Track Co-Chairs:
Luiz Fernando Bittencourt, University of Campinas, Brazil, bit@ic.unicamp.br
Satish Srirama, University of Hyderabad, India, satish.srirama@uohyd.ac.in
Description:
The pervasiveness of mobile devices is a common phenomenon nowadays, and with the emergence of the Internet of Things (IoT), an increasing number of connected devices are being deployed. In Smart Cities, data collection, processing, and distribution play critical roles in everyday quality of life and city planning and development. The use of Cloud computing to support massive amounts of data generated and consumed in such smart environments has some limitations, such as increased latency and substantial network traffic, hampering support for a variety of applications that need low response times. This leads to the edge/fog computing, where the data processing is moved closer to the devices, where it is actually generated. On the other hand, the cloud is important to handle larger applications demanding processing tasks with various data sources that could not be handled at the edge. Therefore, a combination of mobile devices, edge processing devices and the cloud is needed to give support to a variety of applications with heterogeneous requirements. The infrastructure comprising devices, edge, and cloud composes a continuum of computing capacity that needs new management mechanisms and algorithms to support efficient execution of applications.
The Mobile, Edge, and Cloud Computing (MECC) track aims to attract research that explores networking and computing management in the aforementioned computing continuum. The topics of interest include, but are not limited, to:
- Mobile Edge Computing (Multi-access edge computing) management
- Resource management in Edge-Fog-Cloud infrastructures
- Resource allocation in Edge-Fog-Cloud infrastructures
- Joint scheduling and optimization of networking and distributed computing resources
- Edge/fog computing services and infrastructures
- Middleware for cloud/fog computing applications
- Resource slicing in the computing continuum
- Autonomic distributed management
- Business models for the computing continuum
- QoS/QoE management for static and mobile applications
- Distributed infrastructure monitoring
- Performance modeling and evaluation
- Cloud back-ends and resource management for IoT applications
- Microservices and service-mesh
- Virtualization of data center networks
- Debashis De, West Bengal University of Technology, India
- Zoltán Mann, University of Amsterdam, Netherlands
- Antonio Brogi, University of Pisa, Italy
- Yuhong Liu, Santa Clara University, USA
- Khaza Anuarul Hoque, University of Missouri, USA
- Weizhi Meng, Technical University of Denmark, Denmark
- Marco Aiello, University of Stuttgart, Germany
- Ruben Mayer, TU Munich, Germany
- Lin Wang, Vrije Amsterdam, Netherlands
- Kaiwen Zhang, ETS Montreal, Canada
- Changqing Luo, Virginia Commonwealth University, USA
- Prasad Calyam, University of Missouri, USA
- Anwesha Mukherjee, Mahishadal Raj College, India
- Nitin Auluck, Indian Institute of Technology Ropar, India
- Eduardo Cerqueira, Federal University of Para, Brazil
- Minxian Xu, Shenzhen Institutes of Advanced Technology, China
- Mohsen Amini, University of Louisiana, USA
- Shashikant Ilager, TU Wien, Austria
- Shreya Ghosh, IIT Kharagpur, India
- Viktoriya Degler, University of Groningen, Netherlands