Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN...
详细信息
Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN applications. In this study, we present a fully distributed solution, where leaks are detected in a water distribution network via only local collaborations between a sensor node and its close neighbors, without the need for long-distance transmissions via several hops to a centralized fusion center. A complete approach that includes the design, simulation, and physical measurements, showing how distributed computing implemented via a distributed Kalman filter improves the accuracy of leak detection and the power consumption is presented. The results from the physical implementation show that distributed data fusion increases the accuracy of leak detection while preserving WSN lifetime.
Land-cover classification methods are based on the processing of large image volumes to accurately extract representative features. Particularly, convolutional models provide notable characterization properties for im...
详细信息
Land-cover classification methods are based on the processing of large image volumes to accurately extract representative features. Particularly, convolutional models provide notable characterization properties for image classification tasks. distributed learning mechanisms on high-performance computing platforms have been proposed to speed up the processing, while achieving an efficient feature extraction. High-performance computing platforms are commonly composed of a combination of central processing units (CPUs) and graphics processing units (GPUs) with different computational capabilities. As a result, current homogeneous workload distribution techniques for deep learning (DL) become obsolete due to their inefficient use of computational resources. To address this, new computational balancing proposals, such as heterogeneous data parallelism, have been implemented. Nevertheless, these techniques should be improved to handle the peculiarities of working with heterogeneous data workloads in the training of distributed DL models. The objective of handling heterogeneous workloads for current platforms motivates the development of this work. This letter proposes an innovative heterogeneous gradient calculation applied to land-cover classification tasks through convolutional models, considering the data amount assigned to each device in the platform while maintaining the acceleration. Extensive experimentation has been conducted on multiple datasets, considering different deep models on heterogeneous platforms to demonstrate the performance of the proposed methodology.
In this paper we present an approach we have developed to monitor distributed and heterogeneous computing infrastructure with special attention to the implementation in the Virtual research environment for regional In...
详细信息
ISBN:
(纸本)9781538670736
In this paper we present an approach we have developed to monitor distributed and heterogeneous computing infrastructure with special attention to the implementation in the Virtual research environment for regional Interdisciplinary communities in Southeast Europe and the Eastern Mediterranean project (VI-SEEM). The project infrastructure covers a number of countries and administrative domains as well as several computing paradigms, from classic data center virtualization solutions to grid and high performance computing. We have collected and analyzed available data sources, designed data model and implemented the monitoring system suitable for monitoring of this complex infrastructure. To validate the proposed approach we have tested the system within VI-SEEM project and present the test results in this paper.
Platforms for distributed computing are able to solve complex problems such as radio telescope signal analysis or protein design. However, the distributed computing systems are also vulnerable to attacks, especially c...
详细信息
ISBN:
(纸本)9781728132341
Platforms for distributed computing are able to solve complex problems such as radio telescope signal analysis or protein design. However, the distributed computing systems are also vulnerable to attacks, especially considering the fact that some distributed projects reward their participants, so cybercriminals have incentive to sabotage the project for their own gain. The article considers question of distributed computing security. We propose to use metastable blockchain protocol to ensure that integrity of data is preserved. We also discuss advantages of metastable blockchain protocol over regular one for the task of mass distributed computing. Prototype distributed data processing program was designed for the task of calculating checksums. The program was tested in a controlled virtual machine environment with different checksum algorithms and different number of computing units.
There are two central models considered in (fault -free synchronous) distributed computing: the CONGEST model, in which communication channels have limited bandwidth, and the LOCAL model, in which communication channe...
详细信息
ISBN:
(纸本)9783959771009
There are two central models considered in (fault -free synchronous) distributed computing: the CONGEST model, in which communication channels have limited bandwidth, and the LOCAL model, in which communication channels have unlimited bandwidth. Very recently, Le Gall and Magniez (PODC 2018) showed the superiority of quantum distributed computing over classical distributed computing in the CONGEST model. In this work we show the superiority of quantum distributed computing in the LOCAL model: we exhibit two computational tasks that can be solved in a constant number of rounds in the quantum setting but require Q(n) rounds in the classical (randomized) setting, where n denotes the size of the network.
distributed real-time applications often require an optimal assignment of resources to improve performance. This paper proposes a methodology to optimally assign system resources that enables to minimize the processin...
详细信息
ISBN:
(纸本)9781538669624
distributed real-time applications often require an optimal assignment of resources to improve performance. This paper proposes a methodology to optimally assign system resources that enables to minimize the processing and communication time. In this study, we defined a case of study partitioned into six subsystems to be simulated with four available processing units. We used undirected graphs to obtain a representation of the system and subsequently solved the resulting NT -hard problem as a mixed -integer quadratic program (MIQP). We also implemented a comprehensive search as groundwork and compared both methods using computational and global time as metrics. Numerical simulations showed that our methodology obtained both a better assignment of computational resources and significant solution time reduction than the comprehensive search. Moreover, the solution increased the rates of shared information between units during the reconciliation process. This methodology can thus be used in applications like distributed state estimation, distributed control or co-simulation.
In this paper, we consider heuristic rules for resources utilization optimization in distributed computing environments. Existing modern job-flow execution mechanics impose many restrictions for the resources allocati...
详细信息
ISBN:
(纸本)9783030227449;9783030227432
In this paper, we consider heuristic rules for resources utilization optimization in distributed computing environments. Existing modern job-flow execution mechanics impose many restrictions for the resources allocation procedures. Grid, cloud and hybrid computing services operate in heterogeneous and usually geographically distributed computing environments. Emerging virtual organizations and incorporated economic models allow users and resource owners to compete for suitable allocations based on market principles and fair scheduling policies. Subject to these features a set of heuristic rules for coordinated compact scheduling are proposed to select resources depending on how they fit a particular job execution and requirements. Dedicated simulation experiment studies integral job flow characteristics optimization when these rules are applied to conservative backfilling scheduling procedure.
As the amount of publicly shared data increases, developing a robust pipeline to stream, store and process data is critical, as the casual user often lacks the technology, hardware and/or skills needed to work with su...
详细信息
ISBN:
(纸本)9781728140346
As the amount of publicly shared data increases, developing a robust pipeline to stream, store and process data is critical, as the casual user often lacks the technology, hardware and/or skills needed to work with such voluminous data. In this research, the authors employ Amazon EC2 and EMR and Apache Spark to explore 28.5 gigabytes of CMS Open Payments data in an attempt to identify physicians who may have a high propensity to act unethically, owing to significant transfers of wealth from medical companies. A Random Forest Classifier is employed to predict the top decile of physicians who have the highest risk of unethical behavior in the following year, resulting in an F-Score of 91%. The authors also employ an anomaly detection algorithm that correctly identified a high-profile case of a physician leaving his prestigious position, failing to disclose anomalously-large transfers of wealth from medical companies.
This paper presents an implementation of distributed computing to search for the optimal block error control code (covering both linear and nonlinear codes) for binary symmetric channels. The optimality is determined ...
详细信息
ISBN:
(纸本)9781728162973
This paper presents an implementation of distributed computing to search for the optimal block error control code (covering both linear and nonlinear codes) for binary symmetric channels. The optimality is determined by comparing the decoding error probabilities when maximum likelihood decoders are used under the assumption that the codewords are equally likely. Several pre-processing steps are proposed to reduce the size of the search space. The search gives distance distributions which correspond to closed-form expressions for the minimum decoding error probability. distributed computing is utilized to further reduce the search time. The proposed implementation can be extended to an arbitrary number of cloud servers. The amount of time saved by the search space reduction and distributed computing is also demonstrated.
To protect the resources from various vulnerability factors, resources should have various routine security mechanisms such as antivirus capability, firewall capability, usage of secure network connections, provision ...
详细信息
ISBN:
(纸本)9789811315923;9789811315916
To protect the resources from various vulnerability factors, resources should have various routine security mechanisms such as antivirus capability, firewall capability, usage of secure network connections, provision of execution sandbox, invoking dynamic checkpointing, and intrusion detection system-related capabilities. Security is one of the key issues in distributed computing systems like grid and cloud. Whole system is secured when resources have self-defense capability. Adapting security measures in grid environment is an expensive mechanism and leads to delays in service provisioning whereas trust can be, relatively, a simple and fast solution. In view of the interest of the users and quick delivery of the services by the provider, integration of different combinations of trust levels and security mechanisms can reduce the costs and delays involved in adapting security measures. This paper proposes a new approach for integrating security levels along with trust in general for distributed computing systems and in particular for grid computing systems. Our previous work proposed a T-grid computational model suitable for grid computing systems, which will be used for experimenting and testing the proposed idea of the integration. Results of the studies are produced.
暂无评论