2021
Vitoropoulou, M.; Tsitseklis, K.; Karyotis, V.; Papavassiliou, S.
Caching, Recommendations and Opportunistic Offloading at the Network Edge Proceedings Article
In: pp. 112-119, Institute of Electrical and Electronics Engineers Inc., 2021, ISBN: 9781665406680, (cited By 1; Conference of 17th International Conference on Mobility, Sensing and Networking, MSN 2021 ; Conference Date: 13 December 2021 Through 15 December 2021; Conference Code:178754).
Abstract | Links | BibTeX | Tags: Approximation algorithms; Economic and social effects; Heuristic algorithms; Mobile edge computing; Mobile telecommunication systems; Polynomial approximation, Core networks; Delivery delay; Device-to-Device communications; Edge caching; Mobile edge caching; Mobile users; Network edges; Small cells; User mobility pattern; Waiting time, Quality of service
@inproceedings{Vitoropoulou2021112,
title = {Caching, Recommendations and Opportunistic Offloading at the Network Edge},
author = {M. Vitoropoulou and K. Tsitseklis and V. Karyotis and S. Papavassiliou},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128784400&doi=10.1109%2fMSN53354.2021.00031&partnerID=40&md5=b2dead871ec4fdd3a1aba4ab81ae864b},
doi = {10.1109/MSN53354.2021.00031},
isbn = {9781665406680},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Proceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021},
pages = {112-119},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {In this paper, we study the problem of caching at the network edge by taking into account the impact of recommendations on user content requests. We consider a heterogeneous caching network with small cells and mobile users who can offload traffic from the core network by delivering data via Device-to-Device (D2D) communication. Given the user mobility pattern, we derive for each user the expected waiting time to encounter cache-enabled devices and we propose two schemes in order to select the user equipment that will cache content and participate in the offloading. Expressing the user Quality of Experience (QoE) as a function of user-content relevance and its expected delivery delay, we formulate the problem of content placement and recommendations in caching networks as a user QoE maximization problem, which is known to be NP-hard. In order to address it, we provide two heuristic algorithms, the first focusing on user-content relevance and the second focusing on the content delivery delay. We evaluate the performance of our algorithms through simulation over synthetic datasets. The obtained results are compared with a state-of-the-art polynomial-time approximation algorithm and show that the proposed algorithms balance better the trade-off between solution quality and execution time. © 2021 IEEE.},
note = {cited By 1; Conference of 17th International Conference on Mobility, Sensing and Networking, MSN 2021 ; Conference Date: 13 December 2021 Through 15 December 2021; Conference Code:178754},
keywords = {Approximation algorithms; Economic and social effects; Heuristic algorithms; Mobile edge computing; Mobile telecommunication systems; Polynomial approximation, Core networks; Delivery delay; Device-to-Device communications; Edge caching; Mobile edge caching; Mobile users; Network edges; Small cells; User mobility pattern; Waiting time, Quality of service},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we study the problem of caching at the network edge by taking into account the impact of recommendations on user content requests. We consider a heterogeneous caching network with small cells and mobile users who can offload traffic from the core network by delivering data via Device-to-Device (D2D) communication. Given the user mobility pattern, we derive for each user the expected waiting time to encounter cache-enabled devices and we propose two schemes in order to select the user equipment that will cache content and participate in the offloading. Expressing the user Quality of Experience (QoE) as a function of user-content relevance and its expected delivery delay, we formulate the problem of content placement and recommendations in caching networks as a user QoE maximization problem, which is known to be NP-hard. In order to address it, we provide two heuristic algorithms, the first focusing on user-content relevance and the second focusing on the content delivery delay. We evaluate the performance of our algorithms through simulation over synthetic datasets. The obtained results are compared with a state-of-the-art polynomial-time approximation algorithm and show that the proposed algorithms balance better the trade-off between solution quality and execution time. © 2021 IEEE.