Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems

摘要

Social sensing based Edge Computing systems (SSEC) have emerged as a new application paradigm in leveraging privately owned edge/IoT devices to collectively provide ubiquitous sensing, computation, and services. In this demo, we compare and contrast various task allocation strategies in SSEC in supporting delay sensitive social sensing applications. We evaluate the system on two real-time social sensing applications and demonstrate the energy savings as well as the Quality of Service (QoS) of the SSEC system. The demonstrated framework highlights the deficiency in traditional pure top-down and bottom-up task allocation solutions and validates a new hybrid task allocation strategy that is more scalable and efficient.