Hosting database services on cloud systems has become a common practice. This has led to the increasing volume of database workloads, which provides the opportunity for pattern analysis. Discovering workload patterns from a business logic perspective is conducive to better understanding the trends and characteristics of the database system. However, existing workload pattern discovery systems are not suitable for large-scale cloud databases which are commonly employed by the industry. This is because the workload patterns of large-scale cloud databases are generally far more complicated than those of ordinary databases. In this paper, we propose Alibaba Workload Miner (AWM), a real-time system for discovering workload patterns in complicated large-scale workloads. AW M encodes and discovers the SQL query patterns logged from user requests and optimizes the querying processing based on the discovered patterns. First, Data Collection & Preprocessing Module collects streaming query logs and encodes them into high-dimensional feature embeddings with rich semantic contexts and execution features. Next, Online Workload Mining Module separates encoded query by business groups and discovers the workload patterns for each group. Meanwhile, Offline Training Module collects labels and trains the classification model using the labels. Finally, Pattern-based Optimizing Module optimizes query processing in cloud databases by exploiting discovered patterns. Extensive experimental results on one synthetic dataset and two real-life datasets (extracted from Alibaba Cloud databases) show that AW M enhances the accuracy of pattern discovery by 66% and reduce the latency of online inference by 22%, compared with the state-of-the-arts.

A new CAN bus transceiver integrated circuit is described that incorporates an inherent auxiliary data channel. The auxiliary data channel enables CAN packet authentication signatures to accompany primary data payloads. The transceiver is backward compatible with the CAN protocol and thus may be used within existing networks with no modifications required. The clock edge at the transmitter is phase modulated with signature data in a manner that does not exceed clock jitter tolerances in the CAN specifications. The receiver is designed to recover the primary data and the packet signature. By comparing the received signature with the authorized packet signature, a “Go/No Go” output indicates if the received packet is properly authenticated.

In this paper, the suppressing problem of the cable's vibration is studied for a suspension cable system of helicopter with disturbances. The Hamilton's principle is applied to obtain a distributed parameter system of the suspension cable system which includes one partial differential equation and two ordinary differential equations. Two nonlinear disturbance observers are developed to compensate the effect of boundary disturbances. The auxiliary systems are designed to eliminate the effects of input nonlinearities. Based on the designed disturbance observer and auxiliary systems, two boundary controllers are designed at the top and bottom boundaries of the suspension cable. Under the proposed controllers, the amplitude of oscillation is proven to be uniformly ultimately bounded and converges to a small neighborhood of zero by selecting proper design parameters of the antidisturbance control scheme for the suspension cable system. Meanwhile, some sufficient conditions are provided to guarantee the effectiveness of the developed control law. Finally, simulation results show that the controllers developed in this paper work well in handling disturbances for the suspension cable system of helicopter.

High-level synthesis and compiler studies have introduced many compile-time techniques for parallelizing applications. However, one fundamental limitation of compile-time optimization is the requirement for pessimistic dependence assumptions that can significantly restrict parallelism. To avoid this limitation, many compilers require a restrictive coding style that is not practical for many designers. We present a more transparent approach that aggressively parallelizes applications by dynamically analyzing actual runtime dependencies and scheduling functions onto multiple devices when dependencies allow. In addition, the approach applies FPGA-specific pipelining optimizations to exploit deep parallelism in chains of dependent functions. Experimental results show a speedup of 4.9x for a video-processing application compared to sequential software execution, a speedup of 5.6x compared to traditional FPGA execution, with a framework overhead of only 4%.