Detecting the risk of data loss on 5G-enabled devices

Abstract

Embodiments of the present invention provide a computer system, a computer program product, and a method, the method including collecting data that can be replicated from a computing device; detecting a risk of the computing device, where detecting the risk includes detecting surroundings, location, speed, and state of the computing device; initiating data replication on the computing device when the risk is determined to reach a predetermined threshold; and storing the replicated data in a cloud storage system using a 5G network.

Description

[Technical field]

[0001] The present invention relates generally to the field of data protection, and more specifically to detecting risks in 5G devices to prevent data loss by preserving data via data replication and remote data storage. [Background technology]

[0002] Data storage is the recording of information in a storage medium. This recording can be accomplished by virtually any form of energy, with electronic data storage requiring power to store and retrieve data. Electronic data can be stored in much less space than physical data. Furthermore, data replication is the process of storing data at two or more sites or nodes. It simply copies the data of 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 a logical pool. The physical storage is spread across multiple servers, and the cloud storage provider is responsible for keeping the data available and accessible.

[0004] 5G is the fifth generation of cellular network technology in which the service area covered by a provider is divided into smaller geographic areas called cells. All 5G wireless devices in a cell communicate by radio waves with a local antenna array and low-power automated transceivers in that cell through frequency channels assigned by the transceivers from a pool of frequencies reused by other cells.

[0005] However, detecting risks associated with 5G-enabled mobile devices can be problematic. Thus, there is a need in the art to address the above-mentioned issues. Summary of the Invention

[0006] Viewed from a further aspect, the present invention provides a computer-implemented method comprising: accessing data available to be replicated from a computing device; detecting risks to the computing device based at least in part on surroundings, location, speed, and condition of the computing device; initiating data replication on the computing device in response to one of the detected risks reaching or exceeding a predetermined threshold; and establishing a channel using radio waves to facilitate simultaneous transfer of the replicated data.

[0007] Viewed from a further aspect, 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, the program instructions including: program instructions for accessing data available to be replicated from a computing device; program instructions for detecting risks to the computing device based at least in part on surroundings, location, speed, and condition of the computing device; program instructions for initiating data replication on the computing device in response to one of the detected risks reaching or exceeding a predetermined threshold; and program instructions for establishing a channel using radio waves to facilitate simultaneous transfer of the replicated data.

[0008] Viewed from a further aspect, 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, the program instructions including: program instructions for accessing data that can be replicated from a computing device; program instructions for detecting risks to the computing device based at least in part on surroundings, location, speed, and condition of the computing device; program instructions for initiating data replication on the computing device in response to one of the detected risks reaching or exceeding a predetermined threshold; and program instructions for establishing a channel using radio waves to facilitate simultaneous transfer of the replicated data.

[0009] Viewed from a further aspect, the present invention provides a computer program product for managing a computing device, the computer program product comprising a computer readable storage medium readable by a processing circuit, the computer readable storage medium storing instructions for execution by the processing circuit to perform a method implementing steps of the present invention.

[0010] Viewed from a further aspect, the present invention provides a computer program stored on a computer readable medium and loadable into an internal memory of a digital computer, the computer program comprising software code portions for performing the steps of the present invention when said program is executed on a computer.

[0011] Embodiments of the present invention provide computer systems, computer program products, and methods, the method including collecting data that can be replicated from a computing device; detecting a risk to the computing device, where detecting the risk includes detecting surroundings, location, speed, and state of the computing device; initiating data replication on the computing device when the risk is determined to reach a predetermined threshold; and storing the replicated data in a cloud storage system using a 5G network.

[0012] The invention will now be described, by way of example only, with reference to preferred embodiments illustrated in the following figures. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a functional block diagram illustrating an environment with a computing device connected to or in communication with another computing device in accordance with at least one embodiment of the present invention. [Diagram 2] 1 is a flowchart illustrating operational steps for implementing data protection while detecting risk programs according to one embodiment of the present invention. [Diagram 3] 1 is a flowchart illustrating a dynamic risk detection program on a computing device that provides data replication in a 5G network in accordance with at least one embodiment of the present invention. [Figure 4] FIG. 2 is a block diagram of components of the computing system of FIG. 1 in accordance with one embodiment of the present invention. [Diagram 5] FIG. 1 is a diagram of a cloud computing environment according to one embodiment of the present invention. [Figure 6] FIG. 2 is a diagram of abstraction model layers according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] The present invention recognizes the need for a method to provide more efficient data protection and storage using risk detection using 5G networks in an environment consisting of computing devices. The present invention provides a system, method, and computer program product for improving existing data protection and replication systems. Currently, a typical data protection system can initiate a backup process after a predefined regular time interval and use it to recover data when a failure is encountered. Similarly, a typical data protection system backs up a computing device after hardware is damaged and the settings need to be replicated on another machine, which also contains data gaps that may result in some data loss. There are also cloud resources used to protect data by replicating data from computing devices to cloud storage, but they cannot proactively detect risks. The present invention proactively detects risks to a computing device that may lead to data loss, and simultaneously replicates the data that may be at risk on the computing device, using only the 5G network as a communication channel. An embodiment of the present invention can access an approved list of computing devices that can be monitored, collect data to be replicated from those devices, detect the mobility, surroundings, and state of the computing devices to determine associated risks to the data, initiate specific data replication alerts on the computing devices when certain risk thresholds are determined, and securely store the replicated data in the cloud.

[0015] FIG. 1 is a functional block diagram of a computing environment 100 according to one embodiment of the present invention. The computing environment 100 includes a computing device 102 and a server computing device 108. The computing device 102 and the server computing device 108 may be desktop computers, laptop computers, specialized computer servers, smartphones, or any other computing devices known in the art. In one embodiment, the computing device 102 and the server computing device 108 may represent computing devices that utilize multiple computers or components to operate as a single pool of seamless resources when accessed over a network 106. In general, the computing device 102 and the server computing device 108 may represent any electronic device or combination of electronic devices capable of executing machine-readable program instructions, as described in more detail with respect to FIG. 4.

[0016] The computing device 102 may include a program 104. The program 104 may be a standalone program on the computing device 102. In another embodiment, the program 104 may be stored on a server computing device 108. In this embodiment, the program 104 accesses a list of computing devices that may be monitored, accesses data to be replicated on those devices, detects mobility, surroundings, and conditions of the computing devices, determines associated risks to the data using a risk identification algorithm (shown in a later figure), initiates specific data replication alerts on the computing device when a predefined risk threshold is met or exceeded, and securely stores the replicated data in the cloud. In this embodiment, the program 104 sends instructions to the risk identification algorithm, which comprises a cognitive system defined to map content utilizing a priority engine (not shown). The priority engine prioritizes data types on the computing device 102 for data replication. For example, the program 104 accesses a user's smartphone, determines data that may be copied (i.e., texts, phone numbers, and photos), sends instructions to a risk identification algorithm to access the device's camera and GPS to detect the device's location, determine the device's status, detect the device's surroundings to detect risks such as height or flowing water, and initiates data copying over the 5G network 106 after detecting possible risks to the data on the device.

[0017] The network 106 may be a local area network ("LAN"), a wide area network ("WAN") such as the Internet, or a combination of both, and may include wired, wireless, or fiber optic connections. In general, the network 106 may be any combination of connections and protocols that facilitate communication between the computing devices 102 and the server computing device 108, specifically the programs 104 according to preferred embodiments of the present invention. The network 106 may use an orchestration layer of 5G technology in conjunction with existing mobility monitoring tools that sense 5G communication channels and other compatible platforms, and identify deeper insights from data collected from 5G-enabled mobile devices.

[0018] The server computing device 108 may include the program 104 and may communicate with the computing device 102 via the network 106. The server computing device 108 may be a single computing device, a laptop, a cloud-based collection of computing devices, a collection of servers, and other known computing devices. The server computing device 108 may be combined with the 5G network 106 to create a server computing device that is a cloud-based network that may be a fixed access network. In this embodiment, the combination of the server computing device 108 and the 5G network 106 may relay data from the computing device 102 to the server computing device 108 using wireless signals, backhaul networks, optical access networks, optical metro networks, and optical core networks in conjunction with the 5G network 106. The wireless signals are used to carry wireless broadcasts and establish wi-fi connections for cellular devices. The backhaul network constitutes an intermediate link between the core network and smaller sub-networks at the edge of the network, which in this embodiment is the cloud-based storage capability of the 5G network 106. The optical network requires the use of single mode fiber in the outside plant, with upstream and downstream signals sharing the same fiber at separate wavelengths.

[0019] FIG. 2 is a flowchart 200 illustrating operational steps for replicating data after detecting a risk on a computing device over a 5G network.

[0020] In step 202, the program 104 accesses the computing device 102 from the list of computing devices that can be monitored. In this embodiment, the program 104 receives an opt-in / opt-out permission from the user to gain access to a particular computing device from the list of computing devices that can be monitored by the program 104. In this embodiment, the program 104 is already on the computing device 102 and remains dormant on the computing device 102 until the program 104 is given permission to access data stored on the computing device 102. In this embodiment, the program 104 may access some computing devices from the list of computing devices that can be monitored and have data copied. For example, the program 104 accesses the user's smartphone that is on the user's list of computing devices to monitor and, if necessary, copy data.

[0021] In step 204, the program 104 accesses replicable data on a particular computing device (e.g., computing device 102). In this embodiment, the program 104 accesses data found on the computing device 102. In this embodiment, the program 104 accesses data that can be replicated, which may include text messages, phone numbers, and photos. In another embodiment, the program 104 accesses risky data on the computing device 102. For example, the program 104 accesses call logs and photo libraries on the user's particular computing device (e.g., computing device 102).

[0022] In step 206, the program 104 detects a risk associated with the computing device 102. In this embodiment, the program 104 determines a location of the computing device 102, determines the mobility of the computing device 102, determines the speed of the computing device, determines the surrounding conditions of the computing device 102, and calculates a risk associated with the location, speed, and surrounding conditions of the computing device 102. In this embodiment, the program 104 detects a risk associated with a particular computing device using a risk determination algorithm defined as a cognitive system defined to map content using a priority engine. In this embodiment, the program 104 sends instructions to the risk determination algorithm to access the sensors of the particular computing device to detect a particular location of the computing device 102. The program 104 may use the particular location as a means of determining the speed of the computing device 102 and as a means of determining the surrounding conditions of the computing device 102. For example, the program 104 may identify a particular location of the computing device 102 as being at a cliff and determine that the computing device 102 is stationary, in which case the program 104 may not calculate the current surroundings as a risk. However, the program 104 may identify a particular location of the computing device 102 as being at a waterfall, which may be considered a cliff with flowing water, and determine that the computing device 102 is stationary, in which case the program 104 may calculate the current surroundings as a low risk. Additionally, the program 104 may identify a particular location of the computing device 102 as being at a cliff and determine that the computing device 102 is accelerating at 9.8 meters per second (which is the definition of a free-falling object due to gravity), in which case the program 104 may calculate the current surroundings as a high risk.

[0023] Further, in this embodiment, the program 104 may communicate with the computing device 102 using the 5G network 106 to establish a service orchestration instance. In this embodiment, each risk is given a numerical value. A higher numerical value means higher importance and a lower numerical value means less importance. In this embodiment, the program 104 defines a high risk as a numerical value that meets or exceeds a configurable threshold. Conversely, the program 104 defines a low risk as a numerical value that does not meet or exceed a configurable threshold. Furthermore, the program 104 may prioritize low risk for certain data types that need to be replicated if the configurable threshold is not met or exceeded. In that case, the program 104 prioritizes each data type and gives it a priority position. For example, if a particular user values ​​their photo library more than their text messages and call logs, and the program 104 determines a small risk to the computing device 102, the program 104 places the photo library in a prioritized position on the computing device 102 before other data types. In this embodiment, the risk identification algorithm prioritizes the data types using a priority engine. In this embodiment, this prioritization may be governed by user input. In another embodiment, the prioritization may be governed by available space, and certain data types may not be the right size to replicate efficiently.

[0024] To determine the risk level associated with the computing device 102, the program 104 sends instructions to sensors within the computing device 102 to capture ambient conditions, conditions, and risks. For example, the program 104 may use audio and video inputs in conjunction with the smartphone's GPS location tracker to determine the phone's altitude, proximity to cliffs or waterfalls, the smartphone's speed, and the smartphone's temperature to predict whether data replication will be required to protect data on the smartphone when the quantified risk reaches a predetermined threshold. In another embodiment, the program 104 may dynamically determine the threshold in real time, thereby causing the program 104 to adjust this value depending on the risk found at the time of detection.

[0025] At step 208, the program 104 initiates data replication of data on the computing device 102. In this embodiment, when the program 104 determines that the risk associated with the ambient conditions reaches a predetermined risk threshold, the program 104 automatically initiates data replication on the computing device 102 to back up all data that can be replicated. In this embodiment, the program 104 creates a logical channel that uses radio broadcasts and the 5G network 106 to transmit instructions and data to and from the server computing device 108. In this embodiment, the program 104 autonomously initiates data replication of data on the computing device 102. In another embodiment, the program 104 initiates data replication after receiving user approval to replicate data from the user. For example, when the program 104 determines that the smartphone is at significant risk of losing all data due to its ambient conditions, the program 104 automatically initiates a data replication operation transmitted over the 5G network 106, which replicates all critical data and transmits the data securely to the server computing device 108. In another embodiment, the program 104 may discontinue data replication of the data if the risk identification algorithm detects that the quantified risk has fallen below a predetermined threshold.

[0026] At step 210, the program 104 stores the replicated data in the server computing device 108. In this embodiment, the program 104 may transmit and store the replicated data using the 5G network 106. In this embodiment, the program 104 creates a logical channel that facilitates the transfer of the replicated data to the server computing device 108. In this embodiment, the 5G network 106 ensures that the data replication is simultaneous with the storage of the replicated data and ensures protection of the replicated data. In another embodiment, the program 104 transmits and stores the replicated data in the server computing device 108 using wireless broadcast in conjunction with the 5G network 106 and various optical networks. In another embodiment, the program 104 stores the replicated data in the 5G network 106 that functions as a cloud-based storage.

[0027] FIG. 3 is a flowchart 300 illustrating a dynamic risk detection program on a computing device implementing data replication into a 5G network in accordance with at least one embodiment of the present invention.

[0028] In step 302, the program 104 launches on the computing device 102. In this embodiment, the program launches on the computing device 102 and gains access to the computing device's operating system. The computing device's 102 operating system may include a data backup manager, a peripheral computing device controller, a user space data reader, a data streamer, a device operating system connector interface, a GPS manager, and a priority engine.

[0029] At step 304, the program 104 establishes a channel to a radio access network. In this embodiment, the program 104 may establish a channel consisting of 5G control commands and a 5G input stream connected to an eNodeB. The eNodeB is hardware connected to a connected device network that communicates wirelessly directly with mobile handsets, such as a base transceiver station in a GSM network. In this embodiment, the program 104 sends instructions to the computing device 102 to enable the established channel to access the operating system of the computing device.

[0030] At step 306, the program 104 configures a risk identification algorithm on the computing device 102. In this embodiment, the program 104 configures the risk identification algorithm, which is a cognitive system with content for mapping data with a priority engine that determines the importance of certain data on the computing device 102. The priority engine used within the risk identification algorithm determines the importance of certain data by assigning a numerical value to a certain type of data. In this embodiment, the program 104 transmits instructions to the computing device 102 upon gaining access to allow the risk identification algorithm to enter the computing device 102. In this embodiment, after the program 104 transmits instructions to the risk identification algorithm to gain access to the computing device, the program 104 transmits instructions to the risk identification algorithm to access the internal and external sensors of the computing device to track the specific location, speed, and ambient conditions of the computing device 102. In this embodiment, the program 104 transmits instructions to the risk identification algorithm to calculate the level of risk associated with the computing device by assigning a numerical value to each risk, and a predetermined level of risk triggers a signal. In this embodiment, the risk identification algorithm may trigger a signal to the established channel, and the program 104 uses this signal as a predetermined threshold for initiating data replication of the computing device 102. In this embodiment, the risk identification algorithm prioritizes data types using a priority engine. In this embodiment, this prioritization may be governed by user input. In another embodiment, the prioritization may be governed by available space, where certain data types may not be the right size to replicate efficiently.

[0031] At step 308, the program 104 notifies the computing device 102 when it creates a risk identification signal. In this embodiment, the program 104 sends a notification to the computing device 102 when a risk of a predetermined threshold has been identified by the risk identification algorithm such that a signal is established. This notification initiates a data duplication process performed by the program 104 on the computing device 102.

[0032] At step 310, the program 104 initiates data replication on the computing device 102. In this embodiment, once the risk identification algorithm reaches a predefined threshold and the signal is established, the program 104 initiates data replication on the computing device 102. In this embodiment, the program 104 uses a risk identification algorithm to analyze the data on the computing device 102 to determine the level of sensitivity of the data, the risk identification algorithm determines the risk surrounding the computing device and gives each data type a quantifiable value, and the program 104 initiates replication of critical data types and then moves on to less critical data types. In this embodiment, the program 104 uses a 5G established channel, which makes the data replication simultaneous. In another embodiment, the program 104 may halt the data replication operation if the risk identification algorithm detects that the quantified risk has dropped below a predefined threshold.

[0033] In step 312, the program 104 establishes a channel between the radio access network and the 5G network 106. In this embodiment, after the data replication process is initiated, the program 104 establishes a channel between the eNodeB and the 5G network 106, where the 5G network 106 is a fixed access network that may be a cloud-based data storage system. In another embodiment, the program 104 may establish an additional channel with the optical access network. In another embodiment, the program 104 may establish an additional channel between the optical metro network and the optical core network.

[0034] At step 314, the program 104 stores the replicated data in the 5G network 106 via the established channel. In this embodiment, the program 104 stores the replicated data in a cloud-based data storage system, which may be housed in the 5G network 106, by using the established channel between eNobeB and the 5G telecommunications network 106. In this embodiment, the 5G networks include a 5G infrastructure management plane and service orchestration that communicate with each other. In another embodiment, the program 104 may store the replicated data in the server computing device 108 after using the established channel and the 5G network 106.

[0035] Figure 4 illustrates a block diagram of computing system components in computing environment 100 of Figure 1, in accordance with one embodiment of the present invention. It should be appreciated that Figure 4 is intended to provide an illustration of one implementation only and is not intended to suggest any limitation with respect to the environment in which different embodiments may be implemented. Many modifications to the depicted environment may be made.

[0036] The programs described herein are identified based on the applications for which they are implemented in particular embodiments of the invention, but it should be recognized that any specific program names herein are used merely for convenience and thus the invention is not limited to use with only the specific applications identified and suggested by such names.

[0037] Computer system 400 includes a communications fabric 402, which provides communication between cache 416, memory 406, persistent storage 408, communications unit 410, and input / output (I / O) interface 412. Communications fabric 402 may be implemented using any architecture designed to exchange data and / or control information between processors (such as microprocessors, communications and network processors), system memory, peripheral devices, and any other hardware components in the system. For example, communications fabric 402 may be implemented using one or more buses or crossbar switches.

[0038] Memory 406 and persistent storage 408 are computer-readable storage media. In this embodiment, memory 406 includes random access memory (RAM). In general, memory 406 may include any suitable volatile or non-volatile computer-readable storage medium. Cache 416 is a high-speed memory that improves the performance of computer processor 404 by holding recently and soon to be accessed data from memory 406.

[0039] The programs 104 may be stored in persistent storage 408 and memory 406 for execution by one or more of the respective computer processors 404 via cache 416. In one embodiment, persistent storage 408 includes a magnetic hard disk drive. Alternatively, or in addition to a magnetic hard disk drive, persistent storage 408 may include a solid state hard drive, a semiconductor memory device, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, or any other computer-readable storage medium capable of storing program instructions or digital information.

[0040] The media used by persistent storage 408 may be removable. For example, a removable hard drive may be used as persistent storage 408. Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive to transfer data to another computer-readable storage medium that is also part of persistent storage 408.

[0041] The communications unit 410 in these examples provides for communication with other data processing systems or devices. In these examples, the communications unit 410 includes one or more network interface cards. The communications unit 410 may provide for communication through the use of either or both physical and wireless communications links. The programs 104 may be downloaded to the persistent storage 408 through the communications unit 410.

[0042] The I / O interface 412 allows for data input and output with mobile devices, authorization devices, or other devices that may be connected to the server computing system 110, or a combination thereof. For example, the I / O interface 412 may provide a connection to an external device 418, such as a keyboard, a keypad, a touch screen, or some other suitable input device, or a combination thereof. The external device 418 may also include portable computer-readable storage media, such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to implement embodiments of the present invention, such as the program 104, may be stored on such portable computer-readable storage media and loaded into the persistent storage 408 via the I / O interface 412. The I / O interface 412 may also be connected to a display 420.

[0043] Display 420 provides a mechanism for displaying data to a user and may be, for example, a computer monitor.

[0044] The present invention may be a system, a method, and / or a computer program product, which may include a computer-readable storage medium(s) having computer-readable program instructions stored thereon for causing a processor to implement aspects of the present invention.

[0045] A computer readable storage medium may be any tangible device capable of holding and storing instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. A non-exhaustive list of more specific examples of computer readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanically encoded devices such as punch cards or raised structures in grooves in which instructions are recorded, or any suitable combination of the above. A computer-readable storage medium as used in the present invention should not be construed as a transitory signal 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 through a fiber optic cable), or electrical signals transmitted over electrical wires.

[0046] The computer readable program instructions described herein may be downloaded from a computer readable storage medium to each computing / processing device or to an external computer or storage device via a network, such as the Internet, a local area network, a wide area network, or a wireless network, or a combination thereof. The network may include copper transmission cables, optical transmission fiber, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer readable program instructions from the network and transfers the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0047] The computer readable program instructions for carrying out the operations of the present invention may be either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including the "C" programming language or similar programming languages, such as object oriented programming languages ​​like Smalltalk®, C++, etc., and traditional procedural programming languages. The computer readable program instructions may be executed entirely on the user's computer, partially on the user's computer, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server, as a stand-alone software package. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or wide area network (WAN), or the connection may be made to an external computer (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may execute computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry to perform aspects of the invention.

[0048] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or blocks, can be implemented by computer readable program instructions.

[0049] Those computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that the instructions, executed via the processor of the computer or other programmable data processing apparatus, create means for performing the functions / operations specified in one or more blocks of the flowcharts and / or block diagrams. Those computer-readable program instructions may be stored in a computer-readable storage medium capable of directing a computer, programmable data processing apparatus, or other device, or combination thereof, to function in a particular manner such that the computer-readable storage medium on which the instructions are stored constitutes an article of manufacture including instructions implementing aspects of the functions / operations specified in one or more blocks of the flowcharts and / or block diagrams.

[0050] The computer readable program instructions may be loaded into a computer, other programmable data processing apparatus, or other device, causing the computer, other programmable apparatus, or other device to perform a series of operational steps to generate a computer-implemented process, such that the instructions, which execute on the computer, other programmable apparatus, or other device, perform the functions / operations specified in one or more blocks of the flowcharts and / or block diagrams.

[0051] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or part of an instruction, which includes one or more executable instructions for performing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may in fact be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order depending on the functionality involved. It will be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of each block in the block diagrams and / or flowchart illustrations, may be implemented by a special-purpose hardware-based system that performs the specified functions or operates or implements a combination of special-purpose hardware and computer instructions.

[0052] Although this disclosure includes detailed descriptions of cloud computing, it should be understood that implementation of the teachings described herein is not limited to a cloud computing environment. Rather, embodiments of the invention can be implemented in conjunction with any other type of computing environment now known or later developed.

[0053] Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and made available with minimal administrative effort or interaction with service providers. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. The ability provided to the consumer is to provision processing, storage, network, and other basic computing resources, and the consumer can deploy and run any software, which may include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but has control over the operating systems, storage, deployed applications, and possibly limited control over selected networking components (e.g., host firewalls).

[0054] A cloud computing environment is a service that emphasizes statelessness, low coupling, modularity, and semantic interoperability. At the core of cloud computing is an infrastructure that includes a network of interconnected nodes. Referring now to FIG. 5, an exemplary cloud computing environment 500 is depicted. As shown, the cloud computing environment 500 includes one or more cloud computing nodes 502 with which local computing devices used by cloud consumers may communicate, such as a personal digital assistant (PDA) or cellular phone 504A, a desktop computer 504B, a laptop computer 504C, or an automobile mobile computer system 504N, or combinations thereof. The nodes 502 may communicate with each other. They may be physically or virtually grouped (not shown) as one or more networks, such as a private cloud, a community cloud, a public cloud, or a hybrid cloud, as described herein above, or combinations thereof. This enables the cloud computing environment 500 to provide infrastructure, platform, and / or software as a service, for which the cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 504A-N shown in Figure 5 are intended to be merely exemplary, and that the computing nodes 502 and the cloud computing environment 500 can communicate with any type of computerized device through any type of network or network-addressed connection (e.g., using a web browser), or combination thereof.

[0055] Referring now to FIG. 6, a set of functional abstraction layers provided by cloud computing environment 500 (FIG. 5) is shown. It should be understood in advance that the components, layers, and functions shown in FIG. 6 are intended to be merely exemplary, and that embodiments of the present invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: Hardware and software layer 600 includes hardware and software components. Examples of hardware components include mainframe 601, server 602 based on RISC (reduced instruction set computer) architecture, server 603, blade server 604, storage device 605, and network and networking components 606. In some embodiments, software components include network application server software 607, and database software 608. Virtualization layer 700 provides an abstraction layer from which the following examples of virtual entities may 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.

[0056] In one example, the management layer 800 may provide the following functions: Resource provisioning 801 provides dynamic procurement of computing and other resources utilized to perform tasks within the cloud computing environment. Metering and pricing 802 provides cost tracking as resources are utilized within the cloud computing environment and billing or invoicing for the consumption of those resources. In one example, the resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, and protection for data and other resources. User portal 803 provides consumers and system administrators with access to the cloud computing environment. Service level management 804 provides allocation and management of cloud computing resources such that required service levels are met. Service level agreement (SLA) planning and fulfillment 805 provides proactive configuration and procurement of cloud computing resources in anticipation of future needs in accordance with SLAs.

[0057] The workload tier 900 provides examples of functions for which a cloud computing environment may be utilized. Examples of workloads and functions that may be provided from this tier include mapping and navigation 901, software development and lifecycle management 902, virtual classroom instructional delivery 903, data analytics processing 904, transaction processing 905, and data replication storage 906.

[0058] The description of various embodiments of the present invention has been presented for the purpose of explanation, but is not intended to be exhaustive or limited to the disclosed embodiments. Many changes and modifications will be apparent to those skilled in the art without departing from the scope of the present invention. The terminology used in this specification is selected to best explain the principles of the embodiments, practical applications, or technical improvements to the technology found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein. The present disclosure also discloses the following inventions. (Appendix 1) 1. A computer-implemented method for managing a computing device, comprising: accessing data available to be replicated from said computing device; Detecting risk to the computing device based at least in part on surroundings, location, speed, and condition of the computing device; initiating data replication on the computing device in response to a detected risk among the detected risks reaching or exceeding a predetermined threshold; establishing channels using radio waves to facilitate simultaneous transfer of said replicated data; The method includes: (Appendix 2) 2. The computer-implemented method of claim 1, wherein detecting risk of the computing device comprises prioritizing data types on the computing device using a priority engine. (Appendix 3) 3. The computer-implemented method of claim 1 or 2, wherein detecting a risk on the computing device includes simultaneously accessing audio and visual sensors of the computing device to detect changes in the location, speed, state, and surroundings of the computing device. (Appendix 4) 4. The computer-implemented method of any one of claims 1 to 3, wherein initiating data replication includes replicating data based on a user-specified priority of the data types. (Appendix 5) 5. The computer-implemented method of any one of claims 1 to 4, wherein the predetermined threshold is a quantified level of risk associated with the computing device that prompts data replication. (Appendix 6) 6. The computer-implemented method of any of Claims 1 to 5, wherein establishing a channel(s) using radio waves to facilitate simultaneous transfer of the replicated data further comprises storing the replicated data on a server computing device via a telecommunications network. (Appendix 7) 7. The computer-implemented method of any of Claims 1 to 6, further comprising, in response to storing the replicated data reaching the cloud network storage, sending an instruction to interrupt the data replication. (Appendix 8) 8. The computer-implemented method of any of Claims 1 to 7, further comprising automatically suspending data replication after determining that the detected risk has fallen below the predetermined threshold. (Appendix 9) 1. A computer system for managing a computing device, 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, the program instructions comprising: program instructions for accessing data that can be replicated from a computing device; program instructions for detecting risk for the computing device based at least in part on surroundings, location, speed, and state of the computing device; program instructions for initiating data replication on the computing device in response to a detected risk among the detected risks reaching or exceeding a predetermined threshold; program instructions for establishing a channel using radio waves to facilitate the simultaneous transfer of the replicated data; A computer system comprising: (Appendix 10) 10. The computer system of claim 9, wherein the program instructions for detecting risk of the computing device include program instructions for prioritizing data types on the computing device using a priority engine. (Appendix 11) The computer system of claim 9 or claim 10, wherein the program instructions for detecting risk to the computing device include program instructions for simultaneously accessing audio and visual sensors of the computing device to detect changes in the location, speed, status, and surroundings of the computing device. (Appendix 12) 12. The computer system of claim 9, wherein the program instructions for initiating data replication on the computing device when the risk is determined to reach a predetermined threshold include program instructions for replicating data based on a user-specific priority of the data types. (Appendix 13) 13. The computer system of any of Appendix 9 to Appendix 12, wherein the program instructions for storing the replicated data in a cloud storage system using a telecommunications network include program instructions for storing the replicated data on a server computing device via the telecommunications network. (Appendix 14) 14. The computer system of any of claims 9 to 13, wherein the program instructions stored on the one or more computer-readable storage media further include program instructions for sending an instruction to suspend data replication in response to storing replicated data reaching cloud network storage. (Appendix 15) 1. A computer program product for managing a computing device, comprising: A computer program product comprising a computer-readable storage medium readable by a processing circuit, the computer-readable storage medium storing instructions for execution by the processing circuit to perform a method according to any one of claims 1 to 8. (Appendix 16) A computer program stored on a computer readable medium and loadable into the internal memory of a digital computer, the computer program comprising software code portions for performing the method according to any of claims 1 to 8 when said program is run on a computer.

Claims

1. 1. A computer-implemented method for managing a computing device, comprising: accessing data that can be replicated from said computing device; Detecting risk for the computing device based at least in part on surroundings, location, speed, and state of the computing device; quantifying the detected risk of the computing device based on an altitude of the computing device, a proximity of the computing device to a cliff, and a speed of the computing device; establishing a channel over the network using radio waves to facilitate the simultaneous transfer of said replicated data; initiating data replication on the computing device using the network in response to the quantified risk reaching or exceeding a predetermined threshold; The method includes:

2. 10. The computer-implemented method of claim 1, wherein detecting risk for the computing device comprises prioritizing data types on the computing device using a priority engine.

3. 3. The computer-implemented method of claim 1 or 2, wherein detecting risks on the computing device includes simultaneously accessing audio and visual sensors of the computing device to detect changes in the location, speed, status, and surroundings of the computing device.

4. 4. The computer-implemented method of claim 1, wherein initiating data replication comprises replicating data based on a user-specific priority of the data types.

5. 5. The computer-implemented method of claim 1, wherein the predetermined threshold is a quantified level of risk associated with the computing device that prompts data duplication.

6. 6. The computer-implemented method of claim 1, wherein establishing a channel using radio waves to facilitate simultaneous transfer of the replicated data further comprises storing the replicated data on a server computing device over a telecommunications network.

7. A computer-implemented method as described in any one of claims 1 to 6, further comprising automatically suspending data replication after determining that the quantified risk has fallen below the predetermined threshold.

8. The quantification comprises:

8. The computer-implemented method of claim 1, further comprising: calculating a greater risk in response to the computing device experiencing an acceleration that meets the definition of a free-falling object if the computing device is located in a location that includes a cliff or a waterfall; and wherein the network is a 5G network.

9. 1. A computer system for managing a computing device, 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, the program instructions comprising: program instructions for accessing data that can be replicated from a computing device; program instructions for detecting risk for the computing device based at least in part on surroundings, location, speed, and state of the computing device; program instructions for quantifying the detected risk of the computing device based on an altitude of the computing device, a proximity of the computing device to a cliff, and a speed of the computing device; program instructions for establishing a channel over a network using radio waves to facilitate the simultaneous transfer of the replicated data; program instructions for initiating data replication on the computing device using the network in response to the quantified risk reaching or exceeding a predetermined threshold; 1. A computer system comprising:

10. 10. The computer system of claim 9, wherein the program instructions for detecting risk of the computing device include program instructions for prioritizing data types on the computing device using a priority engine.

11. 11. The computer system of claim 9 or 10, wherein the program instructions for detecting risk to the computing device include program instructions for simultaneously accessing audio and visual sensors of the computing device to detect changes in location, speed, status, and surroundings of the computing device.

12. 12. The computer system of claim 9, wherein the program instructions for initiating data replication on the computing device upon determining that the risk reaches a predetermined threshold include program instructions for replicating data based on a user-specific priority of the data types.

13. 13. The computer system of claim 9, wherein the program instructions for storing the replicated data in a cloud storage system using a telecommunications network include program instructions for storing the replicated data on a server computing device via the telecommunications network.

14. The program instructions for quantifying include: and program instructions for calculating a greater risk if the computing device is located at a cliff or waterfall and the computing device is accelerating to meet the definition of a free-falling object.

14. The computer system of claim 9, wherein the network is a 5G network.

15. A computer-readable storage medium having recorded thereon a computer program for causing the method according to any one of claims 1 to 8 to be carried out.

16. A computer program causing a computer to carry out the method according to any one of claims 1 to 8.

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