Optimization of Cross-layer Collaborative Resource Allocation for Mobile Edge Computing, Caching and Communication

Introduction

With the rapid development of mobile communications and the explosive usage of mobile devices (i.e., smart phones, laptops, tablets, etc.), the mobile Internet facilitates us with a pervasive and powerful platform to provide more and more emerging applications. However, many mobile devices usually have limited computation capabilities and battery power. Migrating computational tasks from the distributed devices to the infrastructure-based cloud servers has the potential to address the aforementioned issues. The cloud servers are always located in the center of core network and far away from the users, which may cause delay fluctuation and additional transmission energy cost. Mobile Edge Computing (MEC) is an emerging paradigm which pursues to provide better services by moving infrastructure-based cloud resources (computation, storage, bandwidth and et al) to the edge of the network. MEC is rapidly becoming a key technology of 5G, which helps to achieve the key technical indicators of 5G business, such as ultra-low latency, ultra-high energy efficiency and ultra-high reliability.

Differ from the traditional cloud, MEC is close to the mobile users, which can reduce the access delay and the cost of using the cloud service. However, we are facing many challenges for scheduling the limited and heterogeneous MEC resources (computation resource and network resource). Firstly, how to implement a cross-layer optimization policy for MEC that jointly optimizes the application layer, network layer, data link layer, as well as physical layer of the protocol stack using an application-oriented objective function while satisfying the different user service requirements (i.e., energy saving, reducing execution delay, reducing price, and et al) is very essential. Secondly, a theoretical framework of cross-layer optimization to balance the efficiency and fairness of resource allocation of MEC, as well as maximize the profit of MEC service providers needs to be proposed. Thirdly, how to design cross-layer collaborative distributed resource management systems that meet the harsh requirements of MEC such as latency, scalability and mobility support, also needs to be considered. In addition, it is also essential to jointly optimize the resource allocation of computation and communication of both the mobile users and the MEC service provider to minimize the total energy consumption subject to the users’ latency constraint.

It is highly expected that “mobile edge computing (MEC)” will be a key technology playing the most important role in 5G and future network. More importantly, it can improve user experience and user service quality. In addition, as pointed out in the section 1, the topic of joint cross-layer collaborative resource optimization for mobile edge computing is not only important but also faces many challenges. Therefore it is necessary to address them to come true the MEC based evolution in our life. This topic is very promising and will attract great interests from readers, including researchers from academia and industry, general readers, mobile application developer as well as students who are engaged in this study.

This Special Section in Computer Communications is inviting researchers to report the-stated-of-the-art advances in joint cross-layer collaborative resource optimization. Authors are invited to submit original practical work and survey papers.

Topics of interest include (but are not limited to):

• Theoretical modeling and performance analysis of resource optimization for MEC

• Joint cross-layer resource allocation for MEC

• New integration resource management architecture of cloud, MEC and user

• Cross-layer service discovery and service recommendations for MEC

• Multi-user computation offloading for MEC

• Multi-edge-server collaboration for MEC

• Delay minimization service provision for MEC

• Cross-layer collaborative distributed systems for MEC

• Cross-layer collaborative MEC Applications, such as smart city, smart grid, and Intelligent Transportation Systems

• Software-defined MEC

• Software-defined offloading for MEC

• Mobility management for MEC

• Security, privacy, and trust of MEC

• MEC for vehicular networks

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Important Dates:

Deadline of Submissions: 31 May 2020

Notification of First Round: 31 July 2020

Submission of revision: 30 September 2020

Acceptance: 31 December 2020

Guest Editors

Prof. Shaohua Wan (Managing Guest Editor), Zhongnan University of Economics and Law, China

Prof. Remigiusz Wiśniewski, University of Zielona Góra, Zielona Góra, Poland

Prof. George Alexandropoulos, National and Kapodistrian University of Athens, Greece

Prof. Zonghua Gu, Department of Applied Physics and Electronics, Umea University, 901 87, Umea, Sweden.

Prof. Pierluigi SIANO, University of Salerno, Fisciano, Italy.