New techniques for simulating high performance MPI applications on large storage networks

In this work, we propose new techniques to analyze the behavior, the performance, and specially the scalability of High Performance Computing (in short, HPC) applications on different computing architectures. Our final objective is to test applications using a wide range of architectures (real or merely designed) and scaling it to any number of nodes or components. This paper presents a new simulation framework, called SIMCAN, for HPC architectures. The main characteristic of the proposed simulation framework is the ability to be configured for simulating a wide range of possible architectures that involve any number of components. SIMCAN is developed to simulate complete HPC architectures, but putting special emphasis on the storage and network subsystems. The SIMCAN framework can handle complete components (nodes, racks, switches, routers, etc.), but also key elements of the storage and network subsystems (disks, caches, sockets, file systems, schedulers, etc.). We also propose several methods to implement the behavior of HPC applications. Each method has its own advantages and drawbacks. In order to evaluate the possibilities and the accuracy of the SIMCAN framework, we have tested it by executing a HPC application called BIPS3D on a hardware-based computing cluster and on a modeled environment that represent the real cluster. We also checked the scalability of the application using this kind of architecture by simulating the same application with an increased number of computing nodes.     

Network Awareness of P2P Live Streaming Applications: A Measurement Study

Early P2P-TV systems have already attracted millions of users, and many new commercial solutions are entering this market. Little information is however available about how these systems work, due to their closed and proprietary design. In this paper, we present large scale experiments to compare three of the most successful P2P-TV systems, namely PPLive, SopCast and TVAnts. Our goal is to assess what level of "network awareness" has been embedded in the applications. We first define a general framework to quantify which network layer parameters leverage application choices, i.e., what parameters mainly drive the peer selection and data exchange. We then apply the methodology to a large dataset, collected during a number of experiments where we deployed about 40 peers in several European countries. From analysis of the dataset, we observe that TVAnts and PPLive exhibit a mild preference to exchange data among peers in the same autonomous system the peer belongs to, while this clustering effect is less intense in SopCast. However, no preference versus country, subnet or hop count is shown. Therefore, we believe that next-generation P2P live streaming applications definitively need to improve the level of network-awareness, so to better localize the traffic in the network and thus increase their network-friendliness as well.     

Epitaxially grown graphene based gas sensors for ultra sensitive NO2 detection

Epitaxially grown single layer and multi layer graphene on SiC devices were fabricated and compared for response towards NO₂. Due to electron donation from SiC, single layer graphene is n-type with a very low carrier concentration. The choice of substrate is demonstrated to enable tailoring of the electronic properties of graphene, with a SiC substrate realising simple resistive devices tuned for extremely sensitive NO₂ detection. The gas exposed uppermost layer of the multi layer device is screened from the SiC by the intermediate layers leading to a p-type nature with a higher concentration of charge carriers and therefore, a lower gas response. The single layer graphene device is thought to undergo an n-p transition upon exposure to increasing concentrations of NO₂ indicated by a change in response direction. This transition is likely to be due to the transfer of electrons to NO₂ making holes the majority carriers.     

BOO: Behavior-oriented ontology to describe participant dynamics in collocated design meetings

Facilitating meetings is not an easy task. To assist the facilitator, we have been designing intelligent support systems, which can help contextual sensemaking, decision making and action. However, these systems are constructed based on behavioral models that provide guidelines to understand participant behaviors. This paper presents an ontology to describe participants’ behaviors in collaborative design meetings and rules that correlate them with the group’s acceptance of the final product. This ontology describes the group dynamics at collocated meetings, using verbal and non-verbal cues of attention shifts and attention maintenance as its basic constructs. The objective of creating this ontology was to better understand face-to-face meetings to eventually help meeting facilitators identify issues that may lead to dissatisfaction with the final product through behavioral cues. The ontology was derived through extensive analysis of a series of engineering design session videos. The design group was composed of experts with similar backgrounds, but working in different divisions of the same company. Different points of view were argued and decisions were made at the end of each meeting. After each meeting, participants were asked to asynchronously commit to the decisions made in the group. Our ontology can be used to identify the factors that lead to an undesired outcome, and now serves as a basis for a new project, which uses rules to support design meetings, improve final artifact acceptance and reduce rework. Our conclusions point out correlations between designers’ behaviors and future artifact acceptance and actions that interrupt or bring back group attention. The ontology was validated through application to other meeting situations. These findings may guide software developers in the creation of tools to support group design, and may be applied by an intelligent system.     

Automatic Schaeffer's gestures recognition system

Schaeffer's sign language consists of a reduced set of gestures designed to help children with autism or cognitive learning disabilities to develop adequate communication skills. Our automatic recognition system for Schaeffer's gesture language uses the information provided by an RGB‐D camera to capture body motion and recognize gestures using dynamic time warping combined with k‐nearest neighbors methods. The learning process is reinforced by the interaction with the proposed system that accelerates learning itself thus helping both children and educators. To demonstrate the validity of the system, a set of qualitative experiments with children were carried out. As a result, a system which is able to recognize a subset of 11 gestures of Schaeffer's sign language online was achieved.     

On improving the efficiency of tensor voting

This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used in applications where efficiency is an issue since they have a complexity of order O(1). Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.     

Semantic-based authorization architecture for Grid

There are a few issues that still need to be covered regarding security in the Grid area. One of them is authorization where there exist good solutions to define, manage and enforce authorization policies in Grid scenarios. However, these solutions usually do not provide Grid administrators with semantic-aware components closer to the particular Grid domain and easing different administration tasks such as conflict detection or resolution. This paper defines a proposal based on Semantic Web to define, manage and enforce security policies in a Grid scenario. These policies are defined by means of semantic-aware rules which help the administrator to create higher-level definitions with more expressiveness. These rules also permit performing added-value tasks such as conflict detection and resolution, which can be of interest in medium and large scale scenarios where different administrators define the authorization rules that should be followed before accessing a resource in the Grid. The proposed solution has been also tested providing some reasonable response times in the authorization decision process.     

Skeleton computation of orthogonal polyhedra

Skeletons are powerful geometric abstractions that provide useful representations for a number of geometric operations. The straight skeleton has a lower combinatorial complexity compared with the medial axis. Moreover, while the medial axis of a polyhedron is composed of quadric surfaces the straight skeleton just consist of planar faces. Although there exist several methods to compute the straight skeleton of a polygon, the straight skeleton of polyhedra has been paid much less attention. We require to compute the skeleton of very large datasets storing orthogonal polyhedra. Furthermore, we need to treat geometric degeneracies that usually arise when dealing with orthogonal polyhedra. We present a new approach so as to robustly compute the straight skeleton of orthogonal polyhedra. We follow a geometric technique that works directly with the boundary of an orthogonal polyhedron. Our approach is output sensitive with respect to the number of vertices of the skeleton and solves geometric degeneracies. Unlike the existing straight skeleton algorithms that shrink the object boundary to obtain the skeleton, our algorithm relies on the plane sweep paradigm. The resulting skeleton is only composed of axis‐aligned and 45° rotated planar faces and edges.     

QoS Filtering and Resource Reservation in an Internet Environment

Multimedia group applications often operate in an environment where the various participants are located on systems and communication links with different capabilities. Mechanisms are required that ensure full-quality media for high-performance workstations but lower-quality media for playout at low-end systems. QoS filters have been proposed as a way to adapt QoS to the user specified level by changing the structure of a media stream in a well defined way. Resource reservation and QoS filter instantiation should be closely integrated since both represent one particular aspect of the provision of individualistic QoS for heterogeneous users in multipeer communications. The Internet reservation protocol RSVP is receiver oriented and allows each receiver to specify its resource requirements. However, no actual mechanisms are defined that adapt the data stream to the receiver specified QoS requirements.In this paper we present an enhanced version of RSVP (called RSVP++) that integrates resource reservation and QoS filter control. In order to achieve this integration we extend the RSVP functional model and define a new QoS service class. RSVP++ can coexist with common RSVP systems, thus, openness and interoperability of the system are ensured.