Delay Analysis of Mobile Edge Computing Using Poisson Cluster Process Modeling: A Stochastic Network Calculus Perspective | IEEE Journals & Magazine | IEEE Xplore

Delay Analysis of Mobile Edge Computing Using Poisson Cluster Process Modeling: A Stochastic Network Calculus Perspective

Publisher: IEEE

Abstract:

Wireless networks in next generation will provide users ubiquitous computing services with low delay by devices at the network edge, namely mobile edge computing (MEC). T...View more

Abstract:

Wireless networks in next generation will provide users ubiquitous computing services with low delay by devices at the network edge, namely mobile edge computing (MEC). The intensive computation tasks can be partially offloaded to the MEC server via the wireless link and then processed through the MEC computation resources to cater for the delay demand. A parallel computation process is formed in the MEC network consists of local computation at MEC users (MUs) and MEC computation at MEC servers. However, the fluctuating wireless channel environment, changeable spatial distribution of MUs and the randomness of MEC servers’ locations make it hard to characterize and guarantee the end-to-end quality of service requirements. In this work, we are devoted to analyze and optimize the overall delay bound for MEC networks under two orthogonal frequency division multiple access (OFDMA) strategies via stochastic network calculus (SNC). Specifically, Poisson cluster process is utilized to capture the randomness of MEC servers’ and users’ spatial locations and to derive the Laplace transform of interference suffered by an MU of interest. The upper bounds for the delay violation probability of two OFDMA strategies are established by exploiting SNC with the Mellin transform of signal-to-interference ratio. Furthermore, we propose an optimal task offloading scheme by minimizing the overall delay, which balances the local computation delay and MEC delay.
Published in: IEEE Transactions on Communications ( Volume: 70, Issue: 4, April 2022)
Page(s): 2532 - 2546
Date of Publication: 16 February 2022

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Publisher: IEEE

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I. Introduction

The drastically increasing popularity of new computation-demanding and delay-sensitive mobile applications have been enabled by the increasing popularity of smart mobile devices. These applications bring numerous computation tasks that cannot be tackled easily by the mobile devices owing to their limited processing capabilities. Mobile edge computing (MEC) has emerged as a promising computing paradigm to deal with this problem in future networks, which allows MEC users (MUs) to offload partial tasks to the edge of networks, i.e., MEC servers [1]. MEC is a type of distributed computing architecture that allocates computation resources to the small computing servers deployed at the edge of the network to provide better quality of service (QoS) for delay-sensitive applications [2]. Despite the promising benefits, the MEC network would potentially result in additional interference supposing that the available spectrum resources are reused for MEC offloading [3]. The interference would significantly deteriorate the QoS of the MEC network and reduce the computation efficiency. As a key metric for modern large-scale networks, end-to-end (E2E) delay for MEC networks is easy to be illustrated while hard to be evaluated, considering the randomness of the network architecture and the complex transmission environment. Thus, it is crucial to investigate the influences of the network parameters on the E2E delay of the MEC networks under multiple interferes environment.

References

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