Peer-Based Collaborative Caching and Prefetching in Mobile Broadcast

Caching and prefetching are two effective ways for mobile peers to improve access latency in mobile environments. With short-range communication such as IEEE 802.11 and Bluetooth, a mobile peer can communicate with neighboring peers and share cached or prefetched data objects. This kind of cooperation improves data availability and access latency. In this chapter the authors review several cooperative caching and prefetching schemes in a mobile environment that supports broadcasting. They present two schemes in detail: CPIX (Cooperative PIX) and ACP (Announcement-based Cooperative Prefetching). CPIX is suitable for mobile peers that have limited power and access the broadcast channel in a demand-driven fashion. ACP is designed for mobile peers that have sufficient power and prefetch from the broadcast channel. They both consider the data availability in local cache, neighbors’ cache, and on the broadcast channel. Moreover, these schemes are simple enough so that they do not incur much information exchange among peers and each peer can make autonomous caching and prefetching decisions.

The Last Line of Defense

With the rise of the Internet, computer systems appear to be more vulnerable than ever from security attacks. Much attention has been focused on the role of the network in security attacks, but evidence suggests that the computer server and its operating system deserve closer examination since it is ultimately the operating system and its core defense mechanisms of authentication and authorization which are compromised in an attack. This chapter provides an exploratory and evaluative discussion of the authentication and authorization features of two widely used server operating systems: Windows and Linux.

Dynamic Analysis and Profiling of Multithreaded Systems

As software-intensive systems become larger, more parallel, and more unpredictable the ability to analyze their behavior is increasingly important. There are two basic approaches to behavioral analysis: static and dynamic. Although static analysis techniques, such as model checking, provide valuable information to software developers and testers, they cannot capture and predict a complete, precise, image of behavior for large-scale systems due to scalability limitations and the inability to model complex external stimuli. This chapter explores four approaches to analyzing the behavior of software systems via dynamic analysis: compiler-based instrumentation, operating system and middleware profiling, virtual machine profiling, and hardware-based profiling. We highlight the advantages and disadvantages of each approach with respect to measuring the performance of multithreaded systems and demonstrate how these approaches can be applied in practice.

Enhancing the Efficiency of Memory Management in a Super-Paging Environment by AMSQM

The concept of Super-Paging has been wandering around for more than a decade. Super-Pages are supported by some operating systems. In addition, there are some interesting research papers that show interesting ideas how to intelligently integrate Super-Pages into modern operating systems; however, the page replacement algorithms used by the contemporary operating system even now use the old Clock algorithm which does not prioritize small or large pages based on their size. In this chapter an algorithm for page replacement in a Super-Page environment is presented. The new technique for page replacement decisions is based on the page size and other parameters; hence is appropriate for a Super-Paging environment.

Exploiting Disk Layout and Block Access History for I/O Prefetch

As the major secondary storage device, the hard disk plays a critical role in modern computer system. In order to improve disk performance, most operating systems conduct data prefetch policies by tracking I/O access pattern, mostly at the level of file abstractions. Though such a solution is useful to exploit application-level access patterns, file-level prefetching has many constraints that limit the capability of fully exploiting disk performance. The reasons are twofold. First, certain prefetch opportunities can only be detected by knowing the data layout on the hard disk, such as metadata blocks. Second, due to the non-uniform access cost on the hard disk, the penalty of mis-prefetching a random block is much more costly than mis-prefetching a sequential block. In order to address the intrinsic limitations of filelevel prefetching, we propose to prefetch data blocks directly at the disk level in a portable way. Our proposed scheme, called DiskSeen, is designed to supplement file-level prefetching. DiskSeen observes the workload access pattern by tracking the locations and access times of disk blocks. Based on analysis of the temporal and spatial relationships of disk data blocks, DiskSeen can significantly increase the sequentiality of disk accesses and improve disk performance in turn. We implemented the DiskSeen scheme in the Linux 2.6 kernel and we show that it can significantly improve the effectiveness of filelevel prefetching and reduce execution times by 20-53% for various types of applications, including grep, CVS, and TPC-H.

Alleviating the Thrashing by Adding Medium- Term Scheduler

A technique for minimizing the paging on a system with a very heavy memory usage is proposed. When there are processes with active memory allocations that should be in the physical memory, but their accumulated size exceeds the physical memory capacity. In such cases, the operating system begins swapping pages in and out the memory on every context switch. The authors lessen this thrashing by placing the processes into several bins, using Bin Packing approximation algorithms. They amend the scheduler to maintain two levels of scheduling - medium-term scheduling and short-term scheduling. The mediumterm scheduler switches the bins in a Round-Robin manner, whereas the short-term scheduler uses the standard Linux scheduler to schedule the processes in each bin. The authors prove that this feature does not necessitate adjustments in the shared memory maintenance. In addition, they explain how to modify the new scheduler to be compatible with some elements of the original scheduler like priority and realtime privileges. Experimental results show substantial improvement on very loaded memories.

Application of both Temporal and Spatial Localities in the Management of Kernel Buffer Cache

As the hard disk remains as the mainstream on-line storage device, it continues to be the performance bottleneck of data-intensive applications. One of existing most effective solutions to ameliorate the bottleneck is to use the buffer cache in the OS kernel to achieve two objectives: reduction of direct access of on-disk data and improvement of disk performance. These two objectives can be achieved by applying both temporal locality and spatial locality in the management of the buffer cache. Traditionally only temporal locality is exploited for the purpose, and spatial locality, which refers to the on-disk sequentiality of requested blocks, is largely ignored. As the throughput of access of sequentially-placed disk blocks can be an order of magnitude higher than that of access to randomly-placed blocks, the missing of spatial locality in the buffer management can cause the performance of applications without dominant sequential accesses to be seriously degraded. In the chapter, we introduce a state-of-the-art technique that seamlessly combines these two locality properties embedded in the data access patterns into the management of the kernel buffer cache management. After elaboration on why the spatial locality is needed in addition to the temporal locality, we detail a framework, DULO (DUal LOcality), in which these two properties are taken account of simultaneously. A prototype implementation of DULO in the Linux kernel as well as some experiment results are presented, showing that DULO can significantly increases disk I/O throughput for real-world applications such as Web server, TPC benchmark, file system benchmark, and scientific programs. It reduces their execution times by as much as 53%. We conclude the chapter by identifying and encouraging a new direction for research and practice on the improvement of disk I/O performance, which is to expose more disk-specific data layout and access patterns to the upper-level system software for disk-oriented policies.

The Exokernel Operating System and Active Networks

There are two forces that are demanding a change in the traditional design of operating systems. One force requires a more flexible operating system that can accommodate the evolving requirements of new hardware and new user applications. The other force requires an operating system that is fast enough to keep pace with faster hardware and faster communication speeds. If a radical change in operating system design is not implemented soon, the traditional operating system will become the performance bottle-neck for computers in the very near future. The Exokernel Operating System, developed at the Massachusetts Institute of Technology, is an operating system that meets the needs of increased speed and increased flexibility. The Exokernel is extensible, which means that it is easily modified. The Exokernel can be easily modified to meet the requirements of the latest hardware or user applications. Ease in modification also means the Exokernel’s performance can be optimized to meet the speed requirements of faster hardware and faster communication. In this chapter, the author explores some details of the Exokernel Operating System. He also explores Active Networking, which is a technology that exploits the extensibility of the Exokernel. His investigation reveals the strengths of the Exokernel as well as some of its design concerns. He concludes his discussion by embracing the Exokernel Operating System and by encouraging more research into this approach to operating system design.

Sequential File Prefetching in Linux

Sequential prefetching is a well established technique for improving I/O performance. As Linux runs an increasing variety of workloads, its in-kernel prefetching algorithm has been challenged by many unexpected and subtle problems; As computer hardware evolves, the design goals should also be adapted. To meet the new challenges and demands, a prefetching algorithm that is aggressive yet safe, flexible yet simple, scalable yet efficient is desired. In this chapter, the author explores the principles of I/O prefetching and present a demand readahead algorithm for Linux. He demonstrates how it handles common readahead issues by a host of case studies. Both static, logic and dynamic behaviors of the readahead algorithm are covered, so as to help readers building both theoretical and practical views of sequential prefetching.

Swap Token

Most computer systems use the global page replacement policy based on the LRU principle to reduce page faults. The LRU principle for the global page replacement dictates that a Least Recently Used (LRU) page, or the least active page in a general sense, should be selected for replacement in the entire user memory space. However, in a multiprogramming environment under high memory load, an indiscriminate use of the principle can lead to system thrashing, in which all processes spend most of their time waiting for the disk service instead of making progress. In this chapter, we will rethink the application of the LRU principle on global paging to identify one of root causes for thrashing, and describe a mechanism, named as swap token, to solve the issue. The mechnism is simple in its design and implementation but highly effective in alleviating or removing thrashing. A key feature of the swap token mechanism is that it can distinguish the conditions for an LRU page, or a page that has not been used for relatively long period of time, to be generated and accordingly categorize LRU pages into two types: true and false LRU pages. The mechanism identifies false LRU pages to avoid use of the LRU principle on these pages, in order to remove thrashing. A prototype implementation of the swap token mechanism in the Linux kernel as well as some experiment measurements are presented. The experiment results show that the mechanism can consistently reduce the program execution slowdown in a multiprogramming environment including SPEC2000 programs and other memory-intensive applications by up to 67%. The slowdown reductions mainly come from reductions of up to 95% of total page faults during program interactions. This chapter also shows that the mechanism introduces little overhead to program executions, and its implementations on Linux (and Unix) systems are straightforward.