Provisioning Delay-Aware Services in Mobile Edge Cloud-Networks via Efficient Resource Allocation and Optimisation

Abstract: Thanks to advances in wireless communication and mobile computing, the last decade has seen an explosion of new innovative services on smartphone devices in areas as diverse as transportation, mobile payment and social media. The ubiquity of mobile smart devices and their constant presence in every day life has generated unprecedented data traffic between end users and the remote cloud. To prepare for the increasing data traffic in the coming years and the demand for low-latency computation resources near the user, network service providers are increasingly turning to Mobile Edge Computing to bring cloud computing capabilities to the edge of the network.

Mobile Edge Computing (MEC) is a recent network paradigm and is conceived as consisting of three layers: (1) a layer of users, (2) a layer small-scale data centers called cloudlets situated at the network edge, and (3) geographically distributed clouds with rich resources in remote locations. Users at the edge of the network offload computation tasks to the MEC networks instead of remote clouds, thereby decreasing the response time for offloaded tasks and reducing congestion in the backhaul network.

In the oral presentation, we will focus on the provisioning Delay-Aware Services in MEC by efficiently utilising various resources of MECs and remote clouds to reduce the latency of user offloaded tasks in different application scenarios, while meeting ever-growing user demands. Specifically, we will address the following four main issues:

(1) how to balance the workload among cloudlets in MEC to reduce the average response time of user offloaded tasks; (2) how to minimise the operation cost of service providers while maximising network throughput of tasks with specified service chains; (3) how to deploy network service instances (instances of virtual network functions) to meet the resource demands of mobile users and their Quality-of-Service (QoS) requirements; and finally (4) how to coordinate a massive multi-player Augmented Reality (AR) game among players in MEC to maximise the quality of experience of all participating players.


Mike Jia received the BSc degree in Mathematics and Computer Science from Imperial College London in UK in 2013, and the first-class Honours degree in Computer Science at the Australian National University in 2015. He is currently pursuing his Ph.D study in the Research School of Computer Science at the Australian National University. His research interests include mobile cloud computing, network function virtualisation and software defined networking. His publications can be found from Google scholar

Date & time

11am–12pm 30 Nov 2018


Room:Ian Ross Seminar Room (R214)

Internal speakers

Mr Mike Jia

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