Nec Laboratories America, Inc.

Nec Corporation

Hyun Jin Moon

Yun Chi

Vahit Hakan Hacigumus

Junichi Tatemura

V Hakan Hacigumus

Shenghuo Zhu

Oliver Po

Wang-Pin Hsiung

Pengcheng Xiong

Arsany Sawires

Shenoda Guirguis

Hatem Abdelghani Mahmoud

Wang Pin Hsiung

Sean Barker

Systems and methods for consolidating workload on one or more computing devices, comprising: generating tenant performance profiles for at least one of a buffer memory size and a buffer warmness; assigning one or more tenants to a database management system (DBMS) instance; configuring the one or more tenants to minimize a total server count needed to host the one or more tenants; and reducing the total server count by adjusting of buffer sizes while satisfying Service Level Agreement (SLA) requirements.

System and method for SLA-aware database consolidation using per-tenant memory size configuration

A computer implemented method of workload scheduling under two different types of Service Level Agreements (SLAs), namely soft and hard SLA which employ both a deadline- and cost-aware scheduler called iCBS-DH. The scheduler is evaluated against deadline and cost performance of various scheduling policies under a large range of SLA cost function and deadline types.

Scheduling methods using soft and hard service level considerations

Methods and systems for database migration from a multitenant database include taking a snapshot of an original database to be migrated with a hot backup process, such that the database is still capable of answering queries during the hot backup process; maintaining a query log of all queries to the tenant database after the hot backup process begins; initializing a new database at a target server using the snapshot; replaying the query log synchronize the new database with the original database; and answering new queries with the new database and not the original database.

Latency-aware live migration for multitenant database platforms

An efficient cost-based scheduling method called incremental cost-based scheduling, iCBS, maps each job, based on its arrival time and SLA function, to a fixed point in the dual space of linear functions. Due to this mapping, in the dual space, the job will not change their locations over time. Instead, at the time of selecting the next job with the highest priority to execute, a line with appropriate angle in the query space is used to locate the current job with the highest CBS score in logarithmic time. Because only those points that are located on the convex hull in the dual space can be chosen, a dynamic convex hull maintaining method incrementally maintains the job with the highest CBS score over time.

Highly scalable cost based SLA-aware scheduling for cloud services

Systems and methods are disclosed to schedule jobs in a cloud computing infrastructure by receiving in a first queue jobs with deadlines or constraints specified in a hard service level agreement (SLA); receiving in a second queue jobs with a penalty cost metric specified in a soft SLA; and minimizing both constraint violation count and total penalty cost in the cloud computing infrastructure by identifying jobs with deadlines in the first queue and delaying jobs in the first queue within a predetermined slack range in favor of jobs in the second queue to improve the penalty cost metric.

Constraint-conscious optimal scheduling for cloud infrastructures

A swap-based multitenant database load balancing (SWAT) invention finds an optimal swap set that eliminates hotspots, and finds a sequencing and parallelization of swap executions for the multitenant database.

Replica based load balancing in multitenant databases

Systems and methods are disclosed to consolidate workload on cloud-based computers by co-locating one or more high-penalty tenants on one or more cloud-based servers; reducing service level agreement (SLA) violations by over-provisioning the cloud-based server; and maximizing an SLA profit.

Multi-tenant database management for service level agreement (SLA) profit maximization

A system includes one or more application nodes sending SQL queries to one or more query execution nodes. Each query execution node translates the SQL queries into key-based requests to the storage engine, which comprises one or more storage nodes. The system provides an abstraction layer with an external schema and an internal schema, maps the external schema into the internal schema; and generates one or more microshards for the storage node.

System and methods for database distribution and querying over key-based scalable storage

Systems and methods are disclosed to manage resources in a cloud-based computing system by generating a model of a relationship between cloud database resources and an expected profit based on cloud-server system parameters and service level agreements (SLAs) that indicates profits for different system performances, wherein the model comprises a two level optimization/control problem, wherein model receives system metrics, number of replicas, and arrival rate as the multiple input; and dynamically adjusting resource allocation among different customers based on current customer workload and the expected profit to maximize the expected profit for a cloud computing service provider.

Intelligent management of virtualized resources for cloud database systems

Systems and methods are disclosed for scheduling one or more queries for execution with one or more cloud computers by applying a service level agreement (SLA) analysis using an SLA-tree data structure to each query in a query queue; using the SLA-tree data structure to determine an overall profit in the query queue; and generating a profit-oriented schedule to select the next query for execution by the cloud computers.

Growing community of inventors

Newark, CA, United States of America

Hyun Jin Moon