Abstract: Identifying an indistinct entity within an image can include generating by an image filter multiple gradients, each of which corresponds to one of a plurality of pixels of an image captured by an imager. The image can be searched for a likely repeating pattern. Responsive to detecting, based on the multiple gradients, a likely repeating pattern within the image, data structures can be generated, the data structures comprising a set of probabilistically weighted feature vectors corresponding to the likely repeating pattern. A machine learning model can classify each of the set of probabilistically weighted feature vectors. An identity of the likely repeating pattern can be output, the identity based on the machine learning model classifications of the probabilistically weighted feature vectors.

Abstract: One embodiment of the invention provides a method for reverse proxy inspection (RPI) of encrypted traffic in an edge-based network. The method comprises sharing a first certificate from an RPI instance to an edge-based network gateway. The first certificate is issued to the RPI instance. The method further comprises receiving, at the RPI instance, an encrypted message with an initial layer of encryption and a subsequent layer of encryption. The initial layer is encrypted using a second certificate issued to an edge-based network device. The subsequent layer is encrypted using the first certificate. The method further comprises, at the RPI instance, authenticating the first certificate, and decrypting the subsequent layer using the first certificate, resulting in the encrypted message with the initial layer intact. The method further comprises, at the RPI instance, inspecting the encrypted message, and forwarding the encrypted message to a centralized hub.

Abstract: Runtime binary migration is provided. A slice of a 5G network is provisioned based on time period and bandwidth requirements in accordance with a service level agreement corresponding to a customer requesting performance of a business function transaction. A runtime binary for invoking the slice of the 5G network is migrated to a nodal edge server for a set of edge devices associated with the nodal edge server to perform the business function transaction using the slice of the 5G network.

Abstract: A method of using a computing device to provide non-functional requirement (NFR) fulfilment based technical disposition including identifying, by the computing device, optimal solutions based on overlaying prioritized NFRs for at least one target system as supported by each candidate system of multiple candidate systems. Supportable technical NFRs are used for each combination of options under the multiple candidate systems. Identifying further includes generating a cognitive processing model using machine learning adaptability for extracting NFRs for options for existing system designs. Classification overlay of each individual candidate system is provided across the NFRs prioritized based on business requirement. Unbiased decision processing utilized based on discord, exclusion and similarity as functions of the cognitive processing model. A sub-optimal solution space and adaptability for the sub-optimal solution space in absence of an optimal solution is identified.

Abstract: Hybrid edge computing that includes a nimble framework that identifies services for available in a marketplace. The nimble framework defines a location for computing the services selected from the group consisting of a center server, an edge provision server and an edge node. The hybrid edge computing further includes a third party provider making are request for a service to the nimble framework. The hybrid edge computing further includes a virtualized service being provided by the nimble framework to the third party provider including a matched service to the third party provider request for the service, and an optimal location for computing.

Abstract: A computer-implemented method according to one embodiment includes establishing, for each hop in pathways of a network, a relation between a desired reliability and channel error. Based on the established relations, a maximum number of copies of packets to send from a source in the network to a target in the network is determined. An overhead associated with sending packets from the source to the target in the network is determined for each of the hops, and a first sum of such overheads is also determined. An overhead associated with sending an acknowledgement packet to the source is determined for each of the hops. A second sum is a sum of the overheads associated with sending the acknowledgement packet to the source. In response to a determination that a sum of the first sum and the second sum is less than a predetermined threshold value, the pathways are used.

Abstract: A system, method, and computer program product for determining “impact quantify measure-based” service chains cross interferences. The method includes quantifying the impact of one service chain on another service chain and to what extent so as facilitate making an informed decision whether to garner more resources and to fine tune the computational services for the service chain. There is further provided beforehand a certainty of required computational resources and the providing the impact or interferences details of one service chain on another helps in minimization of service quality degradation failures. The framework further runs a method step to apply a mutual convexity method on service chains to aid in forecasting cross interferences between chains and includes a step wherein, interferences between both dependent and independent service chain is calculated and provided.

Abstract: A process for service chain instance pool sizing receives service requests for processing in a 5G network by a service function chain, of the 5G network, providing network function(s) to process the service requests. The method determines an average number of service requests to be processed, and determines a number of service chain instances to exist in a pool of service chain instances, of the service function chain, as a composite of (i) a number of instances to process service requests having arrived and making an initial relay through the service function chain and (ii) a number of instances to process service requests that were re-introduced after having previously arrived. The method additionally indicates the number of service chain instances to exist in the pool to a component responsible for controlling the number of service chain instances in the pool.

Abstract: A core set of nodes of a graph representing a network of devices is identified, a node of the graph representing a device in the network of devices, an edge of the graph representing an ability to transmit data between two devices represented by corresponding nodes of the graph. A device represented by a node more than one hop from any node in the core set of nodes of the graph is removed from the network of devices, the removing resulting in a validated network of devices. Using a number of devices in the validated network of devices, a number of security keys in use in the validated network is validated. A device in the validated network is caused to perform a task.

Abstract: A computer-implemented method for providing a framework to identify questions and answers dynamically from a dataset based on previous learning and an evaluation score of a user. The method includes creating a library of potential questions and answers from the dataset based on the previous learning and evaluation score of the user, and generating a set of personalized questions, for the user, related to the dataset by utilizing sentence-based machine translation (SBMT) and natural language processing (NLP) tools. The method further includes identifying a plurality of answers for the set of personalized questions for the user, based on collective information available in the dataset, and providing, to the user, the plurality of answers for the set of personalized questions for verification and evaluation.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining user data of at least one user to determine whether a criterion has been satisfied for running a prompting data session for prompting the at least one user; responsively to determining that the criterion has been satisfied for running the prompting data session for prompting the at least one user, running a prompting data session, wherein the running the prompting data session includes (a) establishing and iteratively updating a relationship graph and (b) presenting the iteratively updated relationship graph to one or more user.

Abstract: Identifying an indistinct entity within an image can include generating by an image filter multiple gradients, each of which corresponds to one of a plurality of pixels of an image captured by an imager. The image can be searched for a likely repeating pattern. Responsive to detecting, based on the multiple gradients, a likely repeating pattern within the image, data structures can be generated, the data structures comprising a set of probabilistically weighted feature vectors corresponding to the likely repeating pattern. A machine learning model can classify each of the set of probabilistically weighted feature vectors. An identity of the likely repeating pattern can be output, the identity based on the machine learning model classifications of the probabilistically weighted feature vectors.

Abstract: Cooperative session orchestration includes devising a crypt for pre-distribution of tokens, distributing the tokens to member nodes of the network, based on a request from a delegate node of the network for brokerage of a session between the delegate node and a supplier node of the network, creating and sending, for each of a plurality of potential supplier nodes of the network, a respective individual puzzle, receiving, from each of one or more potential supplier nodes of the plurality of potential supplier nodes, a respective result obtained by the potential supplier node from solving the individual puzzle using the token distributed to the potential supplier, identifying, based on the receiving, candidate supplier node(s) of the one or more potential supplier nodes as a potential supplier for the session with the delegate node, and identifying to the delegate node the candidate supplier node(s) for the session with the delegate node.

Abstract: Prioritizing a work request pertaining to a physical asset can include generating a data structure that encodes the work request as a multidimensional representation indicating at least one classification, each at least one classification including at least one sub-category. In response to identifying multiple work requests encoded as multidimensional representations with respect to the physical asset, each multidimensional representation can be reduced to a one-dimensional (1-D) representation that preserves a variance factor of each sub-category of each multidimensional representation. Each 1-D structure can be input to a machine learning model trained to prioritize each of the work requests. The work requests can be prioritized in accordance with the machine learning model based on the 1-D structures. The priorities of each of the work requests can be output.

Abstract: An approach for assessing terms and conditions (TnC)s of a legal agreement is provided. A block of text, which contains a TnC of the set of TnC, in the legal agreement is identified using a cognitive system. A standardized significance value is assigned to the TnC by the cognitive system by applying the TnC to a TnC model containing corresponding industry TnCs from industry standard documents. A block currency that indicates a significance of an impact of the TnC to a contract party is computed for the TnC by the cognitive system. Based on the standardized significance value and the block currency, a personal impact of the TnC to the contract party is assessed by the cognitive system. The contract party is alerted to the TnC and the personal impact corresponding to the TnC.

Abstract: Setting a primary server within a business density cluster when the business density location changes. A new primary edge provisioning server replaces a current primary edge provisioning server when the business density cluster is determined not to include the current primary edge provisioning server. An edge provisioning framework handles the associations and dissociations of the edge network(s) to build the new primary server within the business density cluster. The former primary server is respawned as a new secondary node to the new primary server.

Abstract: Provisioning business functions is provided. A runtime binary activation code is sent to a nodal edge server that has a needed runtime binary for a set of edge devices to perform a business function. A secure shell protocol connection with root operating system access is established to the nodal edge server that has the needed runtime binary to execute the runtime binary activation code.

Abstract: Edge service deployment with network slice invocation is provided, which includes obtaining one or more service-related parameters for network slice invocation to support an edge service instance, and requesting a network slice from a network based on the obtained one or more service-related parameters. The requesting from the network is via a collaboration platform. Further, the edge service deployment and network slice invocation includes receiving from the network, based on requesting of the network slice, network slice invocation codes, and initiating activating of the edge service instance over the network slice of the network using the network slice invocation codes.

Abstract: Runtime binary migration is provided. A slice of a 5G network is provisioned based on time period and bandwidth requirements in accordance with a service level agreement corresponding to a customer requesting performance of a business function transaction. A runtime binary for invoking the slice of the 5G network is migrated to a nodal edge server for a set of edge devices associated with the nodal edge server to perform the business function transaction using the slice of the 5G network.

Abstract: Edge service deployment with network slice invocation is provided, which includes obtaining one or more service-related parameters for network slice invocation to support an edge service instance, and requesting a network slice from a network based on the obtained one or more service-related parameters. The requesting from the network is via a collaboration platform. Further, the edge service deployment and network slice invocation includes receiving from the network, based on requesting of the network slice, network slice invocation codes, and initiating activating of the edge service instance over the network slice of the network using the network slice invocation codes.