Felix Heine

Towards ontology-driven P2P grid resource discovery

In this paper we present a new approach to semantic resource discovery in the grid. A peer-to-peer network is used to distribute and query the resource catalogue. Each peer can provide resource descriptions and background knowledge, and each peer can query the network for existing resources. We do not require a central ontology for resource description and matching. Each peer has its own, possibly incomplete, ontology, which is completed by the knowledge distributed over the network. This allows to find matching resources even if the concepts used to describe the resources are unknown to the provider, as the network supplies the missing parts of the ontology.

On triple dissemination, forward-chaining, and load balancing in DHT based RDF stores

The Resource Description Framework provides a powerful model for structured knowledge representation that allows the inference of new knowledge. Because of the anticipated scope of semantic information available in the future, centralized databases will become incapable of handling the load. Peer-to-Peer based distributed databases offer better scalability and integration of many different data sources. In this paper we present a detailed data management strategy for a DHT based RDF store that provides reasoning, robustness, and load-balancing.

Scalable p2p based RDF querying

In large-scale distributed systems, information is typically generated decentralized. However, for many applications it is desirable to have a unified view on this knowledge, allowing to query it without regarding the heterogeneity of the underlying systems. In this context, two main requirements have to be fulfilled. On the one hand, we need a flexible knowledge representation, and on the other hand the underlying infrastructure and query evaluation algorithm has to be highly scalable.The combination of p2p networks as basic infrastructure with RDF as a knowledge representation is a promising approach to this problem. Within this paper, we focus on the evaluation of RDF queries with respect to RDF data stored in a DHT-based p2p network. We propose a query algorithm and research different optimizations based on a look-ahead technique and Bloom filters which aim at maximizing the throughput and scalability of the entire system.

On the impact of reservations from the grid on planning-based resource management

Advance Reservations are an important concept to support QoS and Workflow Scheduling in Grid environments. However, the impact of reservations from the Grid on the performance of local schedulers is not yet known. Using discrete event simulations we evaluate the impact of reservations on planning-based resource management of standard batch jobs. Our simulations are based on a real trace from the parallel workload archive. By introducing a new option for scheduling reservations in planning-based resource management, less reservation requests are rejected. Our results are important for increasing the acceptability of the Grid technology. We show, that a limited number of additional resource reservations from the Grid have only a limited impact on the performance of the traditionally submitted batch jobs.

Processing complex RDF queries over P2P networks

In large-scale distributed systems, information is typically generated decentralized. However, for many applications it is desirable to have a unified view on this knowledge, allowing to reason about it and to query it without regarding the heterogeneity of the underlying systems. In this context, two main requirements have to be fulfilled. On the one hand, a retrieval system has to be semantically rich, in order to be able to cope with and mediate between different schemas, and on the other hand it has to be scalable to large numbers of information sources. The dynamic nature of information makes the problem even worse.Within this paper, we propose a solution to this problem. We describe a DHT-based peer-2-peer network storing knowledge in the form of RDF triples. The query evaluation algorithm allows to use arbitrary query patterns, and evaluates the query with respect to taxonomical reasoning. Thus the system combines expressivity and scalability. Although we describe the whole system, the focus of this paper is the query evaluation.The system is generic by nature and suitable for numerous different applications. We describe an example application stemming from the Semantic Grid.

Top k RDF query evaluation in structured P2P networks

Berners-Lees vision of the Semantic Web describes the idea of providing machine readable and processable information using key technologies such as ontologies and automated reasoning in order to create intelligent agents. The prospective amount of machine readable information available in the future will be large. Thus, heterogeneity and scalability will be central issues, rendering exhaustive searches and central storage of data infeasible. This paper presents a scalable peer-to-peer based approach to distributed querying of Semantic Web information that allows ordering of entries in result sets and limiting the size of result sets which is necessary to prevent results with millions of matches. The system relies on the graph-based W3C standard Resource Description Framework (RDF) for knowledge description. Thereby, it enables queries on large, distributed RDF graphs.

Volume Driven Data Distribution for NUMA-Machines

Highly scalable parallel computers, e.g. SCI-coupled workstation clusters, are NUMA architectures. Thus good static locality is essential for high performance and scalability of parallel programs on these machines. This paper describes novel techniques to optimize static locality at compilation time by application of data transformations and data distributions. The metric which guides the optimizations employs Ehrhart polynomials and allows to calculate the amount of static locality precisely. The effectiveness of our novel techniques has been confirmed by experiments conducted on the SCI-coupled workstation cluster of the PC2 at the University of Paderborn.

The Virtual Resource Manager: Local Autonomy Versus QoS Guarantees for Grid Applications

In this paper, we describe the architecture of the virtual resource manager VRM, a management system designed to reside on top of local resource management systems for cluster computers and other kinds of resources. The most important feature of the VRM is its capability to handle quality-of-service (QoS) guarantees and service-level agreements (SLAs). The particular emphasis of the paper is on the various opportunities to deal with local autonomy for resource management systems not supporting SLAs. As local administrators may not want to hand over complete control to the Grid management, it is necessary to define strategies that deal with this issue. Local autonomy should be retained as much as possible while providing reliability and QoS guarantees for Grid applications, e.g., specified as SLAs.

A quality-of-service architecture for future grid computing applications

The next generation grid applications demand grid middleware for a flexible negotiation mechanism supporting various ways of quality-of-service (QoS) guarantees. In this context, a QoS guarantee covers simultaneous allocations of various kinds of different resources, such as processor runtime, storage capacity, or network bandwidth, which are specified in the form of service level agreements (SLA). Currently, a gap exists between the capabilities of grid middleware and the underlying resource management systems concerning their support for QoS and SLA negotiation. In this paper we present an approach which closes this gap. Introducing the architecture of the virtual resource manager, we highlight its main QoS management features like run-time responsibility, co-allocation, and fault tolerance.

SLA-aware job migration in grid environments

Grid Computing promises an efficient sharing of world-wide distributed resources, ranging from hardware, software, expert knowledge to special I/O devices. However, although the main Grid mechanisms are already developed or are currently addressed by tremendous research effort, the Grid environment still suffers from a low acceptance in different user communities. Beside difficulties regarding an intuitive and comfortable resource access, various problems related to the reliability and the Quality-of-Service while using the Grid exist. Users should be able to rely, that their jobs will have certain priority at the remote Grid site and that they will be finished upon the agreed time regardless of any provider problems. Therefore, QoS issues have to be considered in the Grid middleware but also in the local resource management systems at the Grid sites. However, most of the currently used resource management systems are not suitable for SLAs, as they do not support resource reservation and do not offer mechanisms for job checkpointing/migration respectively. The latter are mandatory for Grid providers as rescue anchor in case of system failures or system overload. This paper focuses on SLA-aware job migration and presents a work, which is being performed in the EU supported project HPC4U.