Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.

Mersenne numbers

These notes have been issued on a small scale in 1983 and 1987 and on request at other times. This issue follows two items of news. First, WaIter Colquitt and Luther Welsh found the 'missed' Mersenne prime M110503 and advanced the frontier of complete Mp-testing to 139,267. In so doing, they terminated Slowinski's significant string of four consecutive Mersenne primes. Secondly, a team of five established a non-Mersenne number as the largest known prime. This result terminated the 1952-89 reign of Mersenne primes. All the original Mersenne numbers with p < 258 were factorised some time ago. The Sandia Laboratories team of Davis, Holdridge & Simmons with some little assistance from a CRAY machine cracked M211 in 1983 and M251 in 1984. They contributed their results to the 'Cunningham Project', care of Sam Wagstaff. That project is now moving apace thanks to developments in technology, factorisation and primality testing. New levels of computer power and new computer architectures motivated by the open-ended promise of parallelism are now available. Once again, the suppliers may be offering free buildings with the computer. However, the Sandia '84 CRAY-l implementation of the quadratic-sieve method is now outpowered by the number-field sieve technique. This is deployed on either purpose-built hardware or large syndicates, even distributed world-wide, of collaborating standard processors. New factorisation techniques of both special and general applicability have been defined and deployed. The elliptic-curve method finds large factors with helpful properties while the number-field sieve approach is breaking down composites with over one hundred digits. The material is updated on an occasional basis to follow the latest developments in primality-testing large Mp and factorising smaller Mp; all dates derive from the published literature or referenced private communications. Minor corrections, additions and changes merely advance the issue number after the decimal point. The reader is invited to report any errors and omissions that have escaped the proof-reading, to answer the unresolved questions noted and to suggest additional material associated with this subject.

Distributed intelligent management of active networks

This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

Cascade dicopper architectures of a dibenzodioxatetraazamacrocycle

The dibenzodioxatetraazamacrocycle [26]pbz(2)N(4)O(2) was characterised by single crystal X-ray diffraction and the protonation constants of this compound and the stability constants of its copper(II) and lead(II) complexes were determined by potentiometry in water at 298.2 K in 0.10 mol dm(-3) in KNO3. Mono- and dinuclear complexes were found for both metal ions, the dinuclear complexes being the main species in the 5-7.5 pH range for copper(II) and 7.5-8.5 for lead(II). As expected the values of the stability constants for the copper(II) complexes are lower than those for related macrocycles containing only nitrogen atoms. The presence of mono- and dinuclear copper complexes was also confirmed by electrospray ionization mass spectrometry. These results suggest that the symmetric macrocyclic cavity of [26]pbZ(2)N(4)O(2) has enough space for the coordination of two metal ions. Additionally, NMR spectroscopy showed that the dinuclear complex of lead(II) has high symmetry. The equilibrium constants of the dinuclear copper(II) complexes and dicarboxylate anions (oxalate, malonate and succinate) were also determined in 0.10 mol dm-3 aqueous KNO3 solution. Only species containing one anion, Cu(2)H(h)LA((2+h)), were found, strongly suggesting that the anion bridges the two copper(II) ions. The binding constants of the cascade species formed by [Cu-2[26]pbZ(2)N(4)O(2)(H2O)(4+) with dicarboxylate anions decrease with the increase in length of the alkyl chain of the anion, a fact which was attributed to a higher conformational energy necessary for the rearrangement of the macrocycle to accommodate the larger anions bridging the two copper(II) centres. The variation of the magnetic susceptibility with temperature Of [Cu-2(H-2[26]pbz(2)N(4)O(2))(oxa)(3)]-4H(2)O and [Cu-2([26]pbz(2)N(4)O(2))(suc)Cl-2] were measured and the two complexes showed different behaviour. (c) 2007 Elsevier Ltd. All rights reserved.

Structural diversity in supramolecular architectures of Mn(II) through non-covalent interactions

Two mononuclear complexes of manganese(II), [Mn(OCN)(2)(phen)(2)] 1 and [Mn(NCO)(2)(bpy)(2)] 2 [1,10-phenanthroline (phen); 2,2'-bipyridine (bpy)], have been synthesized and characterized by single crystal X-ray analysis, infra-red spectroscopy and magnetic studies. The coordination structure of complex 2 is already reported. The cyanate anions are pendent in both the complexes. In 1, cyanate anion links manganese(II) through O-atom, whereas in 2 it coordinates through N-atom. The mononuclear fragments of 1 are built up to a supramolecular lamellar 3D architecture by pi-pi interactions only. On the other hand, mononuclear fragments of 2 are assembled to a 2D supramolecular brick-wall architecture by C-H-... pi interactions.

Utilisation of dendritic architectures in molecular recognition and self-assembly processes

This mini-review outlines recent key developments in the use of dendritic architectures in self-assembly processes via utilisation of molecular recognition motifs.

Advanced scalable algorithms for advanced architectures

With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

Economic models and algorithms for distributed systems

Distributed computing paradigms for sharing resources such as Clouds, Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. While there are some success stories such as PlanetLab, OneLab, BOINC, BitTorrent, and SETI@home, a widespread use of these technologies for business applications has not yet been achieved. In a business environment, mechanisms are needed to provide incentives to potential users for participating in such networks. These mechanisms may range from simple non-monetary access rights, monetary payments to specific policies for sharing. Although a few models for a framework have been discussed (in the general area of a "Grid Economy"), none of these models has yet been realised in practice. This book attempts to fill this gap by discussing the reasons for such limited take-up and exploring incentive mechanisms for resource sharing in distributed systems. The purpose of this book is to identify research challenges in successfully using and deploying resource sharing strategies in open-source and commercial distributed systems.