Artikel in Zeitschrift ART-2009-26

Bibliograph.
Daten
Schulz, Sven; Blochinger, Wolfgang; Hannak, Hannes: Capability-Aware Information Aggregation in Peer-to-Peer Grids.
In: Journal of Grid Computing. Vol. 7(2).
Universität Stuttgart, Fakultät Informatik.
S. 135-167, englisch.
Heidelberg: Springer-Verlag, 17. Januar 2009.
DOI: 10.1007/s10723-008-9114-z.
Artikel in Zeitschrift.
CR-Klassif.C.2.1 (Network Architecture and Design)
C.2.2 (Network Protocols)
C.2.4 (Distributed Systems)
C.2.6 (Internetworking)
Kurzfassung

Information aggregation is the process of summarizing information across the nodes of a distributed system. We present a hierarchical information aggregation system tailored for Peer-to-Peer Grids which typically exhibit a high degree of volatility and heterogeneity of resources. Aggregation is performed in a scalable yet efficient way by merging data along the edges of a logical self-healing tree with each inner node providing a summary view of the information delivered by the nodes of the corresponding subtree. We describe different tree management methods suitable for high-efficiency and high-scalability scenarios that take host capability and stability diversity into account to attenuate the impact of slow and/or unstable hosts. We propose an architecture covering all three phases of the aggregation process: Data gathering through a highly extensible sensing framework, data aggregation using reusable, fully isolated reduction networks, and application-sensitive data delivery using a broad range of propagation strategies. Our solution combines the advantages of approaches based on Distributed Hash Tables (DHTs) (i.e., load balancing and self-maintenance) and hierarchical approaches (i.e., respecting administrative boundaries and resource limitations). Our approach is integrated into our Peer-to-Peer Grid platform Cohesion. We substantiate its effectiveness through performance measurements and demonstrate its applicability through a graphical monitoring solution leveraging our aggregation system.

Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Höchstleistungsrechner, Verteilte Systeme
Projekt(e)Grid Computing
Eingabedatum19. April 2010
   Publ. Abteilung   Publ. Institut   Publ. Informatik