Speculative Concurrency Control for Real-Time Databases

In this paper, we propose a new class of Concurrency Control Algorithms that is especially suited for real-time database applications. Our approach relies on the use of (potentially) redundant computations to ensure that serializable schedules are found and executed as early as possible, thus, increasing the chances of a timely commitment of transactions with strict timing constraints. Due to its nature, we term our concurrency control algorithms Speculative. The aforementioned description encompasses many algorithms that we call collectively Speculative Concurrency Control (SCC) algorithms. SCC algorithms combine the advantages of both Pessimistic and Optimistic Concurrency Control (PCC and OCC) algorithms, while avoiding their disadvantages. On the one hand, SCC resembles PCC in that conflicts are detected as early as possible, thus making alternative schedules available in a timely fashion in case they are needed. On the other hand, SCC resembles OCC in that it allows conflicting transactions to proceed concurrently, thus avoiding unnecessary delays that may jeopardize their timely commitment

Oze: Decentralized Graph-based Concurrency Control for Real-world Long Transactions on BoM Benchmark

In this paper, we propose Oze, a new concurrency control protocol that handles heterogeneous workloads which include long-running update transactions. Oze explores a large scheduling space using a fully precise multi-version serialization graph to reduce false positives. Oze manages the graph in a decentralized manner to exploit many cores in modern servers. We also propose a new OLTP benchmark, BoMB (Bill of Materials Benchmark), based on a use case in an actual manufacturing company. BoMB consists of one long-running update transaction and five short transactions that conflict with each other. Experiments using BoMB show that Oze keeps the abort rate of the long-running update transaction at zero while reaching up to 1.7 Mtpm for short transactions with near linear scalability, whereas state-of-the-art protocols cannot commit the long transaction or experience performance degradation in short transaction throughput

Preemptive Thread Block Scheduling with Online Structural Runtime Prediction for Concurrent GPGPU Kernels

Recent NVIDIA Graphics Processing Units (GPUs) can execute multiple kernels concurrently. On these GPUs, the thread block scheduler (TBS) uses the FIFO policy to schedule their thread blocks. We show that FIFO leaves performance to chance, resulting in significant loss of performance and fairness. To improve performance and fairness, we propose use of the preemptive Shortest Remaining Time First (SRTF) policy instead. Although SRTF requires an estimate of runtime of GPU kernels, we show that such an estimate of the runtime can be easily obtained using online profiling and exploiting a simple observation on GPU kernels' grid structure. Specifically, we propose a novel Structural Runtime Predictor. Using a simple Staircase model of GPU kernel execution, we show that the runtime of a kernel can be predicted by profiling only the first few thread blocks. We evaluate an online predictor based on this model on benchmarks from ERCBench, and find that it can estimate the actual runtime reasonably well after the execution of only a single thread block. Next, we design a thread block scheduler that is both concurrent kernel-aware and uses this predictor. We implement the SRTF policy and evaluate it on two-program workloads from ERCBench. SRTF improves STP by 1.18x and ANTT by 2.25x over FIFO. When compared to MPMax, a state-of-the-art resource allocation policy for concurrent kernels, SRTF improves STP by 1.16x and ANTT by 1.3x. To improve fairness, we also propose SRTF/Adaptive which controls resource usage of concurrently executing kernels to maximize fairness. SRTF/Adaptive improves STP by 1.12x, ANTT by 2.23x and Fairness by 2.95x compared to FIFO. Overall, our implementation of SRTF achieves system throughput to within 12.64% of Shortest Job First (SJF, an oracle optimal scheduling policy), bridging 49% of the gap between FIFO and SJF.Comment: 14 pages, full pre-review version of PACT 2014 poste

AN ENERGY-EFFICIENT CONCURRENCY CONTROL ALGORITHM FOR MOBILE AD-HOC NETWORK DATABASES

With the rapid growth of the wireless networking technology and mobile computing devices, there is an increasing demand for processing mobile database transactions in mission-critical applications such as disaster rescue and military operations that do not require a fixed infrastructure, so that mobile users can access and manipulate the database anytime and anywhere. A Mobile Ad-hoc Network (MANET) is a collection of mobile, wireless and battery-powered nodes without a fixed infrastructure; therefore it fits well in such applications. However, when a node runs out of energy or has insufficient energy to function, communication may fail, disconnections may happen, execution of transactions may be prolonged, and thus time-critical transactions may be aborted if they missed their deadlines. In order to guarantee timely and correct results for multiple concurrent transactions, energy-efficient database concurrency control (CC) techniques become critical. Due to the characteristics of MANET databases, existing CC algorithms cannot work effectively.In this dissertation, an energy-efficient CC algorithm, called Sequential Order with Dynamic Adjustment (SODA), is developed for mission-critical MANET databases in a clustered network architecture where nodes are divided into clusters, each of which has a node, called a cluster head, responsible for the processing of all nodes in the cluster. The cluster structure is constructed using a novel weighted clustering algorithm, called MEW (Mobility, Energy, and Workload), that uses node mobility, remaining energy and workload to group nodes into clusters and select cluster heads. In SODA, in order to conserve energy and balance energy consumption among servers so that the lifetime of the network is prolonged, cluster heads are elected to work as coordinating servers. SODA is based on optimistic CC to offer high transaction concurrency and avoid unbounded blocking time. It utilizes the sequential order of committed transactions to simplify the validation process and dynamically adjusts the sequential order of committed transactions to reduce transaction aborts and improve system throughput.Besides correctness proof and theoretical analysis, comprehensive simulation experiments were conducted to study the performance of MEW and SODA. The simulation results confirm that MEW prolongs the lifetime of MANETs and has a lower cluster head change rate and re-affiliation rate than the existing algorithm MOBIC. The simulation results also show the superiority of SODA over the existing techniques, SESAMO and S2PL, in terms of transaction abort rate, system throughput, total energy consumption by all servers, and degree of balancing energy consumption among servers