Server cloud service resource balancing method and system

Abstract

The invention discloses a server cloud service resource balancing method and system. The method comprises the following steps: presetting and storing a constraint relationship between performance configuration purchased by a user and PDP configuration; sorting all current users of the server according to gears configured by performance; counting the average occupancy of server performance configuration in real time; judging whether the average occupancy exceeds a set threshold value or not, if yes, executing the next step, and if not, ending; according to the performance configuration gear of the user, starting from a low-configuration user, reducing PDP configuration of one level for the current user until the average occupancy is lower than the set threshold value; and configuring all CPUs of the user according to the reduced PDP configuration. Compared with the prior art, the cloud service fairness is ensured, the high-configuration user experience is protected, the overall utilization rate of the server is reduced, and the service life of the server is prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cloud computing, and particularly relates to a server cloud service resource balancing method and system. BACKGROUND

[0002] In the field of cloud computing, users can purchase different servers in different ways. For an arm server, assuming that there are 160 cores, the server can be rented and sold to users in core units, such as 2G per core, 8G per dual core, 16G per quad core, and the like. The server allocates these resources to users.

[0003] As the number of purchases increases, a server can have up to hundreds of users, some of whom buy to build websites, some of whom buy to store data, some of whom buy to play games, and some of whom buy to do AI data processing. Generally, a fixed physical CPU is allocated to users, but SLC and DDR on the SOC are common resources for all CPUs. Some users who consume more resources will inevitably affect the use of other users, because SLC and DDR are common resources and must be accessed by all users. Therefore, when the number of users is too large, the server CPU and memory resources need to be limited according to the user's demand and the amount of resources.

[0004] However, for some users who purchase high CPU core numbers and high memory resources, the performance of cloud services will be unnecessarily limited due to the current low resource demand, resulting in a poor experience, and it is difficult to balance fairness and user experience. Moreover, in order to effectively utilize server resources and provide server utilization, the existing technology makes the server work in a high-power consumption environment for a long time, greatly affecting the service life of the server.

[0005] Therefore, there is an urgent need for a service resource balancing method and system that can solve the above problems. SUMMARY

[0006] The present application aims to provide a server cloud service resource balancing method and system that reduces the PDP configuration of low-configuration users when the occupancy rate of server resources is too high, ensures the fairness of cloud services, protects the experience of high-configuration users, reduces the overall utilization rate of the server, and improves the service life of the server.

[0007] In order to achieve the above object, the application provides a server cloud service resource balancing method, comprising: setting and storing a constraint relationship between a performance configuration and a PDP configuration purchased by a user in advance; dividing the performance configuration into multiple gears according to the size of the performance configuration purchased by the user, and corresponding a PDP configuration of one level to each gear of the performance configuration; step 1, sorting all users of the server according to the gears of the performance configuration; step 2, real-time statistics of the average occupancy rate of the performance configuration in the server; step 3, judging whether the average occupancy rate exceeds a set threshold, if yes, proceeding to the next step, if not, ending; step 4, according to the gears of the performance configuration of the user, starting from the user with low configuration, reducing the PDP configuration of the current user by one level until the average occupancy rate is lower than the set threshold; step 5, configuring all CPUs of the user according to the reduced PDP configuration and returning to step 2.

[0008] Preferably, step 4 comprises: selecting a user with low configuration according to the gear sorting of the performance configuration, judging whether the gear of the performance configuration of the user and the PDP configuration conform to the constraint relationship, if not, reducing the PDP configuration of the current user by one level and executing the next step; if yes, selecting a user with performance configuration of a higher gear of the performance configuration and returning to step 4.

[0009] Preferably, the PDP configuration comprises a first PDP configuration related to the performance of CPU and / or a second PDP configuration related to the performance of memory, and the performance configuration comprises CPU configuration and / or memory configuration; the constraint relationship between the performance configuration purchased by the user and the PDP configuration comprises a constraint relationship between the number of CPU cores purchased by the user and the first PDP configuration and / or a constraint relationship between the size of memory purchased by the user and the second PDP configuration; the average occupancy rate comprises a first average occupancy rate of CPU in the server and / or a second average occupancy rate of memory in the server.

[0010] Specifically, setting the constraint relationship between the performance configuration purchased by the user and the PDP configuration comprises the steps of: dividing the CPU configuration into multiple gears according to the number of CPU cores purchased by the user, corresponding a first PDP configuration of one level to each gear of the CPU configuration, and the higher the CPU configuration, the better the performance of the first PDP configuration; and / or dividing the memory configuration into multiple gears according to the size of memory purchased by the user, corresponding a second PDP configuration of one level to each gear of the memory configuration, and the higher the memory configuration, the better the performance of the second PDP configuration.

[0011] Preferably, the PDP configuration includes a first PDP configuration related to CPU performance and a second PDP configuration related to memory performance, and the performance configuration includes CPU configuration and memory configuration; when setting the constraint relationship between the performance configuration purchased by the user and the PDP configuration: taking the CPU configuration as a first coordinate and establishing a first coordinate axis x, taking the memory configuration as a second coordinate and establishing a second coordinate axis y, establishing a performance constraint coordinate system, and setting the PDP configuration corresponding to the performance configuration (x, y) of each gear of the user.

[0012] Preferably, no performance limitation is performed in the PDP configuration corresponding to the highest gear performance configuration, and the corresponding PDP configuration is increased by at least one performance constraint for each gear of the performance configuration.

[0013] Specifically, the PDP configuration includes a first PDP configuration related to CPU performance and / or a second PDP configuration related to memory performance, and the performance configuration includes CPU configuration and / or memory configuration; no CPU performance limitation is performed in the first PDP configuration corresponding to the highest gear CPU performance, and the corresponding first PDP configuration is increased by at least one performance constraint for each gear of the CPU performance; and / or, no memory access bandwidth limitation is performed in the second PDP configuration corresponding to the highest gear memory performance, and the corresponding second PDP configuration is increased by at least one performance constraint for each gear of the memory performance.

[0014] More specifically, the first PDP configuration is implemented based on a micro-architecture level, and the performance constraints of the first PDP configuration include disabling a transmit queue, reducing a transmit queue virtual large, and disabling a speculative execution; and / or, the second PDP configuration is implemented based on a micro-architecture level, and the performance constraints of the second PDP configuration include reducing instruction prefetching and reducing instruction out-of-order execution.

[0015] Preferably, a preset initial PDP configuration is allocated to the user each time the user logs in to the arm server cloud; a preset initial PDP configuration is allocated to the user each time the user logs in to the arm server cloud; when the user initially logs in to the arm server cloud, the highest PDP configuration is allocated to the user as the initial PDP configuration, and after all CPUs of the current user are configured according to the new PDP configuration, the new PDP configuration is recorded as the initial PDP configuration for the next login. In this way, the user can enjoy good experience brought by the high PDP configuration in the normal state, and after a large amount of use, in order to balance fairness, the user is limited from using a large amount of public resources, and the experience of the user with high configuration is prevented from being affected.

[0016] Preferably, when the average occupancy rate is lower than the low limit threshold, the PDP configuration of the current user is increased by one level from the high configuration user until the average occupancy rate is higher than the low limit threshold, and the set threshold is higher than the low limit threshold.

[0017] The application also provides a server cloud service resource balancing system, comprising a processor, a memory, and one or more operation instructions stored in the memory and executed by the processor to perform the server cloud service resource balancing method as described above.

[0018] Compared with the prior art, the application divides the performance configuration into multiple gears, and then matches the corresponding PDP configuration for different performance configurations, so that when the average occupancy rate of the performance configuration in the server does not exceed the set threshold, the user has a good performance experience, and when the performance configuration in the server exceeds the set threshold, the PDP configuration level of the user with low gears is reduced to limit the resource usage rate of the low configuration user, so that when the occupancy rate of the server resource is too high, the PDP configuration of the low configuration user is reduced, the fairness of the cloud service is ensured, the experience of the high configuration user is protected, the overall utilization rate of the server is reduced, and the service life of the server is improved. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a structure diagram of an arm server cloud SOC system.

[0020] Figure 2 is a flowchart of the server cloud service resource balancing method in embodiment 1 of the application.

[0021] Figure 3 is a flowchart of the server cloud service resource balancing method in embodiment 2 of the application.

[0022] Figure 4 is a structure block diagram of the server cloud service resource balancing system of the application. DETAILED DESCRIPTION

[0023] To illustrate the technical content, structural features, achieved purposes and effects of the application, the following will be described in detail in combination with the embodiments and the accompanying drawings.

[0024] Reference Figure 1 The arm server cloud SOC system comprises a CPU processing module 101, a DDR storage module 102, an SCP control module 103, and a system bus 104, wherein the system bus 104 communicates between the CPU processing module 101, the DDR storage module 102, and the SCP control module 103.

[0025] For example, the CPU processing module 101 includes multiple CPUs, and the DDR storage module 102 provides 500G of memory.

[0026] Embodiment 1 Reference Figure 2 The application discloses a server cloud service resource balancing method, including steps S1 to S5.

[0027] Before step S1, a constraint relationship between a performance configuration and a PDP configuration purchased by a user is set and stored in advance: the performance configuration is divided into multiple gears according to the size of the performance configuration purchased by the user, and the performance configuration of each gear corresponds to a level of PDP configuration.

[0028] PDP, Performance Defined Power, performance defined power. This feature limits CPU performance and the memory access bandwidth of the CPU from the micro-architecture perspective.

[0029] In this embodiment, the performance configuration includes a CPU configuration, and the PDP configuration includes a first PDP configuration related to CPU performance. The constraint relationship between the performance configuration and the PDP configuration of the user includes the constraint relationship between the number of CPU cores purchased by the user and the first PDP configuration.

[0030] The constraint relationship between the performance configuration and the PDP configuration purchased by the user includes the following steps: dividing the CPU configuration into multiple gears according to the number of CPU cores purchased by the user, and the CPU configuration of each gear corresponds to a level of first PDP configuration, and the higher the CPU configuration, the better the performance of the first PDP configuration.

[0031] For example, the CPU configuration is divided into a first gear corresponding to 2 cores, a second gear corresponding to 4 cores, a third gear corresponding to 8 cores, and a fourth gear corresponding to 16 cores. This embodiment has four gears. In this embodiment, the fourth gear is the highest gear of the CPU configuration.

[0032] Preferably, the PDP configuration corresponding to the highest gear performance configuration does not limit performance, and the PDP configuration corresponding to each lower gear performance configuration increases at least one performance constraint.

[0033] Preferably, the first PDP configuration corresponding to the highest gear CPU performance does not limit CPU performance, and the first PDP configuration corresponding to each lower gear CPU performance increases at least one performance constraint.

[0034] Specifically, the first PDP configuration is implemented based on the micro-architecture level and contains constraints on performance points such as disabling the transmit queue, reducing the transmit queue virtual large, and disabling the speculative execution.

[0035] S1, sort all users of the server according to the performance configuration level.

[0036] Specifically, sort the users logged in the servers of the same group according to the performance configuration level.

[0037] Specifically, sort the users logged in the servers of the same group according to the performance configuration level.

[0038] Specifically, sort the users logged in the servers of the same group according to the performance configuration level.

[0039] S2, real-time statistics of the average occupancy rate of the performance configuration of the server.

[0040] Specifically, real-time statistics of the first average occupancy rate of the CPU of the current server.

[0041] Specifically, real-time statistics of the first average occupancy rate of the CPU of the current server.

[0042] S3, determine whether the average occupancy rate exceeds the set threshold.

[0043] Specifically, determine whether the first average occupancy rate exceeds the first set threshold.

[0044] If yes, execute step S4, if not, end.

[0045] S4, according to the performance configuration level of the user, start from the low configuration user, reduce the PDP configuration of the current user by one level until the average occupancy rate is lower than the set threshold.

[0046] Step S4 includes steps S41 to S43.

[0047] S41, select the low configuration user according to the performance configuration (CPU performance) level.

[0048] S42, determine whether the performance configuration (CPU performance) level of the user and the PDP configuration (first PDP configuration) meet the constraint relationship.

[0049] The performance configuration (CPU performance) of the user is obtained according to the constraint relationship, and the PDP configuration (first PDP configuration) corresponding to the performance configuration (CPU performance) is obtained. The PDP configuration (first PDP configuration) corresponding to the performance configuration (CPU performance) is the PDP configuration (first PDP configuration) corresponding to the purchased performance configuration (CPU performance). It is determined whether the current PDP configuration (first PDP configuration) of the user is the same as the corresponding PDP configuration (first PDP configuration). If yes, the performance configuration (CPU performance) of the user matches the PDP configuration (first PDP configuration). If no, the performance configuration (CPU performance) of the user does not match the PDP configuration (first PDP configuration).

[0050] If no, the PDP configuration (first PDP configuration) of the current user is reduced by one level, and the next step is performed. Specifically, the first PDP configuration is reduced by one level based on the current first PDP configuration.

[0051] If yes, the user with a higher level of performance configuration (CPU performance) is selected, and the step S41 is returned.

[0052] S5, all CPUs of the user are configured according to the reduced PDP configuration, and the step S2 is returned.

[0053] Specifically, all CPUs of the user are configured according to the reduced first PDP configuration in the CPU dimension, and the step S2 is returned.

[0054] Specifically, for example, the user purchases a 2-core CPU configuration, and the corresponding PDP configuration is a first-level CPU configuration. If the current CPU configuration is a third-level CPU configuration, the CPU configuration is directly reduced to a second-level CPU configuration.

[0055] Preferably, the user is assigned a preset initial PDP configuration each time the user logs in to the arm server cloud. When the user initially logs in to the arm server cloud, the user is assigned the highest PDP configuration as the initial PDP configuration. After all CPUs of the current user are configured according to the new PDP configuration, the new PDP configuration is recorded as the initial PDP configuration for the next login.

[0056] Preferably, when it is determined in real time whether the average occupancy rate is lower than a lower limit threshold, if yes, the PDP configuration of the current user is increased by one level from a high-configuration user until the average occupancy rate is higher than the lower limit threshold. The set threshold is higher than the lower limit threshold.

[0057] Specifically, at S a, the average occupancy rate is determined in real time whether it is lower than the lower limit threshold. At S b, if yes, the high configuration user is selected and step S c is executed. At S c, the selected user is determined whether the gear of its performance configuration matches its PDP configuration, if yes, the user whose performance configuration is one gear lower is selected, and then returns to step S c, if no, one level of PDP configuration is increased.

[0058] Embodiment 2 Reference Figure 3 The application discloses a server cloud service resource balancing method, comprising steps S1 to S5.

[0059] Different from embodiment 1, in embodiment 2, the PDP configuration comprises a second PDP configuration related to memory performance. The performance configuration purchased by the user comprises a memory configuration. The constraint relationship between the performance configuration of the user and the PDP configuration comprises a constraint relationship between the memory size purchased by the user and the second PDP configuration.

[0060] Setting the constraint relationship between the performance configuration purchased by the user and the PDP configuration comprises the following steps: dividing the memory configuration into multiple gears according to the memory size purchased by the user, the memory configuration of each gear corresponding to one level of the second PDP configuration, and the higher the memory configuration, the better the performance of the second PDP configuration.

[0061] For example, the memory configuration (memory configuration) is divided into a first gear corresponding to 4G, a second gear corresponding to 8G, a third gear corresponding to 16G, and a fourth gear corresponding to 32G. In this embodiment, the fourth gear is the highest gear of the memory configuration.

[0062] S1, all users of the server are sorted according to the gears of the performance configuration.

[0063] Specifically, the current users of the server are sorted according to the gears of the CPU performance.

[0064] Among them, the users are divided into multiple groups according to the gears of the CPU performance purchased by the users, and then the users in multiple groups are sorted from low to high according to the gears.

[0065] S2, the average occupancy rate of the performance configuration of the server is calculated in real time.

[0066] Among them, the average occupancy rate of the resources corresponding to the performance configuration of the server in the same group is calculated.

[0067] Specifically, the second average occupancy rate of the memory of the current server is calculated in real time.

[0068] S3, whether the average occupancy rate exceeds the set threshold is determined.

[0069] Specifically, it determines whether the second average occupancy rate exceeds the second set threshold.

[0070] If yes, proceed to step S4; otherwise, end.

[0071] S4. Based on the user's performance configuration level, starting with low-configuration users, reduce the PDP configuration of the current user by one level until the average occupancy rate is lower than the set threshold.

[0072] Step S4 includes steps S41 to S43.

[0073] S41 selects low-configuration users based on performance configuration (memory configuration) tiers.

[0074] S42, determine whether the user's performance configuration (memory configuration) level and the PDP configuration (second PDP configuration) conform to the constraint relationship.

[0075] Specifically, based on the constraint relationship, the PDP configuration (second PDP configuration) corresponding to the user's performance configuration (memory configuration) is obtained. The corresponding PDP configuration (second PDP configuration) is the PDP configuration (second PDP configuration) corresponding to the purchased performance configuration (memory configuration). It is determined whether the user's current PDP configuration (second PDP configuration) is the same as the corresponding PDP configuration (second PDP configuration). If so, the user's performance configuration (memory configuration) level matches the PDP configuration (second PDP configuration); otherwise, they do not match.

[0076] S43, otherwise, downgrade the current user's PDP configuration by one level (first PDP configuration) and proceed to the next step. Specifically, downgrade the first PDP configuration by one level based on the current first PDP configuration.

[0077] If so, select the user with the higher performance configuration (CPU performance) and return to step S41.

[0078] S5, Configure all CPUs of the user according to the reduced PDP configuration and return to step S2.

[0079] Specifically, based on the reduced first PDP configuration, CPU-level configuration is performed on all CPUs of the user and the process returns to step S2.

[0080] Specifically, for example, if a user purchases a 2-core CPU configuration, the corresponding PDP configuration is the first-tier CPU configuration. If the current CPU configuration is the third-tier, it will be directly downgraded to the second-tier CPU configuration.

[0081] Example 3: Based on Embodiments 1 and 2, in Embodiment 3, setting the constraint relationship between the performance configuration purchased by the user and the PDP configuration includes the following steps: dividing the CPU configuration into multiple tiers according to the number of CPU cores purchased by the user, with each tier of CPU configuration corresponding to a first-level PDP configuration, and the higher the CPU configuration, the better the performance of the first-level PDP configuration; dividing the memory configuration into multiple tiers according to the size of the memory purchased by the user, with each tier of memory configuration corresponding to a second-level PDP configuration, and the higher the memory configuration, the better the performance of the second-level PDP configuration.

[0082] In Example 3, the PDP configuration includes a first PDP configuration related to CPU performance and a second PDP configuration related to memory performance. The performance configuration purchased by the user includes CPU configuration and memory configuration. The constraints between the user's performance configuration and the PDP configuration include the constraint between the number of CPU cores purchased by the user and the first PDP configuration, and the constraint between the amount of memory purchased by the user and the second PDP configuration.

[0083] For example, CPU configurations (number of processing cores) are divided into four tiers: 2 cores (first tier), 4 cores (second tier), 8 cores (third tier), and 16 cores (fourth tier). In this embodiment, the fourth tier is the highest CPU configuration. Similarly, memory configurations (purchased memory size) are divided into four tiers: 4GB (first tier), 8GB (second tier), 16GB (third tier), and 32GB (fourth tier). In this embodiment, the fourth tier is the highest memory configuration.

[0084] refer to Figure 4 The present invention also discloses a server cloud service resource balancing system, which includes a processor 21, a memory 22, and one or more operation instructions 23. The one or more operation instructions 23 are stored in the memory 22 and are executed by the processor 21 to perform the server cloud service resource balancing method as described above.

[0085] DSU: DynamIQ Shared Unit, a new type of multi-core management system unit. SOC: System on a Chip, integrating multiple cores and on-chip peripherals. SCP: System Control Processor, a microprocessor used for SOC system control and power management. Cache: High-speed cache, accessing memory much faster than DDR. LLC: Last-Level Cache, the last level of cache, the cache level closest to the DDR controller. SLC: System-Level Cache, sometimes called L3 Cache, the same concept as LLC here. RDT: Resource Director Technology, providing LLC and memory bandwidth allocation and monitoring capabilities. MPAM: Memory System Resource Partitioning and Monitoring, a scheme for managing memory resources on an SOC. PDP: Performance-Defined Power, a method for limiting CPU performance and memory bandwidth access at the microarchitecture level.

[0086] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, any equivalent variations made in accordance with the scope of the present invention are still within the scope of the present invention.

Claims

1. A method for balancing server cloud business resources, characterized in that: include: The constraints between the performance configuration purchased by the user and the PDP configuration are pre-set and stored: the performance configuration is divided into multiple levels according to the size of the performance configuration purchased by the user, and each level of performance configuration corresponds to a level of PDP configuration. Step 1: Sort all current users on the server according to their performance configuration level; Step 2: Real-time statistics on the average utilization of server performance configurations; Step 3: Determine whether the average occupancy rate exceeds the set threshold. If yes, proceed to the next step; otherwise, end. Step 4: Based on the user's performance configuration level, starting with low-configuration users, reduce the PDP configuration of the current user by one level until the average occupancy rate is lower than the set threshold. Step 5: Configure all CPUs of the user according to the reduced PDP configuration and return to step 2.

2. The server cloud service resource balancing method as described in claim 1, characterized in that: Step 4 includes: selecting low-configuration users based on performance configuration tiers, determining whether the user's performance configuration tier and PDP configuration meet the constraint relationship; if not, reducing the PDP configuration of the current user by one level and proceeding to the next step; if yes, selecting users with a higher performance configuration tier and returning to step 4.

3. The server cloud service resource balancing method as described in claim 1, characterized in that: The PDP configuration includes a first PDP configuration related to CPU performance and / or a second PDP configuration related to memory performance. The performance configuration includes CPU configuration and / or memory configuration. The constraint relationship between the performance configuration purchased by the user and the PDP configuration includes the constraint relationship between the number of CPU cores purchased by the user and the first PDP configuration and / or the constraint relationship between the size of memory purchased by the user and the second PDP configuration. The average utilization rate includes a first average utilization rate of CPU in the server and / or a second average utilization rate of memory in the server.

4. The server cloud service resource balancing method as described in claim 3, characterized in that: Setting the constraint relationship between the performance configuration purchased by the user and the PDP configuration includes the following steps: dividing the CPU configuration into multiple tiers according to the number of CPU cores purchased by the user, with each tier of CPU configuration corresponding to a first-level PDP configuration, and the higher the CPU configuration, the better the performance of the first PDP configuration; and / or dividing the memory configuration into multiple tiers according to the memory size purchased by the user, with each tier of memory configuration corresponding to a second-level PDP configuration, and the higher the memory configuration, the better the performance of the second PDP configuration.

5. The server cloud service resource balancing method as described in claim 1, characterized in that: No performance limit is imposed in the PDP configuration corresponding to the highest performance level. For each performance level that is reduced, at least one performance constraint is added to the corresponding PDP configuration.

6. The server cloud service resource balancing method as described in claim 5, characterized in that: The PDP configuration includes a first PDP configuration related to CPU performance and / or a second PDP configuration related to memory performance, wherein the performance configuration includes CPU configuration and / or memory configuration. The first PDP configuration corresponding to the highest CPU performance level does not impose CPU performance limitations. For each CPU performance level that decreases by one tier, the corresponding first PDP configuration adds at least one performance constraint. And / or, the second PDP configuration corresponding to the highest memory performance level does not impose memory access bandwidth limitations. For each memory performance level that decreases by one tier, the corresponding second PDP configuration adds at least one performance constraint.

7. The server cloud service resource balancing method as described in claim 6, characterized in that: The first PDP configuration is implemented at the microarchitecture level, and its performance constraints include disabling the send queue, reducing the virtual size of the send queue, and disabling speculative execution; and / or, The second PDP configuration is implemented at the microarchitecture level, and the performance constraints of the second PDP configuration include reducing instruction prefetching and reducing out-of-order instruction execution.

8. The server cloud service resource balancing method as described in claim 1, characterized in that: Each time a user logs into the ARM server cloud, a preset initial PDP configuration is assigned to the user. When a user first logs into the ARM server cloud, the highest PDP configuration is assigned to the user as the initial PDP configuration. After all CPUs currently allocated to the user are configured according to the new PDP configuration, the new PDP configuration is recorded as the initial PDP configuration for the next login.

9. The server cloud service resource balancing method as described in claim 1, characterized in that: When it is determined in real time whether the average occupancy rate is lower than the lower threshold, if so, starting from the high-configuration user, the PDP configuration of the current user is increased by one level until the average occupancy rate is higher than the lower threshold, and the set threshold is greater than the lower threshold.

10. A server cloud service resource balancing system, characterized in that: It includes a processor, a memory, and one or more operation instructions, wherein the one or more operation instructions are stored in the memory and executed by the processor as described in any one of claims 1-9.

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