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An Approach to QoS-based Task Distribution in Edge Computing Networks for IoT Applications

Research Area:  Edge Computing


   Internet of Things (IoT) is emerging as part of the infrastructures for advancing a large variety of applications involving connections of many intelligent devices, leading to smart communities. Due to the severe limitation of the computing resources of IoT devices, it is common to offload tasks of various applications requiring substantial computing resources to computing systems with sufficient computing resources, such as servers, cloud systems, and/or data centers for processing. However, this offloading method suffers from both high latency and network congestion in the IoT infrastructures.
   In this dissertation research, an approach is presented to periodically distributing tasks within the edge computing network while satisfying the quality-of-service (QoS) requirements of tasks. The QoS requirements include task completion deadline and security requirement.The approach aims to maximize the number of tasks that can be accommodated in the edge computing network, with consideration of tasks’ priorities.The goal is achieved through the joint optimization of the computing resource allocation and network bandwidth provisioning.

Name of the Researcher:  Yaozhong Song

Name of the Supervisor(s):  Sik-Sang Yau, Chair , Dijiang HuangHessam S. Sarjoughian, Yanchao Zhang

Year of Completion:  2018

University:  Arizona State University

Thesis Link:   Home Page Url