
Research Article
Fog-Based Data Offloading in UWSNs with Discounted Rewards: A Contextual Bandit
@INPROCEEDINGS{10.1007/978-3-030-99200-2_38, author={Yuchen Shan and Hui Wang and Zihao Cao and Yujie Sun and Ting Li}, title={Fog-Based Data Offloading in UWSNs with Discounted Rewards: A Contextual Bandit}, proceedings={Communications and Networking. 16th EAI International Conference, ChinaCom 2021, Virtual Event, November 21-22, 2021, Proceedings}, proceedings_a={CHINACOM}, year={2022}, month={4}, keywords={Contextual bandit Collaborative offloading Dynamic fog computing Urban wireless sensor network}, doi={10.1007/978-3-030-99200-2_38} }
- Yuchen Shan
Hui Wang
Zihao Cao
Yujie Sun
Ting Li
Year: 2022
Fog-Based Data Offloading in UWSNs with Discounted Rewards: A Contextual Bandit
CHINACOM
Springer
DOI: 10.1007/978-3-030-99200-2_38
Abstract
Urban wireless sensor networks (UWSNs) are an important application scenario for the Internet of Things (IoT). Nevertheless, applications based on urban environments are often computationally intensive, and sensor nodes are resource-constrained and heterogeneous. Fog computing has the potential to liberate the computation-intensive mobile nodes through data offloading. Therefore, reliable data collection and scalable coordination based on fog computing are seen as a challenge. In this paper, the challenge of data offloading is modeled as a contextual bandit problem—an important extension of the multi-armed bandit. First, the heterogeneity of the sensor nodes is used as contextual information, allowing the network to complete data collection at a small computational cost. Second, an ever-changing environmental scenario is considered in which the distribution of re-wards is not fixed, but varies over time. Based on this non-stationary bandit model, we propose a contextual bandit algorithm NCB-rDO in order to improve the success rate of data offloading, which solves the problem of data loss when the contextual information changes suddenly. Experimental results demonstrate the effectiveness and robustness of this data offloading algorithm.