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Flash memory offers attractive features for storage of data, such as non-volatility, shock resistance, fast access speed, and low power consumption. However, it requires erasing before it can be overwritten. The erase operations are slow and consume comparatively a great deal of power. Furthermore, flash memory can only be erased a limited number of times. To overcome hardware limitations, we use the non-in-place update mechanism that requires a cleaner to reclaim space occupied by obsolete data. To improve cleaning performance and prolong flash memory lifetime, we propose a new data reorganization method. By this method, data in flash memory are dynamically classified and clustered together according to their accessing frequencies. Experimental results show that this clustering technique significantly improved the cleaning performance for a variety of cleaning algorithms. The number of erase operations performed is greatly reduced and flash memory lifetime is prolonged. Even wearing is ensured as well.

Although nonuniform memory access architecture provides better scalability for multicore systems, cores accessing memory on remote nodes take longer than those accessing on local nodes. Remote memory access accompanied by contention for internode interconnection degrades performance. Properly mapping threads to cores and data accessed to their nodes can substantially improve performance and energy efficiency. However, an operating system kernel's load-balancing activity may migrate threads across nodes, which thus messes up the thread mapping. Besides, subsequent data mapping behavior pays for the cost of page migration to reduce remote memory access. Once unsuitable threads are migrated, it is detrimental to system performance. This paper focuses on improving the kernel's internode load balancing on nonuniform memory access systems. We develop a memory-aware kernel mechanism and policies to reduce remote memory access incurred by internode thread migration. The Linux kernel's load balancing mechanism is modified to incorporate selection policies in the internode thread migration, and the kernel is modified to track the amount of memory used by each thread on each node. With this information, well-designed policies can then choose suitable threads for internode migration. The purpose is to avoid migrating a thread that might incur relatively more remote memory access and page migration. The experimental results show that with our mechanism and the proposed selection policies, the system performance is substantially increased when compared with the unmodified Linux kernel that does not consider memory usage and always migrates the first-fit thread in the runqueue that can be migrated to the target central processing unit.

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To support Web clusters with efficient dispatching mechanisms and policies, we propose a light-weight TCP connection transfer mechanism, TCP Rebuilding, and use it to develop a content-aware request dispatching platform, LVS-CAD, in which the request dispatcher can extract and analyze the content in requests and then dispatch each request by its content or type of service requested. To efficiently support HTTP/1.1 persistent connection in Web clusters, request scheduling should be performed per request rather than per connection. Consequently, multiple TCP Rebuilding, as an extension to normal TCP Rebuilding, is proposed and implemented. On this platform, we also devise fast TCP module handshaking to process the handshaking between clients and the request dispatcher in the IP layer instead of in the TCP layer for faster response times. Furthermore, we also propose content-aware request distribution policies that consider cache locality and various types of costs for dispatching requests in this platform, which makes the resource utilization of Web servers more effective. Experimental results of a practical implementation on Linux show that the proposed system, mechanisms, and policies can effectively improve the performance of Web clusters.

Due to the explosive growth of the Internet and increasing service demands from all around the world, the cluster-based system that consists of one request-dispatching server and several requesthandling servers has become a cost-effective way to serve the huge amount of service demands. Nowadays, Web servers have to handle more complex types of requests since requests from clients may be mixed with dynamic Web pages, database processing, or multimedia stream data. Therefore, a Web cluster should be designed with intelligent request dispatching policies for supporting various types of service requests.In this paper, we have proposed two new content-aware request distribution policies named Locality-Aware Request Distribution with Replication and Classification (LARD/RC) and Grouped Client-Aware Policy (GCAP) to dispatch requests efficiently in Web clusters providing multiple types of services and running in homogeneous or heterogeneous environments. We have implemented our proposed policies in the LVS-CAD web cluster that can efficiently perform content-aware request dispatching. Performance evaluation shows that our proposed LARD/RC and GCAP policies could dispatch requests of different types to proper back-end servers in a more efficient way to utilize system resources than the other existing policies in both homogeneous and heterogeneous environments.