Data management in dynamic distributed computing environments

Kelley, Ian Robert 2012. Data management in dynamic distributed computing environments. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Data management in parallel computing systems is a broad and increasingly important research topic. As network speeds have surged, so too has the movement to transition storage and computation loads to wide-area network resources. The Grid, the Cloud, and Desktop Grids all represent different aspects of this movement towards highly-scalable, distributed, and utility computing. This dissertation contends that a peer-to-peer (P2P) networking paradigm is a natural match for data sharing within and between these heterogeneous network architectures. Peer-to-peer methods such as dynamic discovery, fault-tolerance, scalability, and ad-hoc security infrastructures provide excellent mappings for many of the requirements in today’s distributed computing environment. In recent years, volunteer Desktop Grids have seen a growth in data throughput as application areas expand and new problem sets emerge. These increasing data needs require storage networks that can scale to meet future demand while also facilitating expansion into new data-intensive research areas. Current practices are to mirror data from centralized locations, a technique that is not practical for growing data sets, dynamic projects, or data-intensive applications. The fusion of Desktop and Service Grids provides an ideal use-case to research peer-to-peer data distribution strategies in a hybrid environment. Desktop Grids have a data management gap, while integration with Service Grids raises new challenges with regard to cross-platform design. The work undertaken here is two-fold: first it explores how P2P techniques can be leveraged to meet the data management needs of Desktop Grids, and second, it shows how the same distribution paradigm can provide migration paths for Service Grid data. The result of this research is a Peer-to-Peer Architecture for Data-Intensive Cycle Sharing (ADICS) that is capable not only of distributing volunteer computing data, but also of providing a transitional platform and storage space for migrating Service Grid jobs to Desktop Grid environments.

Item Type:	Thesis (PhD)
Status:	Unpublished
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	P2P, BOINC, Desktop Grid, Data Intensive, EGEE, EDGI, EDGeS, Peer to Peer, XtremWeb, ADICS, Attic, Networking, Superpeer
Date of First Compliant Deposit:	30 March 2016
Last Modified:	11 Sep 2023 13:39
URI:	https://orca.cardiff.ac.uk/id/eprint/44477

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