來回即時移轉，指的是把正在執行的虛擬機於兩個實體機器之間往返遷移，而這種移轉有許多種應用，例如資料中心的能源管理計畫。傳統的方法把移轉視為一種單獨事件，因此在每一次的移轉完成後，虛擬機系統資源會於源起地點被釋放掉。然而，許多資源其實可以被保留，用來降低下一次移轉的花費。
這篇論文提出一個優化廣域網路間來回即時移轉的方法，並且實作出此系統(BFmig)。相較於以往的做法，我們的方法保留了資料中心的彈性。我們利用現今已存在於虛擬機管理系統的快照與位元圖模組來達成我們的方法。使用快照，則虛擬機可以從一個已儲存的狀態中快速重新啟動。而位元圖模組則是用來避免冗餘的資料傳輸以降低移轉的花費。我們實作出優化的來回移轉方法在QEMU 2.0版本。我們也建立了一個效能模組，用來分析優化來回即時移轉的方法。
實驗指出我們提出的方法可以有效地降低移轉所需的花費，在某些應用下，整體的移轉時間最多可以被省下百分之九十九。

Back-and-forth live migration, which means a running VM migrates between two physical machines back and forth, has several applications, such as “follow the moon” policy in data canter management. Traditional methods treat each migration as a single event, so the VM releases its system resources on the source site after migration. However, many resources can be kept to mit-igate the cost of the next migration back to the machine.
This thesis proposes and implements performance optimization methods for back-and-forth live migration over WAN (BFMig). Different from previous work, our approach can keep the data center resiliency. We leverage the technique of snapshot and the bitmap model, which are available in most existing VM management systems. Using the snapshot, a VM can be immediately re-started from the saved state. The bitmaps model is used to avoid redundant data transmission to decrease the costs of migration. We implemented the bank-and-forth live migration optimization methods in QEMU-KVM 2.0. A performance model is also built to analyze the performance im-provement of our approaches.
The experiments show that the proposed methods can significantly reduce the overhead of migrations. The total migration time can be saved up to 99% for some applications.

摘要 1
Abstract 2
Table of Contents 3
1. Introduction 3
2. Related Work 6
2.1. Existing Live Migration Schemes 6
2.1.1. Methods to reduce transferred memory pages 6
2.1.2. Methods to reduce transferred disk data 7
3. Live Migration of Pre-copy Mechanism 9
3.1. Design of Pre-copy Live Migration over WAN 9
3.2. Back-and-forth Live Migration over WAN 12
3.2.1. Snapshot 12
3.2.2. Bitmap Model 13
3.2.3. System Architecture Overview 14
3.2.4. Performance Model 20
4. Performance Evaluation 22
4.1. Environment Setup 22
4.2. Performance of BFMig 23
5. Conclusion 28
5.1. Future Work 29
5.1.1. Integration with other Techniques 29
5.1.2. Migration on Docker 29
6. References 31

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