Xiang Li, Mustafa Abdallah, Yuan-Yao Lou, Mung Chiang, Kwang Taik Kim, Saurabh Bagchi
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Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks
Edge computing is deemed a promising technique to execute latency-sensitive
applications by offloading computation-intensive tasks to edge servers.
Extensive research has been conducted in the field of end-device to edge server
task offloading for several goals, including latency minimization, energy
optimization, and resource optimization. However, few of them consider our
mobile computing devices (smartphones, tablets, and laptops) to be edge
devices. In this paper, we propose a novel multi-tier edge computing framework,
which we refer to as M-TEC, that aims to optimize latency, reduce the
probability of failure, and optimize cost while accounting for the sporadic
failure of personally owned devices and the changing network conditions. We
conduct experiments with a real testbed and a real commercial CBRS 4G network,
and the results indicate that M-TEC is capable of reducing the end-to-end
latency of applications by at least 8\% compared to the best baseline under a
variety of network conditions, while providing reliable performance at an
affordable cost.