Improving Storage with Stackable Extensions

Storage is a central part of computing. Driven by exponentially increasing content generation rate and a widening performance gap between memory and secondary storage, researchers are in the perennial quest to push for further innovation. This has resulted in novel ways to "squeeze" more capacity and performance out of current and emerging storage technology. Adding intelligence and leveraging new types of storage devices has opened the door to a whole new class of optimizations to save cost, improve performance, and reduce energy consumption. In this dissertation, we first develop, analyze, and evaluate three storage extensions. Our first extension tracks application access patterns and writes data in the way individual applications most commonly access it to benefit from the sequential throughput of disks. Our second extension uses a lower power flash device as a cache to save energy and turn off the disk during idle periods. Our third extension is designed to leverage the characteristics of both disks and solid state devices by placing data in the most appropriate device to improve performance and save power. In developing these systems, we learned that extending the storage stack is a complex process. Implementing new ideas incurs a prolonged and cumbersome development process and requires developers to have advanced knowledge of the entire system to ensure that extensions accomplish their goal without compromising data recoverability. Futhermore, storage administrators are often reluctant to deploy specific storage extensions without understanding how they interact with other extensions and if the extension ultimately achieves the intended goal. We address these challenges by using a combination of approaches. First, we simplify the storage extension development process with system-level infrastructure that implements core functionality commonly needed for storage extension development. Second, we develop a formal theory to assist administrators deploy storage extensions while guaranteeing that the given high level goals are satisfied. There are, however, some cases for which our theory is inconclusive. For such scenarios we present an experimental methodology that allows administrators to pick an extension that performs best for a given workload. Our evaluation demostrates the benefits of both the infrastructure and the formal theory.

Optimizing storage and memory systems for energy and performance

Electrical energy is an essential resource for the modern world. Unfortunately, its price has almost doubled in the last decade. Furthermore, energy production is also currently one of the primary sources of pollution. These concerns are becoming more important in data-centers. As more computational power is required to serve hundreds of millions of users, bigger data-centers are becoming necessary. This results in higher electrical energy consumption. Of all the energy used in data-centers, including power distribution units, lights, and cooling, computer hardware consumes as much as 80%. Consequently, there is opportunity to make data-centers more energy efficient by designing systems with lower energy footprint. Consuming less energy is critical not only in data-centers. It is also important in mobile devices where battery-based energy is a scarce resource. Reducing the energy consumption of these devices will allow them to last longer and re-charge less frequently. Saving energy in computer systems is a challenging problem. Improving a system's energy efficiency usually comes at the cost of compromises in other areas such as performance or reliability. In the case of secondary storage, for example, spinning-down the disks to save energy can incur high latencies if they are accessed while in this state. The challenge is to be able to increase the energy efficiency while keeping the system as reliable and responsive as before. This thesis tackles the problem of improving energy efficiency in existing systems while reducing the impact on performance. First, we propose a new technique to achieve fine grained energy proportionality in multi-disk systems; Second, we design and implement an energy-efficient cache system using flash memory that increases disk idleness to save energy; Finally, we identify and explore solutions for the page fetch-before-update problem in caching systems that can: (a) control better I/O traffic to secondary storage and (b) provide critical performance improvement for energy efficient systems.

Changes in mass and nutrient content of wood during decomposition in a south Florida mangrove forest

1. Large pools of dead wood in mangrove forests following disturbances such as hurricanes may influence nutrient fluxes. We hypothesized that decomposition of wood of mangroves from Florida, USA (Avicennia germinans, Laguncularia racemosa and Rhizophora mangle), and the consequent nutrient dynamics, would depend on species, location in the forest relative to freshwater and marine influences and whether the wood was standing, lying on the sediment surface or buried. 2. Wood disks (8–10 cm diameter, 1 cm thick) from each species were set to decompose at sites along the Shark River, either buried in the sediment, on the soil surface or in the air (above both the soil surface and high tide elevation). 3. A simple exponential model described the decay of wood in the air, and neither species nor site had any effect on the decay coefficient during the first 13 months of decomposition. 4. Over 28 months of decomposition, buried and surface disks decomposed following a two-component model, with labile and refractory components. Avicennia germinans had the largest labile component (18 ± 2% of dry weight), while Laguncularia racemosa had the lowest (10 ± 2%). Labile components decayed at rates of 0.37–23.71% month−1, while refractory components decayed at rates of 0.001–0.033% month−1. Disks decomposing on the soil surface had higher decay rates than buried disks, but both were higher than disks in the air. All species had similar decay rates of the labile and refractory components, but A. germinans exhibited faster overall decay because of a higher proportion of labile components. 5. Nitrogen content generally increased in buried and surface disks, but there was little change in N content of disks in the air over the 2-year study. Between 17% and 68% of total phosphorus in wood leached out during the first 2 months of decomposition, with buried disks having the greater losses, P remaining constant or increasing slightly thereafter. 6. Newly deposited wood from living trees was a short-term source of N for the ecosystem but, by the end of 2 years, had become a net sink. Wood, however, remained a source of P for the ecosystem. 7. As in other forested ecosystems, coarse woody debris can have a significant impact on carbon and nutrient dynamics in mangrove forests. The prevalence of disturbances, such as hurricanes, that can deposit large amounts of wood on the forest floor accentuates the importance of downed wood in these forests.

Performance analysis of disk mirroring techniques

Unequaled improvements in processor and I/O speeds make many applications such as databases and operating systems to be increasingly I/O bound. Many schemes such as disk caching and disk mirroring have been proposed to address the problem. In this thesis we focus only on disk mirroring. In disk mirroring, a logical disk image is maintained on two physical disks allowing a single disk failure to be transparent to application programs. Although disk mirroring improves data availability and reliability, it has two major drawbacks. First, writes are expensive because both disks must be updated. Second, load balancing during failure mode operation is poor because all requests are serviced by the surviving disk. Distorted mirrors was proposed to address the write problem and interleaved declustering to address the load balancing problem. In this thesis we perform a comparative study of these two schemes under various operating modes. In addition we also study traditional mirroring to provide a common basis for comparison.