Co-located with FiCloud conference

With the emergence of wireless communications, geolocation technologies and cloud computing, innovative applications are designed for the Internet of Things (IoT) and Cyber-physical systems, targeting intensive data computations and virtualization technologies. Due to their constraints in terms of energy, computational power, memory, high mobility, sporadic connectivity, and sometimes security constraints, some smart devices need to outsource data storage, application hosting and computation to the Cloud. Hence, the IoT and Cyber-physical systems require efficient and adaptive energy management solutions that optimize energy consumptions through energy-aware communications protocols, scheduling methods, self-organization mechanisms, offloading techniques, and security solutions, among others. In addition, alternative energy sources available in their surrounding environments could be used to achieve perpetual functioning without replacing or recharging batteries as often through energy harvesting. Furthermore, energy management and optimization are also a concern for cloud data centers that need efficient managements of power and performance for computing and air conditioning, and of environmental impact. These factors largely improvise cost versus energy optimization, which can be achieved through various approaches like optimization, computational intelligence and machine learning.

This workshop will address a range of problems related to energy-aware, energy-efficient management solutions for designing distributed computing platforms (software and hardware) for the IoT, Cyber-physical and Cloud Computing systems.

Prospective authors are invited to submit original, previously unpublished work, reporting on novel and significant research contributions, on-going research projects, experimental results and recent developments related to, but not limited to, the following topics:

  • Energy-aware/energy harvesting scheduling algorithms using intelligence
  • Adaptive middleware for energy-efficient computing
  • Instrumentation and measurement of energy-efficient computing and networking
  • Enhanced performance and QoS in energy-efficient systems
  • Resource management in large infrastructures (such as data centres) and in power/energy constrained systems
  • Data management in energy-efficient systems
  • Sensing, monitoring, control, and management of energy systems
  • Modelling, control, and architectures for renewable energy generation resources
  • Privacy and security in energy-aware platforms
  • Metrics, benchmarks, interfaces, and tools to consider energy dimension
  • Energy-aware hardware platforms
  • Specifications and validation of energy-aware platforms
  • Energy efficiency and virtualization in Cloud of Things
  • Energy services for smart cities
  • Intelligent optimisation and computational intelligence for IoT devices
  • Machine learning approaches for energy management
  • Learning of patterns of energy deployment in smart applications
  • Prediction of anticipated energy consumption.