Joint computation and communication cooperation for mobile edge computing

By Xiaowen Cao, Feng Wang, Jie Xu, Rui Zhang, Shuguang Cui. 2017

99 citations recorded by the source corpus.

This paper proposes a joint computation and communication cooperation approach in mobile edge computing (MEC) systems for improving the energy efficiency in mobile computing. In particular, we consider a basic three-node MEC system that consists of a user node, a helper node, and an access point (AP) node attached with an MEC server. We focus on the user's latency-constrained computation over a finite-length block and develop a four-slot protocol for implementing the joint computation and communication cooperation. Under this setup, we jointly optimize the task partition and time allocation, and the transmit power for offloading and central processing unit (CPU) frequencies of local computing at the user and the helper, so as to minimize their total energy consumption subject to the user's computation latency constraint. This problem is optimally solved via convex optimization techniques. Numerical results show that the proposed approach significantly improves the computation capacity and the energy efficiency for the user, as compared to other benchmark schemes without such a joint design.

Subfields: Artificial Intelligence, Biomedical Engineering, Computer Networks and Communications

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Medhi Bennis
2. Jihong Park
3. Khaled Ben Letaief
4. Sumudu Samarakoon
5. Merouane Debbah
6. Sameh Sorour
7. Shuguang Cui
8. Umair Mohammad

In Biomedical Engineering

1. Sameh Sorour
2. Rui Zhang
3. Shuguang Cui
4. Khaled Ben Letaief
5. Kaibin Huang
6. Jie Xu

In Computer Networks and Communications

1. Medhi Bennis
2. Merouane Debbah
3. Sameh Sorour
4. Khaled Ben Letaief
5. Umair Mohammad
6. Rui Zhang
7. Jie Xu
8. Jihong Park

Citations in the corpus

• Wireless Network Intelligence at the Edge (2018, background): “Processing the training operations together with other incumbent applications is another viable solution, in which their operation scheduling is optimized as done in MEC [199] and in the context of exploration–exploitation tradeoff [200].”
• A Survey on Mobile Edge Computing: The Communication Perspective (2017, methodology): “a four-slot joint computation-and-communication cooperation protocol was proposed in [127], where the helper not only computes part of the tasks offloaded from the user, but also acts as a relay node to forward the tasks to the MEC server.”
• Multi-Objective Resource Optimization for Hierarchical Mobile Edge Computing (2018, background): “The work of [6] proposes an MEC architecture that allows for some peer-to-peer (P2P) offloading.”
• Joint Computation and Communication Cooperation for Energy-Efficient Mobile Edge Computing (2018, background): “Part of this paper has been presented at the International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks Workshop on Edge and Fog Computing for Intelligent IoT Applications, Shanghai, China, May 7–11, 2018 [1].”
• Adaptive Task Allocation for Mobile Edge Learning (2018, methodology): “This booming need for edge processing is supported by the late advancements in mobile edge computing (MEC) [3]–[6] and hierarchical MEC (H-MEC) [7], [8].”