Distributed scheduler for high performance data-centric systems

Sushant Goel; Hema Sharda; David Taniar

Distributed scheduler for high performance data-centric systems

Sushant Goel, Hema Sharda, David Taniar

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Abstract

Amount of data stored in enterprises are increasing rapidly. Volume of data stored in database is approaching to terabyte size. Response time is directly proportional to the amount of data in databases. Requirement of fast response time under these circumstances have motivated the research of Parallel Database Systems (PDS) during last decade. Despite distribution of data in PDS to various Processing Elements (PE), concurrency control algorithms uses centralized scheduling approach. This approach has inherent weakness, under heavy load conditions, such as - big lock table, more number of messages in the system, central overloaded scheduler. In this paper we distribute the scheduling responsibilities to the nodes where data is actually located. We also propose a new serializability criterion, Parallel Database Quasi-Serializability, to meet these requirements.

Original language	English
Title of host publication	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1157-1161
Number of pages	5
Publication status	Published - 2003
Event	IEEE Tencon (IEEE Region 10 Conference) 2003 - Bangalore, India Duration: 15 Oct 2003 → 17 Oct 2003 https://ieeexplore.ieee.org/xpl/conhome/8975/proceeding?isnumber=28487 (Proceedings)

Conference

Conference	IEEE Tencon (IEEE Region 10 Conference) 2003
Abbreviated title	TENCON 2003
Country/Territory	India
City	Bangalore
Period	15/10/03 → 17/10/03
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8975/proceeding?isnumber=28487 (Proceedings)

Cite this

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title = "Distributed scheduler for high performance data-centric systems",

abstract = "Amount of data stored in enterprises are increasing rapidly. Volume of data stored in database is approaching to terabyte size. Response time is directly proportional to the amount of data in databases. Requirement of fast response time under these circumstances have motivated the research of Parallel Database Systems (PDS) during last decade. Despite distribution of data in PDS to various Processing Elements (PE), concurrency control algorithms uses centralized scheduling approach. This approach has inherent weakness, under heavy load conditions, such as - big lock table, more number of messages in the system, central overloaded scheduler. In this paper we distribute the scheduling responsibilities to the nodes where data is actually located. We also propose a new serializability criterion, Parallel Database Quasi-Serializability, to meet these requirements.",

author = "Sushant Goel and Hema Sharda and David Taniar",

year = "2003",

language = "English",

pages = "1157--1161",

booktitle = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE Tencon (IEEE Region 10 Conference) 2003, TENCON 2003 ; Conference date: 15-10-2003 Through 17-10-2003",

url = "https://ieeexplore.ieee.org/xpl/conhome/8975/proceeding?isnumber=28487",

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T1 - Distributed scheduler for high performance data-centric systems

AU - Goel, Sushant

AU - Sharda, Hema

AU - Taniar, David

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AB - Amount of data stored in enterprises are increasing rapidly. Volume of data stored in database is approaching to terabyte size. Response time is directly proportional to the amount of data in databases. Requirement of fast response time under these circumstances have motivated the research of Parallel Database Systems (PDS) during last decade. Despite distribution of data in PDS to various Processing Elements (PE), concurrency control algorithms uses centralized scheduling approach. This approach has inherent weakness, under heavy load conditions, such as - big lock table, more number of messages in the system, central overloaded scheduler. In this paper we distribute the scheduling responsibilities to the nodes where data is actually located. We also propose a new serializability criterion, Parallel Database Quasi-Serializability, to meet these requirements.

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M3 - Conference Paper

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BT - IEEE Region 10 Annual International Conference, Proceedings/TENCON

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE Tencon (IEEE Region 10 Conference) 2003

Y2 - 15 October 2003 through 17 October 2003

ER -

Distributed scheduler for high performance data-centric systems

Abstract

Conference

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