Ms. Wen Jing Li Profile

Wen Jing Li

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Proceedings Article | 7 December 2023 Paper

Energy-aware edge computing resource scheduling method

Guangping Zhu, Qiang Li, Wenjing Li, Dongdong Lv, Yongshan Guo

Proceedings Volume 12941, 1294118 (2023) https://doi.org/10.1117/12.3011803

KEYWORDS: Data transmission, Batteries, Mathematical optimization, Lithium, Internet of things, Fusion energy, Cloud computing, Computing systems, Relays, Performance modeling

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Currently, various energy sources such as electricity, heat, gas, and water in cities are relatively independently supplied, making it difficult to meet the demand for integrated energy utilization in new smart cities. The urban energy supply structure urgently needs to evolve from single transmission to gradual integration and coupling of multiple flows, which highlights the pressing need to enhance capabilities such as accurate perception of energy status data, trustworthy fusion and sharing, and precise energy efficiency services. These capabilities will greatly contribute to the improvement of overall urban energy efficiency and economic structure optimization. This article primarily focuses on the scheduling of computational resources between edge servers and terminal devices. Edge computing reduces data transmission latency and enhances computational agility during the computation offloading process. However, the computational capacity of edge servers is also limited, and in certain specific computation offloading scenarios (such as ultra-dense networks), interference may arise, leading to unexpected transmission delays. Therefore, it is not advisable to offload all tasks for execution on edge servers; some tasks should be handled by the terminal devices (SMD). Despite consuming more energy through local execution, this approach eliminates the need to consider data transmission time, thus significantly boosting task responsiveness. This article aims to design a task offloading scheme that is aware of terminal energy consumption and involves scheduling computational resources between edge servers and terminal devices.

Proceedings Article | 29 March 2023 Paper

Research on blockchain scalability based on sharding strategy

Xin Su Mei, WenJing Guo, Zhu Liu, Yu Min Liu, Wen Jing Li, Pei Yao Zhang

Proceedings Volume 12566, 1256640 (2023) https://doi.org/10.1117/12.2667350

KEYWORDS: Blockchain, Databases, Design and modelling, Data modeling, Telecommunications, Tolerancing, Systems modeling, Failure analysis, Technology, Computing systems

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The emergence of cryptocurrencies has promoted the development of blockchain technology. However, due to the low performance and poor scalability of the blockchain, it is difficult to apply the blockchain technology to production. Analysis of its essential reason is mainly caused by the distributed consensus protocol. Distributed consensus protocols provide data transparency, integrity, and immutability in a decentralized and untrusted environment, but good security greatly sacrifices scalability. In order to improve the performance and scalability of the system. This paper first improves the Byzantine consensus protocol and improves the throughput of a single shard; on this basis, an efficient shard formation protocol is designed, which can safely assign nodes to shards. This paper relies on trusted hardware (SGX) to achieve consensus and sharding protocol performance improvements. Second, we design a transaction protocol that ensures transaction security and flexibility even when the transaction coordinator is malicious; finally, our research is extensively evaluated on local clusters and on Google Cloud Platform. The results show that the consensus and shard formation protocol in this paper outperforms other advanced solutions in scale and can well scale the blockchain system through sharding and consensus formation protocol. More importantly, the scalable blockchain system based on the sharding strategy proposed in this paper achieves high throughput and can handle Visa-level workloads.

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