You are here

Multi-Access Mobile Edge Computing for Heterogeneous IoT

Feature Topic


The convergence of mobile internet and wireless systems have witnessed an explosive growth in resource-hungry and computation-intensive services and applications, which
cover broad paradigms of so-called heterogeneous Internet of Things (H-IoTs). These systems include real-time video/audio surveillance, remote e-health systems, intelligent transportation systems, and Internet of Vehicles (IoV), and etc. Mobile edge computing, by placing various cloud resources (e.g., computational and storage resources) closer to smart devices/objects, has been envisioned as an enabling and highly promising technology to realize and reap the promising benefits of H-IoTs applications. However, the growing demands for ultra-low latency, massive connectivity, and high reliability of the large number of H-IoTs applications has yielded a critical issue in mobile edge computing, i.e. the limited connections (such as connection capacity, bandwidth, or the number of simultaneously affordable connections) between mobile edge cloud and smart devices/objects.

Multi-access mobile edge computing (MA-MEC), which actively exploits a systematic and adaptive integration of recent radio access technologies including 5G, LTE, and Wi-Fi to enhance the access capacity of smart devices to mobile edge platforms, has been considered as a highly promising technology to tackle this issue. The evolution towards the architecture of ultra-dense small-cells (micro / pico / femto cells, and Wi-Fi hotspots) in future radio access networks facilitates the MA-MEC, i.e., the densely deployed small cells can significantly improve the capacity and quality of the connections between smart devices and mobile edge cloud. For instance, the emerging small-cell dual-connectivity in small-cell networks enables smart mobile devices to communicate with conventional macro-cells and off load data traffic to small cells simultaneously. This enhances the access capacity of mobile edge cloud at small cells.

Therefore, with the strength of multi-access for capacity-enhancement, the MA-MEC is expected to bring a variety of benefits, such as i) ultra-low latency between smart devices and edge cloud for real-time, interactive, and mission-critical applications, e.g., the real-time indoor navigation and augmented virtual-reality, ii) privacy and security in local communications to access mobile edge cloud, and iii) the big data analytics at the point of capture for IoT applications. For instance, the MA-MEC can facilitate the implementation of various safety-oriented applications in transport systems, in which MA-MEC provides robust and ultra-low latency connections for smart vehicles to efficiently access mobile edges for real-time safety-related information processing at mobile edge at the road-side units.

However, the success of MA-MEC still requires tackling many new challenges. To efficiently exploit computation and storage resources at mobile edge nodes, a joint optimization of placement of computation/storage resource and cell-association with radio resource allocation is necessitated. Such joint optimization should be adaptive according to time-varying environments, e.g., the varying wireless channel states when users move across the cells and the dynamic computation/storage resource utilizations. Therefore, this Feature Topic (FT) aims at soliciting high quality and unpublished work regarding recent advances in MA-MEC, with the main focus on addressing the fundamental design issues in MA-MEC, and the emerging paradigms and testbeds that use MA-MEC. We solicit papers covering the topics of interests in the following two main categories:

  • Fundamental design issues in MA-MEC
    • Radio resource management for MA-MEC
    • Task scheduling and computation resource management for MA-MEC
    • Virtualization and network slicing for MA-MEC
    • Location and sizing of computation and storage elements for MA-MEC
    • Communication protocols and network architectures for MA-MEC
    • Security, privacy, and reliability in MA-MEC
    • QoE and QoS provisioning in MA-MEC
    • 5G/LTE/WiFi enabled MA-MEC
    • Energy management and green MA-MEC
    • Edge-to-cloud integration and protocols for MA-MEC
    • Human and social-driven design of MA-MEC
  • MA-MEC for Heterogeneous IoT
    • MA-MEC for smart cities
    • MA-MEC for video/audio surveillance
    • MA-MEC for industrial IoT
    • MA-MEC for smart energy systems
    • MA-MEC for smart healthcare
    • MA-MEC for intelligent transportation systems
    • MA-MEC for big data analytics


Yan Zhang
University of Oslo, Norway

Yuan Wu
Zhejiang University of Technology, China

Hassnaa Moustafa
Intel Corporation, USA

Danny H.K. Tsang
Hong Kong University of Science and Technology, Hong Kong

Alberto Leon-Garcia
University of Toronto, Canada

Usman Javaid
Vodafone, UK