TY - GEN
T1 - Edge-boost
T2 - 2019 IEEE International Conference on Multimedia and Expo, ICME 2019
AU - Balasubramanian, Venkatraman
AU - Wang, Mu
AU - Reisslein, Martin
AU - Xu, Changqiao
N1 - Funding Information:
This work is supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 61871048 and 61872253.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - By moving computation and caching to the network edge, Mobile Edge Computing (MEC) offloads core networks and shortens data access latencies, which is important for large scale mobile multimedia services. Increasing the density of edge data centers to service these multimedia requests is uneconomical. Recent research has proven the benefits of involving devices in the delivery of multimedia services. This is done by exploiting the idle computation and storage resources via device-to-device (D2D) communication, i.e., by forming a so-called Mobile Device Cloud (MDC). Despite the flexibility and cost efficiency of this MDC paradigm, the timely allocation of caching resources to satisfy the dynamic user demands is challenging. This is mainly due to the uncertainty in resource availability of mobile devices. To this end, we propose Edge-Boost, a novel MDC caching architecture for lowlatency multimedia streaming services. We develop a novel fluid-based model to capture the dynamically changing network status. Additionally, we propose a dynamic caching allocation to jointly minimize caching cost and service latency. Edge-Boost achieves over 20% higher average cache utilization and 15% shorter average access latency than the state-ofthe-art MDC approach.
AB - By moving computation and caching to the network edge, Mobile Edge Computing (MEC) offloads core networks and shortens data access latencies, which is important for large scale mobile multimedia services. Increasing the density of edge data centers to service these multimedia requests is uneconomical. Recent research has proven the benefits of involving devices in the delivery of multimedia services. This is done by exploiting the idle computation and storage resources via device-to-device (D2D) communication, i.e., by forming a so-called Mobile Device Cloud (MDC). Despite the flexibility and cost efficiency of this MDC paradigm, the timely allocation of caching resources to satisfy the dynamic user demands is challenging. This is mainly due to the uncertainty in resource availability of mobile devices. To this end, we propose Edge-Boost, a novel MDC caching architecture for lowlatency multimedia streaming services. We develop a novel fluid-based model to capture the dynamically changing network status. Additionally, we propose a dynamic caching allocation to jointly minimize caching cost and service latency. Edge-Boost achieves over 20% higher average cache utilization and 15% shorter average access latency than the state-ofthe-art MDC approach.
KW - Low latency
KW - Mobile edge computing
KW - Multimedia processing
UR - http://www.scopus.com/inward/record.url?scp=85070981332&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070981332&partnerID=8YFLogxK
U2 - 10.1109/ICME.2019.00290
DO - 10.1109/ICME.2019.00290
M3 - Conference contribution
AN - SCOPUS:85070981332
T3 - Proceedings - IEEE International Conference on Multimedia and Expo
SP - 1684
EP - 1689
BT - Proceedings - 2019 IEEE International Conference on Multimedia and Expo, ICME 2019
PB - IEEE Computer Society
Y2 - 8 July 2019 through 12 July 2019
ER -