# US 10,771,870 B2 · Technologies for dynamic remote resource allocation

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- Number: US 10,771,870 B2
- Document ID: US10771870B2
- Status: Granted
- Kind: B2
- Application number: 15/395,183
- Filed: 2016-12-30
- Published: 2018-01-25
- Granted: 2020-09-08
- Earliest claimed: 2016-07-22
- Assignees: Intel Corporation
- Applicants: Intel Corporation
- Inventors: Susanne M. Balle; Rahul Khanna; Nishi Ahuja; Mrittika Ganguli
- Web page: https://patentgrep.com/patent/US10771870B2

## CPC

- G06F 3/061: {Improving I/O performance}
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- H03M 7/6005: {Decoder aspects}
- H03M 7/6023: {Parallelization}
- H04B 10/25: Arrangements specific to fibre transmission
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- H04L 9/14: using a plurality of keys or algorithms
- H04L 9/3247: {involving digital signatures}
- H04L 9/3263: {involving certificates, e.g. public key certificate [PKC] or attribute certificate [AC]; Public key infrastructure [PKI] arrangements (network architectures or network communication protocols for supporting authentication of entities using certificates in a packet data network H04L63/0823)}
- H04L 12/2809: {indicating that an appliance service is present in a home automation network (monitoring functionality H04L43/0817; discovery or management thereof, e.g. service location protocol [SLP] or web services, H04L67/51)}
- H04L 41/024: {using relational databases for representation of network management data, e.g. managing via structured query language [SQL]}
- H04L 41/046: comprising network management agents or mobile agents therefor
- H04L 41/0813: characterised by the conditions triggering a change of settings
- H04L 41/082: the condition being updates or upgrades of network functionality
- H04L 41/12: Discovery or management of network topologies
- H04L 41/149: for prediction of maintenance
- H04L 41/40: using virtualisation of network functions or resources, e.g. SDN or NFV entities
- H04L 41/5019: Ensuring fulfilment of SLA
- H04L 43/065: related to network devices
- H04L 43/16: Threshold monitoring
- H04L 45/02: Topology update or discovery
- H04L 45/52: Multiprotocol routers
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- H04L 47/38: by adapting coding or compression rate
- H04L 47/765: triggered by the end-points
- H04L 47/782: {Hierarchical allocation of resources, e.g. involving a hierarchy of local and centralised entities}
- H04L 47/805: {QOS or priority aware}
- H04L 47/82: {Miscellaneous aspects}
- H04L 49/15: Interconnection of switching modules
- H04L 49/555: {Error detection}
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- H04L 67/1012: based on compliance of requirements or conditions with available server resources
- H04L 67/1014: based on the content of a request
- H04L 67/1029: using data related to the state of servers by a load balancer
- H04L 67/1034: Reaction to server failures by a load balancer
- H04L 67/1097: for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
- H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L 67/34: {involving the movement of software or configuration parameters (network booting or remote initial program loading [RIPL] G06F9/4416)}
- H04L 67/51: Discovery or management thereof, e.g. service location protocol [SLP] or web services
- H04Q 1/04: Frames or mounting racks for selector switches; Accessories therefor, e.g. frame cover
- H04Q 11/00: Selecting arrangements for multiplex systems (multiplex systems H04J)
- H04Q 11/0005: {Switch and router aspects}
- H04Q 11/0062: {Network aspects}
- H04Q 11/0071: {Provisions for the electrical-optical layer interface}
- H04Q 2011/0037: {Operation}
- H04Q 2011/0041: {Optical control}
- H04Q 2011/0052: {Interconnection of switches}
- H04Q 2011/0073: {Provisions for forwarding or routing, e.g. lookup tables}
- H04Q 2011/0079: {Operation or maintenance aspects}
- H04Q 2011/0086: {Network resource allocation, dimensioning or optimisation}
- H04Q 2213/13523: bandwidth management, e.g. capacity management
- H04Q 2213/13527: protocols - X.25, TCAP etc.
- H04W 4/023: {using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds}
- H04W 4/80: Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
- H05K 1/0203: {Cooling of mounted components (H05K1/0272 takes precedence)}
- H05K 1/181: associated with surface mounted components
- H05K 5/0204: {Mounting supporting structures on the outside of casings}
- H05K 7/1418: {Card guides, e.g. grooves (H05K7/1425 takes precedence)}
- H05K 7/1421: {Drawers for printed circuit boards}
- H05K 7/1422: {Printed circuit boards receptacles, e.g. stacked structures, electronic circuit modules or box like frames}
- H05K 7/1447: {External wirings; Wiring ducts; Laying cables}
- H05K 7/1461: {Slidable card holders; Card stiffeners; Control or display means therefor}
- H05K 7/1485: {Servers; Data center rooms, e.g. 19-inch computer racks}
- H05K 7/1487: {Blade assemblies, e.g. blade cases or inner arrangements within a blade}
- H05K 7/1489: {characterized by the mounting of blades therein, e.g. brackets, rails, trays (H05K7/1491 takes precedence)}
- H05K 7/1491: {having cable management arrangements (management of optical cables G02B6/444; in telecommunication cabinets H04Q1/06)}
- H05K 7/1492: {having electrical distribution arrangements, e.g. power supply or data communications}
- H05K 7/1498: {Resource management, Optimisation arrangements, e.g. configuration, identification, tracking, physical location (thermal management H05K7/20836)}
- H05K 7/2039: {characterised by the heat transfer by conduction from the heat generating element to a dissipating body (arrangements for increasing/decreasing heat-transfer, e.g. fins details, F28F13/00)}
- H05K 7/20709: {for server racks or cabinets; for data centers, e.g. 19-inch computer racks}
- H05K 7/20727: {within server blades for removing heat from heat source}
- H05K 7/20736: {within cabinets for removing heat from server blades}
- H05K 7/20745: {within rooms for removing heat from cabinets, e.g. by air conditioning device}
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- G11C: STATIC STORES (semiconductor memory devices H10B)
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- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
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- Y02P: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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## Abstract

Technologies for dynamically allocating resources among a set of managed nodes include an orchestrator server to receive telemetry data from the managed nodes indicative of resource utilization and workload performance by the managed nodes as the workloads are executed, generate a resource allocation map indicative of allocations of resources among the managed nodes, determine, as a function of the telemetry data and the resource allocation map, a dynamic adjustment to allocation of resources to at least one of the managed nodes to improve performance of at least one of the workloads executed on the at least one of the managed nodes, and apply the adjustment to the allocation of the resources among the managed nodes as the workloads are executed. Other embodiments are also described and claimed.

## Claims

### Claim 1

An orchestrator server to dynamically allocate resources among a set of managed nodes, the orchestrator server comprising:
one or more processors;
one or more memory devices having stored therein a plurality of instructions that, when executed by the one or more processors, cause the orchestrator server to:
receive telemetry data from the managed nodes, wherein the telemetry data is indicative of resource utilization and workload performance by the managed nodes as the workloads are executed;
generate a resource allocation map indicative of resources that have been allocated among the managed nodes;
determine, as a function of the telemetry data and the resource allocation map, a dynamic adjustment to allocation of resources to at least one of the managed nodes to improve performance of at least one of the workloads executed on the at least one of the managed nodes; and
apply the adjustment to the allocation of resources among the managed nodes as the workloads are executed.

### Claim 2 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to dynamically allocate memory from one of the managed nodes to another of the managed nodes.

### Claim 3 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to dynamically adjust an amount of remote accelerator resources allocated to the at least one of the managed nodes.

### Claim 4 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to dynamically adjust an amount of storage resources allocated to the at least one of the managed nodes.

### Claim 5 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to dynamically adjust an amount of memory resources allocated to the at least one of the managed nodes.

### Claim 6 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to allocate data storage from one of the managed nodes to another of the managed nodes.

### Claim 7 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to reassign a portion of a workload from one of the managed nodes to another of the managed nodes to allocate additional compute resources to the workload.

### Claim 8 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to reassign a portion of a workload from one of the managed nodes to another of the managed nodes to allocate accelerator resources to the workload.

### Claim 9 (depends on 1)

The orchestrator server of claim 1, wherein to apply the adjustment comprises to deallocate one or more memory resources, data storage resources, compute resources, or accelerator resources.

### Claim 10 (depends on 1)

The orchestrator server of claim 1, wherein to determine the adjustment comprises to determine a resource utilization pattern of one or more of the workloads.

### Claim 11 (depends on 1)

The orchestrator server of claim 1, wherein to determine the adjustment comprises to predict a future resource utilization of one or more of the workloads.

### Claim 12 (depends on 1)

The orchestrator server of claim 1, wherein to determine the adjustment comprises to compare a set of presently allocated resources to a present or predicted resource utilization of one or more of the workloads.

### Claim 13 (depends on 1)

The orchestrator server of claim 1, wherein to determine the adjustment comprises to:
determine whether one or more resources allocated to a managed node are utilized less than a threshold amount; and
determine, in response to a determination that one or more of the resources allocated to the managed node are utilized less than the threshold amount, to deallocate the one or more resources from the managed node.

### Claim 14 (depends on 1)

The orchestrator server of claim 1, wherein to determine the adjustment comprises to:
determine whether resource contention is present or predicted to occur in one of the managed nodes; and
determine, in response to a determination that resource contention is present or predicted to occur, to allocate additional resources to the managed node from another one of the managed nodes.

### Claim 15

One or more machine-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause an orchestrator server to:
receive telemetry data from the managed nodes, wherein the telemetry data is indicative of resource utilization and workload performance by the managed nodes as the workloads are executed;
generate a resource allocation map indicative of resources that have been allocated among the managed nodes;
determine, as a function of the telemetry data and the resource allocation map, a dynamic adjustment to allocation of resources to at least one of the managed nodes to improve performance of at least one of the workloads executed on the at least one of the managed nodes; and
apply the adjustment to the allocation of resources among the managed nodes as the workloads are executed.

### Claim 16 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to allocate memory from one of the managed nodes to another of the managed nodes.

### Claim 17 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to dynamically adjust an amount of remote accelerator resources allocated to the at least one of the managed nodes.

### Claim 18 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to dynamically adjust an amount of storage resources allocated to the at least one of the managed nodes.

### Claim 19 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to dynamically adjust an amount of memory resources allocated to the at least one of the managed nodes.

### Claim 20 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to dynamically allocate data storage from one of the managed nodes to another of the managed nodes.

### Claim 21 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to reassign a portion of a workload from one of the managed nodes to another of the managed nodes to allocate additional compute resources to the workload.

### Claim 22 (depends on 15)

The one or more machine-readable storage media of claim 15, wherein to apply the adjustment comprises to reassign a portion of a workload from one of the managed nodes to another of the managed nodes to allocate accelerator resources to the workload.

### Claim 23

An orchestrator server to dynamically allocate resources among a set of managed nodes, the orchestrator server comprising:
circuitry for receiving telemetry data from the managed nodes, wherein the telemetry data is indicative of resource utilization and workload performance by the managed nodes as the workloads are executed;
circuitry for generating a resource allocation map indicative of resources that have been allocated among the managed nodes;
means for determining, as a function of the telemetry data and the resource allocation map, a dynamic adjustment to allocation of resources to at least one of the managed nodes to improve performance of at least one of the workloads executed on the at least one of the managed nodes; and
means for applying the adjustment to the allocation of resources among the managed nodes as the workloads are executed.

### Claim 24

A method for dynamically allocating resources among a set of managed nodes, the method comprising:
receiving, by the orchestrator server, telemetry data from the managed nodes, wherein the telemetry data is indicative of resource utilization and workload performance by the managed nodes as the workloads are executed;
generating, by the orchestrator server, a resource allocation map indicative of resources that have been allocated among the managed nodes;
determining, by the orchestrator server and as a function of the telemetry data and the resource allocation map, a dynamic adjustment to allocation of resources to at least one of the managed nodes to improve performance of at least one of the workloads executed on the at least one of the managed nodes; and
applying, by the orchestrator server, the adjustment to the allocation of resources among the managed nodes as the workloads are executed.

### Claim 25 (depends on 24)

The method of claim 24, wherein applying the adjustment comprises allocating memory from one of the managed nodes to another of the managed nodes.