在外部資源部份本系規劃將從產、學、研三個方向下手來爭取重點領域相關的資源，在產業界方面將試著與業界如中華電信Hi-Cloud、Google、IBM、微軟、台達電、廣達合作，由他們提供更多的資源 (如雲端平台等) 於課程教學中。在學界方面，本系將與教育部補助資訊軟體人才培育推廣計畫中的「雲端計算與服務」軟體創作跨校資源中心爭取網路計算服務或企業雲端服務相關資源給學生使用。而在研究方面將積極爭取與工研院雲端運算行動應用中心合作，安排課外參訪的活動，讓學生能了解應用領域目前的發展現況以及最新的研究成果。本課程的主要目標，在於讓學生了解雲端計算系統相關技術, 特別是在雲端計算系統上的實作與應用。本課程可使學生學習到符合未來發展趨勢的雲端計算系統之基礎原理與相關的實作技術，並且輔以數個雲端計算系統相關技術的實習和實作，以達到理論與實務兼備的教學目的。另外，為提高未來於各校推廣時的適用性，本計畫邀請國內相關領域教授進行教學模組及實驗模組的設計與規劃。其主要達成之目標如下：
•針對雲端計算系統技術開發課程教材與實驗教材
•讓學生暸解與熟悉雲端計算系統的基本原理, 應用,實現的方法以及效能的考量。
•讓學生暸解與熟悉雲端計算之熱門議題，如：Iaas、PaaS、SaaS、全虛擬化、半虛擬化、網路虛擬化、儲存虛擬化、Shared Storage、分散式資料庫、Hadoop、MapReduce、Big Data。
•提高學生對於雲端計算系統的興趣，培植國內雲端計算系統的可用人力。
•在雲端計算系統平台實作，以瞭解雲端計算相關之效能要素。
•利用系統實作，達到理論與實務兼備的教學目的。譬如，學生將會學習虛擬化環境建置(實驗A：KVM安裝)、虛擬機器管理平台建置(實驗B：OpenNebula平台建置) 、虛擬資源管理平台建置(實驗C：OpenStack平台建置)、操作不同的雲端系統(實驗D：Amazon Elastic Compute Cloud系統應用，實驗E：Windows Azure系統應用，以及實驗F：Google App Engine系統應用)分散式資料庫建置(實驗G：Hadoop環境建置)、Hadoop MapReduce程式設計(實驗I：Hadoop MapReduce programming)與雲端儲存環境建置(實驗H：FreeNAS儲存系統建置)。
•在學習的過程中，培養學生獨立思考以及解決問題的能力。
•邀請相關領域教授進行教學模組設計與規劃，以便未來推廣至各校，使其培育之資工人才可以成為我國雲端計算產業研發的主力。

In terms of external resources, the department plans to strive for resources related to key areas from three directions: industry, academia, and research. In terms of industry, it will try to cooperate with industries such as Chunghwa Telecom Hi-Cloud, Google, IBM, Microsoft, Delta, and Quanta, and they will provide more resources (such as cloud platforms, etc.) in course teaching. In the academic field, the department will cooperate with the "Cloud Computing and Services" Software Creation Cross-School Resource Center under the Information Software Talent Training and Promotion Program subsidized by the Ministry of Education to strive for resources related to network computing services or enterprise cloud services for students to use. In terms of research, we will actively strive to cooperate with the Cloud Computing Mobile Application Center of ITRI and arrange extracurricular visits so that students can understand the current development status and the latest research results in the application field. The main goal of this course is to enable students to understand cloud computing system-related technologies, especially the implementation and application of cloud computing systems. This course enables students to learn the basic principles and related implementation technologies of cloud computing systems that are in line with future development trends, and is supplemented by internships and implementations of several cloud computing system-related technologies to achieve the teaching purpose of both theory and practice. In addition, in order to improve the applicability when promoting it in various schools in the future, this plan invites domestic professors in related fields to design and plan teaching modules and experimental modules. Its main goals are as follows:
•Develop course teaching materials and experimental teaching materials for cloud computing system technology
•Let students understand and become familiar with the basic principles, applications, implementation methods and performance considerations of cloud computing systems.
•Let students understand and become familiar with popular topics in cloud computing, such as: Iaas, PaaS, SaaS, full virtualization, paravirtualization, network virtualization, storage virtualization, Shared Storage, distributed database, Hadoop, MapReduce, Big Data.
•Increase students' interest in cloud computing systems and cultivate available manpower for domestic cloud computing systems.
•Implement on the cloud computing system platform to understand the performance factors related to cloud computing.
•Use systematic implementation to achieve the teaching purpose of both theory and practice. For example, students will learn to build a virtualized environment (Lab A: KVM installation), build a virtual machine management platform (Lab B: OpenNebula platform construction), build a virtual resource management platform (Lab C: OpenStack platform construction), operate different cloud systems (Lab D: Amazon Elastic Compute Cloud system application, Lab E: Windows Azure system application, and Lab F: Google App Engine system application) distributed database construction (Lab G: Hadoop environment construction), Hadoop MapReduce programming (Lab I: Hadoop MapReduce programming) and cloud storage environment construction (Lab H: FreeNAS storage system construction).
•In the process of learning, cultivate students' ability to think independently and solve problems.
•Invite professors in related fields to design and plan teaching modules so that they can be promoted to various schools in the future so that the talents they cultivate can become the main force in the research and development of my country's cloud computing industry.

Cloud Computing for Enterprise Architectures (Computer Communications and Networks) [Hardcover]
Zaigham Mahmood (Editor), Richard Hill (Editor)

Cloud Computing for Enterprise Architectures (Computer Communications and Networks) [Hardcover]
Zaigham Mahmood (Editor), Richard Hill (Editor)