تقرير
CAVE: Crowdsourcing Passing-By Vehicles for Reliable In-Vehicle Edge Computing
| العنوان: | CAVE: Crowdsourcing Passing-By Vehicles for Reliable In-Vehicle Edge Computing |
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| المؤلفون: | Cao, Jiahe, Liu, Qiang, Chen, Dawei, Han, Kyungtae |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Networking and Internet Architecture |
| الوصف: | In-vehicle edge computing is a much anticipated paradigm to serve ever-increasing computation demands originated from the ego vehicle, such as passenger entertainments. In this paper, we explore the unique idea of crowdsourcing passing-by vehicles to augment computing of the ego vehicle. The challenges lie in the high dynamics of passing-by vehicles, time-correlated task computation, and the stringent requirement of computing reliability for individual user tasks. To this end, we formulate an optimization problem to minimize the end-to-end latency by optimizing the task assignment and resource allocation of user tasks. To address the complex problem, we propose a new algorithm (named CAVE) with multiple key designs. We build an end-to-end network and compute simulator and conduct extensive simulation to evaluate the performance of the proposed algorithm. Comment: This paper is accepted by IEEE GLOBECOM 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2408.00621 |
| رقم الأكسشن: | edsarx.2408.00621 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |