International Business Machines Corporation

Balaji Viswanathan

Akshat Verma

Praveen Jayachandran

Senthilnathan Natarajan

Gargi Banerjee Dasgupta

Krishnasuri Narayanam

Vinayaka D Pandit

Koustuv Dasgupta

Amit Anil Nanavati

Sougata Mukherjea

Ajay Gupta

Xiaolan Zhang

Florian Graf

Madhusudanan Kandasamy

Arvind Agarwal

Lakshminarayanan Renganarayana

Rema Ananthanarayanan

Kamal Bhattacharya

Dipanjan Chakraborty

Harshit Kumar

Rahul Singh

Deepak Kumar Jeswani

Marcel Schlatter

Kristiann J Schultz

Bharat Krishnamurthy

Gaurab Basu

Ramblias Varma

Sourav Dutta

Sankalp Gera

Yu Gu

Ajay Mohindra

Ravi Kothari

Roberta Jo Cochrane

Anindya Neogi

Rohit Ranchal

Manish Sethi

Shripad Jayant Nadgowda

Chander Govindarajan

Mudit Verma

Seep Goel

Tapan Kumar Nayak

An example operation may include one or more of connecting, by a lead peer, to a blockchain network of an organization configured to store assets, receiving, by the lead peer, from an ordering server, a block that contains a plurality of chaincode transactions belonging to plurality of peers of the blockchain network, applying, by the lead peer, a filter to the block, determining, by the lead peer, a recipient peer of the block in response to the application of the filter, receiving, by the lead peer, a validation result of the block from the recipient peer, and committing, by the lead peer, the block to the blockchain network.

Sparse peer with transient participation

An example operation may include one or more of connecting, by a sparse peer, to a blockchain network of a plurality of peers controlled by orderers, selecting, by the sparse peer, a subset of data to be replicated, specifying, by the sparse peer, data selection filters based on the selected subset of the data, providing, by the sparse peer, the selection filters to the plurality of the peers, receiving, by the sparse peer, blocks matching the selection filters over a gossip protocol from the plurality of the peers, constructing, by the sparse peer, a local ledger of the sparse peer from the received blocks, and bootstrapping the sparse peer based on the local ledger.

An example operation may include one or more of connecting, by a lead peer, to a blockchain network of an organization configured to store assets, receiving, by the lead peer, a block from an ordering server, that contains a plurality of chaincode transactions belonging to a plurality of peers of the blockchain, applying, by the lead peer, a filter to the block, determining, by the lead peer, a recipient peer of the block in response to the application of the filter, and receiving, by the lead peer, a notification of validation and commitment of the block to the blockchain by the recipient peer.

A computer-implemented method gathers a set of previously filed applications, performs intent identification on the set, clusters applications in the set based on identified common intents, receives input from user and identifying intent of the input, matches the input to a cluster based on a common intent, and generates a new application based on the input using filed applications in a cluster having a common intent between the cluster and the input.

Automatical process application generation

An example operation may include one or more of receiving, via a network, a blockchain request from a client device, simulating a transaction of the blockchain request to generate a read set of data being read by the transaction and a write set of data being written by the transaction, determining whether to endorse the transaction with respect to a distributed ledger by executing customizable endorsement logic of the blockchain node, wherein the executing customizable endorsement logic receives, as input, the generated read and write sets and determines whether or not the transaction should be committed to a data block of the distributed ledger based on the generated read and write sets, and transmitting information about a result of the customized endorsement logic determination to the client device.

Customized endorsement logic for blockchain

One embodiment provides a method, including: obtaining a plurality of previously submitted application documents, wherein each of the previously submitted application documents comprises information provided by a user who initiated a given previously submitted application document; clustering the plurality of previously submitted application documents into clusters of application documents based upon topics of the previously submitted application documents; selecting a representative application document; identifying entities contained within a given representative application document, wherein each of the entities corresponds to information to be entered into a new application document created from the given representative application document; and engaging in a dialogue with a user to create the new application document utilizing a similar representative application document to request information from the user, wherein the similar representative application document comprises a representative application document of a cluster having a topic similar to a topic of the new application document.

Generation and population of new application document utilizing historical application documents

An example operation may include one or more of a processor configured to receive a database command from a client system, the database command comprising a database function and parameters to be used by the database function, and to execute the database command on database data, and an interface configured to transmit the database command to one or more other databases that are within a decentralized database system in which each database node is controlled by a different entity, wherein in response to receiving a request from an ordering node of the decentralized database system, the processor may commit results of executing the database command to a database and store information about the database command in an append-only immutable database log.

Distributed database having blockchain attributes

An example operation may include one or more of connecting, by a sparse peer, to a blockchain network of a plurality of peers controlled by orderers, configuring the sparse peer to operate with a partial state of a chain to reduce a bootstrap time of the sparse peer, specifying, by the sparse peer, data selection filters based on the partial state of the chain, receiving, by the sparse peer, blocks that match the selection filters from the plurality of the peers via a gossip, storing, by the sparse peer, the blocks in a ledger of the sparse peer, determining, by the sparse peer, if the ledger of the sparse peer is up-to-date based on the partial state of the chain, and in response to the determination that the ledger of the sparse peer is up-to-date, bootstrapping the sparse peer.

The example embodiments are directed to a system and method for detecting phantom data items in a blockchain transaction. In an example, the method includes one or more of generating a transaction data set during a read phase of a blockchain transaction, the transaction data set including an identification of each query of the transaction executed during the read phase and results of each query, generating a validation data set by re-executing each query during a validation phase of the blockchain transaction, the validation data set including query results of each respective re-executed query, determining whether the blockchain transaction observes one or more phantom data items based on the query results of the transaction data set and the validation data set, and, in response to determining the transaction observes the one or more phantom data items, preventing the transaction data set from being written to the blockchain.

Detecting phantom items in distributed replicated database

An example operation may include one or more of receiving a request comprising a file segmented into a plurality of segments corresponding to a plurality of storage nodes, identifying a segment from among the plurality of segments which is designated for the storage node from among remaining segments designated for other storage nodes, storing the identified segment in a local storage of the storage node, hashing the identified segment, and transmitting a response to a client system which includes the hashed identified segment.

Private and fault-tolerant storage of segmented data

Techniques for non-invasive diagnosis of configuration errors in distributed system are disclosed including obtaining data packets from a network that include inflows and outflows associated with a given component of the network. The number of inflows and the number of outflows for the given component of the network are determined based on the obtained data packets. An intersection point corresponding to a predetermined number of inflows and a predetermined number of outflows is obtained and a score for the given component is determined based on a relationship between the intersection point and the determined number of inflows and outflows for the given component. Whether the score for the given component is greater than a predetermined threshold is determined, and the given component is identified as having a configuration error in response to determining that the score for the given component is greater than a predetermined threshold.

Non-invasive diagnosis of configuration errors in distributed system

An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

Adjustment to managed-infrastructure-as-a-service cloud standard

A service method and associated system is provided. The method includes generating event types for events and services associated with the events. Virtual or physical machines associated with the services are provisioned and a message associated with a first event is published. The message is routed to a queue of a second service and the second service is notified of the message. The services are enabled and a selection for a sub-set of the services is received. The selection is enabled.

Modularly managed service platform

Methods and arrangements for providing assistance with troubleshooting for system updates. There is sent, to a first database, a feature log associated with an update event at a first location. The feature log is pooled in the first database with feature logs associated with update events at other locations. A signature is created of at least one update from the first database, and the signature is added to a signature database. The signature database is employed to identify one or more deviations, when the at least one update fails in at least one location. The one or more deviations are ranked with respect to at least one other deviation. Other variants and embodiments are broadly contemplated herein.

Growing community of inventors

Bengaluru, India

Balaji Viswanathan