Abstract not found

We propose and evaluate the concept of a semantically-smart disk system (SDS). As opposed to a traditional "smart" disk, an SDS has detailed knowledge of how the file system above is using the disk system, including information about the on-disk data structures of the file system. An SDS exploits this knowledge to transparently improve performance or enhance functionality beneath a standard block read/write interface. To automatically acquire this knowledge, we introduce a tool (EOF) that can discover file-system structure for certain types of file systems, and then show how an SDS can exploit this knowledge on-line to understand file-system behavior. We quantify the space and time overheads that are common in an SDS, showing that they are not excessive. We then study the issues surrounding SDS construction by designing and implementing a number of prototypes as case studies; each case study exploits knowledge of some aspect of the file system to implement powerful functionality beneath the standard SCSI interface. Overall, we find that a surprising amount of functionality can be embedded within an SDS, hinting at a future where disk manufacturers can compete on enhanced functionality and not simply cost-per-byte and performance.

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We describe an evolutionary path that allows operating systems to be used in a more flexible and appropriate manner by higher-level services An inf okernel exposes key pieces of inf rmation about its algorithms and internal state; thus, its def ault policies become mechanisms, which can be controlledf rom user-level We have implemented two prototype inf okernels based on the Linux 2 4 and NetBSD 1 5 kernels, called inf Linux and inf BSD, respectively The inf okernels export key abstractions as well as basic inf ormation primitives Using inf oLinux, we have implemented f ur case studies showing that policies within Linux can be manipulated outsideof the kernel Specifically, we show that the def ault file cache replacement algorithm, file layout policy, disk scheduling algorithm, and TCP congestion control algorithm can each be turned into base mechanisms For each case study, we havef ound that inf okernel abstractions can be implemented with little code and that the overhead and accuracyof synthesizing policies at user-level is acceptable Categories a n Subject Descriptors: D.4.7 [Operatin g Systems]: Organ inE in and Desi2 Ge n ral Terms: Desi9 , Experi51 tati1 , Performance Keywords: Poli) , MechaniE) Informatir 1.

Cellular networks are a critical component of the economic and social infrastructures in which we live. In addition to voice services, these networks deliver alphanumeric text messages to the vast majority of wireless subscribers. To encourage the expansion of this new service, telecommunications companies offer connections between their networks and the Internet. The ramifications of such connections, however, have not been fully recognized. In this paper, we evaluate the security impact of the SMS interface on the availability of the cellular phone network. Specifically, we demonstrate the ability to deny voice service to cities the size of Washington D.C. and Manhattan with little more than a cable modem. Moreover, attacks targeting the entire United States are feasible with resources available to medium-sized zombie networks. This analysis begins with an exploration of the structure of cellular networks. We then characterize network behavior and explore a number of reconnaissance techniques aimed at effectively targeting attacks on these systems. We conclude by discussing countermeasures that mitigate or eliminate the threats introduced by these attacks.

We present NeST, a flexible software-only storage appliance designed to meet the storage needs of the Grid. NeST has three key features that make it well-suited for deployment in a Grid environment. First, NeST provides a generic data transfer architecture that supports multiple data transfer protocols (including GridFTP and NFS), and allows for the easy addition of new protocols. Second, NeST is dynamic, adapting itself on-the-fly so that it runs effectively on a wide range of hardware and software platforms. Third, NeST is Grid-aware, implying that features that are necessary for integration into the Grid, such as storage space guarantees, mechanisms for resource and data discovery, user authentication, and quality of service, are a part of the NeST infrastructure.

Operating systems are complex and their behavior depends on many factors. Source code, if available, does not directly help one to understand the OS’s behavior, as the behavior depends on actual workloads and external inputs. Runtime profiling is a key technique to prove new concepts, debug problems, and optimize performance. Unfortunately, existing profiling methods are lacking in important areas—they do not provide enough information about the OS’s behavior, they require OS modification and therefore are not portable, or they incur high overheads thus perturbing the profiled OS. We developed OSprof: a versatile, portable, and efficient OS profiling method based on latency distributions analysis. OSprof automatically selects important profiles for subsequent visual analysis. We have demonstrated that a suitable workload can be used to profile virtually any OS component. OSprof is portable because it can intercept operations and measure OS behavior from user-level or from inside the kernel without requiring source code. OSprof has typical CPU time overheads below 4%. In this paper we describe our techniques and demonstrate their usefulness through a series of profiles conducted on Linux, FreeBSD, and Windows, including client/server scenarios. We discovered and investigated a number of interesting interactions, including scheduler behavior, multi-modal I/O distributions, and a previously unknown lock contention, which we fixed.

For operating system intensive applications, the ability of designers to understand system call performance behavior is essential to achieving high performance. Conventional performance tools, such as monitoring tools and profilers, collect and present their information off-line or via out-ofband channels. We believe that making this information first-class and exposing it to applications via in-band channels on a per-call basis presents opportunities for performance analysis and tuning not available via other mechanisms. Furthermore, our approach provides direct feedback to applications on time spent in the kernel, resource contention, and time spent blocked, allowing them to immediately observe how their actions affect kernel behavior. Not only does this approach provide greater transparency into the workings of the kernel, but it also allows applications to control how performance information is collected, filtered, and correlated with application-level events. To demonstrate the power of this approach, we show that our implementation, DeBox, obtains precise information about OS behavior at low cost, and that it can be used in debugging and tuning application performance on complex workloads. In particular, we focus on the industry-standard SpecWeb99 benchmark running on the Flash Web Server. Using DeBox, we are able to diagnose a series of problematic interactions between the server and the OS. Addressing these issues as well as other optimization opportunities generates an overall factor of four improvement in our SpecWeb99 score, throughput gains on other benchmarks, and latency reductions ranging from a factor of 4 to 47.

An Architecture for Highly Concurrent, Well-Conditioned Internet Services by Matthew David Welsh Doctor of Philosophy in Computer Science University of California at Berkeley Professor David Culler, Chair This dissertation presents an architecture for handling the massive concurrency and load conditioning demands of busy Internet services. Our thesis is that existing programming models and operating system structures do not adequately meet the needs of complex, dynamic Internet servers, which must support extreme concurrency (on the order of tens of thousands of client connections) and experience load spikes that are orders of magnitude greater than the average. We propose a new software framework, called the staged event-driven architecture (or SEDA), in which applications are constructed as a network of event-driven stages connected with explicit queues. In this model, each stage embodies a robust, reusable software component that performs a subset of request processing. By performing admission control on each event queue, the service can be well-conditioned to load, preventing resources from being overcommitted when demand exceeds service capacity. SEDA employs dynamic control to tune runtime parameters (such as the scheduling parameters of each stage) automatically, as well as to manage load, for example, by performing adaptive load shedding.

We introduce Shear, a user-level software tool that characterizes RAID storage arrays. Shear employs a set of controlled algorithms combined with statistical techniques to automatically determine the important properties of a RAID system, including the number of disks, chunk size, level of redundancy, and layout scheme. We illustrate the correctness of Shear by running it upon numerous simulated configurations, and then verify its real-world applicability by running Shear on both software-based and hardware-based RAID systems. Finally, we demonstrate the utility of Shear through three case studies. First, we show how Shear can be used in a storage management environment to verify RAID construction and detect failures. Second, we demonstrate how Shear can be used to extract detailed characteristics about the individual disks within an array. Third, we show how an operating system can use Shear to automatically tune its storage subsystems to specific RAID configurations.