Patent Publication Number: US-10334031-B2

Title: Load balancing based on impending garbage collection in execution environment

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a Continuation of and claims benefit from U.S. patent application Ser. No. 11/254,649 that was filed on Oct. 20, 2005 and that is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     Memory management in a managed execution environment may include temporarily suspending managed threads during a sweep or scan of a memory heap. However, a prolonged suspension of the managed threads may time-out execution of the corresponding application. 
     SUMMARY 
     Execution of portions of an application, program, method, function, or other assemblage of code in a managed execution environment may be influenced by, at least, the potential magnitude of a memory management implementation. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       Load balancing in a managed execution environment is presently described in accordance with the following figures. 
         FIG. 1  shows devices communicating over a network, with the devices implementing example technologies for load balancing. 
         FIG. 2  shows an example of an execution environment for implementing example technologies for load balancing. 
         FIG. 3  shows an example data flow among data nodes in accordance with an example implementation of load balancing. 
         FIG. 4  shows an example processing flow in accordance with an example implementation of load balancing. 
     
    
    
     DETAILED DESCRIPTION 
     Load balancing is described herein. More particularly, the present description relates to controlling certain behavior of at least portions of an application, program, method, function, or other assemblage of code based on data regarding, at least, the potential magnitude of a memory management implementation in the respective execution environment. 
     Within the context of this detailed description and as pertaining to object-oriented programming, a method may be regarded as the processing that an object performs. Therefore, for instance, when a message is sent to an object, the method is implemented. 
     “Process,” as described herein, may refer to the actual running of a module or assembly of code pertaining to an application, program, function, or other assemblage of programmable and executable code. 
     “Assembly,” as described herein, may refer to a unit of deployment of code, which may or may not be versionable. 
     “Resource,” as described herein, may include both physical and logical resources associated with a given computing environment. As non-limiting examples, such resources may range from files to ports to shared state; that is, any non-executable entity that may be shared by more than one executable entity. 
     “Threads,” as described herein, may refer to execution paths within an application, program, function, or other assemblage of programmable and executable code. Threads enable multiple paths or streams of execution of modules of executable instructions to occur concurrently within the same application, program, function, or other assemblages of programmable and executable code; whereby, within each stream, a different transaction or message may be processed. A multitasking or multiprocessing environment, in which multi-threading processes may be executed, may be found in either a managed execution environment or an unmanaged execution environment. 
     “Isolation boundary,” as described herein, may refer to a logical or physical construct that may serve as a unit of isolation. Processes are an example of an isolation boundary. Within a managed execution environment, such an isolation boundary may be referred to as an application domain, in which multiple threads of execution may be contained. Such terminology is provided as an example only. That is, the example implementations described herein are not limited to application domains or even to managed execution environments as stated above, but rather may be applied within various other isolation boundaries implementations in other execution environments. More particularly, isolation boundaries, as related to the scope of resource distribution described herein, may further pertain to machine boundaries, process boundaries, threads, and class or assembly boundaries. Even more particularly, the scope of resource distribution may pertain to public/private exposure, assemblies, or classes. Further, resource distribution may have multiple axis or annotations including, e.g., a type of resource as well as visibility of the resource. 
     Isolation boundaries may enable the code to be executed therein to be loaded from a specified source; an isolation boundary may be aborted independent of other such isolation boundaries; and processing within an isolation boundary may be isolated so that a fault occurring therein does not affect other isolation boundaries within the process. More particularly, isolation boundaries may isolate the consumption of resources therein to the extent that other isolation boundaries either do not see any changes to a resource or, rather, see the resources in a serialized, atomic fashion. 
       FIG. 1  shows example network environment  100  having processing nodes that may communicate with each other in various quantities and combinations thereof to implement one or more examples of load balancing. However, implementations of load balancing are not limited to nodes in a network environment. Still, in the example network environment of  FIG. 1 , client device  105 , server devices  110 A and  110 B, and “other” device  115  may be communicatively coupled to one another via network  125 ; and, further, at least one of client device  105 , server devices  110 A and  110 B, and “other” device  115  may be capable of implementing load balancing  120 , as described herein. 
     Client device  105  may be at least one of a variety of conventional computing devices, including a desktop personal computer (PC), workstation, mainframe computer, Internet appliance, and set-top box. Further, client device  105  may be at least one of any device that is capable of being associated with network  125  by a wired and/or wireless link, including a personal digital assistant (PDA), laptop computer, cellular telephone, etc. Further still, client device  105  may represent the client devices described above in various quantities and/or combinations thereof. “Other” device  115  may also be embodied by any of the above examples of client device  105 . 
     Server devices  110 A and  110 B may provide any of a variety of data and/or functionality to client device  105  or “other” device  115  in accordance with at least one implementation of load balancing  120 . The data may be publicly available or alternatively restricted, e.g., restricted to only certain users or only if an appropriate subscription or licensing fee is paid. Either of server devices  110 A and  110 B may be a network server, an application server, or a blade server, in various quantities and combinations thereof. Typically, server devices  110 A and  110 B serve as content sources, and client device  105  receives such content either via network  125  or in an off-line manner. However, according to the example implementations described herein, client device  105  and server devices  110 A and  110 B may interchangeably be sending nodes or receiving nodes in network environment  100 . Further, according to at least one example of load balancing  120 , server devices  110 A and  110 B may be implemented as one of many server devices on network  125 . Such configuration may be regarded, informally, as a “server farm.” In such a server farm, the two or more networked servers may share in the execution of at least portions of a same application, program, function, or other assemblage of programmable and executable code. Further still, “other” device  115  may also be embodied by any of the above examples of server devices  110 A and  110 B. 
     “Other” device  115  may be any further device that is capable of implementing load balancing  120  according to one or more of the examples described herein. That is, “other” device  115  may be a software-enabled computing or processing device that is capable of implementing load balancing  120  for at least a portion of an application, program, function, or other assemblage of programmable and executable code in at least a managed execution environment. More particularly, “other” device  115  may serve as a load balancer. As a load balancer, “other” device  115  may be implemented as a hardware device that is physically separate from either of client device  105  or server devices  110 A and  110 B; alternatively, “other” device  115  may be implemented as firmware or software on at least one of client device  105  or server devices  110 A and  110 B. Thus, “other” device  115  may be a computing, processing, or server device having at least one of an operating system, an interpreter, converter, compiler, or runtime execution environment implemented thereon. These examples are not intended to be limiting in any way, and therefore should not be construed in that manner. 
     Network  125  may represent any of a variety of conventional network topologies and types, which may include wired and/or wireless networks. Network  125  may further utilize any of a variety of conventional network protocols, including public and/or proprietary protocols. Network  125  may include, for example, the Internet as well at least portions of one or more local area networks (also referred to, individually, as a “LAN”), such as an 802.11 system; a personal area network (i.e., PAN), such as Bluetooth. 
     Computer architecture in at least one of devices  105 ,  110 A,  110 B, and  115  has typically defined computing platforms in terms of hardware and software. Software for computing devices came to be categorized into groups, based on function, which include: a hardware abstraction layer (alternatively referred to as a “HAL”), an operating system (alternatively referred to as “OS”), and applications. 
     A runtime execution environment may refer to an isolated space, which may be between the OS and an application, in which the application may execute specific tasks on at least one of processing device  105 , one or more of server devices  110 A and  110 B, or other device  115 . More particularly, a runtime execution environment is intended to enhance the reliability of the execution of applications on a growing range of processing devices including servers, desktop computers, laptop computers, mobile processing devices, set-top boxes, and gaming consoles by providing a layer of abstraction and services for an application running on such processing devices, and further providing the application capabilities including memory management and configuration thereof. 
     A runtime execution environment may serve as at least one of an application programming and application execution platform. 
     As an application programming platform, a runtime execution environment may compile targeted applications, which may be written in one of multiple computing languages, into an intermediate language (hereafter “IL”). IL is typically independent of the platform and the central processing unit (hereafter “CPU”) executes IL. In fact, IL is a higher level language than many CPU machine languages. 
     As an application execution platform, a runtime execution environment may interpret compiled IL into native machine instructions. A runtime execution environment may utilize either an interpreter or a “just-in-time” (hereafter “JIT”) compiler to execute such instructions. Alternatively, a runtime execution environment may execute, read, interpret, or otherwise analyze intermediate language code (i.e., “IL”) that is distributed to the runtime execution environment in IL format rather than in a native platform execution format and is already compiled into any one of assemblies, methods, or types. A source of such IL may be disposed in either of a non-managed execution environment or a separate implementation of the runtime execution environment on a same or separate one of devices  105 ,  110 , and  115 . The source may deploy the IL at, or prior to, install time for the application, program, method, function, or other assemblage of programmable and executable code to which the IL corresponds. 
     Regardless, the native machine instructions may then be directly executed by the CPU. Since IL is CPU-independent, IL may execute on a CPU platform as long as the OS running on that CPU platform hosts an appropriate runtime execution environment. Examples of runtime environments, to which load balancing  120  may pertain, include: Visual Basic runtime environment; Java® Virtual Machine runtime environment that is used to run, e.g., Java® routines; or Common Language Runtime (CLR) to compile, e.g., Microsoft.NET™ applications into machine language before executing a calling routine. However, such listing provides examples only. The example implementations are not limited to just these managed execution environments. Further, the example implementations are not just limited to managed execution environments, for one or more examples may be implemented within testing environments and/or unmanaged execution environments. 
     An application compiled into IL may be referred to as “managed code,” and therefore a runtime execution environment may be alternatively referred to as a “managed execution environment.” Portions of managed code may be referred to as a “managed image.” Code that does not utilize a runtime execution environment to execute may be referred to as native code applications. 
       FIG. 2  shows an example of runtime execution environment  200  in which examples of load balancing  120  (see  FIG. 1 ) may be implemented. 
     According to at least one example implementation, runtime execution environment  200  may facilitate execution of managed code for a computing device platform. Managed code may be considered to be part of a core set of application-development technologies, and may further be regarded as code that is compiled for execution on runtime execution environment  200  to provide a corresponding service to the computing device platform. In addition, runtime execution environment  200  may translate managed code at an interpretive level into instructions that may be proxied and then executed by a processor. A framework for runtime execution environment  200  may also provide class libraries, which may be regarded as software building blocks for managed applications. 
     According to a further example implementation, runtime execution environment  200  may provide at least partial functionality that may otherwise be expected from a kernel, which may or may not be lacking from a computing device platform depending upon resource constraints for any particular one of devices  105 ,  110 A,  110 B, and  115 . Thus, at least one example of runtime execution environment  200  may implement the following: input/output (hereafter “I/O”) routine management, memory management, administration, and service routine management. Thus, runtime execution environment  200  may include I/O component  205 , at least one memory manager  210 , administrator  215 , and execution component  220 . These components, which are to be described in further detail below, are provided as examples only; that is, the examples are not intended to be limiting to any particular implementation, and no such inference should be made. Further, the components may be implemented in examples of runtime execution environment  200  in various combinations and configurations thereof. 
     I/O component  205  of runtime execution environment  200  may provide asynchronous access to data sources (i.e., processor and peripherals) associated with the computing device platform. Examples of such data sources may be one or more of devices  105 ,  110 A,  110 B, and  115 , described above with regard to  FIG. 1 . More particularly, I/O component  205  may provide runtime execution environment  200  with robust system throughput and further streamline performance of code from which an I/O request originates. 
     Memory manager  210  may refer to a module within or associated with runtime execution environment  200  that is regarded as a “garbage collector.” Garbage collection (alternatively referred to hereafter as “GC”) may be regarded as a robust feature of managed code execution environments by which an object is freed (i.e., de-allocated) if an object is no longer used by any applications, upon a sweep or scan of a memory heap. In at least one example of memory manager  210 , a sweep of free memory heap may be implemented as a linear search. Such implementation may be well-suited for an example of a computing device platform for which memory size is constrained and for which a delay in completion of a sweep may be perceived by a user of a corresponding device. 
     An example of memory manager  210  may implement “concurrent GC” functionality to allow managed threads to continue to run during a sweep or scan of a memory heap. That is, during de-allocation, concurrent GC may allow allocation to continue in parallel. Concurrent GC functionality (alternatively referred to herein as “concurrent GC”) may be suitable for an interactive or GUI (graphical user interface)-based application. 
     However, although load balancing  120  may be relevant to concurrent GC functionality, the present example implementations of load balancing  120  are described in the context of non-concurrent GC functionality, by which one or more managed threads may be suspended during a sweep or scan of a memory heap. 
     Further functions implemented by memory manager  210  may include: managing one or more contiguous blocks of finite volatile RAM (i.e., memory heap) storage or a set of contiguous blocks of memory amongst the tasks running on the computing device platform; allocating memory to at least one application running on the computing device platform; freeing at least portions of memory on request by at least one of the applications; and preventing any of the applications from intrusively accessing memory space that has been allocated to any of the other applications. 
     Administrator  215  may refer to a module within or associated with runtime execution environment  220  that serves to receive at least a portion of an application, program, method, function, or other assemblage of programmable and executable code for execution in runtime execution environment  200 . Further, in accordance with at least one example implementation of load balancing  120 , administrator  215  may coordinate with memory manager  210  to control the behavior of the application, program, method, function, or other assemblage of programmable and executable code within runtime execution environment  220 , at compile time, initial runtime, or at any time thereafter during execution of an application. 
     Execution component  220  may refer to a module within or associated with runtime execution environment  200  that serves to enable execution of managed code for the computing device platform. Execution component  220  may be regarded as the environment in which execution of the code of the application is implemented, and in which runtime services (e.g., device access and memory management) may be provided. 
       FIG. 3  shows example data flow  300  in accordance with an example implementation of load balancing  120  (see  FIG. 1 ). Example data flow  300  is presently described with references to features from  FIGS. 1 and 2 , although such implementations are provided only as examples and are not intended to be construed in any limiting manner. 
     Processes  305 A,  305 B, and  305 C may be regarded as logical or physical constructs, in accordance with at least the description of “isolation boundaries” provided above. Thus, processes  305 A,  305 B, and  305 C may pertain to machine boundaries, process boundaries, threads, application domains, and class or assembly boundaries, in accordance with various implementations of load balancing  120 . Further, the implementations of load balancing  120  are in no way limited to three such constructs (i.e.,  305 A,  305 B, and  305 C), which are illustrated and explained herein only for descriptive purposes. 
     As an example, processes  305 A,  305 B, and  305 C may pertain to multiple servers (i.e., machine boundaries). Implemented as hardware, servers  305 A,  305 B, and  305 C may be separate hardware devices, on which at least one runtime execution environment  200  is running as an application execution platform. Implemented as software servers, processes  305 A,  305 B, and  305 C may be modularized components of a common application, program, method, function, or other assemblage of programmable and executable code being executed by an implementation of runtime execution environment  200 . 
     Memory management data  310 , originating from at least one of processes  305 A,  305 B, and  305 C, may include data referring to an impending sweep or scan of a memory heap (i.e., GC) to free (i.e., de-allocate) one or more objects that are no longer used by an application, program, method, function, or other assemblage of code being executed by an implementation of runt e execution environment  200 . 
     By the example in which processes  305 A,  305 B, and  305 C are implemented as separate hardware devices, memory management data  310  may originate from an implementation of runtime execution environment  200  running on one or more of such devices. By the example in which processes  305 A,  305 B, and  305 C are implemented as modularized components of a common application, program, method, function, or other assemblage of programmable and executable code, memory management data  310  may originate from an implementation of runtime execution environment  200  on which the modularized components are being executed. More particularly, by the above examples, memory management data  310  may originate from memory manager  210  or administrator module  215 , either singularly or combined. 
     Memory management data  310  may implement transactions by using one or more application program interfaces (API) that are compatible with APIs of various system architectures. More particularly, the APIs corresponding to memory management data  310  may be capable of initiating load balancing among processes  305 A,  305 B, and  305 C (i.e., across machine boundaries, process boundaries, threads, application domains, and class or assembly boundaries) in accordance with various implementations of load balancing  120 . As described herein, an API may be regarded as one or more routines used by an application, program, method, function, or other assemblage of programmable and executable code to direct the performance of procedures by runtime execution environment  200  or even an operating system. 
     Memory management data  310  may include one or more APIs implemented by memory manager  210  or administrator module  215 , either singularly or combined. The nomenclature for such APIs listed and described below is provided for descriptive purposes, and are provided as non-limiting examples. 
     MaxGenerationNotifier may refer to a class of which instantiations may be intended to prompt load balancer  315  to redistribute at least a portion of the same or another application, program, method, function, or other assemblage of code being executed by a particular implementation of runtime execution environment  200 . More particularly, MaxGenerationNotifier may be instantiated when memory manager  210  or administrator  215 , either singularly or combined, detect that an impending GC on runtime execution environment  200  may run so long as to cause a time-out in the execution of the same or another application, program, method, function, or other assemblage of code on runtime execution environment  200 . Such detection may be based upon the allocation of the threshold amount of memory heap during the current execution of the application, program, method, function, or other assemblage of code. Effectively, then, an instantiation of MaxGenerationNotifier may provide load balancer with a proactive notification of the state of runtime execution environment  200 . 
     More particularly, MaxGenerationNotifier may be instantiated when memory manager  210  or administrator  215 , either singularly or combined, detect that an impending GC may potentially exceed a threshold logical or physical magnitude. For example, MaxGenerationNotifier may be instantiated when memory manager  210  or administrator  215 , either singularly or combined, detect that the impending GC is an implementation of a late generation GC, and therefore is likely to sweep or scan the largest amount of heap (e.g., 2 GB) permitted under currently-available processing capabilities. As a result, execution of an application, program, method, function, or other assemblage of code may time-out before completion of the late-generation GC since managed threads may be suspended during a sweep or scan of a memory heap. Thus, before a GC of such magnitude begins. MaxGenerationNotifier may be instantiated to notify load balancer  315  of at least a need to redistribute at least a portion of the execution of the application, program, method, function, or other assemblage of code. 
     Of course, the 2 GB heap is described above only as an example of a late-generation GC. The magnitude of an impending GC that may act as a catalyst for instantiation of MaxGenerationNotifier may vary based on myriad of factors, and may increase as process ng capabilities evolve. Such factors may relate to process ng capabilities of the processing device as well as time anticipated for the GC to complete. Further, the preference of the programmer who wrote the executing application, program, method, function, or other assemblage of code, as indicated to administrator  215 , may also initiate an instantiation of MaxGenerationNotifier, when the programmer is motivated by at least one of efficiency and security concerns. 
     Further still, at least one alternative implementation of MaxGenerationNotifier may include one or more specific instructions for redirecting execution for at least a portion of the corresponding application, program, method, function, or other assemblage of code being executed by runt me execution environment  200 . 
     MaxGenerationCompleteNotifier may refer to a class of which instantiations are intended to notify load balancer  315  that the CC instantiated by MaxGenerationNotifier has been completed. Therefore, an instantiation of MaxGenerationCompleteNotifier may serve to notify load balancer  315  that redistribution of one or more portions of the executing application, program, method, function, or other assemblage of code may cease without adversely affecting execution by runtime execution environment  200 . More particularly, the MaxGenerationNotifier may be instantiated when memory manager  210  or administrator  215 , either singularly or combined, detect at least one of: completion of the GC that served as catalyst of a most recent instantiation of MaxGenerationNotifier; a predetermined threshold of time has passed since the instantiation of MaxGenerationNotifier; or another programmed module of code has been executed for the currently executing application, program, method, function, or other assemblage of code. 
     Load Balancer  315  may refer to a either a hardware device that is physically separate from either of client device  105  or as firmware or software component on at least one of client device  105  or server devices  110 A and  110 B. 
     Upon an instantiation of MaxGenerationNotifier, load balancer  315  may redistribute processing of at least portions of a currently executing application, program, method, function, or other assemblage of code to avoid a time-out during GC. For example, upon receiving memory management data  310  which includes an instantiation of MaxGenerationNotifier referring to an impending GC on process  305 A, load balancer  315  may receive one or more requests for execution of portions of the same or another currently executing application, program, method, function, or other assemblage of code, and re-direct such execution to at least one of process  305 B and process  305 C. 
     Upon an instantiation of MaxGenerationCompleteNotifier, load balancer  315  may cease redistribution of processing of portions of a currently executing application, program, method, function, or other assemblage of code to process  305 B and process  305 C. Thus, load balancer  315  may have the option of having the balance of the currently executing application, program, method, function, or other assemblage of code executed on process  305 A. 
     At least one alternative implementation of data flow  300  does not include load balancer  315 . That is such alternative implementations achieves load balancing by having processes  305 A,  305 B, and  305 C 
       FIG. 4  shows example processing flow  400  corresponding to at least one example implementation of load balancing  120  (see  FIG. 1 ). Example processing flow  400  is described below with references to features from  FIGS. 1-3 , although such implementations are provided only as examples and are not intended to be construed in any limiting manner. 
     Block  405  may refer to execution of at least a portion of an application, program, method, function, or other assemblage of code being implemented as part of process  305 A, process  305 B, or process  305 C, either singularly or collaboratively in various combinations. Although load balancing  120  is not so limited, block  405  may refer to execution in a managed execution environment (i.e., runtime execution environment  200 ). 
     Block  410  may refer to memory manager  210  or administrator  215 , either singularly or in combination, determining that a threshold amount of heap has already been allocated during execution of a currently executing application, program, method, function, or other assemblage of code, and therefore a GC may be impending. Alternatively, block  410  may refer to memory manager  210  or administrator  215 , either singularly or in combination, inspecting at least a portion of the programmed code to determine that a sweep or scan of a memory heap of the processing device upon which runtime execution environment  200  is running may be impending. 
     Decision  415  may refer to memory manager  210  or administrator  215 , either singularly or in combination, assessing the magnitude of the anticipated GC implementation relative to a predetermined threshold value. The assessment may be made to determine whether the physical magnitude of the memory heap exceeds a predetermined threshold value (e.g., 2 GB or more) that would likely time-out execution of a currently executing application, program, method, function, or other assemblage of code. According to one alternative, the assessment may be made of the time anticipated for the GC to complete against a predetermined time threshold for avoiding a time-out. According to yet another example, the assessment may even include inspecting at least a portion of the programmed code to determine whether the impending GC is deliberately intended to serve as a catalyst for at least portions of the executing application, program, method, function, or other assemblage of code to be redistributed. 
     Block  420 A, subsequent to negative decision  415 , may refer to memory manager  210  implementing GC for the executing application, program, method, function, or other assemblage of code on the host one of processes  305 A,  305 B, or  305 C. Processing flow may then return to block  405  to continue execution of the currently executed application, program, method, function, or other assemblage of code. 
     Block  425 , subsequent to positive decision  415 , may refer to memory manager  210  or administrator  215 , either singularly or in combination, notifying load balancer  315  that the anticipated GC meets or exceeds the predetermined threshold values. That is, upon determining that a logical or physical parameter of the anticipated CC is expected to exceed a threshold value, management module  210  or administrator  215 , either singularly or in combination, may notify load balancer that the impending GC is likely to cause a time-out for a currently executed application, program, method, function, or other assemblage of code. Even more particularly, management module  210  or administrator  215 , either singularly or in combination, may instantiate an API (e.g., MaxGenerationNotifier), which provides a notification of anticipated state. 
     In at least one alternative implementation of block  425 , memory manager  210  or administrator  215 , either singularly or in combination, may provide a notification in another form. For example, the notification may be an event that includes calling the application, program, method, function, or other assemblage of code that is executed as part of process  305 A, process  305 B, or process  305 C previously registered with memory manager  210  or administrator  215 . 
     An example of such a notification event may include each of processes  305 A,  305 B, and  305 C in  FIG. 3  subscribing to the one or more memory management events (e.g., MaxGenerationNotifier) via memory manager  210  or administrator  215  either singularly or combined. For example, process  305 A may implement two functions that may be called when MaxGenNotifier is issued by memory manager  210  or administrator  215  either singularly or in combination. Non-limiting examples of such calls are as follows;
     (1) GC.MaxGenerationNotifier+=new MaxGenerationNotificationHandler(On_MaxGeneration_Notify1);   (2) GC.MaxGenerationNotifier+=new MaxGenerationNotificationHandler(On_MaxGeneration_Notify2);
 
whereby MaxGeneration_Notify1 and MaxGeneration_Notify2 are the aforementioned functions. Further, functions MaxGeneration_Notify1 and MaxGeneration_Notify2 may notify load balancer  315  of the subscribed events. Therefore, upon occurrence of a subscribed event, load balancer  315  may take requested load balancing action.
   

     Block  430  may refer to load balancer  315  redistributing at least portions of the currently executed application, program, method, function, or other assemblage of code among processes  305 A,  305 B, and  305 C. Thus, for example, if the notification at block  425  is received in anticipation of a GC implementation in accordance with host process  305 A, block  430  may refer to load balancer  315  receiving a request for execution of at least a portion of the same or another currently executed application, program, method, function, or other assemblage of code, and re-direct the requested execution to at least one of processes  305 B and  305 C. That is, block  430  may refer to load balancer  315  redistributing at least portions of the currently executed application, program, method, function, or other assemblage of code from currently running process  305 A to a concurrently running one of processes  305 B and  305 C. 
     Block  420 B may refer to memory manager  210  implementing GC for the executing application, program, method, function, or other assemblage of code on the host one of processes  305 A,  305 B, or  305 C, while at least portions of the respective application, program, method, function, or other assemblage of code are being executed on others of concurrently running processes  305 A,  305 B, and  305 C. Thus, for example, if the notification at block  425  is received in anticipation of a GC implementation in accordance with host process  305 A, block  430  may refer to load balancer  315  redistributing at least portions of the current y executed application, program, method, function, or other assemblage of code to at least one of processes  305 B and  305 C, and block  420 A may refer to memory manager  210  implementing GC on host process  305 A. 
     Block  435  may refer to memory manager  210  or administrator  215 , either singularly or in combination, notifying load balancer  315  that the GC has been completed. The notification may or may not include instructions to cease a current load balancing implementation. Even more particularly, management module  210  or administrator  215 , either singularly or in combination, may instantiate an API (e.g., MaxGenerationNotifier), which provides a notification of current state. Processing flow may then return to block  405  to continue execution of a currently executed application, program, method, function, or other assemblage of code. 
     Similar to processing at block  425 , a notification event may include each of processes  305 A,  305 B, and  305 C in  FIG. 3  subscribing to the one or more memory management events (e.g., MaxGenerationCompleteNotifier) via memory manager  210  or administrator  215  either singularly or combined. Thus, for example, process  305 A may implement two functions that may be called when MaxGenCompleteNotifier is issued by memory manager  210  or administrator  215  either singularly or in combination. Non-limiting examples of such calls are as follows:
     (1) GC.MaxGenerationCompleteNotifier+=new MaxGenerationCompleteNotificationHandler(On_MaxGenerationComplete_Notify1);   (2) GC.MaxGenerationCompleteNotifier+=new MaxGenerationCompleteNotificationHandler(On_MaxGenerationComplete_Notify2);
 
whereby MaxGenerationComplete_Notify1 and MaxGenerationComplete_Notify2 are the aforementioned functions. Further, functions MaxGenerationComplete_Notify1 and MaxGenerationComplete_Notify2 may notify load balancer  315  of the subscribed events. Therefore, upon occurrence of a subscribed event, load balancer  315  may at least temporarily cease load balancing, as requested.
   

     The description above, pertaining to  FIGS. 1-4 , load balancing with regard to one or more applications executing on a runtime execution environment may be implemented in accordance with data associated with memory management data. However, the example limitations described herein are not limited to just load balancing based on memory management data. Rather, a notification (i.e., notification) may be instantiated to implement load balancing based on myriad logical and physical criteria. 
     The computer environment for any of the examples and implementations described above may include a computing device having, for example, one or more processors or processing units, a system memory, and a system bus to couple various system components. 
     The computing device may include a variety of computer readable media, including both volatile and non-volatile media, removable and non-removable media. The system memory may include computer readable media in the form of volatile memory, such as random access memory (RAM); and/or non-volatile memory, such as read only memory (ROM) or flash RAM. It is appreciated that other types of computer readable media which can store data that is accessible by a computer, such as magnetic cassettes or other magnetic storage devices, flash memory cards. CD-ROM, digital versatile disks (DVD) or other optical storage, random access memories (RAM), read only memories (ROM), electric erasable programmable read-only memory (EEPROM), and the like, can also be utilized to implement the example computing system and environment. 
     Reference has been made throughout this specification to “an example,” “alternative examples,” “at least one example,” “an implementation,” or “an example implementation” meaning that a particular described feature, structure, or characteristic is included in at least one implementation of the present invention. Thus, usage of such phrases may refer to more than just one implementation. Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more implementations. 
     One skilled in the relevant art may recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, resources, materials, etc. In other instances, well known structures, resources, or operations have not been shown or described in detail merely to avoid obscuring aspects of the invention. 
     While example implementations and applications of the present invention have been illustrated and described, it is to be understood that the invention is not limited to the precise configuration and resources described above. Various modifications, changes, and variations apparent to those skilled in the art may be made in the arrangement, operation, and details of the methods and systems of the present invention disclosed herein without departing from the scope of the invention, as both described above and claimed below.