Skip to main content

Seamless Support of Low Latency Mobile Applications with NFV-Enabled Mobile Edge-Cloud.

Yang, B., Chai, W. K., Pavlou, G. and Katsaros, K.V., 2016. Seamless Support of Low Latency Mobile Applications with NFV-Enabled Mobile Edge-Cloud. In: IEEE International Conference on Cloud Networking (CloudNet), 3-5 October 2016, Pisa, Italy.

Full text available as:

SubmittedVersion.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.



Emerging mobile multimedia applications, such as augmented reality, have stringent latency requirements and high computational cost. To address this, mobile edge-cloud (MEC) has been proposed as an approach to bring resources closer to users. Recently, in contrast to conventional fixed cloud locations, the advent of network function virtualization (NFV) has, with some added cost due to the necessary decentralization, enhanced MEC with new flexibility in placing MEC services to any nodes capable of virtualizing their resources. In this work, we address the question on how to optimally place resources among NFV- enabled nodes to support mobile multimedia applications with low latency requirement and when to adapt the current resource placements to address workload changes. We first show that the placement optimization problem is NP-hard and propose an online dynamic resource allocation scheme that consists of an adaptive greedy heuristic algorithm and a detection mechanism to identify the time when the system will no longer be able to satisfy the applications’ delay requirement. Our scheme takes into account the effect of current existing techniques (i.e., auto- scaling and load balancing). We design and implement a realistic NFV-enabled MEC simulated framework and show through ex- tensive simulations that our proposal always manages to allocate sufficient resources on time to guarantee continuous satisfaction of the application latency requirements under changing workload while incurring up to 40% less cost in comparison to existing overprovisioning approaches.

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:24918
Deposited By: Symplectic RT2
Deposited On:02 Nov 2016 16:21
Last Modified:14 Mar 2022 14:00


Downloads per month over past year

More statistics for this item...
Repository Staff Only -