| 書目名稱 | Mapping Biological Systems to Network Systems |
| 編輯 | Heena Rathore |
| 視頻video | http://file.papertrans.cn/624/623741/623741.mp4 |
| 概述 | Shows how bio-inspired systems – which are inherently robust, flexible and have high resilience towards critical errors - hold immense potential for next generation network systems.Outlines computing |
| 圖書封面 |  |
| 描述 | Thebook presents the challenges inherent in the paradigm shift of network systemsfrom static to highly dynamic distributed systems – it proposes solutions thatthe symbiotic nature of biological systems can provide into altering networkingsystems to adapt to these changes. The author discuss how biological systems –which have the inherent capabilities of evolving, self-organizing,self-repairing and flourishing with time – are inspiring researchers to takeopportunities from the biology domain and map them with the problems faced innetwork domain. The book revolves around the central idea of bio-inspiredsystems -- it begins by exploring why biology and computer network research aresuch a natural match. This is followed by presenting a broad overview ofbiologically inspired research in network systems -- it is classified by thebiological field that inspired each topic and by the area of networking inwhich that topic lies.?Each case elucidates how biological concepts havebeen most successfully applied in various domains.?Nevertheless, it alsopresents a case study discussing the security aspects of wireless sensornetworks and how biological solution stand out in comparison to optimizedso |
| 出版日期 | Book 2016 |
| 關(guān)鍵詞 | Bio-Inspired Machine Learning; Bio-inspired systems; Biologically inspired research in network systems |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-29782-8 |
| isbn_softcover | 978-3-319-80652-5 |
| isbn_ebook | 978-3-319-29782-8 |
| copyright | Springer International Publishing Switzerland 2016 |
|Archiver|手機(jī)版|小黑屋|
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