Computing and Information Systems - Research Publications

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    Scheduling parameter sweep applications on global Grids: A deadline and budget constrained cost-time optimization algorithm
    Buyya, R ; Murshed, M ; Abramson, D ; Venugopal, S (Wiley, 2005)
    Computational Grids and peer-to-peer (P2P) networks enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. The management and composition of resources and services for scheduling applications, however, becomes a complex undertaking. We have proposed a computational economy framework for regulating the supply of and demand for resources and allocating them for applications based on the users' quality-of-service requirements. The framework requires economy-driven deadline- and budget-constrained (DBC) scheduling algorithms for allocating resources to application jobs in such a way that the users' requirements are met. In this paper, we propose a new scheduling algorithm, called the DBC cost-time optimization scheduling algorithm, that aims not only to optimize cost, but also time when possible. The performance of the cost-time optimization scheduling algorithm has been evaluated through extensive simulation and empirical studies for deploying parameter sweep applications on global Grids.
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    Lock-free parallel dynamic programming
    Stivala, A ; Stuckey, PJ ; Garcia de la Banda, M ; Hermenegildo, M ; Wirth, A (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2010-08)
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    An SCP-based heuristic approach for scheduling distributed data-intensive applications on global grids
    Venugopal, S ; Buyya, R (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2008-04)
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    A least flow-time first load sharing approach for distributed server farm
    Tari, Z ; Broberg, J ; Zomaya, AY ; Baldoni, R (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2005-07)
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    Secure communication in Mobile Ad Hoc network using efficient certificateless encryption
    Lee, PHJ ; Parampalli, U ; Narayan, S (Academy Publisher, 2009-11-10)
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    A taxonomy of data grids for distributed data sharing, management, and processing
    Venugopal, S ; Buyya, R ; Ramamohanarao, K (Association for Computing Machinery (ACM), 2006)
    Data Grids have been adopted as the next generation platform by many scientific communities that need to share, access, transport, process, and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this article, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks, and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation, and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration.
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    A grid workflow environment for brain imaging analysis on distributed systems
    Pandey, S ; Voorsluys, W ; Rahman, M ; Buyya, R ; Dobson, JE ; Chiu, K (WILEY, 2009-11)
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    Multiobjective differential evolution for scheduling workflow applications on global Grids
    Talukder, AKMKA ; Kirley, M ; Buyya, R (WILEY, 2009-09-10)
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    Portfolio and investment risk analysis on global grids
    Moreno-Vozmediano, R ; Nadiminti, K ; Venugopal, S ; Alonso-Conde, AB ; Gibbins, H ; Buyya, R (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2007-12)
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    Intrusion detection for routing attacks in sensor networks
    Loo, CE ; Ng, MY ; Leckie, C ; Palaniswami, M (SAGE PUBLICATIONS INC, 2006)
    Security is a critical challenge for creating robust and reliable sensor networks. For example, routing attacks have the ability to disconnect a sensor network from its central base station. In this paper, we present a method for intrusion detection in wireless sensor networks. Our intrusion detection scheme uses a clustering algorithm to build a model of normal traffic behavior, and then uses this model of normal traffic to detect abnormal traffic patterns. A key advantage of our approach is that it is able to detect attacks that have not previously been seen. Moreover, our detection scheme is based on a set of traffic features that can potentially be applied to a wide range of routing attacks. In order to evaluate our intrusion detection scheme, we have extended a sensor network simulator to generate routing attacks in wireless sensor networks. We demonstrate that our intrusion detection scheme is able to achieve high detection accuracy with a low false positive rate for a variety of simulated routing attacks.