Over the past decade, the quest for a sustainable future has driven significant advancements in the integration of Software-Defined Networking (SDN) and Machine Learning (ML) within Hybrid Intelligent Computing. SDN's centralized control and programmability provide a robust foundation for resource optimization, reducing energy consumption in network infrastructures and data centers. This architecture seamlessly integrates renewable energy sources, further lowering the carbon footprint of network operations. ML enhances network management by leveraging historical and real-time data to forecast traffic patterns, detect anomalies, and optimize routing decisions, thereby complementing SDN's capabilities. This proactive and adaptable approach enhances network efficiency, reduces energy consumption during peak usage, and supports environmental initiatives. The combination of SDN and ML effectively optimizes resources, ensuring efficient utilization of processing power and energy, minimizing waste, and enabling proactive maintenance that decreases network downtime and improves reliability. Additionally, the efficient implementation of edge computing reduces data transmission distances, conserving energy.
The integration of SDN and ML plays a pivotal role in smart city initiatives and IoT deployments, enabling effective traffic control, reducing congestion, and minimizing pollution. By utilizing real-time sensor data, these technologies optimize traffic flow through dynamic traffic light adjustments and routing, contributing to a more environmentally friendly urban environment. Overall, the synergy between SDN and ML in Hybrid Intelligent Computing represents a crucial advancement toward a sustainable and environmentally conscious future, ensuring that network management aligns with principles of environmental responsibility. This workshop will focus on the latest research and applications that have accelerated this transformation in the computing world. It will highlight innovative solutions built on complex networks based on distributed computing systems, with a particular emphasis on areas such as healthcare, transportation, smart cities, green computing, and 5G. We invite researchers to submit their work on these emerging topics, fostering discussions and collaborations that drive the field forward. The workshop will focus on women participation in the research targeting the following (but not limited to) emerging fields:
5G and Beyond
Ad-hoc, Sensor, PAN and Mesh Networks
Backscatter and Ultra-low Power Networks
Biological Distributed Algorithms
Blockchains
Cloud Computing and Big Data Processing
Cognitive Networking
Disaster response
Distributed AI/ML
Distributed Data-Analytics
Distributed game theory
Energy and Sustainability
Edge, Fog Computing and Mobile Offloading
Fault-tolerance, Reliability, and Availability of Distributed Systems
Federated Learning
Internet of Things and Cyber-Physical systems
Mobile Crowdsensing and Social Network Analysis and Mining
Next-generation internet
Pervasive and Mobile Computing
Peer-to-Peer Networks - Architectures and Algorithms
Security, Privacy and Game Theory in Distributed Computing and Networking
Smart City Applications
Self-* (Self-organization, Self-stabilization, Self-healing etc) and Autonomic Computing
Unmanned Aerial Vehicles
Vehicular Networks