Performance Evaluation of Distributed Security Protocols Using Discrete Event Simulation

The Border Gateway Protocol (BGP) that manages inter-domain routing on the Internet lacks security. Protective measures using public key cryptography introduce complexities and costs. To support authentication and other security functionality in large networks, we need public key infrastructures (PKIs). Protocols that distribute and validate certificates introduce additional complexities and costs. The certification path building algorithm that helps users establish trust on certificates in the distributed network environment is particularly complicated. Neither routing security nor PKI come for free. Prior to this work, the research study on performance issues of these large-scale distributed security systems was minimal. In this thesis, we evaluate the performance of BGP security protocols and PKI systems. We answer the questions about how the performance affects protocol behaviors and how we can improve the efficiency of these distributed protocols to bring them one step closer to reality. The complexity of the Internet makes an analytical approach difficult; and the scale of Internet makes empirical approaches also unworkable. Consequently, we take the approach of simulation. We have built the simulation frameworks to model a number of BGP security protocols and the PKI system. We have identified performance problems of Secure BGP (S-BGP), a primary BGP security protocol, and proposed and evaluated Signature Amortization (S-A) and Aggregated Path Authentication (APA) schemes that significantly improve efficiency of S-BGP without compromising security. We have also built a simulation framework for general PKI systems and evaluated certification path building algorithms, a critical part of establishing trust in Internet-scale PKI, and used this framework to improve algorithm performance

Jenga: Harnessing Heterogeneous Memories through Reconfigurable Cache Hierarchies

Conventional memory systems are organized as a rigid hierarchy, with multiple levels of progressively larger and slower memories. Hierarchy allows a simple, fixed design to benefit a wide range of applications, because working sets settle at the smallest (and fastest) level they fit in. However, rigid hierarchies also cause significant overheads, because each level adds latency and energy even when it does not capture the working set. In emerging systems with heterogeneous memory technologies such as stacked DRAM, these overheads often limit performance and efficiency. We propose Jenga, a reconfigurable cache hierarchy that avoids these pathologies and approaches the performance of a hierarchy optimized for each application. Jenga monitors application behavior and dynamically builds virtual cache hierarchies out of heterogeneous, distributed cache banks. Jenga uses simple hardware support and a novel software runtime to configure virtual cache hierarchies. On a 36-core CMP with a 1 GB stacked-DRAM cache, Jenga outperforms a combination of state-of-the-art techniques by 10% on average and by up to 36%, and does so while saving energy, improving system-wide energy-delay product by 29% on average and by up to 96%

A Study of Client-based Caching for Parallel I/O

The trend in parallel computing toward large-scale cluster computers running thousands of cooperating processes per application has led to an I/O bottleneck that has only gotten more severe as the the number of processing cores per CPU has increased. Current parallel file systems are able to provide high bandwidth file access for large contiguous file region accesses; however, applications repeatedly accessing small file regions on unaligned file region boundaries continue to experience poor I/O throughput due to the high overhead associated with accessing parallel file system data. In this dissertation we demonstrate how client-side file data caching can improve parallel file system throughput for applications performing frequent small and unaligned file I/O. We explore the impacts of cache page size and cache capacity using the popular FLASH I/O benchmark and explore a novel cache sharing approach that leverages the trend toward multi-core processors. We also explore a technique we call progressive page caching that represents cache data using dynamic data structures rather than fixed-size pages of file data. Finally, we explore a cache aggregation scheme that leverages the high-level file I/O interfaces provided by the PVFS file system to provide further performance enhancements. In summary, our results indicate that a correctly configured middleware-based file data cache can dramatically improve the performance of I/O workloads dominated by small unaligned file accesses. Further, we demonstrate that a well designed cache can offer stable performance even when the selected cache page granularity is not well matched to the provided workload. Finally, we have shown that high-level file system interfaces can significantly accelerate application performance, and interfaces beyond those currently envisioned by the MPI-IO standard could provide further performance benefits

A comparison of software and hardware synchronization mechanisms for distributed shared memory multiprocessors

technical reportEfficient synchronization is an essential component of parallel computing. The designers of traditional multiprocessors have included hardware support only for simple operations such as compare-and-swap and load-linked/store-conditional, while high level synchronization primitives such as locks, barriers, and condition variables have been implemented in software [9,14,15]. With the advent of directory-based distributed shared memory (DSM) multiprocessors with significant flexibility in their cache controllers [7,12,17], it is worthwhile considering whether this flexibility should be used to support higher level synchronization primitives in hardware. In particular, as part of maintaining data consistency, these architectures maintain lists of processors with a copy of a given cache line, which is most of the hardware needed to implement distributed locks. We studied two software and four hardware implementations of locks and found that hardware implementation can reduce lock acquire and release times by 25-94% compared to well tuned software locks. In terms of macrobenchmark performance, hardware locks reduce application running times by up to 75% on a synthetic benchmark with heavy lock contention and by 3%-6% on a suite of SPLASH-2 benchmarks. In addition, emerging cache coherence protocols promise to increase the time spent synchronizing relative to the time spent accessing shared data, and our study shows that hardware locks can reduce SPLASH-2 execution times by up to 10-13% if the time spent accessing shared data is small. Although the overall performance impact of hardware lock mechanisms varies tremendously depending on the application, the added hardware complexity on a flexible architecture like FLASH [12] or Avalanche [7] is negligible, and thus hardware support for high level synchronization operations should be provided

Scalable Proxy Architecture for Mobile and Peer-to-Peer Networks

The growth of wireless telecommunications has stipulated the interest for anywhere-anytime computing. The synergy between networking and mobility will engender new collaborative applications with mobile devices on heterogeneous platforms. One such middleware is “SYSTEM ON MOBILE DEVICES”, SYD developed by the Yamacraw Embedded Systems research team. This type of middleware is an opening step towards Peer-to-Peer mobile networks. This project envisioned collaborative applications among mobile devices and PDAs were used as servers. This thesis studies various existing architectures in mobile computing and their scalability issues. We also proposed new scalable flexible thick client proxy system FTCPS, an architecture suitable for mobile Peer-to-Peer networks. Our empirical study showed that FTCPS has low response time compared to other architectures

MFS: an Adaptive Distributed File System for Mobile Hosts

Mobility is a critical feature of computer systems, and while wireless networks are common, most applications that run on mobile hosts lack flexible mechanisms for data access in an environment with large and frequent variations in network connectivity. Such conditions arise, for example, in collaborative work applications, particularly when wireless and wired users share files or databases. In this paper, we describe some techniques for adapting data access to network variability in the context of MFS, a client cache manager for a distributed file system. We show how MFS is able to adapt to widely varying bandwidth levels through the use of modeless adaptation, and evaluate the benefit of mechanisms for improving file system performance and cache consistency using microbenchmarks and file system traces

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications

A Holistic Approach to Lowering Latency in Geo-distributed Web Applications

User perceived end-to-end latency of web applications have a huge impact on the revenue for many businesses. The end-to-end latency of web applications is impacted by: (i) User to Application server (front-end) latency which includes downloading and parsing web pages, retrieving further objects requested by javascript executions; and (ii) Application and storage server(back-end) latency which includes retrieving meta-data required for an initial rendering, and subsequent content based on user actions. Improving the user-perceived performance of web applications is challenging, given their complex operating environments involving user-facing web servers, content distribution network (CDN) servers, multi-tiered application servers, and storage servers. Further, the application and storage servers are often deployed on multi-tenant cloud platforms that show high performance variability. While many novel approaches like SPDY and geo-replicated datastores have been developed to improve their performance, many of these solutions are specific to certain layers, and may have different impact on user-perceived performance. The primary goal of this thesis is to address the above challenges in a holistic manner, focusing specifically on improving the end-to-end latency of geo-distributed multi-tiered web applications. This thesis makes the following contributions: (i) First, it reduces user-facing latency by helping CDNs identify and map objects that are more critical for page-load latency to the faster CDN cache layers. Through controlled experiments on real-world web pages, we show the potential of our approach to reduce hundreds of milliseconds in latency without affecting overall CDN miss rates. (ii) Next, it reduces back-end latency by optimally adapting the datastore replication policies (including number and location of replicas) to the heterogeneity in workloads. We show the benefits of our replication models using real-world traces of Twitter, Wikipedia and Gowalla on a 8 datacenter Cassandra cluster deployed on EC2. (iii) Finally, it makes multi-tier applications resilient to the inherent performance variability in the cloud through fine-grained request redirection. We highlight the benefits of our approach by deploying three real-world applications on commercial cloud platforms