Authors:
Jia Sun
;
Salimur Choudhury
and
Kai Salomaa
Affiliation:
School of Computing, Queen’s University, 99 University Ave, Kingston, Canada
Keyword(s):
Task Assignment, Smart Vehicles, Heuristics, Stable Matching, Multi-Access Edge Computing.
Abstract:
With significant advances in recent technology, computational power must meet new demands. As a result, Multi-access Edge Computing (MEC) is a new networking paradigm that has received a surge in interest from both academia and industry. MEC aims to push powerful computing and storage capabilities from remote cloud servers to up-close edge servers. Vehicular Edge Computing (VEC), a subfield of MEC, has been introduced to specifically increase the computing capacity of vehicular networks, an essential component for the development of Intelligent Transportation Systems (ITS). A problem in the current development of VEC is the high cost of installing enough edge servers to compute all offloaded tasks at peak hours. However, we have observed that parked vehicles (PVs) are a rich reserve of underutilized computing resources, and their incorporation into the VEC network could lead to a solution to the aforementioned problem. This paper proposes a task offloading system with an assumed park
ing time estimation mechanism. Then, a novel formulation of the task offloading problem is presented that minimizes both task delay and wireless channel load. Finally, a matching based heuristic is proposed and evaluated at various configurations of the VEC environment.
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