Dell Products Inc.

Malathi Ramakrishnan

Deeder M Aurongzeb

Parminder Singh Sethi

Ramesh Doddaiah

Shelesh Chopra

Atishay Jain

A noise and carbon dioxide (CO2) emissions minimizing load-balancing system executing on a unified endpoint management platform information handling system comprising a network interface device to receive telemetry measurements for a first server operating within peak hours, including power analytics, geographic location, ambient temperature and humidity, CO2 emissions value, and measured noise level exceeding a first CO2 load-balancing noise threshold value for the first server, a hardware processor to reject processing requests made to the first server above a CO2 optimal request load predicted, via a neural network modeling a relationship between changes in CO2 emissions values and changes in the telemetry measurements to cause the first server to emit noise below the first CO2 load-balancing noise threshold value, and the hardware processor to redistribute rejected processing requests across candidate offload servers emitting noise below a candidate-specific CO2 load-balancing noise threshold value determined for each of the candidate offload servers.

System and method for load-balancing processing requests across client information handling systems to minimize noise and carbon dioxide emissions in a data center

A hardware life extension learning recommendation and reward system of an information handling system may comprise a network interface device to receive operational telemetries from a first and a second computing device that each include a high temperature warning, an error for a labeled hardware type, and execution of a specific application, and a processor to determine, based on these telemetries, that failure of a first component of the labeled hardware type previously occurred at the first device, failure of a second component of the labeled hardware type has occurred at the second device, and execution at the first device of a previous recommendation to limit access to resources of the first component made available to the specific application extended the first component lifetime. A new recommendation may be transmitted to the second device to limit access to resources of the second component to the specific application.

System and method for recommending and rewarding configuration adjustments for extending information handling system hardware life

An adaptive carbon dioxide (CO2) emissions reduction system operating on a client information handling system may comprise a processor, a network interface device, and a graphical user interface (GUI) to gather analytics for an executing software application hardware power consumption analytics, and a location for the client information handling system, determine a power CO2 emissions value estimating CO2 emitted during a measured consumption of power at the location based on the hardware power consumption analytics, determine that updated power consumption exceeds a maximum power draw threshold value determined based on user input for decreasing the power CO2 emissions value and location, and display a hardware reconfiguration recommendation for reconfiguring a hardware component currently configured for high performance to a power conservation setting.

System and method for adaptively reducing carbon footprint for an information handling system

An enterprise-wide carbon dioxide (CO2) emissions minimizing load-balancing system executing on a unified endpoint management platform information handling system comprising a processor receiving operational telemetry measurements for a first client information handling system including power analytics, a load of remote processing calls made to a processor, a geographic location, and a first client CO2 emissions value determined to exceed a first CO2 load-balancing emissions threshold value limiting the first client information handling system, the processor to reject remote processing call requests made to the first client information handling system above a CO2 optimal request load determined based on CO2 emitted per remote processing call request processed at the first client information handling system, and the processor to redistribute the rejected remote processing call requests across offload information handling systems having CO2 emissions values below a per-machine CO2 load-balancing emissions threshold value determined for each of the offload information handling systems.

System and method for balancing processing load distribution for data centers based on server location to minimize greenhouse gas emissions

An information handling system executing a software test suite green data center policy generation system comprising a network interface device receiving data center hardware utilization analytics and a software test suite identifier for a selected software test suit and a processor to identify a reserved capacity of the data center processing system reserved for general execution of software test suites according to general quality of service requirements for input/output commands and to predict a future data center processor utilization rate and execution duration for the selected software test suite by forecasting actual use of data center resources during a future execution of the selected software test suite that is below the reserved capacity, and the network interface device to transmit an instruction to throttle power supplied to an over-allocated portion of the data center resources from the reserved capacity duration execution of the selected software test suite.

System and method for developing green data center policies to minimize CO2 generated during execution of test suites on a per software feature testing basis

An information handling system of an orchestrating Internet of Things (IoT) gateway executing a carbon dioxide (CO2) minimizing IoT edge gateway data processing orchestration system comprises a network interface device receiving processed IoT sensor data generated by alteration of unprocessed IoT sensor data via access point (AP) IoT servers executing a common data processing method, a processor executing code instructions to determine that an initial volume of CO2 emitted per unit of processed sensor data transferred from the AP IoT servers to a cloud platform, via the orchestrating IoT gateway in an enterprise wide area network, is greater than an adjusted volume of estimated CO2 that would be emitted per unit of data if the common data processing method were performed at the orchestrating IoT gateway instead of the AP IoT servers, and transmitting an instruction to cease execution of the common data processing method at the AP IoT servers.

System and method to reduce redundant data processing tasks executing across interconnected internet of things (IoT) edge devices among data centers via a primary processing orchestration node

A method of recommending reuse of hardware components across client information handling systems to extend hardware life may comprise receiving operational telemetries from a first and second information handling system, each including an error associated with a hardware type, and measured workloads on the hardware type, determining, based on the operational telemetries that a hardware component of the same type is failing at both the first and second information handling systems, and that the first information handling system is within a preset maximum distance from the second information handling system, determining failure of the component at the first information handling system is due to a workload on that component that is higher than the workload on the same component at the second information handling system, and transmitting a recommendation to replace the component at the second information handling system with the component from the first information handling system.

System and method for recommending reuse of hardware components across information handling systems to extend hardware life

An information handling system executing a predictive hash table and carbon dioxide (CO2) minimizing system may comprise a network interface device to receive from a remote data center deduplication process workload metrics, fingerprint hash table size metrics, and a current reserved memory size allocated for storage of a fingerprint hash table, a processor executing code instructions to predict a future workload of deduplication processes and a future fingerprint hash table size to determine a predicted amount of memory to reserve for storage of a future fingerprint hash table based on the predicted future workload of deduplication processes and fingerprint hash table size, and to determine an over-allocated portion of the current reserved memory size where the network interface device transmits an instruction to the data center to limit power provided to the over-allocated portion of the current reserved memory size.

System and method for minimizing CO2 emissions due to utilization of allocated data center memory resources for storage of fingerprint hash tables

A method for managing data replication includes: identifying data being used by an application programming interface (API), in which the data is stored in a source device; tagging the data based on a usage level of the data by the API; obtaining a predicted probability of the usage level of the data; making a first determination that the data is tagged as important data and the predicted probability of the usage level of the data is low; and replicating, based on the first determination, the data from the source device to a target device.

Method and system for proactively managing horizontal scaling of a node

A hardware failure prediction and avoidance system executing on a unified endpoint management platform information handling system comprising a network interface device (NID) to receive failed operational telemetries for client devices including power and software analytics, and event viewer error logs, and an error associated with a hardware type, a processor to execute a classification supervised learning algorithm on the failed operational telemetries to determine that a hardware or software configuration will likely co-occur with a future error of the hardware type, identify the hardware or software configuration as problematic, the processor to identify the problematic system configuration in a current operational telemetry by correlating the current operational telemetry with a portion of the failed operational telemetries, and the NID to transmit a recommendation to the first client device to adjust the problematic system configuration in order to avoid occurrence of the error at the first client device.

System and method for predicting and avoiding hardware failures using classification supervised machine learning

A protective carbon dioxide (CO2) emissions minimization system executing on a unified endpoint management platform information handling system may comprise a network interface device to receive operational telemetry measurements for a client information handling system including a non-eco-friendly state transition threshold value, a neural network modeling a relationship between changes in CO2 emissions values and operational telemetry measurements to predict that a user-adjustable operational telemetry measurement will cause a future determined CO2 emissions value for the client information handling system exceeding the non-eco-friendly state transition threshold value, a hardware processor to identify a remediation user instruction predicted to change operation of the client information handling system, causing a change in the user-adjustable operational telemetry measurement to prevent the future determined CO2 emissions value from exceeding the non-eco-friendly state transition threshold value, and the network interface device to transmit the remediation user instruction to the client information handling system.

System and method for pro-actively limiting a client information handling system from increase in greenhouse gas emissions

An information handling system executing a reinforcement learning (RL) based data center power consumption minimizing system may comprise a network interface device to receive operational telemetry measurements for a plurality of data center processors forming a processing node, including performance and utilization analytics, and a user-specified low-utility threshold value, a hardware processor to predict a future time window in which a utilization rate for the processing node executing a future workload falls below the user-specified low-utility threshold value, the hardware processor to identify an optimal load-balancing instruction for redistributing the future workload across a sub-portion of the processing system associated with a highest reward value for satisfying quality of service (QoS) requirements, and the network interface device to transmit the optimal load-balancing instruction and an instruction to throttle power supplied to a remainder of the processing system.

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Madurai, India

Malathi Ramakrishnan