DETECTING THE RISK OF DATA LOSS IN 5G-ENABLED UNITS

Abstract

A computer-implemented method (200) for managing a data processing unit (102), wherein the method comprises: Accessing (202) replicable data from the data processing unit (102); Detecting (206) risks of the data processing unit (102) based on a GPS location tracker in the data processing unit (102) to determine the altitude, proximity to a cliff or waterfall, speed of the data processing unit (102) and temperature of the data processing unit (102); in response to a detected risk reaching or exceeding a predetermined threshold, initiating (208) a data replication on the data processing unit (102); and Establish (304) channels using radio waves to enable simultaneous transfer of the replicated data.

Description

AREA OF INVENTION

[0001] The present invention relates generally to the field of data protection and in particular to the detection of a risk on 5G units in order to prevent data loss by preserving data via data replication and remotely arranged data storage. BACKGROUND

[0002] Data storage is the recording of information on a storage medium. This recording can be accomplished using virtually any form of energy, and electronic data storage requires electrical energy to store and retrieve the data. Electronic data can be stored in a much smaller space than physical data. Furthermore, data replication is the process of storing data in more than one location or node. It is simply copying data from a database from one server to another, so that all users can share the same data without inconsistencies.

[0003] Cloud storage is a model of computer data storage in which digital data is stored in logic pools. The physical storage spans multiple servers, and cloud storage providers are responsible for keeping the data available and accessible.

[0004] 5G is a fifth-generation mobile network technology in which the service area covered by providers is divided into small geographical areas called cells. All wireless 5G devices in a cell exchange data via radio waves with a local antenna array and an energy-saving automatic transmit / receive unit (ACU) within the cell. This data is transmitted over frequency channels allocated by the ACU from a pool of frequencies reused by other cells.

[0005] In this context, several published documents already exist. Document US 10007577 B2 describes the possibilities for performing a distributed data backup. The distributed data backup is monitored by a controller that detects a trigger event and identifies one or more devices capable of receiving the backup. Furthermore, document US 10085140 B2 describes a method that prevents data loss in a mobile communication device. This involves measuring the temperature from a sensor and determining whether a critical temperature range has been reached. If a critical temperature range is reached, a data backup is automatically performed.

[0006] Despite these advances, problems can still arise in detecting risks with 5G-enabled mobile devices. Therefore, there is a need for technological advancements to address the aforementioned issue. SUMMARY

[0007] This task is accomplished by the subject matter of the independent patent claims. Further details are provided in the dependent patent claims.

[0008] From another perspective, the present invention provides a computer-implemented method comprising: accessing replicable data from a data processing unit; detecting risks to the data processing unit, at least partially, based on the environment, location, speed, and state of the data processing unit; in response to a detected risk reaching or exceeding a predetermined threshold, initiating data replication on the data processing unit; and establishing radio wave-utilizing channels to enable simultaneous transfer of the replicated data.

[0009] From another perspective, the present invention provides a computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, wherein the program instructions comprise: program instructions for accessing replicable data from a data processing unit; program instructions for detecting risks of the data processing unit, at least partially based on the environment, location, speed, and state of the data processing unit; and, in response to a detected risk reaching or exceeding a predetermined threshold, program instructions for initiating data replication on the data processing unit.and programming instructions for setting up radio wave-based channels to enable simultaneous transfer of the replicated data.

[0010] From another perspective, the present invention provides a computer system comprising: one or more computer processors; one or more computer-readable storage media; and program instructions stored on the one or more computer-readable storage media for execution by at least one of the one or more processors, wherein the program instructions comprise: program instructions for accessing replicable data from a data processing unit; program instructions for detecting risks of the data processing unit, at least partially based on the environment, location, speed, and state of the data processing unit; and, in response to a detected risk reaching or exceeding a predetermined threshold, program instructions for initiating data replication on the data processing unit.and programming instructions for setting up radio wave-based channels to enable simultaneous transfer of the replicated data.

[0011] From another perspective, the present invention provides a computer program product for managing a data processing unit, wherein the computer program product comprises a computer-readable storage medium that is readable by a processing circuit and storage instructions for execution by the processing circuit to carry out a method for performing the steps of the invention.

[0012] From another perspective, the present invention provides a computer program that is stored on a computer-readable medium and can be loaded into the internal main memory of a digital computer, and which includes software program parts for carrying out the steps of the invention when the program is executed on a computer.

[0013] Embodiments of the present invention provide a computer system, a computer program product, and a method comprising: capturing replicable data from a data processing unit; detecting risks of the data processing unit, wherein risk detection includes detecting the environment, location, velocity, and state of the unit; initiating data replication on the data processing unit as soon as it is determined that the risks reach a predetermined threshold; and storing the replicated data in a cloud storage system using a 5G network. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will now be described only as an example with reference to preferred embodiments, as illustrated in the following figures: Fig. Figure 1 is a functional block diagram representing an environment with a data processing unit that is connected to or exchanging data with another data processing unit, according to at least one embodiment of the present invention. Fig. Figure 2 is a flowchart illustrating operational steps for carrying out a data protection program while simultaneously detecting a risk according to an embodiment of the present invention. Fig. Figure 3 is a flowchart illustrating a dynamic risk detection program on a data processing unit that performs data replication in a 5G network according to at least one embodiment of the invention. Fig. 4 shows a block diagram of components of the computer system of Fig. 1 according to an embodiment of the present invention. Fig. Figure 5 represents a cloud computing environment according to an embodiment of the present invention; and Fig. Figure 6 represents abstraction model layers according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] Embodiments of the present invention recognize the need for ways to provide more efficient data protection and data storage by utilizing risk detection via 5G networks in a data processing unit environment. Embodiments of the present invention provide systems, methods, and computer program products for improving existing data protection and replication systems. Currently, conventional data protection systems initiate backup processes at predefined, regular intervals, which can be used to restore data in the event of a failure. Similarly, conventional data protection systems back up data processing units after hardware damage, and the configuration must be replicated on another device, which also introduces a data gap that can lead to data loss.There are also cloud resources that serve to protect data by replicating the data from the data processing unit in cloud storage, but are incapable of actively detecting risks. Embodiments of the present invention actively detect risks to a data processing unit that could lead to data loss, simultaneously replicate the data that may be at risk on the data processing unit, and exclusively use a 5G network as data transmission channels.Embodiments of the present invention can access a registration list of monitorable data processing units, capture data to be replicated from these units, detect mobility, surrounding environments and states of the data processing unit in order to identify associated risks to the data, initiate a specific data replication alert on the data processing unit when a certain risk threshold is detected, and securely store replicated data in the cloud.

[0016] Fig. Figure 1 is a functional block diagram of a data processing environment 100 according to an embodiment of the present invention. The data processing environment 100 comprises a data processing unit 102 and a server data processing unit 108. The data processing unit 102 and the server data processing unit 108 can be desktop computers, laptop computers, specialized computer servers, smartphones, or any other data processing units known in the art. In certain embodiments, the data processing unit 102 and the server data processing unit 108 can represent data processing units that utilize multiple computers or components to function as a single pool of seamless resources when accessed via a network 106.In general, the Data Processing Unit 102 and the Server Data Processing Unit 108 can be representative of any electronic units or combination of electronic units capable of executing machine-readable program instructions, as described in relation to . Fig. 4 is described in more detail.

[0017] The data processing unit 102 can include a program 104. The program 104 can be a standalone program on the data processing unit 102. In another embodiment, the program 104 can be stored on a server data processing unit 108. In this embodiment, the program 104 accesses a list of monitorable data processing units; accesses data to be replicated on these units; detects the mobility, surrounding environments, and states of the data processing unit in order to determine associated risks to the data using a risk detection algorithm (shown in the following figure); initiates a specific data replication alert on the data processing unit when a predefined risk threshold is reached or exceeded; and securely stores replicated data in the cloud.In this embodiment, the program 104 sends instructions to the risk detection algorithm, which has a cognitive system defined to map content using a priority control component (not shown). The priority control component prioritizes data types on the data processing unit 102 for data replication. For example, the program 104 accesses a user's smartphone; identifies data that can be replicated (i.e., texts, phone numbers, and photos); sends instructions to the risk detection algorithm to access the camera and GPS units; detects the unit's location, determines the unit's state, and detects the unit's environment to identify risks such as altitude or flowing water; and, after detecting existential risks to the data on the unit, initiates data replication over a 5G network 106.

[0018] The network 106 can be a local area network (“LAN”), a wide area network (“WAN”) such as the internet, or a combination of both; and it can include wired, wireless, or fiber optic connections. In general, the network 106 can be any combination of connections and protocols that support data transmission between the data processing unit 102 and the server data processing unit 108, in particular the program 104 according to a desired embodiment of the invention. The network 106 can utilize a 5G technology orchestration layer together with existing mobility monitoring tools that detect 5G data transmission channels and other compatible platforms and derive deeper insights from data acquired by 5G-enabled mobile devices.

[0019] The server data processing unit 108 can include the program 104 and can exchange data with the data processing unit 102 over the network 106. The server data processing unit 108 can be a single data processing unit, a laptop, a cloud-based array of data processing units, a cluster of servers, and other known data processing units. The server data processing unit 108 can be combined with a 5G network 106, creating a server data processing unit that is a cloud-based network, which can be a fixed access network.In this embodiment, the combination of the server data processing unit 108 and the 5G network 106 can utilize radio signals, access and aggregation networks, optical access networks, optical metro networks, and optical core networks to forward data from the data processing unit 102 to the server data processing unit 108 in combination with the 5G network 106. Radio signals are used to carry radio transmissions and establish WLAN connections for mobile communication units. Access and aggregation networks provide the intermediate connections between the core network and the small subnetworks at the network edge, which in this embodiment would represent the cloud-based storage capabilities of the 5G network 106. An optical network utilizes a single-mode fiber in an external network so that upstream and downstream signals share the same fiber at different wavelengths.

[0020] Fig. 2 is a flowchart 200 that illustrates operational steps for replicating data after identifying risks to a data processing unit over a 5G network.

[0021] In step 202, the program 104 accesses a data processing unit 102 from a list of monitorable data processing units. In this embodiment, the program 104 receives a login or logout permission from a user to access a specific data processing unit from a list of data processing units that are monitorable by the program 104. In this embodiment, the program 104 is already on the data processing unit 102 and remains inactive on the data processing unit 102 until the program 104 receives permission to access the data 102 stored on the data processing unit. In this embodiment, the program 104 can access a number of data processing units from a list of monitorable data processing units that are capable of replicating data.For example, the program 104 accesses a user's smartphone, which is on a list of the user's data processing units, to monitor data and replicate it if necessary.

[0022] In step 204, program 104 accesses replicable data from the specified data processing unit (e.g., data processing unit 102). In this embodiment, program 104 accesses the data found on data processing unit 102. In this embodiment, program 104 accesses replicable data that may include text messages, telephone numbers, and photos. In another embodiment, program 104 accesses data that is at risk on data processing unit 102. For example, program 104 accesses a call log and photo library of a user's specified data processing unit (e.g., data processing unit 102).

[0023] In step 206, the program 104 identifies the risks associated with the data processing unit 102. In this embodiment, the program 104 determines the location of the data processing unit 102, its mobility, its speed, and its environment, and calculates the risks associated with its location, speed, and environment. In this embodiment, the program 104 uses a risk assessment algorithm, defined as a cognitive system, which maps content using a priority control component to identify the risks associated with the specific data processing unit.In this embodiment, the program 104 sends instructions to the risk assessment algorithm to access the sensors of the specific data processing unit (DPU) in order to determine the specific location of the DPU 102. The program 104 can use the specific location as a means of determining the speed of the DPU 102 and as a means of determining the environmental conditions of the DPU 102. For example, if the program 104 locates the specific location of the DPU 102 as a location with a steep wall and determines that the DPU 102 is stationary, then the program 104 might not calculate this current environment as a risk.For example, if program 104 locates the specific position of data processing unit 102 as a location with a waterfall, which can be considered a cliff face with flowing water, and determines that data processing unit 102 is stationary, then program 104 may calculate this current environment as a risk. Furthermore, if program 104 locates the specific position of data processing unit 102 as a location with a cliff face and determines that data processing unit 102 is moving at 9.8 meters per second. 2 If the process accelerates, which is the definition of an object in free fall due to gravity, then program 104 determines this current environment as a high risk.

[0024] Furthermore, in this embodiment, the program 104 can use the 5G network 106 to exchange data with the data processing unit 102 to establish a service orchestration instance. In this embodiment, each risk identified by the program 104 is assigned a numerical value. Larger numerical values ​​indicate a higher risk, while smaller numerical values ​​indicate a lower risk. In this embodiment, the program 104 defines a high risk as a numerical value that reaches or exceeds a configurable threshold. Conversely, the program 104 defines a low risk as a numerical value that does not reach or exceed a configurable threshold. Furthermore, the program 104 can prioritize a low risk for a specific data type, which must be replicated if it does not reach the configurable threshold.In this case, where program 104 prioritizes, each data type is assigned a priority position. For example, a particular user might place more value on their photo library than on their text messages and call logs; program 104 determines a low risk for data processing unit 102; and program 104 places the photo library in a priority position ahead of the other data types on data processing unit 102. In this embodiment, the risk detection algorithm prioritizes data types using a priority control component. In this embodiment, this prioritization can be controlled by user input. In another embodiment, the prioritization can be controlled by available space, and certain data types may not be of a suitable size to be efficiently replicated.

[0025] To determine the risk levels associated with the data processing unit 102, the program 104 sends instructions to sensors in the data processing unit 102 to detect environments, conditions, and risks. For example, the program 104 uses audio and video inputs, in conjunction with GPS location tracking on a smartphone, to determine the smartphone's altitude, proximity to a cliff or waterfall, speed, and temperature. This allows the program to predict whether data replication is needed to protect the data on the smartphone after the quantified risks reach a predetermined threshold. In another embodiment, the program 104 can dynamically set the threshold in real time, causing it to adjust this numerical value depending on the risk detected at the time of detection.

[0026] In step 208, the program 104 initiates data replication of the data on the data processing unit 102. In this embodiment, the program 104 automatically initiates data replication on the data processing unit 102 to back up all replicable data as soon as the program 104 detects that the risk associated with the environmental conditions reaches a predetermined threshold. In this embodiment, the program 104 creates a logic channel using radio signals and the 5G network 106 to send instructions and data to and from the server data processing unit 108. In this embodiment 208, the program 104 automatically initiates data replication of the data on the data processing unit 102. In another embodiment, the program 104 initiates data replication after obtaining the user's consent to replicate a user's data.For example, as soon as program 104 detects that the smartphone is at serious risk of losing all data due to its environment, program 104 automatically initiates a data replication task, which is sent over the 5G network 106. During this data replication, all essential data is replicated and the data is securely sent to the server data processing unit 108. In another embodiment, program 104 can abort the data replication if the risk detection algorithm detects a reduction in the quantified risks below the predefined threshold.

[0027] In step 210, the program 104 stores the replicated data in the server data processing unit 108. In this embodiment, the program 104 can use a 5G network 106 to send and store the replicated data. In this embodiment, the program 104 creates a logic channel to enable the transfer of the replicated data to the server data processing unit 108. In this embodiment, the 5G network 106 ensures that data replication occurs simultaneously with the storage of the replicated data and ensures the protection of the replicated data. In another embodiment, the program 104 uses radio signals in conjunction with the 5G network 106 and various optical networks to send the replicated data and store it on the server data processing unit 108. In yet another embodiment, the program 104 stores the replicated data within the 5G network 106, which functions as cloud-based storage.

[0028] Fig. Figure 3 is a flowchart 300 illustrating a dynamic risk detection program on a data processing unit that performs data replication in a 5G network according to at least one embodiment of the invention.

[0029] In step 302, program 104 is activated on a data processing unit 102. In this embodiment, the program is activated on a data processing unit 102 and gains access to the data processing unit's operating system. The data processing unit 102's operating system may include a data backup manager, a peripheral data processing unit control unit, a user area data read unit, a data streaming unit, a connection interface to the unit's operating system, a GPS manager, and a priority control component.

[0030] In step 304, program 104 establishes a channel to a radio access network. In this embodiment, program 104 can establish a channel consisting of a 5G control command and a 5G input stream, connected to an eNode B. An eNode B is the hardware connected to a network of the connected unit and directly exchanges data with mobile handheld devices, such as a base transceiver station in GSM networks. In this embodiment, program 104 sends instructions to the data processing unit 102 to allow the established channels to access the data processing unit's operating system.

[0031] In step 306, the program 104 sets up a risk detection algorithm on the data processing unit 102. In this embodiment, the program 104 sets up a risk detection algorithm, which is a cognitive system containing content to map data using a priority control component to determine the importance of certain data on the data processing unit 102. The priority control component used in the risk detection algorithm determines the importance of certain data by assigning a numerical value to specific types of data. In this embodiment, upon receiving access, the program 104 sends instructions to the data processing unit 102 to allow the risk detection algorithm to enter the data processing unit 102.In this embodiment, the program 104 sends instructions to the risk detection algorithm to gain access to the internal and external sensors of the data processing unit in order to track a specific location, speed, and environmental conditions of the data processing unit 102, after the program 104 has sent instructions to the risk detection algorithm to gain access to the data processing unit. In this embodiment, the program 104 sends instructions to the risk detection algorithm to calculate the level of risks associated with the data processing unit by assigning a numerical value to each risk, and a predetermined level of risk triggers a signal.In this embodiment, the risk detection algorithm can trigger a signal to the established channels, and the program 104 uses this signal as a predefined threshold to initiate data replication by the data processing unit 102. In this embodiment, the risk detection algorithm prioritizes data types using a priority control component. In this embodiment, this prioritization can be controlled by user input. In another embodiment, the prioritization can be controlled by available space, and certain data types may not be of a suitable size for efficient replication.

[0032] In step 308, program 104 informs data processing unit 102 after generating a risk detection signal. In this embodiment, program 104 sends a message to data processing unit 102 as soon as a defined signal is established because a predetermined risk threshold is detected by the risk detection algorithm. This message initiates a data replication process on data processing unit 102 by program 104.

[0033] In step 310, program 104 initiates data replication on the data processing unit 102. In this embodiment, program 104 begins replicating the data on the data processing unit 102 as soon as the risk detection algorithm reaches a predetermined threshold and a signal is established. In this embodiment, program 104 analyzes the data on the data processing unit 102 to determine the sensitivity level of the data using the risk detection algorithm, which identifies the risks in the vicinity of the data processing unit and assigns a quantifiable value to each type of data. Program 104 begins by replicating important data types before moving on to less important data types. In this embodiment, program 104 utilizes the established 5G channels, enabling simultaneous data replication.In another embodiment, program 104 can abort the data replication task if the risk detection algorithm detects a reduction in the quantified risks below the specified threshold.

[0034] In step 312, program 104 establishes a channel between the radio access network and a 5G network 106. In this embodiment, after initiating the data replication process, program 104 establishes a channel between eNode B and a 5G network 106, and the 5G network 106 is a fixed access network, which may be a cloud-based data storage system. In this embodiment, program 104 can establish an additional channel with an optical access network. In another embodiment, program 104 can establish an additional channel with an optical metro network or an optical core network.

[0035] In step 314, the program 104 stores replicated data within the 5G network 106 via established channels. In this embodiment, the program 104 stores the replicated data within the cloud-based data storage system, which may be located within a 5G network 106, by utilizing the established channels between the eNode B and the 5G telecommunications network 106. In this embodiment, the 5G network has a 5G infrastructure management layer and a service orchestration layer that communicate with each other. In another embodiment, the program 104 can store replicated data within a server data processing unit 108 after utilizing the established channels and the 5G network 106.

[0036] Fig. Figure 4 presents a block diagram of components of computer systems within a data processing environment. 100 of Fig. Figure 1 represents an embodiment of the present invention. It should be evident that Fig. Figure 4 merely provides an illustration of one implementation and does not indicate any limitations regarding the environments in which different embodiments may be realized. Many modifications can be made to the depicted environment.

[0037] The programs described herein are designated based on the application for which they are implemented in a particular embodiment of the invention. However, it should be clear that any specific program nomenclature used herein is for convenience only, and thus the invention is not intended to be limited solely to a particular application designated and / or implied by such nomenclature.

[0038] A computer system 400 comprises a data transmission structure 402, which provides data transmission between a cache 416, a memory 406, a persistent memory 408, a data transmission unit 410, and input / output (I / O) interface(s) 412. The data transmission structure 402 can be implemented with any architecture designed for the transfer of data and / or control information between processors (such as microprocessors, data transmission and network processors, etc.), system memory, peripheral units, and any other hardware components within a system. For example, the data transmission structure 402 can be implemented with one or more buses or a crossbar switch.

[0039] Memory 406 and persistent memory 408 are computer-readable storage media. In this embodiment, memory 406 comprises random-access memory (RAM). In general, memory 406 can comprise any suitable volatile or non-volatile computer-readable storage media. The cache 416 is a fast memory that improves the performance of the computer processor(s) 404 by keeping recently retrieved data and data close to the retrieved data from memory 406.

[0040] The program 104 can be stored in persistent memory 408 and in memory 406 for execution by one or more of the respective computer processors 404 via the cache 416. In one embodiment, persistent memory 408 comprises a magnetic hard disk drive. Alternatively or additionally to a magnetic hard disk drive, persistent memory 408 can comprise a semiconductor storage disk, a semiconductor memory unit, a read-only memory (ROM), a erasable programmable read-only memory (EPROM), flash memory, or any computer-readable storage medium capable of storing program instructions or digital information.

[0041] The media used for permanent storage (408) can also be removable. For example, a removable hard drive can be used as permanent storage (408). Other examples include optical and magnetic disks, USB flash drives, and smart cards, which are inserted into a storage device slot for transferring data to another computer-readable medium that is also part of the permanent storage (408).

[0042] In these examples, the Data Transfer Unit 410 facilitates data exchange with other data processing systems or units. In these examples, the Data Transfer Unit 410 contains one or more network interface cards. The Data Transfer Unit 410 can provide data transfers using a physical and / or wireless data transfer connection. The program 104 can be downloaded into persistent memory 408 by the Data Transfer Unit 410.

[0043] The I / O interface(s) 412 enables the input and output of data to and from other units, which may be connected to a mobile unit, an consent unit, and / or the server data processing unit 110. For example, the I / O interface 412 can provide a connection to external units 418 such as a keyboard, a keypad, a touchscreen, and / or any other suitable input unit. The external units 418 may include, among others, portable computer-readable storage media such as USB flash drives, portable optical or magnetic disks, and memory cards. Software and data used to implement embodiments of the present invention, e.g., the program 104, can be stored on such portable computer-readable storage media and loaded into the persistent memory 408 via the I / O interface(s) 412.The I / O interface(s) 412 is / are also connected to the display 420.

[0044] Display 420 provides a mechanism to display data to a user, which could be, for example, a computer monitor.

[0045] The present invention may be a system, a method, and / or a computer program product. The computer program product may comprise a computer-readable storage medium (or media) containing computer-readable program instructions to induce a processor to execute aspects of the present invention.

[0046] A computer-readable storage medium can be any physical unit capable of retaining and storing instructions for use by a system to execute instructions. For example, a computer-readable storage medium can be an electronic storage unit, a magnetic storage unit, an optical storage unit, an electromagnetic storage unit, a semiconductor storage unit, or any suitable combination thereof, without limitation. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: a portable computer disk, a hard disk, random-access memory (RAM), read-only memory (ROM), and erasable programmable read-only memory (EPROM).Flash memory), static random-access memory (SRAM), portable compact storage disk-read-only memory (CD-ROM), a DVD (digital versatile disc), a memory stick, a floppy disk, a mechanically coded unit such as punched cards or raised structures in a groove on which instructions are stored, and any suitable combination thereof. A computer-readable storage medium shall not, in its use herein, be understood as volatile signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses traveling through an optical fiber cable), or electrical signals transmitted by a wire.

[0047] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to individual data processing units or, via a network such as the internet, a local area network, a wide area network, and / or a wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission lines, wireless transmission, routing computers, firewalls, switching units, gateway computers, and / or edge servers. A network adapter card or network interface in each data processing unit receives computer-readable program instructions from the network and forwards them for storage on a computer-readable storage medium within the respective data processing unit.

[0048] Computer-readable program instructions for executing work steps of the present invention may be assembly instructions, ISA (Instruction Set Architecture) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., as well as conventional procedural programming languages ​​such as the programming language "C" or similar programming languages.The computer-readable program instructions can be executed entirely on the user's computer, partially on the user's computer as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In the latter case, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, via the internet using an internet service provider).In some embodiments, electronic circuits, including, for example, programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), can execute computer-readable program instructions by using state information from the computer-readable program instructions to personalize the electronic circuits to implement aspects of the present invention.

[0049] Aspects of the present invention are described herein with reference to flowcharts and / or block diagrams of processes, devices (systems), and computer program products according to embodiments of the invention. It is pointed out that each block of the flowcharts and / or block diagrams, as well as combinations of blocks in the flowcharts and / or block diagrams, can be executed by means of computer-readable program instructions.

[0050] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or any other programmable data processing device to create a machine, such that the instructions executed by the processor of the computer or other programmable data processing device will generate a means of implementing the functions / steps specified in the block(s) of the flowcharts and / or block diagrams.These computer-readable program instructions may also be stored on a computer-readable storage medium capable of controlling a computer, programmable data processing device and / or other units to function in a particular manner, such that the computer-readable storage medium on which instructions are stored has a manufactured product, including instructions that implement aspects of the function / step specified in the block(s) of the flowchart and / or block diagrams.

[0051] The computer-readable program instructions can also be loaded onto a computer, other programmable data processing device or other unit to cause a series of process steps to be executed on the computer or other programmable device or other unit in order to generate a process executed on a computer, such that the instructions executed on the computer, other programmable device or other unit implement the functions / steps specified in the block(s) of the flowcharts and / or block diagrams.

[0052] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible embodiments of systems, methods, and computer program products according to various embodiments of the present invention. In this context, each block in the flowcharts or block diagrams can represent a module, segment, or part of instructions that includes one or more executable instructions for performing the specific logical function(s). In some alternative embodiments, the functions specified in the blocks may occur in a different order than shown in the figures. For example, two blocks shown consecutively may in reality be executed essentially simultaneously, or the blocks may sometimes be executed in reverse order, depending on the corresponding functionality.It should also be noted that each block of the block diagrams and / or flowcharts, as well as combinations of blocks in the block diagrams and / or flowcharts, can be implemented by special hardware-based systems that perform the specified functions or steps, or execute combinations of special hardware and computer instructions.

[0053] It should be clarified from the outset that the implementation of the teachings set forth herein is not limited to a cloud computing environment, although this disclosure contains a detailed description of cloud computing. Instead, embodiments of the present invention can be implemented together with any type of data processing environment, now known or hereafter invented.

[0054] Cloud computing is a service delivery model that enables seamless, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, main memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management overhead or interaction with a service provider. This cloud model can include at least five characteristics, at least three service models, and at least four implementation models. The function provided to the user is to provide processing, storage, networking, and other basic computing resources, enabling the user to deploy and run any software, which may include operating systems and applications. The user manages and / orIt does not control the underlying cloud infrastructure, but has control over operating systems, storage, deployed applications and possibly limited control over selected network components (e.g. host firewalls).

[0055] A cloud computing environment is service-oriented, focusing on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing lies an infrastructure comprising a network of interconnected nodes. Referring to Fig. Figure 5 illustrates the Cloud Computing Environment 500. As shown, the Cloud Computing Environment 500 comprises one or more Cloud Computing Nodes 502, with which local data processing units used by cloud users, such as the electronic assistant (PDA, personal digital assistant) or mobile phone 504A, the desktop computer 504B, the laptop computer 504C, and / or the automotive computer system 504N, can exchange data. The Nodes 502 can exchange data with each other. They can be grouped physically or virtually into one or more networks, such as private, community, public, or hybrid clouds (not shown), as described above, or a combination thereof. This enables the Cloud Computing Environment 500 to offer infrastructure, platforms, and / or software as services, for which a cloud user does not need to maintain resources on a local data processing unit.It should be noted that the types of in . Fig. The 5 data processing units 504A to N shown are for illustrative purposes only, and the data processing nodes 502 and the cloud computing environment 500 can exchange data with any type of computer unit via any type of network and / or any type of network-accessible connection (e.g., using a web browser).

[0056] Now, with reference to Fig. Figure 6 shows a set of functional abstraction layers that are used by the Cloud Computing Environment 500 ( Fig. 5) be provided. It should be clear from the outset that the in Fig.The components, layers, and functions shown in Figure 6 are intended to be illustrative only, and embodiments of the invention are not limited to them. As shown, the following layers and corresponding functions are provided: A hardware and software layer 600 contains hardware and software components. Examples of hardware components include: mainframe computers 601; servers 602 based on the RISC (Reduced Instruction Set Computer) architecture; servers 603; blade servers 604; storage units 605; and networks and network components 606. In some embodiments, network application server software 607 and database software 608 are among the software components.The virtualization layer 700 provides an abstraction layer from which the following examples of virtual entities can be provided: virtual servers 701, virtual storage 702, virtual networks 703, including virtual private networks, virtual applications and operating systems 704; and virtual clients 705.

[0057] In one example, the 800 administration layer can provide the following functions. Resource provisioning (801) provides the dynamic procurement of compute resources and other resources used to perform tasks within the cloud computing environment. Metering and pricing (802) provides cost tracking for resource usage within the cloud computing environment and billing for that resource usage. In one example, these resources might include application software licenses. Security provides identity verification for cloud users and tasks, as well as protection for data and other resources. A user portal (803) provides users and system administrators with access to the cloud computing environment.Service Scope Management (804) provides the allocation and management of cloud computing resources to ensure that required service goals are met. Service Level Agreement (SLA) Planning and Fulfillment (805) provides the advance planning and procurement of cloud computing resources for which a future requirement is anticipated, in accordance with an SLA.

[0058] A workload layer 900 provides examples of the functionality for which the cloud computing environment can be used. Examples of workloads and functions that can be provided by this layer include: mapping and navigation 901; software development and lifecycle management 902; delivery of training in virtual classrooms 903; data analytics processing 904; transaction processing 905; and data replication storage 906.

Claims

[1] A computer-implemented method (200) for managing a data processing unit (102), wherein the method comprises: Accessing (202) replicable data from the data processing unit (102); Detecting (206) risks of the data processing unit (102) based on a GPS location tracker in the data processing unit (102) to determine the altitude, proximity to a cliff or waterfall, speed of the data processing unit (102) and temperature of the data processing unit (102); in response to a detected risk reaching or exceeding a predetermined threshold, initiating (208) a data replication on the data processing unit (102); and Establish (304) channels using radio waves to enable simultaneous transfer of the replicated data. [2] A computer-implemented method (200) according to claim 1, wherein the detection (206) of risks of the data processing unit (102) comprises classifying data types on the data processing unit (102) using a priority control component. [3] A computer-implemented method (200) according to one of the preceding claims, wherein the risk detection (206) on the data processing unit (102) comprises simultaneous access to audio and visual sensors of the data processing unit (102) to detect changes in the location, speed, state and environment of the data processing unit (102). [4] A computer-implemented method (200) according to any of the preceding claims, wherein the initiation (208) of data replication comprises replicating data based on the user-specific priority of the data type. [5] A computer-implemented method (200) according to any of the preceding claims, wherein the specified threshold is a quantified risk level associated with the data processing unit (102) to initiate data replication (208). [6] A computer-implemented method (200) according to one of the preceding claims, wherein the setup (304) of the radio wave-utilizing channels to enable simultaneous transfer of the replicated data further comprises storing (210) the replicated data on a server data processing unit (102) via a telecommunications network. [7] A computer-implemented method (200) according to any of the preceding claims, further comprising sending instructions to abort data replication in response to the fact that replicated data reaches a cloud network storage device during storage. [8] A computer-implemented method (200) according to one of the preceding claims, which further comprises an automatic cessation of data replication after determining a reduction in detected risks below the specified threshold. [9] Computer system (400) for managing a data processing unit (102), wherein the system comprises: one or more computer processors (404); one or more computer-readable storage media; and Program instructions stored on one or more computer-readable storage media for execution by at least one of the one or more computer processors (404), wherein the program instructions instruct the one or more computer processors (404) to execute a method (200) according to any one of claims 1 to 8. [10] Computer program product for managing a data processing unit (102), wherein the computer program product comprises: a computer-readable storage medium that is readable by a processing circuit and stores instructions for execution by the processing circuit to carry out a method (200) according to any one of claims 1 to 8. [11] Computer program which is stored on a medium readable by a computer (400) and which can be loaded into the internal memory (406) of a digital computer and which includes software program parts for carrying out the method (200) according to any one of claims 1 to 8 when the program is executed on a computer (400).

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