Sim_Dsc: Simulator for Optimizing the Performance of Disk Scheduling Algorithms

Disk scheduling involves a careful examination of pending requests to determine the most efficient way to service these requests. A disk scheduler examines the positional relationship among waiting requests, then reorders the queue so that the requests will be serviced with minimum seek. The purpose of the study is to obtain the best scheduling algorithm based on the seek time, rotation time and transfer time for moveable head disks. Keeping in view an attempt has been made to design a simulator for optimizing the performance of disk scheduling algorithms using Box-Muller transformation. The input for the simulator has been derived by using an algorithm for generating pseudo random numbers which follows box-muller transformations. Simulator takes access time which is generated using seek time, rotation time and transfer time, as the request of cylinder numbers, current position of read/write head as inputs. On the basis of these inputs, total head movement of each disk scheduling algorithm is calculated under various loads

From Cooperative Scans to Predictive Buffer Management

In analytical applications, database systems often need to sustain workloads with multiple concurrent scans hitting the same table. The Cooperative Scans (CScans) framework, which introduces an Active Buffer Manager (ABM) component into the database architecture, has been the most effective and elaborate response to this problem, and was initially developed in the X100 research prototype. We now report on the the experiences of integrating Cooperative Scans into its industrial-strength successor, the Vectorwise database product. During this implementation we invented a simpler optimization of concurrent scan buffer management, called Predictive Buffer Management (PBM). PBM is based on the observation that in a workload with long-running scans, the buffer manager has quite a bit of information on the workload in the immediate future, such that an approximation of the ideal OPT algorithm becomes feasible. In the evaluation on both synthetic benchmarks as well as a TPC-H throughput run we compare the benefits of naive buffer management (LRU) versus CScans, PBM and OPT; showing that PBM achieves benefits close to Cooperative Scans, while incurring much lower architectural impact.Comment: VLDB201

Cooperative scans

Data mining, information retrieval and other application areas exhibit a query load with multiple concurrent queries touching a large fraction of a relation. This leads to individual query plans based on a table scan or large index scan. The implementation of this access path in most database systems is straightforward. The Scan operator issues next page requests to the buffer manager without concern for the system state. Conversely, the buffer manager is not aware of the work ahead and it focuses on keeping the most-recently-used pages in the buffer pool. This paper introduces cooperative scans -- a new algorithm, based on a better sharing of knowledge and responsibility between the Scan operator and the buffer manager, which significantly improves performance of concurrent scan queries. In this approach, queries share the buffer content, and progress of the scans is optimized by the buffer manager by minimizing the number of disk transfers in light of the total workload ahead. The experimental results are based on a simulation of the various disk-access scheduling policies, and implementation of the cooperative scans within PostgreSQL and MonetDB/X100. These real-life experiments show that with a little effort the performance of existing database systems on concurrent scan queries can be strongly improve

Effect of update merging on reliable storage performance

Performance of a reliable storage subsystem for a centralized database system was stu­died by simulation. The reliable storage subsystem studied consists of three redundant disk units that are updated one at a time from a consistent database state to another consistent database state, Thus, even if a central processor and/or one disk unit fail simultaneously, at least one disk unit will contain a consistent database state. Redundant multiple disk units allow simultaneous processing of multiple read opera­tions. Our simulation result shows that when all transactions are read-only transactions, the throughput of a three-unit system is 2.5 times higher than that of a single-unit system. On the other hand, redundant disk units slows down write operations, ,since each disk unit must be updated for each virtual page updated. The major result in this paper shows that this adverse effect can be mitigated if updates of multiple transactions are merged and if an efficient disk scheduling policy (e.g., CSCAN) is employed. When the ratio of write opera­tions to read operations is between 10 to 30%, the throughput of the three-unit system is still 89 to 144% higher than that of the single-unit system, which is not reliable. Th.is result is significant when we consider that the performance of a reliable storage subsystem based on log­ging cannot exceed that of a single-unit storage subsystem