Cost-Efficient NFV-Enabled Mobile Edge-Cloud for Low Latency Mobile Applications

Authors: Yang, B., Chai, W.K., Xu, Z., Katsaros, K.V. and Pavlou, G.

http://eprints.bournemouth.ac.uk/30160/

Journal: IEEE Transactions on Network and Service Management

Publisher: Institute of Electrical and Electronics Engineers

ISSN: 1932-4537

DOI: 10.1109/TNSM.2018.2790081

Mobile edge-cloud (MEC) aims to support low la- tency mobile services by bringing remote cloud services nearer to mobile users. However, in order to deal with dynamic workloads, MEC is deployed in a large number of fixed-location micro- clouds, leading to resource wastage during stable/low work- load periods. Limiting the number of micro-clouds improves resource utilization and saves operational costs, but faces service performance degradations due to insufficient physical capacity during peak time from nearby micro-clouds. To efficiently support services with low latency requirement under varying workload conditions, we adopt the emerging Network Function Virtualization (NFV)-enabled MEC, which offers new flexibility in hosting MEC services in any virtualized network node, e.g., access points, routers, etc. This flexibility overcomes the limitations imposed by fixed-location solutions, providing new freedom in terms of MEC service-hosting locations. In this paper, we address the questions on where and when to allocate resources as well as how many resources to be allocated among NFV- enabled MECs, such that both the low latency requirements of mobile services and MEC cost efficiency are achieved. We propose a dynamic resource allocation framework that consists of a fast heuristic-based incremental allocation mechanism that dynamically performs resource allocation and a reoptimization algorithm that periodically adjusts allocation to maintain a near- optimal MEC operational cost over time. We show through ex- tensive simulations that our flexible framework always manages to allocate sufficient resources in time to guarantee continuous satisfaction of applications’ low latency requirements. At the same time, our proposal saves up to 33% of cost in comparison to existing fixed-location MEC solutions.

This data was imported from Scopus:

Authors: Yang, B., Chai, W.K., Xu, Z., Katsaros, K.V. and Pavlou, G.

http://eprints.bournemouth.ac.uk/30160/

Journal: IEEE Transactions on Network and Service Management

Volume: 15

Issue: 1

Pages: 475-488

ISSN: 1932-4537

DOI: 10.1109/TNSM.2018.2790081

© 2004-2012 IEEE. Mobile edge-cloud (MEC) aims to support low latency mobile services by bringing remote cloud services nearer to mobile users. However, in order to deal with dynamic workloads, MEC is deployed in a large number of fixed-location micro-clouds, leading to resource wastage during stable/low workload periods. Limiting the number of micro-clouds improves resource utilization and saves operational costs, but faces service performance degradations due to insufficient physical capacity during peak time from nearby micro-clouds. To efficiently support services with low latency requirement under varying workload conditions, we adopt the emerging network function virtualization (NFV)-enabled MEC, which offers new flexibility in hosting MEC services in any virtualized network node, e.g., access points, routers, etc. This flexibility overcomes the limitations imposed by fixed-location solutions, providing new freedom in terms of MEC service-hosting locations. In this paper, we address the questions on where and when to allocate resources as well as how many resources to be allocated among NFV-enabled MECs, such that both the low latency requirements of mobile services and MEC cost efficiency are achieved. We propose a dynamic resource allocation framework that consists of a fast heuristic-based incremental allocation mechanism that dynamically performs resource allocation and a reoptimization algorithm that periodically adjusts allocation to maintain a near-optimal MEC operational cost over time. We show through extensive simulations that our flexible framework always manages to allocate sufficient resources in time to guarantee continuous satisfaction of applications' low latency requirements. At the same time, our proposal saves up to 33% of cost in comparison to existing fixed-location MEC solutions.

This data was imported from Web of Science (Lite):

Authors: Yang, B., Chai, W.K., Xu, Z., Katsaros, K.V. and Pavlou, G.

http://eprints.bournemouth.ac.uk/30160/

Journal: IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT

Volume: 15

Issue: 1

Pages: 475-488

ISSN: 1932-4537

DOI: 10.1109/TNSM.2018.2790081

The data on this page was last updated at 05:12 on February 26, 2020.