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

Modeling and Simulation Study of Designer’s Bidirectional Behavior of Task Selection in Open Source Design Process

Open source design (OSD) is an emerging mode of product design. In OSD process, how to select right tasks directly influences the efficiency and quality of task completion, hence impacting the whole evolution process of OSD. In this paper, designer’s bidirectional behavior of task selection integrating passive selection based on website recommendation and autonomous selection is modeled. First, the model of passive selection behavior by website recommendation is proposed with application of collaborative filtering algorithm, based on a three-dimensional matrix including information of design agents, tasks, and skills; second, the model of autonomous selection behavior is described in consideration of factors such as skill and incentive; third, the model of bidirectional selection behavior is described integrating the aforementioned two selection algorithms. At last, contrast simulation analysis of bidirectional selection, passive selection based on website recommendation, and autonomous selection is proposed with ANOVA, and results show that task selection behavior has significant effect on OSD evolution process and that bidirectional selection behavior is more effective to shorten evolution cycle according to the experiment settings. In addition, the simulation study testifies the model of bidirectional selection by describing the task selection process of OSD in microperspective

Software Defined Applications in Cellular and Optical Networks

abstract: Small wireless cells have the potential to overcome bottlenecks in wireless access through the sharing of spectrum resources. A novel access backhaul network architecture based on a Smart Gateway (Sm-GW) between the small cell base stations, e.g., LTE eNBs, and the conventional backhaul gateways, e.g., LTE Servicing/Packet Gateways (S/P-GWs) has been introduced to address the bottleneck. The Sm-GW flexibly schedules uplink transmissions for the eNBs. Based on software defined networking (SDN) a management mechanism that allows multiple operator to flexibly inter-operate via multiple Sm-GWs with a multitude of small cells has been proposed. This dissertation also comprehensively survey the studies that examine the SDN paradigm in optical networks. Along with the PHY functional split improvements, the performance of Distributed Converged Cable Access Platform (DCCAP) in the cable architectures especially for the Remote-PHY and Remote-MACPHY nodes has been evaluated. In the PHY functional split, in addition to the re-use of infrastructure with a common FFT module for multiple technologies, a novel cross functional split interaction to cache the repetitive QAM symbols across time at the remote node to reduce the transmission rate requirement of the fronthaul link has been proposed.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

ICARUS Training and Support System

The ICARUS unmanned tools act as gatherers, which acquire enormous amount of information. The management of all these data requires the careful consideration of an intelligent support system. This chapter discusses the High-Performance Computing (HPC) support tools, which were developed for rapid 3D data extraction, combination, fusion, segmentation, classification and rendering. These support tools were seamlessly connected to a training framework. Indeed, training is a key in the world of search and rescue. Search and rescue workers will never use tools on the field for which they have not been extensively trained beforehand. For this reason, a comprehensive serious gaming training framework was developed, supporting all ICARUS unmanned vehicles in realistic 3D-simulated (based on inputs from the support system) and real environments

Resource allocation for dataflow applications in FANETs using anypath routing

Management of network resources in advanced IoT applications is a challenging topic due to their distributed nature from the Edge to the Cloud, and the heavy demand of real-time data from many sources to take action in the deployment. FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous multi-modal use cases, which require strict quality in the network communications, as well as the coordination of the computing capabilities, in order to operate correctly the final service. In this paper, we present a Virtual Network Embedding (VNE) framework designed for the allocation of dataflow applications, composed of nano-services that produce or consume data, in a wireless infrastructure, such as an airborne network. To address the problem, an anypath-based heuristic algorithm that considers the quality demand of the communication between nano-services is proposed, coined as Quality-Revenue Paired Anypath Dataflow VNE (QRPAD-VNE). We also provide a simulation environment for the evaluation of its performance according to the virtual network (VN) request load in the system. Finally, we show the suitability of a multi-parameter framework in conjunction with anypath routing in order to have better performance results that guarantee minimum quality in the wireless communications.Xunta de Galicia | Ref. ED431C 2022/04 T254Ministerio de Universidades | Ref. FPU19/01284Agencia Estatal de Investigación | Ref. PCI2020-112174Agencia Estatal de Investigación | Ref. PID2020-113795RB-C33Agencia Estatal de Investigación | Ref. PID2020-116329GB-C21Universidade de Vigo/CISU

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security