Publications

Remote Procedure Call (RPC) is a widely used abstraction for cloud computing. The programmer specifies type information for each remote procedure, and a compiler generates stub code linked into each application to marshal and unmarshal arguments into message buffers. Increasingly, however, application and service operations teams need a high degree of visibility and control over the flow of RPCs between services, leading many installations to use sidecars or service mesh proxies for manageability and policy flexibility. These sidecars typically involve inspection and modification of RPC data that the stub compiler had just carefully assembled, adding needless overhead. Further, upgrading diverse application RPC stubs to use advanced hardware capabilities such as RDMA or DPDK is a long and involved process, and often incompatible with sidecar policy control. In this paper, we propose, implement, and evaluate a novel approach, where RPC marshalling and policy enforcement are done as a system service rather than as a library linked into each application. Applications specify type information to the RPC system as before, while the RPC service executes policy engines and arbitrates resource use, and then marshals data customized to the underlying network hardware capabilities. Our system, mRPC, also supports live upgrades so that both policy and marshalling code can be updated transparently to application code. Compared with using a sidecar, mRPC speeds up a standard microservice benchmark, DeathStarBench, by up to 2.5$\times$ while having a higher level of policy flexibility and availability.

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13 Abstract 14 Besides optimizing classier predictive performance and addressing the curse of the dimensionality problem, feature selection techniques support a classication model as simple as possible. In this paper, we present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the tness function to be maximized. Moreover, we present a methodology to better estimate the quality of the reduced feature set. Experiments conducted over six public datasets demonstrated that the proposed approach provides statistically signicant more compact sets and, in some cases, it can indeed improve the classication eectiveness.

Single crystal superalloys are the preferred materials for manufacturing turbine blades of advanced aero-engines, due to their excellent high temperature comprehensive performance. The interfacial reaction between alloys and ceramic mould are an important factor to influence the surface quality and service performance of the turbine blade. It is very important to reveal the interfacial reaction mechanism to improve turbine blade quality and yield rate. In this paper, the interfacial reactions between DD6 single crystal superalloy and ceramic mould were investigated by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction analysis (XRD). The results show that the main reaction products were HfO2, Al2O3 and Y3Al5O12 when the yttrium oxide powders were the prime coat materials, while alloy surface suffered undesirable sand fusion; the thicknesses of the reaction layers were over 20 μm. The reaction layer can be divided into two layers, the layer close to the alloy was mainly composed of Al2O3 and Y3Al5O12, and the layer close to the mould was composed of SiO2, Al2O3 and Y3Al5O12. Avoiding the formation of Y2O3-Al2O3-SiO2 ternary low-melts can solve the interfacial reaction between DD6 alloy and yttrium oxide mould.