It is projected that there will be billions of connected devices and trillions of digitized entities in the years ahead. Increasingly our everyday devices are being empowered with more processing, memory, storage and input/output capacities. The size of the data getting generated by these devices are humongous whereas the scope, speed, and structure of data are varying. Our environments are being stuffed with multifaceted sensors, actuators and devices. The challenge is to aggregate all the property and people data to do localized and cognitive analytics to extricate and disseminate actionable insights in time to produce smarter devices and people-centric services. The traditional cloud environments are massive in their processing and storage capabilities but the real-time data capture, analytics, decision-making and actuation are hard. The strategic alternative is to form edge device clouds for instantaneous data capture, cleansing and crunching of sensor and actuator data
- The Evolution of localized and real-time computing models ( Edge, Fog, Mist, Dew, Cloudlet and mobile cloud computing)
- The realization of smarter Applications and Services through Edge Analytics throug edge platforms (Apache Edgent and Eclipse Kura)
- The Approaches for the formation of Edge Clouds
- The modeling and simuation of edge computing systems and environments through iFogSim toolkit
- The Techniques and tips for the integration of Edge and Traditional Clouds (Private and Public Clouds)
- Envisioning highly sychronized and sophisticated applications through multi-cloud environments comprising edge clouds