k-RP*s: a scalable distributed data structure for high-performance multi-attribute access

Litwin, Witold; Neimat, Marie-Anne

doi:10.1109/pdis.1996.568674

Cited by 22 publications

(16 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly the anti-tetanus toxoid probably contained Gm (a-fb-), Gm (a -b + ) and Gm (a-b -) molecules. The antilevan from this subject was subsequently shown to be Gm (f+ ) but once again the titer was much lower than would be expected (131). The data are best interpreted on the hypothesis that contact with antigen causes chance stimulation of certain lines of cells which then elaborate antibody yG globulin with Gm determinants corresponding to those of the type for which their synthetic capacities were originally programmed.…”

Section: S Tructure and H Eterogeneity Of A Ntibodies* Ea K A B A Tmentioning

confidence: 67%

Structure and Heterogeneity of Antibodies

Kabat¹

1966

Acta Haematol

View full text Add to dashboard Cite

Section: S Tructure and H Eterogeneity Of A Ntibodies* Ea K A B A Tmentioning

confidence: 67%

Structure and Heterogeneity of Antibodies

Kabat¹

1966

Acta Haematol

View full text Add to dashboard Cite

“…Some SDDSs are range partitioned, from RP* based systems [10] up to BATON [4] most recently. There were also proposals for k-d partitioning, e.g., k-RP [14] using distributed kd-trees for data points, or hQT* [10] using quad-trees for the same purpose. Hambrusch and Khokhar [6] present a distributed data structure based on orthogonal bisection trees (2-d KD trees).…”

Section: Related Workmentioning

confidence: 99%

Virtual and Consistent Hyperbolic Tree: A New Structure for Distributed Database Management

Magoni

2015

Networked Systems

View full text Add to dashboard Cite

Abstract. This paper describes a new scalable, reliable and consistent structure for implementing a distributed database system. This structure is based on the hyperbolic geometry and we call it a Virtual and Consistent Hyperbolic tree (VCH-tree). This structure is intended for supporting queries over possibly large spatial datasets distributed over interconnected servers. The VCH-tree is comparable to the well-known R-tree structure, but it uses the hyperbolic geometry properties of the Poincaré disk model. It uses a distributed balanced Q-degree spatial tree that scales with data objects' insertions into potentially any number of storage servers through virtual hyperbolic coordinates. A user application manipulates the structure from a client node. The client can connect to the system through one of the database servers that is already in the VCH-tree. Messages are then routed towards the proper server by a greedy algorithm which is using the virtual hyperbolic coordinates attributed to each server. We have performed simulations to assess the efficiency and reliability of the VCH-tree. Results show that our VCHtree is consistent and has expected performances given the scalability and flexibility it provides to distributed database applications.

show abstract

“…Several other approaches that use distributed hierarchical index structures such as R-tree based SD-Rtree [14] and kdtree based k-RP [15] have been proposed for parallel spatial query processing. The major problem with the tree-based approaches is that they do not scale due to the traditional topdown search that overloads the nodes near the tree root, and fail to provide full decentralization.…”

Section: B Cloud-based Spatial Index Structuresmentioning

confidence: 99%

ToSS-it: A Cloud-Based Throwaway Spatial Index Structure for Dynamic Location Data

Akdogan

Shahabi

Demiryurek

2014

2014 IEEE 15th International Conference on Mobile Data Management

View full text Add to dashboard Cite

Abstract-The widespread use of GPS-enabled devices have led to a number of emerging applications that require monitoring and querying a large number of moving objects, such as in location-based services, mobile phone social networking, UAV surveillance, and car navigation systems. In such applications, indexes for moving objects must support queries efficiently and also cope with frequent updates. In this paper, we propose a cloud-based throwaway index structure, dubbed ToSS-it, where we generate the index from scratch in a short period of time rather than updating it with every location change of the moving objects.ToSS-it employs inter-node and intra-node multi-core parallelism paradigm to rapidly construct a distributed Voronoi Diagram. ToSS-it scales out by using a voronoi partitioning technique that minimizes the network message exchanges between the nodes (i.e., the major overhead in parallel generation of Voronoi Diagrams), and scales up since it fully exploits the multi-core CPUs available on each server. As a comparison point, with the state-of-the-art cloud-based spatial index structure (RT-CAN), if at least 7% of the objects are moving and issue updates to the index, it is faster to recreate ToSS-it from scratch than updating RT-CAN.

show abstract

k-RP*s: a scalable distributed data structure for high-performance multi-attribute access

Cited by 22 publications

References 8 publications

Structure and Heterogeneity of Antibodies

Structure and Heterogeneity of Antibodies

Virtual and Consistent Hyperbolic Tree: A New Structure for Distributed Database Management

ToSS-it: A Cloud-Based Throwaway Spatial Index Structure for Dynamic Location Data

Contact Info

Product

Resources

About