# Delay constrained Energy Optimization for Edge Cloud Offloading

## TL;DR

This paper presents an optimal solution for energy-efficient cloud offloading under delay constraints, including resource allocation and delay minimization in multi-user edge cloud systems.

## Contribution

It introduces a closed-form optimal decision-making framework for energy and delay optimization in multi-user edge cloud offloading scenarios.

## Key findings

- Derived a closed-form solution for offloading decisions.
- Optimized cloud resource allocation for multiple users.
- Evaluated minimum achievable delay given bandwidth and user count.

## Abstract

Resource limited user-devices may offload computation to a cloud server, in order to reduce power consumption and lower the execution time. However, to communicate to the cloud server over a wireless channel, additional energy is consumed for transmitting the data. Also a delay is introduced for offloading the data and receiving the response. Therefore, an optimal decision needs to be made that would reduce the energy consumption, while simultaneously satisfying the delay constraint. In this paper, we obtain an optimal closed form solution for these decision variables in a multi-user scenario. Furthermore, we optimally allocate the cloud server resources to the user devices, and evaluate the minimum delay that the system can provide, for a given bandwidth and number of user devices.