Patent Publication Number: US-2023138727-A1

Title: Carbon footprint-based control of cloud resource consumption

Description:
BACKGROUND 
     The present invention relates to managing cloud resources, and more particularly to controlling cloud resource usage based on carbon emission. 
     Industries are advocating for greener data centers and are targeting a reduced carbon footprint as part of their corporate social responsibility. Companies are working towards green computer environments and a reduced carbon footprint while executing their business applications. Since cloud companies do not provide carbon footprint details of cloud resources, companies using the cloud resources do not know the carbon footprint and the impact on sustainable environment caused by processing their business logic, applications, and workload. 
     SUMMARY 
     In one embodiment, the present invention provides a computer system that includes a central processing unit (CPU), a memory coupled to the CPU, and one or more computer readable storage media coupled to the CPU. The one or more computer readable storage media collectively contain instructions that are executed by the CPU via the memory to implement a method of determining a carbon footprint-based consumption of cloud resources. The method includes the computer system receiving requirements of cloud resources and a carbon footprint cap of a workload of a cloud consumer organization. The requirements of the cloud resources and the carbon footprint cap are based on a sustainability target of the cloud consumer organization, published by the cloud consumer organization to a publish-subscribe platform, a multi-cloud management platform, or a hybrid cloud brokerage platform, and subscribed by cloud service providers. The method further includes in response to the receiving the requirements of the cloud resources and the carbon footprint cap, the computer system sending a list of cloud resources that satisfy the requirements of the cloud resources and sending carbon emission values of the cloud resources in the list at different load levels of the workload. The method further includes the computer system receiving a service level agreement (SLA) requirement of the workload, a criticality level of the workload, a peak load duration of the workload, and previous success rates of cloud service providers satisfying cloud resource requirements for the cloud consumer organization. The method further includes based on the SLA requirement, the criticality level, the peak load duration, and the previous success rates, the computer system selecting an optimized configuration of one or more cloud resources and one or more cloud service providers providing the one or more cloud resources for the workload. The one or more cloud resources are selected from the list of cloud resources and have a carbon footprint that does not exceed the carbon footprint cap at a given load level. 
     A computer program product and a method corresponding to the above-summarized computer system are also described herein. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a system for carbon footprint-based control of cloud resource consumption, in accordance with embodiments of the present invention. 
         FIGS.  2 A- 2 B  depict a flowchart of a process of controlling cloud resource consumption based on carbon footprints of cloud resources, in accordance with embodiments of the present invention. 
         FIG.  3    is a flowchart of a process of forming a team of cloud service providers to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. 
         FIG.  4    is a flowchart of a process of using credit points to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. 
         FIG.  5    is a flowchart of a process of using an artificial intelligence engine to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. 
         FIG.  6    is a block diagram of a computer that is included in the system of  FIG.  1    and that implements the processes of  FIGS.  2 A- 2 B ,  FIG.  3   ,  FIG.  4   , and  FIG.  5   , in accordance with embodiments of the present invention. 
         FIG.  7    depicts a cloud computing environment, in accordance with embodiments of the present invention. 
         FIG.  8    depicts abstraction model layers, in accordance with embodiments of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Overview 
     Regarding carbon emission related to cloud resources used by an organization, leaving accountability solely with the cloud service provider means that the organization is not fulfilling its social responsibility and there is no environmental benefit. Every organization who uses cloud resources should be held responsible for respective carbon emissions and should control the cloud resource usage (or select appropriate greener resources) as part of executing their business applications. 
     Embodiments of the present invention address the aforementioned unique challenges related cloud resource management by shifting the accountability of carbon emission to the individual organizations who are using the cloud resources. In one embodiment, a cloud resource consumption management system utilizes a publish/subscribe (i.e., pub-sub) system where cloud consumer organizations post their cloud resource requirements together with an affordable carbon footprint cap measured in CO2e units, which is based on the organizations&#39; sustainability targets. The posted cloud resource requirements are subscribed by cloud service providers, which return respective lists of cloud resources meeting the requirements (or the nearest match by trading off with other parameters) together with the carbon footprint of each of the cloud resources at different workload levels. The system selects an optimized greener configuration (or a combination of configurations from multiple cloud service providers) by considering workload service level agreement (SLA) requirements, criticality level of the workload or application, peak load duration, and previous success rates with respective cloud service providers. 
     In one embodiment, the cloud resource consumption management system provides decision inputs or recommendations to move an organization&#39;s workload dynamically to a different cloud service provider or to another facility of the current cloud service provider in response to a change in a carbon emission value, while keeping the organization within its carbon footprint cap. In one embodiment, in response to a negative variation (or a predication of a negative variation) in meeting an agreed upon targeted carbon emission value, the cloud resource consumption management system creates automatic bids to the pub-sub system to meet sustainability targets at an optimal cost. 
     In one embodiment, the cloud resource consumption management system allows a first cloud resource consumer to trade-off with a second cloud resource consumer who is in custody of a greener cloud resource by generating a bid for the greener cloud resource for a specific amount of time during which the greener cloud resource is used by the first cloud resource consumer to process a large workload (i.e., a workload that exceeds a predetermined threshold workload amount). In response to completing the processing of the large workload, the system automatically returns the cloud resource to the second cloud resource consumer. 
     In one embodiment, the cloud resource consumption management system enables a formation of a team of cloud service providers at a brokerage platform level or a multi-cloud management platform level. A single cloud service provider in a team serves a request by a consumer for cloud resources (even if the single cloud service provider is not in custody of all the requested cloud resources) by working with other cloud service providers in the team based on service provider level agreements and/or discounts, and by placing software-as-a-service (SaaS) kind of applications on suitable cloud service providers to ensure a decrease in the carbon footprint. 
     In one embodiment, the cloud resource consumption management system tracks credits earned by different consumers by comparing the carbon emission values of workloads before moving to a target environment with carbon emission values of the workloads after the move to the target environment over a period of time and assigning credit points based on the aforementioned comparison. The pub-sub system provides a mechanism to exchange these credits with other registered consumers who fail to meet carbon emission targets. The cloud service provider may provide the credits to cloud users who fail to meet (i) a service level agreement (SLA) target relative to carbon emissions or (ii) an agreed upon carbon footprint cap. 
     System for Carbon Footprint-Based Control of Cloud Resource Consumption 
       FIG.  1    is a block diagram of a system for carbon footprint-based control of cloud resource consumption, in accordance with embodiments of the present invention. A carbon footprint-based control of cloud resource consumption system  100  includes a cloud consumer computer  102  operated by a cloud consumer and a cloud service provider computer  104  operated by a cloud service provider. Cloud consumer computer  102  and cloud service provider computer  104  are operatively coupled to a platform  106  via one or more computer networks (not shown). In one embodiment, platform  106  is a publish-subscribe platform that sets up a publish-subscribe portal. In another embodiment, platform  106  is a multi-cloud management platform. In another embodiment, platform  106  is a hybrid cloud brokerage platform. 
     In one embodiment, one or more additional cloud consumer computers (not shown) are in communication with platform  106  and have functionalities that match the functionalities of cloud consumer computer  102 . In one embodiment, one or more additional cloud service provider computers (not shown) are in communication with platform  106  via one or more computer networks and have functionalities that match the functionalities of cloud service provider computer  104 . 
     Cloud consumer computer  102  includes and executes a cloud resource requirements and carbon footprint cap publishing module  108 , a bid/re-bid preparing and submitting module  110 , a dynamic sustainability target identifier module  112 , and a cloud resource finalizing module  114 . 
     Cloud service provider computer  104  includes and executes a cloud resource requirement listener and computation module  116 , a cloud resource state and future availability assessment module  118 , a dynamic carbon emission calculator  120 , a carbon credit calculator and assigner  122 , a cloud group formation module  124 , a carbon emission value publishing module  126 , a workload mover to facility module  128 , and an SLA miss carbon credit exchange module  130 . 
     Each of the following components is located in cloud consumer computer  102 , cloud service provider computer  104 , or another computer (not shown): a workload mover to provider module  132 , a carbon credit database  134 , an enterprise/user carbon credit exchange module  136 , and an artificial intelligence engine  138 . 
     Although not shown in  FIG.  1   , a software-based first cloud resource consumption control system is executed by cloud consumer computer  102  and includes cloud resource requirements and carbon footprint cap publishing module  108 , bid/re-bid preparing and submitting module  110 , dynamic sustainability target identifier module  112 , and cloud resource finalizing module  114 . Although not shown in  FIG.  1   , a software-based second cloud resource consumption control system is executed by cloud service provider computer  104  and includes cloud resource requirement listener and computation module  116 , cloud resource state and future availability assessment module  118 , dynamic carbon emission calculator  120 , carbon credit calculator and assigner  122 , cloud group formation module  124 , carbon emission value publishing module  126 , workload mover to facility module  128 , and SLA miss carbon credit exchange module  130 . 
     Cloud resource requirements and carbon footprint cap publishing module  108  enables the cloud consumer to publish cloud resource requirements of the cloud consumer to platform  106 , together with a total carbon footprint cap (i.e., carbon emission cap) that the cloud consumer can afford. 
     Cloud resource requirement listener and computation module  116  gathers requirements of the cloud consumer (i.e., cloud resource requirements and the carbon footprint cap) that were published in the portal provided by platform  106  and provides a list of cloud resources that satisfy the cloud resource requirements and the carbon footprint cap. 
     Cloud group formation module  124  forms a group of cloud service providers to serve requests by a single cloud service provider acting as a broker among the group of cloud service providers, including one cloud service provider acting as an aggregator. For example, cloud group formation module  124  forms a team of software-as-a-service (SaaS) and infrastructure-as-a-service (IaaS) providers that ensure a decreased carbon footprint. 
     Cloud resource state and future availability assessment module  118  is used by a cloud service provider to identify the available resources for a requested duration that satisfy the requirements based on individual and combined carbon footprint caps by analyzing the current and future expected workload (i.e., predicted workload). 
     Carbon emission value publishing module  126  for each cloud resource is used by the cloud service provider to publish the carbon emission value for the cloud resource based on a historical average emission value for a specified workload (e.g., a reasonable agreed upon workload). 
     Dynamic carbon emission calculator  120  for cloud resources is used by the cloud service provider to identify and publish the dynamic carbon emission details for each cloud resource at a specific load on the cloud resource (e.g., 25%, 50%, 75%, and 100% loads). 
     Carbon credit calculator and assigner  122  calculates carbon credit points as (i) the difference between carbon emission on-premises (i.e., previous state) and the current state (i.e., target state) or (ii) the difference between the carbon emission amount associated with the right to emit and the carbon emission amount saved by using actions that favor sustainability targets (i.e., greener options). 
     In response to the workload mover to facility module  128  determining that the cloud service provider serving a carbon emission target for a workload cannot meet the target within a threshold period, the workload mover to facility module  128  moves the workload to another facility of the same cloud service provider where the target can be met. 
     In response to the SLA miss carbon credit exchange module  130  determining that the cloud service provider cannot meet the carbon emission target with any of its facilities and misses the agreed upon target, SLA miss carbon credit exchange module  130  offers carbon credit points that can be exchanged with other users of the cloud service provider as compensation. 
     In response to the bid/re-bid preparing and submitting module  110  determining that the cloud service provider is unable to meet an agreed upon carbon emission target for a specific component or for an entire workload, the bid/re-bid preparing and submitting module  110  prepares a bid again for the entire workload of a specific portion of the workload and publishes in the portal provided by platform  106 . 
     Workload mover to provider module  132  moves the workload from one cloud service provider to another cloud service provider based on a decision made by carbon footprint-based control of cloud resource consumption system  100 . If the cloud service provider serving the carbon emission target cannot meet the target for a threshold period, workload mover to provider module  132  moves the workload to another facility of a different cloud service provider where the target is met. Workload mover to provider module  132  selects the different cloud service provider to meet the target depending on the response of the different cloud service provider based on the dynamic re-bid. 
     If an enterprise target for carbon emission for a workload changes, dynamic sustainability target identifier module  112  uses natural language processing (NLP) techniques and/or manual inputs to dynamically capture new target values from documentations. In response to the dynamic capture of the new target values, bid/re-bid preparing and submitting module  110  prepares or re-prepares a bid according to the new target values. 
     Cloud resource finalizing module  114  finalizes a selection of cloud service provider(s) to provide the cloud resources to meet the requirements of the cloud consumer. 
     Carbon credit database  134  keeps track of carbon credit points earned, spent, and exchanged using the aforementioned modules for each user, enterprise, and/or department level. 
     Enterprise/user carbon credit exchange module  136  provides a platform for users and/or enterprises to exchange carbon credit points. 
     Artificial intelligence engine  138  is integrated with the aforementioned modules and uses random forest methodology to capture and re-calculate any deviation due to different or unforeseen cloud resource consumption requirements. 
     The functionality of the components shown in  FIG.  1    is described in more detail in the discussion of  FIGS.  2 A- 2 B ,  FIG.  3   ,  FIG.  4   ,  FIG.  5   , and  FIG.  6    presented below. 
     Process for Carbon Footprint-Based Control of Cloud Resource Consumption 
       FIGS.  2 A- 2 B  depict a flowchart of a process of controlling cloud resource consumption based on carbon footprints of cloud resources, in accordance with embodiments of the present invention. The process of  FIGS.  2 A- 2 B  begins at a start node  200  in  FIG.  2 A . Prior to step  202 , cloud service provider computer  102  (see  FIG.  1   ) and other cloud service provider computers subscribe to published cloud resources requirements and carbon footprint caps of workloads. Prior to step  202 , cloud resources requirements and carbon footprint cap publishing module  108  (see  FIG.  1   ) publishes the cloud resource requirements and the carbon footprint cap of a workload of a cloud consumer organization based on a sustainability target of the cloud consumer organization. 
     In step  202 , in response to cloud service provider computer  104  (see  FIG.  1   ) subscribing to published cloud resources requirements and carbon footprint caps of workloads, cloud resource requirement listener and computation module  116  (see  FIG.  1   ) receives the published cloud resources requirements and the carbon footprint cap of the workload of the cloud consumer organization. 
     In step  204 , cloud resource requirement listener and computation module  116  (see  FIG.  1   ) sends a list of cloud resources satisfying the cloud resources requirements received in step  202  together with the carbon footprint (i.e., estimated carbon emission value) of each of the cloud resources at different load levels (e.g., 25%, 50%, 75%, and 100% load levels of the workload). In one embodiment, step  204  is repeated with one or more other cloud service provider computers sending other list(s) of cloud resources satisfying the cloud resources requirements received in step  202  and carbon footprints of the cloud resources at different load levels. 
     In step  206 , bid/re-bid preparing and submitting module  110  (see  FIG.  1   ) receives an SLA requirement of the workload, a criticality level of the workload, a peak load duration of the workload, and previous success rates of cloud service providers satisfying cloud resource requirements for the cloud consumer organization. 
     In step  208 , based on the SLA requirement of the workload, the criticality level of the workload, the peak load duration of the workload, and the previous success rates of cloud service providers satisfying cloud resource requirements for the cloud consumer organization received in step  206 , bid/re-bid preparing and submitting module  110  (see  FIG.  1   ) selects an optimized configuration of cloud resource(s) and cloud service provider(s), where the cloud resource(s) are selected from the list of cloud resources sent in step  204 . Also in step  208 , bid/re-bid preparing and submitting module  110  (see  FIG.  1     ii ) prepares and submits a bid for the optimized configuration of cloud resource(s) via platform  106  (see  FIG.  1   ). 
     In one embodiment not shown in  FIGS.  2 A- 2 B , the process of controlling cloud resource consumption based on carbon footprints of cloud resources ends after step  208 . In the embodiment shown in  FIGS.  2 A- 2 B , the process of controlling cloud resource consumption based on carbon footprints of cloud resources also includes steps  210  through  222 , where the optimized configuration selected in step  208  includes a single cloud service provider as the provider of the cloud resource(s) in the optimized configuration. The single cloud service provider is also referred to in the discussion of  FIGS.  2 A- 2 B  as the initial cloud service provider. 
     In step  210 , system  100  provides the optimized configuration selected in step  208  by using an initial facility of an initial cloud service provider providing the cloud resource(s) for the workload. 
     In step  212 , dynamic carbon emission calculator  120  (see  FIG.  1   ) detects an increase in a carbon emission value of the workload. 
     In step  214 , in response to the increase in the carbon emission value detected in step  212 , workload mover to provider module  132  (see  FIG.  1   ) dynamically selects another cloud service provider and moves the workload so that the selected other cloud service provider provides the cloud resource(s) for the workload. 
     Alternatively, in step  214 , in response to the increase in the carbon emission value detected in step  212 , workload mover to facility module  128  (see  FIG.  1   ) dynamically selects another facility of the initial cloud service provider and moves the workload to the selected other facility, so that the other facility provides the cloud resource(s) for the workload. 
     After step  214 , the process of  FIGS.  2 A- 2 B  continues with step  216  in  FIG.  2 B . In step  216 , bid/re-bid preparing and submitting module  110  (see  FIG.  1   ) determines that a load level of the workload increases to exceed a threshold amount. 
     In step  218 , in response to step  216 , bid/re-bid preparing and submitting module  110  (see  FIG.  1   ) submits a bid for a trade-off with other cloud consumer organization(s) so that other cloud resource(s) of the other cloud consumer organization(s) are provided for the workload for a specified duration instead of the cloud resource(s) included in the configuration selected in step  208 . 
     In step  220 , system  100  performs the trade-off for which the bid was submitted in step  218 . 
     In step  222 , after the specified duration associated with the trade-off, system  100  returns the other cloud resource(s) to the other cloud consumer organization(s), so that the cloud resource(s) included in the configuration selected in step  208  are again provided for the workload by the cloud service provider specified in the configuration selected in step  208 . 
     After step  222 , the process of  FIGS.  2 A- 2 B  ends at an end node  224 . 
       FIG.  3    is a flowchart of a process of forming a team of cloud service providers to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. The process of  FIG.  3    begins at a start node  300 . In the process of  FIG.  3   , platform  106  (see  FIG.  1   ) includes a multi-cloud management platform (MCMP) or a hybrid cloud brokerage platform. In step  302 , platform  106  (see  FIG.  1   ) forms a team of cloud service providers by using the MCMP or the hybrid cloud brokerage platform. 
     In step  304 , a single cloud service provider receives a request from a cloud consumer organization for multiple cloud resources for the workload. The request is received via the cloud resource consumption control system in cloud consumer computer  102  (see  FIG.  1   ). 
     In step  306 , a service of the single cloud service provider initiates processing of the request for the multiple cloud resources, even though the single cloud service provider does not have custody of all of the requested multiple cloud resources. 
     In step  308 , based on service provider level agreements, the single cloud service provider sends the request to other cloud service provider(s) in the team formed in step  302 , which requests that the other cloud service provider(s) provide the multiple cloud resources. If the single cloud service provider can provide one or more (but not all) of the requested multiple cloud resources, then the request sent to the other cloud service provider(s) requests that the other cloud service provider(s) provide the cloud resource(s) included in the multiple cloud resources that cannot be provided by the single cloud service provider. 
     After step  308 , the other cloud service provider(s) or the single cloud service provider together with the other cloud service provider(s) provide the multiple cloud resources for the workload. The process of  FIG.  3    ends at an end node  310 . 
       FIG.  4    is a flowchart of a process of using credit points to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. The process of  FIG.  4    begins at a start node  400 . In the process of  FIG.  4   , platform  106  (see  FIG.  1   ) includes a publish-subscribe platform. In step  402 , platform  106  (see  FIG.  1   ) registers the cloud consumer organization and another cloud consumer organization in a portal of the publish-subscribe platform. 
     In step  404 , carbon credit calculator and assigner  122  (see  FIG.  1   ) determines a decrease in carbon emission for the workload by comparing a carbon emission value of the workload before applying the configuration selected in step  208  (see  FIG.  2 A ) and after applying the configuration to the workload. 
     In step  406 , in response to determining the decrease in carbon emission in step  404 , carbon credit calculator and assigner  122  (see  FIG.  1   ) assigns carbon credit points to the cloud consumer organization. 
     In step  408 , via the portal of the publish-subscribe platform, enterprise/user carbon credit exchange module  136  (see  FIG.  1   ) exchanges the carbon credit points with the other cloud consumer organization so that the other cloud consumer organization satisfies a sustainability target of the other cloud consumer organization. 
     After step  408 , the process of  FIG.  4    ends at an end node  410 . 
       FIG.  5    is a flowchart of a process of using an artificial intelligence engine to manage cloud resource consumption within the process of  FIGS.  2 A- 2 B , in accordance with embodiments of the present invention. The process of  FIG.  5    begins at a start node  500 . In step  502 , system  100  (see  FIG.  1   ) identifies a trend in deviations in cloud resources requirements by using artificial intelligence engine  138  (see  FIG.  1   ), which uses random forest methodology. 
     In step  504 , based on the trend identified in step  502 , artificial intelligence engine  138  (see  FIG.  1   ) predicts an upcoming deviation in the cloud resources requirements initially received in step  202  (see  FIG.  2 A ). 
     In step  506 , based on the upcoming deviation predicted in step  504 , artificial intelligence engine  138  (see  FIG.  1   ) generates a recommendation to select a different set of cloud service provider(s) to provide the cloud resource(s) that were in the configuration selected in step  208  (see  FIG.  2 A ). 
     In step  508 , system  100  selects the different set of cloud service provider(s) in accordance with the recommendation generated in step  506  and provides the cloud resource(s) by using the selected different set of cloud service provider(s). 
     After step  508 , the process of  FIG.  5    ends at an end node  510 . 
     Computer System 
       FIG.  6    is a block diagram of a computer that is included in the system of  FIG.  1    and that implements the processes of  FIGS.  2 A- 2 B ,  FIG.  3   ,  FIG.  4   , and  FIG.  5   , in accordance with embodiments of the present invention. Computer  600  is a computer system that generally includes a central processing unit (CPU)  602 , a memory  604 , an input/output (I/O) interface  606 , and a bus  608 . In one embodiment, computer  600  is cloud consumer computer  102  (see  FIG.  1   ) and functionality of components of computer  600  are identical to functionality of analogous components (not shown) that are included in cloud service provider computer  104 . Further, computer  600  is coupled to I/O devices  610  and a computer data storage unit  612 . CPU  602  performs computation and control functions of computer  600 , including executing instructions included in program code  614  for carbon footprint-based control of cloud resource consumption system  100  (see  FIG.  1   ) to perform a method of controlling cloud resource consumption based on carbon footprints of cloud resources, where the instructions are executed by CPU  602  via memory  604 . CPU  602  may include a single processing unit or processor or be distributed across one or more processing units or one or more processors in one or more locations (e.g., on a client and server). 
     Memory  604  includes a known computer readable storage medium, which is described below. In one embodiment, cache memory elements of memory  604  provide temporary storage of at least some program code (e.g., program code  614 ) in order to reduce the number of times code must be retrieved from bulk storage while instructions of the program code are executed. Moreover, similar to CPU  602 , memory  604  may reside at a single physical location, including one or more types of data storage, or be distributed across a plurality of physical systems or a plurality of computer readable storage media in various forms. Further, memory  604  can include data distributed across, for example, a local area network (LAN) or a wide area network (WAN). 
     I/O interface  606  includes any system for exchanging information to or from an external source. I/O devices  610  include any known type of external device, including a display, keyboard, etc. Bus  608  provides a communication link between each of the components in computer  600 , and may include any type of transmission link, including electrical, optical, wireless, etc. 
     I/O interface  606  also allows computer  600  to store information (e.g., data or program instructions such as program code  614 ) on and retrieve the information from computer data storage unit  612  or another computer data storage unit (not shown). Computer data storage unit  612  includes one or more known computer readable storage media, where a computer readable storage medium is described below. In one embodiment, computer data storage unit  612  is a non-volatile data storage device, such as, for example, a solid-state drive (SSD), a network-attached storage (NAS) array, a storage area network (SAN) array, a magnetic disk drive (i.e., hard disk drive), or an optical disc drive (e.g., a CD-ROM drive which receives a CD-ROM disk or a DVD drive which receives a DVD disc). 
     Memory  604  and/or storage unit  612  may store computer program code  614  that includes instructions that are executed by CPU  602  via memory  604  to control cloud resource consumption based on carbon footprints of cloud resources. Although  FIG.  6    depicts memory  604  as including program code, the present invention contemplates embodiments in which memory  604  does not include all of code  614  simultaneously, but instead at one time includes only a portion of code  614 . 
     Further, memory  604  may include an operating system (not shown) and may include other systems not shown in  FIG.  6   . 
     As will be appreciated by one skilled in the art, in a first embodiment, the present invention may be a method; in a second embodiment, the present invention may be a system; and in a third embodiment, the present invention may be a computer program product. 
     Any of the components of an embodiment of the present invention can be deployed, managed, serviced, etc. by a service provider that offers to deploy or integrate computing infrastructure with respect to controlling cloud resource consumption based on carbon footprints of cloud resources. Thus, an embodiment of the present invention discloses a process for supporting computer infrastructure, where the process includes providing at least one support service for at least one of integrating, hosting, maintaining and deploying computer-readable code (e.g., program code  614 ) in a computer system (e.g., computer  600 ) including one or more processors (e.g., CPU  602 ), wherein the processor(s) carry out instructions contained in the code causing the computer system to control cloud resource consumption based on carbon footprints of cloud resources. Another embodiment discloses a process for supporting computer infrastructure, where the process includes integrating computer-readable program code into a computer system including a processor. The step of integrating includes storing the program code in a computer-readable storage device of the computer system through use of the processor. The program code, upon being executed by the processor, implements a method of controlling cloud resource consumption based on carbon footprints of cloud resources. 
     While it is understood that program code  614  for controlling cloud resource consumption based on carbon footprints of cloud resources may be deployed by manually loading directly in client, server and proxy computers (not shown) via loading a computer-readable storage medium (e.g., computer data storage unit  612 ), program code  614  may also be automatically or semi-automatically deployed into computer  600  by sending program code  614  to a central server or a group of central servers. Program code  614  is then downloaded into client computers (e.g., computer  600 ) that will execute program code  614 . Alternatively, program code  614  is sent directly to the client computer via e-mail. Program code  614  is then either detached to a directory on the client computer or loaded into a directory on the client computer by a button on the e-mail that executes a program that detaches program code  614  into a directory. Another alternative is to send program code  614  directly to a directory on the client computer hard drive. In a case in which there are proxy servers, the process selects the proxy server code, determines on which computers to place the proxy servers&#39; code, transmits the proxy server code, and then installs the proxy server code on the proxy computer. Program code  614  is transmitted to the proxy server and then it is stored on the proxy server. 
     Another embodiment of the invention provides a method that performs the process steps on a subscription, advertising and/or fee basis. That is, a service provider can offer to create, maintain, support, etc. a process of controlling cloud resource consumption based on carbon footprints of cloud resources. In this case, the service provider can create, maintain, support, etc. a computer infrastructure that performs the process steps for one or more customers. In return, the service provider can receive payment from the customer(s) under a subscription and/or fee agreement, and/or the service provider can receive payment from the sale of advertising content to one or more third parties. 
     The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) (i.e., memory  604  and computer data storage unit  612 ) having computer readable program instructions  614  thereon for causing a processor (e.g., CPU  602 ) to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions (e.g., program code  614 ) for use by an instruction execution device (e.g., computer  600 ). The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium or computer readable storage media, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions (e.g., program code  614 ) described herein can be downloaded to respective computing/processing devices (e.g., computer  600 ) from a computer readable storage medium or to an external computer or external storage device (e.g., computer data storage unit  612 ) via a network (not shown), for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card (not shown) or network interface (not shown) in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions (e.g., program code  614 ) for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations (e.g.,  FIGS.  2 A- 2 B ,  FIG.  3   ,  FIG.  4   , and  FIG.  5   ) and/or block diagrams (e.g.,  FIG.  1    and  FIG.  6   ) of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions (e.g., program code  614 ). 
     These computer readable program instructions may be provided to a processor (e.g., CPU  602 ) of a general purpose computer, special purpose computer, or other programmable data processing apparatus (e.g., computer  600 ) to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium (e.g., computer data storage unit  612 ) that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions (e.g., program code  614 ) may also be loaded onto a computer (e.g. computer  600 ), other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be accomplished as one step, executed concurrently, substantially concurrently, in a partially or wholly temporally overlapping manner, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     While embodiments of the present invention have been described herein for purposes of illustration, many modifications and changes will become apparent to those skilled in the art. Accordingly, the appended claims are intended to encompass all such modifications and changes as fall within the true spirit and scope of this invention. 
     Cloud Computing Environment 
     It is to be understood that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed. 
     Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. 
     Characteristics are as follows: 
     On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service&#39;s provider. 
     Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs). 
     Resource pooling: the provider&#39;s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter). 
     Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time. 
     Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service. 
     Service Models are as follows: 
     Software as a Service (SaaS): the capability provided to the consumer is to use the provider&#39;s applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. 
     Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 
     Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls). 
     Deployment Models are as follows: 
     Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises. 
     Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. 
     Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. 
     Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds). 
     A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that includes a network of interconnected nodes. 
     Referring now to  FIG.  7   , illustrative cloud computing environment  50  is depicted. As shown, cloud computing environment  50  includes one or more cloud computing nodes  10  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  54 A, desktop computer  54 B, laptop computer  54 C, and/or automobile computer system  54 N may communicate. Nodes  10  may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment  50  to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices  54 A,  54 B,  54 C and  54 N shown in  FIG.  7    are intended to be illustrative only and that computing nodes  10  and cloud computing environment  50  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
     Referring now to  FIG.  8   , a set of functional abstraction layers provided by cloud computing environment  50  (see  FIG.  7   ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG.  8    are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: 
     Hardware and software layer  60  includes hardware and software components. Examples of hardware components include: mainframes  61 ; RISC (Reduced Instruction Set Computer) architecture based servers  62 ; servers  63 ; blade servers  64 ; storage devices  65 ; and networks and networking components  66 . In some embodiments, software components include network application server software  67  and database software  68 . 
     Virtualization layer  70  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers  71 ; virtual storage  72 ; virtual networks  73 , including virtual private networks; virtual applications and operating systems  74 ; and virtual clients  75 . 
     In one example, management layer  80  may provide the functions described below. Resource provisioning  81  provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing  82  provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal  83  provides access to the cloud computing environment for consumers and system administrators. Service level management  84  provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment  85  provides pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
     Workloads layer  90  provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation  91 ; software development and lifecycle management  92 ; virtual classroom education delivery  93 ; data analytics processing  94 ; transaction processing  95 ; and carbon footprint-based control of cloud resource consumption  96 .