Abstract

Abstract
In this work we perform a detailed study of different or-scheduling strategies varying several parameters in two or-parallel systems, YapOr and ThOr, running on multi-core machines. Our results show that some kinds of applications are sensitive to the choice of scheduling strategy adopted. In particular, the choice of scheduling parameters mostly affect applications that have short execution times, which, despite having speedups, have their performance significantly affected. Our results also show that topmost dispatching can be more advantageous than bottommost dispatching, a finding that contradicts previous works in this area. One last finding is that YapOr and ThOr are affected differently by changes in scheduling with ThOr performing significantly better than YapOr in several applications.

Abstract
Interconnection of different access network technologies is an important research topic in mobile telecommunications systems. In this paper, we propose an ns-3 architecture for simulating the interconnection of wireless local area network (WLAN) and Universal Mobile Telecommunications System (UMTS). This architecture is based on the architecture proposed by the Third Generation Partnership Project, being the use of virtual interfaces as its main innovation. In order to demonstrate the value of the proposed simulation framework, we implemented the UMTS and WLAN interconnection considering three joint radio resource management strategies for distributing arriving calls. From the simulations results, we can conclude that the proposed simulation architecture is suitable to test and evaluate performance aspects related to the interconnection and joint management of UMTS and WLAN technologies. Copyright (c) 2012 John Wiley & Sons, Ltd.

Abstract
Dance movements are a complex class of human behavior which convey forms of non-verbal and subjective communication that are performed as cultural vocabularies in all human cultures. The singularity of dance forms imposes fascinating challenges to computer animation and robotics, which in turn presents outstanding opportunities to deepen our understanding about the phenomenon of dance by means of developing models, analyses and syntheses of motion patterns. In this article, we formalize a model for the analysis and representation of popular dance styles of repetitive gestures by specifying the parameters and validation procedures necessary to describe the spatiotemporal elements of the dance movement in relation to its music temporal structure (musical meter). Our representation model is able to precisely describe the structure of dance gestures according to the structure of musical meter, at different temporal resolutions, and is flexible enough to convey the variability of the spatiotemporal relation between music structure and movement in space. It results in a compact and discrete mid-level representation of the dance that can be further applied to algorithms for the generation of movements in different humanoid dancing characters. The validation of our representation model relies upon two hypotheses: (i) the impact of metric resolution and (ii) the impact of variability towards fully and naturally representing a particular dance style of repetitive gestures. We numerically and subjectively assess these hypotheses by analyzing solo dance sequences of Afro-Brazilian samba and American Charleston, captured with a MoCap (Motion Capture) system. From these analyses, we build a set of dance representations modeled with different parameters, and re-synthesize motion sequence variations of the represented dance styles. For specifically assessing the metric hypothesis, we compare the captured dance sequences with repetitive sequences of a fixed dance motion pattern, synthesized at different metric resolutions for both dance styles. In order to evaluate the hypothesis of variability, we compare the same repetitive sequences with others synthesized with variability, by generating and concatenating stochastic variations of the represented dance pattern. The observed results validate the proposition that different dance styles of repetitive gestures might require a minimum and sufficient metric resolution to be fully represented by the proposed representation model. Yet, these also suggest that additional information may be required to synthesize variability in the dance sequences while assuring the naturalness of the performance. Nevertheless, we found evidence that supports the use of the proposed dance representation for flexibly modeling and synthesizing dance sequences from different popular dance styles, with potential developments for the generation of expressive and natural movement profiles onto humanoid dancing characters.

Abstract
Slicing a large-scale distributed system is the process of autonomously partitioning its nodes into k groups, named slices. Slicing is associated to an order on node-specific criteria, such as available storage, uptime, or bandwidth. Each slice corresponds to the nodes between two quantiles in a virtual ranking according to the criteria. For instance, a system can be split in three groups, one with nodes with the lowest uptimes, one with nodes with the highest uptimes, and one in the middle. Such a partitioning can be used by applications to assign different tasks to different groups of nodes, e.g., assigning critical tasks to the more powerful or stable nodes and less critical tasks to other slices. Assigning a slice to each node in a large-scale distributed system, where no global knowledge of nodes' criteria exists, is not trivial. Recently, much research effort was dedicated to guaranteeing a fast and correct convergence in comparison to a global sort of the nodes. Unfortunately, state-of-the-art slicing protocols exhibit flaws that preclude their application in real scenarios, in particular with respect to cost and stability. In this paper, we identify steadiness issues where nodes in a slice border constantly exchange slice and large memory requirements for adequate convergence, and provide practical solutions for the two. Our solutions are generic and can be applied to two different state-of-the-art slicing protocols with little effort and while preserving the desirable properties of each. The effectiveness of the proposed solutions is extensively studied in several simulated experiments. © 2012 IFIP International Federation for Information Processing.

Abstract
This paper describes a methodology for finding and describing significant events in time evolving complex networks. We first group the nodes of the network in clusters, according to their similarity in terms of a set of local properties such as degree and clustering coefficient. We then monitor the behavior of these groups over time, looking for significant changes on the size of the groups. These events are notable since they show that the position of a number of nodes in the network has changed. We describe this evolution by extracting the correspondent transition patterns. We examined our methodology on three different real network datasets. Our experiments show that the discovered rules are significant and can describe the occurring events.