autonomic

简明释义

英[ˌɔːtəˈnɒmɪk]美[ˌɔːtəˈnɑːmɪk]

adj. 自主的；不受意志支配的；与自主神经系统有关的

英英释义

单词用法

同义词

反义词

例句

1.The major benefit of autonomic computing on these platforms is standards-based manageability.

这些平台上的自主计算的主要好处是基于标准的易管理性。

2.As discussed in the Manageability section, autonomic computing is a requirement for cloud storage architectures.

正如在可管理性部分所讨论的，自主计算是云存储架构所必需的。

3.Autonomic computing seems to be a feasible solution to these problems.

自主运算看起来似乎是解决这些问题的一个可行的方案。

4.The latter can be thought of as sitting at the top of the autonomic computing management value chain (as you'll see in Figure 1).

可以认为自主管理应用程序位于自主计算管理价值链的顶部（如图1中所示）。

5.An understanding of what autonomic computing is about is key to understanding the usefulness of new and existing features.

理解自主计算是理解这些新特性和已有特性有效性的关键。

6.To help administrators service and maintain their servers, Lotus Domino 7.0 offers autonomic diagnostic collection.

为了帮助管理员维修和维护其服务器，LotusDomino 7.0提供了称为自动诊断收集的新功能。

7.This design supports the autonomic computing self-healing capability.

该设计支持自主运算自愈合能力。

8.The human body regulates its functions through the autonomic 自主的 nervous system.

人类身体通过自主的神经系统调节其功能。

9.In software development, an autonomic 自主的 system can manage itself without human intervention.

在软件开发中，自主的系统可以在没有人工干预的情况下自我管理。

10.The autonomic 自主的 responses of our body help us react quickly to danger.

我们身体的自主的反应帮助我们迅速对危险作出反应。

11.Researchers are exploring autonomic 自主的 computing systems for better resource management.

研究人员正在探索更好的资源管理的自主的计算系统。

12.The autonomic 自主的 functions of the nervous system include heart rate and digestion.

神经系统的自主的功能包括心率和消化。

作文

In recent years, the term autonomic (自主的) computing has gained significant attention in the field of information technology. This concept refers to systems that can manage themselves without human intervention, much like the autonomic nervous system in biological organisms, which regulates bodily functions automatically. The goal of autonomic (自主的) computing is to create self-managing systems that can adapt to changing conditions, optimize performance, and recover from failures independently. The rise of cloud computing and the Internet of Things (IoT) has made autonomic (自主的) computing more relevant than ever. As organizations increasingly rely on complex networks of devices and services, the need for systems that can autonomously manage resources becomes critical. For example, an autonomic (自主的) system could automatically allocate computing power based on demand, ensuring that applications run smoothly even during peak usage times. Moreover, the implementation of autonomic (自主的) computing can lead to significant cost savings for businesses. By reducing the need for human oversight and intervention, organizations can streamline operations and focus their resources on innovation rather than maintenance. This shift allows IT professionals to concentrate on strategic initiatives that drive growth, rather than getting bogged down by routine tasks. However, the transition to autonomic (自主的) computing is not without its challenges. One major concern is security. As systems become more autonomous, they may also become more vulnerable to cyberattacks. Ensuring that autonomic (自主的) systems can defend themselves against threats is a critical area of research. Developers must implement robust security protocols that allow these systems to identify and respond to potential risks without human input. Another challenge lies in the complexity of creating truly autonomic (自主的) systems. While some level of automation is achievable, fully autonomous systems require advanced algorithms and artificial intelligence to make decisions that were traditionally made by humans. This necessitates ongoing research and development in machine learning and AI technologies. Despite these challenges, the future of autonomic (自主的) computing looks promising. As technology continues to evolve, we can expect to see more sophisticated systems that can learn from their environments and improve their performance over time. For instance, in healthcare, autonomic (自主的) systems could monitor patient data in real-time, adjusting treatments based on individual responses without the need for constant human oversight. In conclusion, autonomic (自主的) computing represents a significant advancement in how we approach system management. By developing technologies that can operate independently, we can enhance efficiency, reduce costs, and improve overall performance. However, as we move towards this future, it is essential to address the accompanying challenges, particularly in security and complexity. With continued innovation and collaboration across sectors, the dream of fully autonomic (自主的) systems may soon become a reality, transforming industries and improving our daily lives.

近年来，术语autonomic（自主的）计算在信息技术领域引起了显著关注。这个概念指的是能够自我管理的系统，无需人类干预，就像生物体中的自主神经系统一样，自动调节身体功能。autonomic（自主的）计算的目标是创建自我管理的系统，这些系统能够适应变化的条件，优化性能，并独立从故障中恢复。 随着云计算和物联网（IoT）的兴起，autonomic（自主的）计算变得比以往任何时候都更加相关。随着组织越来越依赖复杂的设备和服务网络，能够自主管理资源的系统的需求变得至关重要。例如，一个autonomic（自主的）系统可以根据需求自动分配计算能力，确保应用程序即使在高峰使用时也能顺利运行。 此外，实施autonomic（自主的）计算可以为企业带来显著的成本节约。通过减少对人工监督和干预的需求，组织可以简化操作，将资源集中在创新上，而不是维护上。这一转变使IT专业人员能够专注于推动增长的战略性举措，而不必被日常任务所困扰。 然而，向autonomic（自主的）计算的过渡并非没有挑战。一个主要问题是安全性。随着系统变得更加自主，它们可能也会变得更容易受到网络攻击。确保autonomic（自主的）系统能够防御威胁是一个关键研究领域。开发人员必须实施强大的安全协议，使这些系统能够在没有人工输入的情况下识别和响应潜在风险。 另一个挑战在于创建真正的autonomic（自主的）系统的复杂性。虽然某种程度的自动化是可实现的，但完全自主的系统需要先进的算法和人工智能，以做出传统上由人类做出的决策。这需要在机器学习和人工智能技术方面进行持续的研究和开发。 尽管面临这些挑战，autonomic（自主的）计算的未来看起来充满希望。随着技术的不断发展，我们可以期待看到更多复杂的系统，这些系统能够从其环境中学习，并随着时间的推移改善其性能。例如，在医疗保健领域，autonomic（自主的）系统可以实时监测患者数据，根据个体反应调整治疗方案，而无需不断的人为监督。 总之，autonomic（自主的）计算代表了我们管理系统的方法的重大进步。通过开发能够独立操作的技术，我们可以提高效率，降低成本，改善整体性能。然而，随着我们朝着这个未来迈进，解决随之而来的挑战，特别是在安全性和复杂性方面，是至关重要的。随着各行业的持续创新与合作，完全的autonomic（自主的）系统的梦想或许很快就会成为现实，改变行业并改善我们的日常生活。