基于“蚂蚁喂鸟”算法的分布式系统实现

Preeti Mulay, Krishna Patel, Hector Gómez Gauchía
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引用次数: 0

摘要

不断发展的技术错综复杂地交织在社会和制度系统的结构中。随着“万物互联(IoE)”概念的发明,现在使用动物或人类以电子方式传输细节是现实的。具有传感器技术的物联网概念可以在任何领域证明奇迹,从农业、电子健康、医疗保健等领域开始。人类可以通过使用各种由“自然启发算法”驱动或基于“自然启发算法”的互联设备来改造电子产品。IT、心理学与非IT系统的融合将成为新一代生活的一部分。这种协作概念可以在基于“云到露计算”的技术的帮助下实际实现。为了将如此多的概念整合在一起,必须将重点放在与这些概念实施相关的网络安全和风险上。露水计算在根级将有效地照顾网络安全。露水计算作为分布式系统的后端支持,可以资源化地处理多个实体。“动物数据交换标准”被认为是当今乃至未来几年的创新商机。这些标准已经开始了他们的工作,重点是乳制品相关动物标准。每只奶牛都应该享受生活,保持健康,提高生产力。通过IoE可以轻松实现动物生命数据和动物识别、行为、季节变化、健康等方面的增量学习。
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Distributed System Implementation Based on “Ants Feeding Birds” Algorithm
Evolving technologies are intricately woven into the fabric of social and institutional systems. With the invent of “Internet of Everything (IoE)” concept it is realistic now to employ animals and or humans to transmit details electronically. IoE concepts with sensor technology can prove wonders in any domain for that matter starting from eFarming, eHealth, eCare and what not. Humans can transform electronics by using various eConnected gadgets also motivated due to or based on “Nature Inspired Algorithms”. The confluence of IT, psychology with non-IT systems will be part of new generation's life. Such collaborative concept can be implemented practically with the help of “Cloud-to-Dew-Computing” based technologies. To include so many concepts together, it is essential to concentrate also on Cyber Security and Risk associated with such conceptual implementation. Dew-Computing at root levels will take care of Cyber Security effectually. Dew-Computing being backend support of Distributed System, can process multiple entities resourcefully. “Animal Data Interchange Standards” are very well considered innovative business opportunity these days and for years to come. These standards have started their work focusing on the Dairy related animal standard. Every dairy animal should enjoy life to remain healthy and more productive. Incremental Learning about Animal Life Data and Animal Identification, behavior, seasonal-changes, health etc. can be easily achieved with IoE.
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来源期刊
CiteScore
1.80
自引率
40.00%
发文量
20
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