Zeke Scheduler Tutorial

[Latisha Gervase]

Viewthe PAC (Product Availability and Compatibility) matrix for the English user interface of version 9.0.00Customer Advisories Date Tracking NumbersDescriptionAvailable Formats Technical Bulletin 09-Nov-2021Alerts all INCONTROL customers to necessary 2021 year-end procedures.PDF03-Nov-2020Alerts all INCONTROL customers to necessary 2020 year-end procedures.PDF24-Nov-2019BMC is announcing a new method for sending files to Customer Support.PDF03-Nov-2019Alerts all INCONTROL customers to necessary 2019 year-end procedures.PDF31-Oct-2019BMC is notifying users of end of support for Control-M version 9.0.00.PDF20-Dec-2018Alerts customers of Control-M for z/OS to a potentially problematic configuration of IOAVAR when shared between LPARsPDF15-Oct-2018Alerts all INCONTROL customers to necessary 2018 year-end proceduresPDF01-Nov-2017Alerts all INCONTROL customers to necessary 2017 year-end proceduresPDF29-Sep-2017Announces that IBM z/OS version 2.3 is supported on INCONTROL for z/OS products versions 8.0.06 and later, and 9.0.04 and later.PDF18-Oct-2016Alerts all INCONTROL customers to necessary 2016 year-end proceduresPDF08-Oct-2015Alerts all INCONTROL customers to necessary 2015 year-end proceduresPDF30-Sep-2015Announces that IBM z/OS version 2.2 is supported on INCONTROL for z/OS products versions 7.0.04 and later, 8.0.03 and later, and 9.0.00 and later.PDF17-Feb-2013Support change notification for Control-M Workload Automation products and components, containing a list of the products and version numbers that is changing on December 31, 2014PDF Release Notes 06-Jun-2017Describes the Control-M for z/OS Conversion Tool that allows you to convert several schedulers to the Control-M environment.PDF26-Oct-2016Describes the Control-M for z/OS Conversion Tool that allows you to convert several schedulers to the Control-M environment.PDF02-Jul-2015Describes the Control-M for z/OS Conversion Tool that allows you to convert several schedulers to the Control-M environment.PDF02-Jul-2015Release notes for users who want to install or upgrade to INCONTROL for z/OS version 9.0.00.PDF Product DocumentsLanguage : AllEnglishFrenchGerman

Title Date Format BMC Control-M Workload Automation JCL Verify User GuideDescribes how to use BMC Control-M Workload Automation JCL Verify.02-Jul-2015PDF Control-M for z/OS Getting Started GuideProvides an introduction to the functionality of Control-M, and a step by step tutorial on how to use Control-M.02-Jul-2015PDF Control-M for z/OS User GuideDescribes how to use Control-M.02-Jul-2015PDF Control-M for z/OS for A-AUTO Conversion GuideReviews basic concepts relevant to converting from A-AUTO to CONTROL-M.17-Jan-2021PDF Control-M for z/OS for ADC2 Conversion GuideDescribes how to use the Control-M Conversion Tool to convert an ADC2 scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for APEX Conversion GuideDescribes how to use the Control-M Conversion Tool to convert an APEX scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for APM/HS5000 Conversion GuideDescribes how to use the Control-M Conversion Tool to convert an APM/HS5000 scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for CA ESP Conversion GuideDescribes how to use the Control-M Conversion Tool to convert an CA ESP scheduling environment to a Control-M scheduling environment.29-Oct-2020PDF Control-M for z/OS for CA-7 Conversion GuideDescribes how to use the Control-M Conversion Tool to convert a CA-7 scheduling environment to a Control-M scheduling environment.29-Oct-2020PDF Control-M for z/OS for CA-JOBTRAC Conversion GuideDescribes how to use the Control-M Conversion Tool to convert a CA-JOBTRAC scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for CA-MANAGER Conversion GuideDescribes how to use the Control-M Conversion Tool to convert a CA-MANAGER scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for CA-SCHEDULER Conversion GuideDescribes how to use the Control-M Conversion Tool to convert a CA-SCHEDULER scheduling environment to a Control-M scheduling environment.29-Oct-2020PDF Control-M for z/OS for DJC Conversion GuideDescribes how to use the Control-M Conversion Tool to convert a DJC scheduling environment to a Control-M scheduling environment.02-Jul-2015PDF Control-M for z/OS for OPC/A, OPC/ESA, Tivoli Workload Scheduler (TWS), and IBM Workload Scheduler (IWS) Conversion GuideDescribes how to use the Control-M Conversion Tool to convert OPC/A, OPC/ESA, Tivoli Workload Scheduler (TWS), and IBM Workload Scheduler (IWS) scheduling environments to Control-M.29-Oct-2020PDF Control-M for z/OS for ZEKE Conversion GuideDescribes how to use the Control-M Conversion Tool to convert an ZEKE scheduling environment to a Control-M scheduling environment.29-Oct-2020PDF Control-M/Assist Implementation GuideProvides information necessary for the implementation of Control-M/Assist at your site.17-Dec-2015PDF Control-M/Restart User GuideProvides instructions how to use Control-M/Restart, the Control-M automated job restart system.02-Jul-2015PDF INCONTROL for z/OS Administrator GuideDescribes administrative procedures.02-Jul-2015PDF INCONTROL for z/OS Installation Guide: CustomizingDescribes the customization process.02-Jul-2015PDF INCONTROL for z/OS Installation Guide: InstallingDescribes the installation process.02-Jul-2015PDF INCONTROL for z/OS Installation Guide: MaintainingDescribes the maintenance process.02-Jul-2015PDF INCONTROL for z/OS Installation Guide: UpgradingDescribes the upgrading process.02-Jul-2015PDF INCONTROL for z/OS Messages ManualThe INCONTROL for z/OS Messages Manual contains all messages, and message explanations, for the INCONTROL family of products.02-Jul-2015PDF INCONTROL for z/OS Security GuideDescribes security procedures for INCONTROL products.02-Jul-2015PDF INCONTROL for z/OS Utilities GuideDescribes INCONTROL utilities.02-Jul-2015PDF KeyStroke Language (KSL) User GuideProvides instructions how to use the IOA standard KeyStroke Language (KSL), which is used for simulating, in batch, keystrokes entered in the IOA Online facility.02-Jul-2015PDF

Please check the individual page for the detailed program of each workshop or tutorial. The workshops and tutorials will happen in the Seeley W. Mudd building on the Columbia University Morningside Heights campus. Directions to the building can be found here. Only the south entrance (4th floor, campus-side, shown in the map) will be open to workshop and tutorial participants. The entrance from 120th Street (1st floor) requires swipe access. There will be a registration desk directly behind the entrance. The building will be open between 8:00am and 9pm.

Abstract: Wi-Fi sensing systems leverage wireless signals from widely deployed Wi-Fi devices to realize sensing for a broad range of applications. However, current Wi-Fi sensing systems heavily rely on channel state information (CSI) to learn the signal propagation characteristics, while the availability of CSI is highly dependent on specific Wi-Fi chipsets. Through a city-scale measurement, we discover that the availability of CSI is extremely limited in operational Wi-Fi devices. In this work, we propose a new wireless sensing system called BeamSense that exploits compressed beamforming reports (CBR). Due to the extensive support of transmit beamforming in operational Wi-Fi devices, CBR is commonly accessible and hence enables a ubiquitous sensing capability. BeamSense adopts a novel multi-path estimation algorithm that can efficiently and accurately map bidirectional CBR to a multi-path channel based on intrinsic fingerprints. We implement BeamSense on several prevalent models of Wi-Fi devices and evaluated its performance with microbenchmarks and three representative Wi-Fi sensing applications. The results show that BeamSense is capable of enabling existing CSI-based sensing algorithms to work with CBR with high sensing accuracy and improved generalizability.

Abstract: The emergence of water-proof mobile and wearable devices (e.g., Garmin Descent and Apple Watch Ultra) designed for underwater activities like professional scuba diving, opens up opportunities for underwater networking and localization capabilities on these devices. Here, we present the first underwater acoustic positioning system for smart devices. Unlike conventional systems that use floating buoys as anchors at known locations, we design a system where a dive leader can compute the relative positions of all other divers, without any external infrastructure. Our intuition is that in a well-connected network of devices, if we compute the pairwise distances, we can determine the shape of the network topology. By incorporating orientation information about a single diver who is in the visual range of the leader device, we can then estimate the positions of all the remaining divers, even if they are not within sight. We address various practical problems including detecting erroneous distance estimates, addressing rotational and flipping ambiguities as well as designing a distributed timestamp protocol that scales linearly with the number of devices. Our evaluations show that our distributed system running on underwater deployments of 4-5 commodity smart devices can perform pairwise ranging and localization with median errors of 0.5-0.9 m and 0.9-1.6 m. Project page with code:

Abstract: Millimeter wave (mmWave) technology enables wireless devices to communicate using very high-frequency signals. Operating at those frequencies provides larger bandwidth which can be used to enable high-data-rate links, and very accurate localization of devices. However, radios operating at high-frequencies consume significant amount of power, making them unsuitable for applications with limited energy sources. This paper presents MilBack, a backscatter network operating at mmWave bands. Backscattering is the most energy-efficient wireless communication technique, where nodes piggyback their data on an access point's signal instead of generating their own signals. Eliminating the need for signal generation significantly reduces the energy-consumption of the nodes. In contrast to past mmWave backscatter work which supports only uplink, MilBack is the first mmWave backscatter network which supports uplink, downlink and accurate localization. MilBack addresses the key challenges that prevent existing backscatter networks to enable both uplink and downlink at mmWave bands. We implemented MilBack and evaluated its performance empirically. Our results show that MilBack is capable of achieving accurate localization, uplink and downlink communication at up to 10 m while consuming only 32 mW and 18 mW, respectively.

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