Cluster-Fault Tolerant Routing in a Torus.

The number of Internet-connected devices grows very rapidly, with even fears of running out of available IP addresses. It is clear that the number of sensors follows this trend, thus inducing large sensor networks. It is insightful to make the comparison with the huge number of processors of modern supercomputers. In such large networks, the problem of node faults necessarily arises, with faults often happening in clusters. The tolerance to faults, and especially cluster faults, is thus critical. Furthermore, thanks to its advantageous topological properties, the torus interconnection network has been adopted by the major supercomputer manufacturers of the recent years, thus proving its applicability. Acknowledging and embracing these two technological and industrial aspects, we propose in this paper a node-to-node routing algorithm in an n-dimensional k-ary torus that is tolerant to faults. Not only is this algorithm tolerant to faulty nodes, it also tolerates faulty node clusters. The described algorithm selects a fault-free path of length at most n ( 2 k + ⌊ k / 2 ⌋ - 2 ) with an O ( n 2 k 2 | F | ) worst-case time complexity with F the set of faulty nodes induced by the faulty clusters.

Torus Pairwise Disjoint-Path Routing.

Modern supercomputers include hundreds of thousands of processors and they are thus massively parallel systems. The interconnection network of a system is in charge of mutually connecting these processors. Recently, the torus has become a very popular interconnection network topology. For example, the Fujitsu K, IBM Blue Gene/L, IBM Blue Gene/P, and Cray Titan supercomputers all rely on this topology. The pairwise disjoint-path routing problem in a torus network is addressed in this paper. This fundamental problem consists of the selection of mutually vertex disjoint paths between given vertex pairs. Proposing a solution to this problem has critical implications, such as increased system dependability and more efficient data transfers, and provides concrete implementation of green and sustainable computing as well as security, privacy, and trust, for instance, for the Internet of Things (IoT). Then, the correctness and complexities of the proposed routing algorithm are formally established. Precisely, in an n-dimensional k-ary torus ( n < k , k ≥ 5 ), the proposed algorithm connects c ( c ≤ n ) vertex pairs with mutually vertex-disjoint paths of lengths at most 2 k ( c - 1 ) + n ⌊ k / 2 ⌋ , and the worst-case time complexity of the algorithm is O ( n c 4 ) . Finally, empirical evaluation of the proposed algorithm is conducted in order to inspect its practical behavior.

Supporting reconstruction of the blood vessel network using graph theory: an abstraction method.

The blood vessel network (BVN) has a complex structure. As this structure is unique for each individual, it is not possible to establish a general model for the BVN. However, many medical applications do rely on this structure. For example, a drug delivery system would be greatly improved if it could control the drug flow towards destination. To address this BVN structure issue, several reconstruction methods have been introduced. In this paper, we describe an abstraction method supporting BVN reconstruction by using graph theory. Starting from an original BVN reconstruction, we define the so-called induced graph of that reconstruction, allowing for an efficient analysis. By applying this method, we were able to improve an original BVN reconstruction of a human kidney by pointing out probable errors inside that original reconstruction.

Variations in prevalence and conduct of school food gardens in tropical and subtropical regions of north-eastern Australia.

OBJECTIVES: To determine the prevalence and usage of food gardens in primary schools in three distinct climatic regions of north-eastern Australia. DESIGN: Cross-sectional surveys combining quantitative and qualitative data collection. Two separate telephone questionnaires were developed and implemented, according to the presence or absence of a food garden within the school. Main outcome measures were answers to scaled response and open-ended questions related to factors supporting and inhibiting the establishment and sustainability of school food gardens. SETTING: All state primary schools in three disparate regions of the north-eastern Australian state of Queensland were asked to participate in the study. RESULTS: A total of 71% (n 128) of schools agreed to participate. Of these, thirty-seven primary schools had functioning food gardens. The variations in prevalence between regions combined with respondent views indicated climate as a major factor affecting the success of food gardens. Gardens were often used as a tool by schools to teach science, environment or social skills. Gardening activities were generally linked to curriculum studies on plants, fruit and vegetable intake, and healthy eating. The main issues for schools and teachers in establishing food gardens were the time required and the lack of personnel to coordinate garden activities. Of the schools with food gardens, 92% believed their garden had been a success. CONCLUSIONS: The study revealed strong grass-roots support for school-based food gardens. Although climate and location were important factors associated with the presence of a functioning food garden, respondents nominated teacher involvement and sustained motivation as essential factors for successful school food gardens.