TY - JOUR
T1 - Latency Minimization for Mobile Edge Computing Networks
AU - Chen, Chang Lin
AU - Brinton, Christopher G.
AU - Aggarwal, Vaneet
N1 - Funding Information:
This work was supported in part by the National Science Foundation under award CNS-1618335, CISCO, Office of Naval Research under Award N00014-21-1-2472, and National Spectrum Consortium under Award W15QKN-15-9-1004
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - The proliferation of data-intensive mobile applications is causing latency to become an issue in mobile edge computing (MEC) systems. In this work, we propose a novel methodology that optimizes communication, computation, and caching configurations in MEC to minimize the mean latency experienced by mobile devices. Transmission and computation processes are modeled using M/G/1 queues to account for service rates and warm-up times. Our caching scheme includes time variables for each file at each edge server in determining when to discard files from storage. We theoretically analyze the latency experienced by mobile devices due to communication, computation, and caching, showing how MEC system latency depends on the offloading decisions of mobile devices, bandwidth and CPU resources, and expiration times of files in the storage of edge servers. Our method for solving the latency minimization problem consists of two main components: iNner cOnVex Approximation (NOVA) to deal with non-convexity in the optimization, and an online algorithm for preventing cache storage violations as new tasks arrive and are serviced by the MEC system. Simulation results show that our algorithm outperforms several baselines in minimizing latency, and verify the benefit of including different resource allocation variables in our optimization.
AB - The proliferation of data-intensive mobile applications is causing latency to become an issue in mobile edge computing (MEC) systems. In this work, we propose a novel methodology that optimizes communication, computation, and caching configurations in MEC to minimize the mean latency experienced by mobile devices. Transmission and computation processes are modeled using M/G/1 queues to account for service rates and warm-up times. Our caching scheme includes time variables for each file at each edge server in determining when to discard files from storage. We theoretically analyze the latency experienced by mobile devices due to communication, computation, and caching, showing how MEC system latency depends on the offloading decisions of mobile devices, bandwidth and CPU resources, and expiration times of files in the storage of edge servers. Our method for solving the latency minimization problem consists of two main components: iNner cOnVex Approximation (NOVA) to deal with non-convexity in the optimization, and an online algorithm for preventing cache storage violations as new tasks arrive and are serviced by the MEC system. Simulation results show that our algorithm outperforms several baselines in minimizing latency, and verify the benefit of including different resource allocation variables in our optimization.
KW - Cloud computing
KW - caching
KW - latency minimization
KW - mobile edge computing
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U2 - 10.1109/TMC.2021.3117511
DO - 10.1109/TMC.2021.3117511
M3 - Article
AN - SCOPUS:85119582185
SN - 1536-1233
VL - 22
SP - 2233
EP - 2247
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 4
ER -