Infotainment Enabled Smart Cars: A Joint Communication, Caching, and Computation Approach

S. M. Ahsan Kazmi; Tri Nguyen Dang; Ibrar Yaqoob; Anselme Ndikumana; Ejaz Ahmed; Rasheed Hussain; Choong Seon Hong

doi:10.1109/TVT.2019.2930601

Infotainment Enabled Smart Cars: A Joint Communication, Caching, and Computation Approach

S. M. Ahsan Kazmi
, Tri Nguyen Dang
, Ibrar Yaqoob
, Anselme Ndikumana
, Ejaz Ahmed
, Rasheed Hussain
, Choong Seon Hong^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

78 Citations (Scopus)

Abstract

Remarkable prevalence of cloud computing has enabled smart cars to provide infotainment services. However, retrieving infotainment contents from long-distance data centers poses a significant delay, thus hindering to offer stringent latency-aware infotainment services. Multi-access edge computing is a promising option to meet strict latency requirements. However, it imposes severe resource constraints with respect to caching, and computation. Similarly, communication resources utilized to fetch the infotainment contents are scarce. In this paper, we jointly consider communication, caching, and computation (3C) to reduce infotainment content retrieval delay for smart cars. We formulate the problem as a mix-integer, nonlinear, and nonconvex optimization to minimize the latency. Furthermore, we relax the formulated problem from NP-hard to linear programming. Then, we propose a joint solution (3C) based on the alternative direction method of multipliers technique, which operates in a distributed manner. We compare the proposed 3C solution with various approaches, namely, greedy, random, and centralized. Simulation results reveal that the proposed solution reduces delay up to 9% and 28 compared to the greedy and random approaches, respectively.

Original language	English
Article number	8769920
Pages (from-to)	8408-8420
Number of pages	13
Journal	IEEE Transactions on Vehicular Technology
Volume	68
Issue number	9
DOIs	https://doi.org/10.1109/TVT.2019.2930601
Publication status	Published - Sept 2019

Bibliographical note

Funding Information:
Manuscript received January 3, 2019; revised April 29, 2019 and July 5, 2019; accepted July 16, 2019. Date of publication July 23, 2019; date of current version September 17, 2019. This work was supported in part by the Institute of Iunfor-mation and communications Technology Planning and Evaluation (IITP) under Grant 2019-0-01287, funded by the Korea Government (MSIT), in part by the Evolvable Deep Learning Model Generation Platform for Edge Computing, and in part by the MSIT, Korea, under the Grand Information Technology Research Center support program under Grant IITP-2018-2015-0-00742 supervised by the IITP. The review of this paper was coordinated by the Guest Editors of the Special Section on Vehicle Connectivity and Automation Using 5G. (Corresponding author: Choong Seon Hong.) S. M. A. Kazmi is with the Networks and Blockchain Lab, Institute of Information Security and Cyber Physical System, Innopolis University, In-nopolis 420500, Russia, and also with the Department of Computer Science and Engineering, Kyung Hee University, Seoul 17104, South Korea (e-mail: [email protected]).

Publisher Copyright:
© 1967-2012 IEEE.

Keywords

5G network
caching
multi-access edge computing
Smart cars
vehicular networks

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title = "Infotainment Enabled Smart Cars: A Joint Communication, Caching, and Computation Approach",

abstract = "Remarkable prevalence of cloud computing has enabled smart cars to provide infotainment services. However, retrieving infotainment contents from long-distance data centers poses a significant delay, thus hindering to offer stringent latency-aware infotainment services. Multi-access edge computing is a promising option to meet strict latency requirements. However, it imposes severe resource constraints with respect to caching, and computation. Similarly, communication resources utilized to fetch the infotainment contents are scarce. In this paper, we jointly consider communication, caching, and computation (3C) to reduce infotainment content retrieval delay for smart cars. We formulate the problem as a mix-integer, nonlinear, and nonconvex optimization to minimize the latency. Furthermore, we relax the formulated problem from NP-hard to linear programming. Then, we propose a joint solution (3C) based on the alternative direction method of multipliers technique, which operates in a distributed manner. We compare the proposed 3C solution with various approaches, namely, greedy, random, and centralized. Simulation results reveal that the proposed solution reduces delay up to 9\% and 28 compared to the greedy and random approaches, respectively.",

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note = "Funding Information: Manuscript received January 3, 2019; revised April 29, 2019 and July 5, 2019; accepted July 16, 2019. Date of publication July 23, 2019; date of current version September 17, 2019. This work was supported in part by the Institute of Iunfor-mation and communications Technology Planning and Evaluation (IITP) under Grant 2019-0-01287, funded by the Korea Government (MSIT), in part by the Evolvable Deep Learning Model Generation Platform for Edge Computing, and in part by the MSIT, Korea, under the Grand Information Technology Research Center support program under Grant IITP-2018-2015-0-00742 supervised by the IITP. The review of this paper was coordinated by the Guest Editors of the Special Section on Vehicle Connectivity and Automation Using 5G. (Corresponding author: Choong Seon Hong.) S. M. A. Kazmi is with the Networks and Blockchain Lab, Institute of Information Security and Cyber Physical System, Innopolis University, In-nopolis 420500, Russia, and also with the Department of Computer Science and Engineering, Kyung Hee University, Seoul 17104, South Korea (e-mail: [email protected]). Publisher Copyright: {\textcopyright} 1967-2012 IEEE.",

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AU - Ndikumana, Anselme

AU - Ahmed, Ejaz

AU - Hussain, Rasheed

AU - Hong, Choong Seon

N1 - Funding Information: Manuscript received January 3, 2019; revised April 29, 2019 and July 5, 2019; accepted July 16, 2019. Date of publication July 23, 2019; date of current version September 17, 2019. This work was supported in part by the Institute of Iunfor-mation and communications Technology Planning and Evaluation (IITP) under Grant 2019-0-01287, funded by the Korea Government (MSIT), in part by the Evolvable Deep Learning Model Generation Platform for Edge Computing, and in part by the MSIT, Korea, under the Grand Information Technology Research Center support program under Grant IITP-2018-2015-0-00742 supervised by the IITP. The review of this paper was coordinated by the Guest Editors of the Special Section on Vehicle Connectivity and Automation Using 5G. (Corresponding author: Choong Seon Hong.) S. M. A. Kazmi is with the Networks and Blockchain Lab, Institute of Information Security and Cyber Physical System, Innopolis University, In-nopolis 420500, Russia, and also with the Department of Computer Science and Engineering, Kyung Hee University, Seoul 17104, South Korea (e-mail: [email protected]). Publisher Copyright: © 1967-2012 IEEE.

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ER -

Infotainment Enabled Smart Cars: A Joint Communication, Caching, and Computation Approach

Abstract

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Keywords

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