglish
JournalIEEE Transactions on Network and Service Management
Publication statusAccepted/In press - 23 Nov 2022

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