Computation Offloading for Real-Time Applications : Server Time Reservation for Periodic Tasks

Detta är en Master-uppsats från KTH/Skolan för elektroteknik och datavetenskap (EECS)

Sammanfattning: Edge computing is a distributed computing paradigm where computing resources are located physically closer to the data source compared to the traditional cloud computing paradigm. Edge computing enables computation offloading from resource-constrained devices to more powerful servers in the edge and cloud. To offer edge and cloud support to real-time industrial applications, the communication to the servers and the server-side computation needs to be predictable. However, the predictability of offloading cannot be guaranteed in an environment where multiple devices are competing for the same edge and cloud resources due to potential server-side scheduling conflicts. To the best or our knowledge, no offloading scheme has been proposed that provides a highly predictable real-time task scheduling in the face of multiple devices offloading to a set of heterogeneous edge/cloud servers. Hence, this thesis approaches the problem of predictable offloading in real-time environments by proposing a centralized server time reservation system to schedule the offloading of real-time tasks to edge and cloud servers. Our reservation system allows end-devices to request external execution time in advance for real-time tasks that will be generated in the future, therefore when such a task is created, it already has a designated offloading server that guarantees its timely execution. Furthermore, this centralized reservation system is capable of optimizing the reservation scheduling strategy with the goal of minimizing energy consumption of edge servers while meeting the stringent deadline constraints of real-time applications.

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