An Approach to QoS-based Task Distribution in Edge Computing Networks for IoT Applications
|Abstract||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.
Recently edge computing has emerged to reduce the negative impacts of tasks offloading to remote computing systems. As edge computing is in close ... (more)
|Contributor||Song, Yaozhong (Author) / Yau, Sik-Sang (Advisor) / Huang, Dijiang (Committee member) / Sarjoughian, Hessam S (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)|
|Subject||Computer engineering / Computer science / edge computing / Internet of Things / load balancing / network flow / optimization / task distribution|
|Note||Doctoral Dissertation Computer Engineering 2018|
|Collaborating Institutions||Graduate College / ASU Library|
|Additional Formats||MODS / OAI Dublin Core / RIS|