Flash memory is becoming an increasingly important storage component among non-volatile storage devices. Its cost is decreasing dramatically, which makes it a serious competitor of disks and a candidate for being the storage device of the future. Consequently, there is an urgent need for models and tools to analyse its behaviour and evaluate its effects on a system's performance. We propose a fluid model with priority to investigate the response time characteristics of Flash memory accesses. This model can represent well the Flash access operations, respecting the erase/write/read relative priorities.
A workload analysis technique is presented that processes data from operation type traces and creates a Hidden Markov Model (HMM) to represent the workload that generated those traces. The HMM can be used to create representative traces for performance models, such as simulators, avoiding the need to repeatedly acquire suitable traces. It can also be used to estimate directly the transition probabilities and rates of a Markov modulated arrival process, for use as input to an analytical performance model of Flash memory. The HMMs obtained from industrial workloads -both synthetic benchmarks, preprocessed by a file translation layer, and real, time-stamped user traces -are validated by comparing their autocorrelation functions and other statistics with those of the corresponding monitored time series. Further, the performance model applications, referred to above, are illustrated by numerical examples.
In this paper 1 , we propose an embedded satellite storage architecture based on the MLC NAND FLASH memory chips. We focuse on data reliability and enhance it by adapting the RAID5 mechanism to the Flash technology. This adaptation takes into account both the application and the technology characteristics : the specific access profile determines the striping granularity and the specific Flash technology determines the data placement/management policy. It results an efficient mechanism, simple to implement at the FTL (Flash Translation Layer) level without any use of the garbage collection. Thus, improving reliability using this mechanism leads to improving performance in the particular on-board satellite storage context.
Useful analytical models of storage system performance must support the characteristics exhibited by real I/O workloads. Two essential features are the ability to cater for bursty arrival streams and to support a given distribution of I/O request size. This paper develops and applies the theory of bulk arrivals in queueing networks to support these phenomena in models of I/O request response time in zoned disks and RAID systems, with a specific focus on RAID levels 01 and 5. We represent a single disk as an M X /G/1 queue, and a RAID system as a fork-join queueing network of M X /G/1 queues. We find the response time distribution for a randomly placed request within a random bulk arrival. We also use the fact that the response time of a random request with size sampled from some distribution will be the same as that of an entire batch whose size has the same distribution. In both cases, we validate our models against measurements from a zoned disk drive and a RAID platform.
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