【 摘 要 】
Next-generation printing service is an instance of the emerging class of cyber-physical systems; it is characterized by the large quantity of data that documents the factory operations. These data are ephemeral; the value of the data decays rapidly with time. The service solutions to serve this type of business must be scalable, provide high-throughput processing and low-latency (near real-time) analytical service, and cannot impose a prohibitive storage load. We describe a web service using provenance analytics engine as backend to aid and automate the print service management. It can leverage cloud computing infrastructure to ensure the scalability and multi- tenancy; adopts a novel use of component behavioral models, blends simulation and event management and querying, and provides multiple level of granularity through hierarchical process sequencing graph - all these contributes and ensures near real-time service delivery; uses component behavioral models to reproduce, rather than store, intermediate results * this can greatly reduce the storage demand as the intermediate content data in printing can be large; uses a non-annotation based approach eliminating the extra workload (computing & network bandwidth) that a growing header may impose to regular content data processing. Upon the instrumentation of this service, it can provide causality analysis & dependency analysis, replay ("roll back") and forecasting ("roll forward") service and real-time monitoring and alert.
【 预 览 】
Files | Size | Format | View |
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RO201804100000322LZ | 772KB | download |