Kernel task scheduling is important for application performance, adaptability to new hardware, and complex user requirements. However, developing, testing, and debugging new scheduling algorithms in Linux, the most widely used cloud operating system, is slow and difficult. We developed Enoki, a framework for high velocity development of Linux kernel schedulers. Enoki schedulers are written in safe Rust, and the system supports live upgrade of new scheduling policies into the kernel, userspace debugging, and bidirectional communication with applications. A scheduler implemented with Enoki achieved near identical performance (within 1% on average) to the default Linux scheduler CFS on a wide range of benchmarks. Enoki is also able to support a range of research schedulers, specifically the Shinjuku scheduler, a locality aware scheduler, and the Arachne core arbiter, with good performance.

Any battery powered electric vehicle is a safety critical system due to very high probability of untimed power failure. In this work a model predictive controller has been implemented in Field Programmable Gate Array (FPGA) for safe state generation by enhancing the runtime of electric car based on predicted battery state of charge. Initially an area and time efficient Coulomb counting technique has been implemented in FPGA. Subsequently a proactive load controller has been developed using FPGA from predicted State of Charge (SOC). The controller proactively optimizes the constrained battery energy by varying the power delivered to the noncritical loads and supports critical loads as per demand. The paper validates the proposed mechanism by experimental results.