Research Area:  Edge Computing

Abstract:

The collaboration of Internet of Things (IoT) devices is promising nowadays to achieve complex requests in edge networks. In this setting, the functionalities of IoT devices are usually encapsulated as IoT services. A request can be fulfilled by the composition of data- or computation-intensive IoT services, which require to either consume a relatively large amount of sensory data or mandate a heavy computation capacity. Discovering functionally complementary IoT services, while satisfying their pre-specified spatial constraints, is a challenge, since certain IoT services may non-exist with respect to current IoT services deployment situation. To remedy this issue, we propose an energy-aware Data- and Computation-intensive service Migration and Scheduling mechanism (DCMS) to re-schedule certain services from their hosting devices to the ones within the geographical region prescribed by the request. Extensive experiments are conducted and evaluation results show that our DCMS is promising in reducing the energy consumption and average delay, in comparison with the state of the arts techniques.

Keywords:  

Author(s) Name:  Xiaocui Li; Zhangbing Zhou; Zhuofeng Zhao; Sami Yangui; Wenbo Zhang

Publisher name:  IEEE

DOI:  10.1109/ICWS53863.2021.00058

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/9590288