TAILIEUCHUNG - Availability in Globally Distributed Storage Systems

At the same time, the majority of users are not ma- licious, and would enable client-side enforcement to avoid exploits such as cross-site scripting andWeb-based worms. Even if only benign users with enhanced clients might perform security enforcement, those users would be protected, and all users would benefit from fewer at- tacks on the Web application. Unfortunately, there are many obstacles to the adop- tion of new, enhanced security mechanisms in popular Web browsers. Even when such enhancements are prac- tical and easy to implement, they may not be deployed widely. Therefore, to increase its chance of widespread adoption, a Web client security mechanism should be practical, simple, and flexible, and be able. | Availability in Globally Distributed Storage Systems Daniel Ford Francois Labelle Fiorentina I. Popovici Murray Stokely Van-Anh Truong Luiz Barroso Carrie Grimes and Sean Quinlan ford flab florentina mstokely @ vatruong@ luiz cgrimes sean @ Google Inc. Abstract Highly available cloud storage is often implemented with complex multi-tiered distributed systems built on top of clusters of commodity servers and disk drives. Sophisticated management load balancing and recovery techniques are needed to achieve high performance and availability amidst an abundance of failure sources that include software hardware network connectivity and power issues. While there is a relative wealth of failure studies of individual components of storage systems such as disk drives relatively little has been reported so far on the overall availability behavior of large cloudbased storage services. We characterize the availability properties of cloud storage systems based on an extensive one year study of Google s main storage infrastructure and present statistical models that enable further insight into the impact of multiple design choices such as data placement and replication strategies. With these models we compare data availability under a variety of system parameters given the real patterns of failures observed in our fleet. 1 Introduction Cloud storage is often implemented by complex multitiered distributed systems on clusters of thousands of commodity servers. For example in Google we run Bigtable 9 on GFS 16 on local Linux file systems that ultimately write to local hard drives. Failures in any of these layers can cause data unavailability. Correctly designing and optimizing these multilayered systems for user goals such as data availability relies on accurate models of system behavior and performance. In the case of distributed storage systems this includes quantifying the impact of failures and prioritizing hardware and software subsystem .

Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.