WiMi Researches A Blockchain-Assisted Resource Management Scheme for Edge Computing Networks

Rhea-AI Summary

WiMi Hologram Cloud (NASDAQ: WIMI) announced research into a blockchain-assisted resource management solution for edge computing networks. The company is developing a system that uses deep reinforcement learning (DRL) algorithms to optimize the allocation of computational resources between task processing and blockchain consensus processes.

The solution aims to address inefficiencies in traditional edge computing networks by treating task processing and resource allocation as an integrated system rather than separate processes. The DRL algorithm continuously learns from environmental feedback to dynamically adjust resource allocation based on computational demands and blockchain consensus requirements, working to minimize processing latency and energy consumption.

Positive

• Development of innovative technology combining blockchain and edge computing
• Potential improvement in system efficiency and resource utilization
• Advanced implementation of deep reinforcement learning for resource optimization

Negative

• Research stage only - no commercial implementation yet
• No clear timeline for product deployment
• No financial metrics or market impact provided

Insights

Tech Expert

This research into blockchain-assisted resource management represents an incremental technological advancement but lacks immediate commercial impact. The described deep reinforcement learning system for optimizing edge computing resource allocation, while technically interesting, is still in early research phases without clear monetization potential or market implementation timeline.

The technology aims to solve real infrastructure challenges in edge computing networks by balancing computational resources between blockchain consensus processes and task processing. However, there are several limitations to consider:

• No clear path to productization or revenue generation
• Absence of performance metrics or comparative advantages over existing solutions
• No mention of partnerships or commercial applications
• Research stage only with no indication of implementation timeline

For a company with a $83.5M market cap, this type of early-stage research, while promising, is unlikely to generate meaningful near-term value for shareholders.

BEIJING, Dec. 4, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that they are exploring a resource management solution for blockchain-assisted edge computing networks. By leveraging deep reinforcement learning (DRL) algorithms, they aim to achieve effective matching between computational task allocation and the blockchain consensus process, thereby enhancing the overall system performance.

In traditional edge computing networks, task processing and resource allocation are often treated as two separate and independently optimized processes. However, this approach overlooks the inherent connection between resource allocation for computational tasks and the blockchain consensus process, leading to resource waste and inefficiency. The resource management solution being researched by WiMi in blockchain-assisted edge computing networks is a comprehensive approach that leverages deep reinforcement learning technology to view the allocation of computational task resources and the blockchain consensus process as a unified entity. This enables dynamic optimization and intelligent allocation of resources. In this architecture, deep reinforcement learning algorithms are used to jointly optimize task scheduling, transmission power control, and computational resource allocation, making resource allocation more intelligent and adaptive in order to minimize overall task processing latency and energy consumption.

The deep reinforcement learning algorithm optimizes its decision-making process by continuously learning from environmental feedback to achieve the optimal resource allocation strategy. Specifically, it can dynamically adjust the allocation of computational resources based on the current network state and task requirements. For example, when a task has high computational demands, the algorithm automatically increases the allocation of computational resources to reduce processing latency. Conversely, when the task has low computational demands, the algorithm reduces the allocation of computational resources to lower energy consumption. Importantly, the algorithm can dynamically adjust the allocation of computational resources based on the requirements of the blockchain consensus process. For instance, when the blockchain consensus process requires more computational resources, the algorithm prioritizes the smooth operation of the consensus process to ensure system security and trustworthiness. Conversely, when the blockchain consensus process has lower demands for computational resources, the algorithm allocates more resources to task processing to improve system efficiency. By balancing the allocation of computational resources between the two processes, timely task processing and smooth operation of the blockchain consensus process are ensured.

The resource management solution developed by WiMi Research, which is based on blockchain-assisted edge computing networks, achieves effective matching between computational task allocation and the blockchain consensus process through deep reinforcement learning algorithms, thereby enhancing the overall performance of edge computing systems. This solution not only addresses the issues of resource waste and inefficiency in traditional edge computing networks but also provides a new approach for resource management in the future era of the Internet of Things.

About WiMi Hologram Cloud

WiMi Hologram Cloud, Inc. (NASDAQ:WiMi) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.

Safe Harbor Statements

This press release contains "forward-looking statements" within the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates," and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release and the Company's strategic and operational plans contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the US Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases, and other written materials, and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. Several factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition, and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services.

Further information regarding these and other risks is included in the Company's annual report on Form 20-F and the current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release. The Company does not undertake any obligation to update any forward-looking statement except as required under applicable laws.

 

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SOURCE WiMi Hologram Cloud Inc.

FAQ

What is WiMi's new blockchain-assisted resource management solution?

WiMi is developing a resource management solution that uses deep reinforcement learning algorithms to optimize resource allocation between computational tasks and blockchain consensus processes in edge computing networks.

How does WIMI's deep reinforcement learning algorithm work in their new system?

The algorithm continuously learns from environmental feedback to dynamically adjust resource allocation based on network state and task requirements, optimizing between processing latency and energy consumption.

What problem is WIMI trying to solve with their new edge computing solution?

WIMI is addressing resource waste and inefficiency in traditional edge computing networks where task processing and resource allocation are treated as separate processes instead of an integrated system.