The calendar clock is a hardware system clock that runs continuously, even if the router is powered off or rebooted. The hardware system clock is separate from the software clock settings, which are erased when the router is power cycled or rebooted.
In the following example, the hardware clock settings are copied to the software clock with the clock read-calendar command. The show clock command is then entered to display the new software clock settings.
realand time clock software 22
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Generally, if the system is synchronized by a valid outside timing mechanism, such as a Network Time Protocol (NTP) clock source, or if you have a networking device with calendar capability, you need not set the software clock. Use the clock set command if no other time sources are available. The time specified in this command is relative to the configured time zone.
To configure the system to switch automatically to summer time (daylight saving time), use the clock summer-time command in global configuration mode. To remove the daylight saving time setting, use the no form of this command.
clock summer-time zone recurring week day month hh:mm week day month hh:mm [offset]
Use the recurring keyword to apply the rules on the configured day each year. If clock summer-time zone recurring is specified without parameters, the summer time rules default to United States standards. The default for the offset argument is 60 minutes.
The hardware clock (calendar) runs continuously, even if the router is powered off or rebooted. If the software clock and calendar are not synchronized and the software clock is more accurate, use this command to update the hardware calendar clock to the correct date and time.
In a router running Cisco IOS XR software the time clock in the primary RP is synchronized with the other RPs, DRPs, and LCs in the system. This synchronization ensures that the standby RP has an accurate time setting if it assumes the primary role and that the events in logs between different RPs and LCs can be easily correlated during debugging.
The show clock sync command verifies that the cards in the router are synchronized with the primary RP. When this command is run, the primary RP queries the clocks on each card in the system and displays the time difference between each card and the primary RP. If the time setting on the card is different from the time on the primary RP, the display shows if the clock on the card is being adjusted to synchronize with the primary RP.
The show clock sync command shows the relative time difference between the RP where it is run and the cards in that SDR. If the command is run on the primary RP for the owner SDR, then the results show the relative time settings for the cards assigned to the owner SDR. If the command is run on the DSDRSC for a non-owner SDR, then the results are for the cards in that SDR. The show clock sync command can also be run on the standby RP, but the times displayed are relative to that RP.
The ability to accurately estimate job runtime properties allows a scheduler to effectively schedule jobs. State-of-the-art online cluster job schedulers use history-based learning, which uses past job execution information to estimate the runtime properties of newly arrived jobs. However, with fast-paced development in cluster technology (in both hardware and software) and changing user inputs, job runtime properties can change over time, which lead to inaccurate predictions.
Our system, Graham, leverages the fact that the local clock still keeps time even when connectivity is lost and builds a failure model using the characteristics of the local clock and the desired synchronization accuracy. Graham characterizes the local clock using commodity sensors present in nearly every server and leverages this data to further improve clock accuracy, increasing the tolerance of Graham to failures. Graham reduces the clock drift of a commodity server by up to 2000, reducing the maximum assumed drift in most situations from 200ppm to 100ppb.
In-situ programmability refers to the capability for network devices to update data plane functions and protocol processing logic at runtime without interrupting the services, driven by dynamic and interactive network operations towards autonomous networks. The existing programmable switch architecture (e.g., PISA) and programming language (e.g., P4) were designed for monolithic and static implementation, which requires a complete programming and deployment cycle for functional update, incurring long delay and service interruption. Addressing the fundamental reasons for such inflexibility, we design a new In-situ Programmable Switch Architecture (IPSA) and the corresponding design flow using rP4, a P4 language extension, as a fix. The compiler contains algorithms to support efficient resource mapping for both base design and incremental updates. To manifest the in-situ programming feasibility, we demonstrate several practical use cases on both a software switch, ipbm, and an FPGA-based prototype. Our experiments and analysis show that IPSA incurs moderate hardware cost which can be justified by its benefits and compensated by newer chip technologies. The in-situ programmability enabled by IPSA and rP4 advances the state of the art of programmable networks and opens a promising new design space.
In this paper, we argue that this dynamics problem motivates reframing telemetry systems as resource schedulers---a significant departure from state-of-the-art. More concretely, rather than statically partition queries across hardware and software platforms, telemetry systems ought to decide on their own and at runtime when and for how long to execute the set of active queries on the data plane. To this end, we propose an efficient approximation and scheduling algorithm that exposes accuracy and latency tradeoffs with respect to query execution to reduce hardware resource usage. We evaluate our algorithm by building DynATOS, a hardware prototype built around a reconfigurable approach to ASIC programming. We show that our approach is more robust than state-of-the-art methods to traffic dynamics and can execute dynamic workloads comprised of multiple concurrent and sequential queries of varied complexities on a single switch while meeting per-query accuracy and latency goals.
Network monitoring and measurement have always been critical components of network management. Recent developments in sketch-based monitoring techniques and the deployment opportunities arising from the increasing programmability of network elements (e.g., programmable switches, SmartNICs, and software switches) have made the possibility of accurate, detailed, network-wide telemetry tantalizingly within reach. However, the wide heterogeneity of the programmable hardware and dynamic changes in both resources available and resources needed for monitoring over time make existing approaches to network-wide monitoring impractical.
In this paper, we systematically study the impact of temporal and spatial traffic locality on the performance of commodity servers equipped with high-speed network interfaces. Our results show that (i) the performance of a variety of widely deployed applications degrade substantially with even the slightest lack of traffic locality, and (ii) a traffic trace from our organization reveals poor traffic locality as networking protocols, drivers, and the underlying switching/routing fabric spread packets out in time (reducing locality). To address these issues, we built Reframer, a software solution that deliberately delays packets and reorders them to increase traffic locality. Despite introducing μs-scale delays of some packets, we show that Reframer increases the throughput of a network service chain by up to 84% and reduces the flow completion time of a web server by 11% while improving its throughput by 20%. 2ff7e9595c
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