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HSkip+: A self-stabilizing overlay network for nodes with heterogeneous bandwidths 14

HSkip+: A self-stabilizing overlay network for nodes with he...

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14th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2014

作者： Feldotto, Matthias Scheideler, Christian Graffi, Kalman Heinz Nixdorf Institute Department of Computer Science University of Paderborn Germany Theory of Distributed Systems Group Department of Computer Science University of Paderborn Germany Technology of Social Networks Group Department of Computer Science University of Düsseldorf Germany

ISBN: (纸本)9781479962013

In this paper we present and analyze HSkip+, a self-stabilizing overlay network for nodes with arbitrary heterogeneous bandwidths. HSkip+ has the same topology as the Skip+ graph proposed by Jacob et al. [1] but its self-stabilization mechanism significantly outperforms the self-stabilization mechanism proposed for Skip+. Also, the nodes are now ordered according to their bandwidths and not according to their identifiers. Various other solutions have already been proposed for overlay networks with heterogeneous bandwidths, but they are not self-stabilizing. In addition to HSkip+ being self-stabilizing, its performance is on par with the best previous bounds on the time and work for joining or leaving a network of peers of logarithmic diameter and degree and arbitrary bandwidths. Also, the dilation and congestion for routing messages is on par with the best previous bounds for such networks, so that HSkip+ combines the advantages of both worlds. Our theoretical investigations are backed by simulations demonstrating that HSkip+ is indeed performing much better than Skip+ and working correctly under high churn rates. © 2014 IEEE.

关键词： Bandwidth

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Computation and communication efficient graph processing with distributed immutable view 14

Computation and communication efficient graph processing wit...

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23rd ACM Symposium on High-Performance parallel and distributed Computing, HPDC 2014

作者： Chen, Rong Ding, Xin Wang, Peng Chen, Haibo Zang, Binyu Guan, Haibing Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450327480

Cyclops is a new vertex-oriented graph-parallel framework for writing distributed graph analytics. Unlike existing distributed graph computation models, Cyclops retains simplicity and computation-efficiency by synchronously computing over a distributed immutable view, which grants a vertex with read-only access to all its neighboring vertices. The view is provided via readonly replication of vertices for edges spanning machines during a graph cut. Cyclops follows a centralized computation model by assigning a master vertex to update and propagate the value to its replicas unidirectionally in each iteration, which can significantly reduce messages and avoid contention on replicas. Being aware of the pervasively available multicore-based clusters, Cyclops is further extended with a hierarchical processing model, which aggregates messages and replicas in a single multicore machine and transparently decomposes each worker into multiple threads ondemand for different stages of computation. We have implemented Cyclops based on an open-source Pregel clone called Hama. Our evaluation using a set of graph algorithms on an in-house multicore cluster shows that Cyclops outperforms Hama from 2.06X to 8.69X and 5.95X to 23.04X using hash-based and Metis partition algorithms accordingly, due to the elimination of contention on messages and hierarchical optimization for the multicore-based clusters. Cyclops (written in Java) also has comparable performance with PowerGraph (written in C++) despite the language difference, due to the significantly lower number of messages and avoided contention. Copyright © 2014 ACM.

关键词： Iterative methods

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Concurrent and consistent virtual machine introspection with hardware transactional memory

Concurrent and consistent virtual machine introspection with...

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20th IEEE International Symposium on High Performance computer Architecture, HPCA 2014

作者： Liu, Yutao Xia, Yubin Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781479930975

Virtual machine introspection, which provides tamperresistant, high-fidelity 'out of the box' monitoring of virtual machines, has many prominent security applications including VM-based intrusion detection, malware analysis and memory forensic analysis. However, prior approaches are either intrusive in stopping the world to avoid race conditions between introspection tools and the guest VM, or providing no guarantee of getting a consistent state of the guest VM. Further, there is currently no effective means for timely examining the VM states in question. In this paper, we propose a novel approach, called TxIntro, which retrofits hardware transactional memory (HTM) for concurrent, timely and consistent introspection of guest VMs. Specifically, TxIntro leverages the strong atomicity of HTM to actively monitor updates to critical kernel data structures. Then TxIntro can mount introspection to timely detect malicious tampering. To avoid fetching inconsistent kernel states for introspection, TxIntro uses HTM to add related synchronization states into the read set of the monitoring core and thus can easily detect potential inflight concurrent kernel updates. We have implemented and evaluated TxIntro based on Xen VMM on a commodity Intel Haswell machine that provides restricted transactional memory (RTM) support. To demonstrate the effectiveness of TxIntro, we implemented a set of kernel rootkit detectors using TxIntro. Evaluation results show that TxIntro is effective in detecting these rootkits, and is efficient in adding negligible performance overhead. © 2014 IEEE.

关键词： Malware

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Bipartite-oriented distributed graph partitioning for big learning 14

Bipartite-oriented distributed graph partitioning for big le...

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5th ACM Asia-Pacific Workshop on systems, APSYS 2014

作者： Chen, Rong Shi, Jiaxin Zang, Binyu Guan, Haibing Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450330244

Many machine learning and data mining (MLDM) problems like recommendation, topic modeling and medical diagnosis can be modeled as computing on bipartite graphs. However, most distributed graph-parallel systems are oblivious to the unique characteristics in such graphs and existing online graph partitioning algorithms usually causes excessive replication of vertices as well as significant pressure on network communication. This article identifies the challenges and opportunities of partitioning bipartite graphs for distributed MLDM processing and proposes BiGraph, a set of bipartite-oriented graph partitioning algorithms. BiGraph leverages observations such as the skewed distribution of vertices, discriminated computation load and imbalanced data sizes between the two subsets of vertices to derive a set of optimal graph partition algorithms that result in minimal vertex replication and network communication. BiGraph has been implemented on PowerGraph and is shown to have a performance boost up to 17.75X (from 1.38X) for four typical MLDM algorithms, due to reducing up to 62% vertex replication, and up to 96% network traffic. © 2014 ACM.

关键词： Data mining

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Coupling algorithms for partitioned multi-physics simulations 44

Coupling algorithms for partitioned multi-physics simulation...

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44. Jahrestagung der Gesellschaft fur Informatik INFORMATIK 2014 - Big Data - Komplexitat meistern - Big Data - Mastering Complexity: 44th Annual Meeting of the Society for computer science, INFORMATICS 2014

作者： Uekermann, Benjamin Gatzhammer, Bernhard Mehl, Miriam Department of Computer Science Technische Universität München Boltzmannstraße 3 Garching85748 Germany Institute for Parallel and Distributed Systems Universität Stuttgart Universitätsstraße 38 Stuttgart70569 Germany

ISBN: (纸本)9783885796268

Partitioned coupling approaches are an important tool in order to achieve a decent time-to-solution for multi-physics problems with more than two physical fields or changing combinations of fields. We study different approaches to deduce coupling schemes for partitioned multi-physics scenarios, by means of a simple, but yet challenging fluid-structure-fluid model problem. To our knowledge, this is the first time that a fully implicit black-box coupling scheme for partitioned multi-physics scenarios is described. This allows the simulation of a new range of applications in a partitioned way.

关键词： Fluid structure interaction

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Concurrent and consistent virtual machine introspection with hardware transactional memory

Concurrent and consistent virtual machine introspection with...

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IEEE Symposium on High-Performance computer Architecture

作者： Yutao Liu Yubin Xia Haibing Guan Binyu Zang Haibo Chen Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Department of Computer Science Shanghai Jiao Tong University

Virtual machine introspection, which provides tamperresistant, high-fidelity “out of the box” monitoring of virtual machines, has many prominent security applications including VM-based intrusion detection, malware analysis and memory forensic analysis. However, prior approaches are either intrusive in stopping the world to avoid race conditions between introspection tools and the guest VM, or providing no guarantee of getting a consistent state of the guest VM. Further, there is currently no effective means for timely examining the VM states in question. In this paper, we propose a novel approach, called TxIntro, which retrofits hardware transactional memory (HTM) for concurrent, timely and consistent introspection of guest VMs. Specifically, TxIntro leverages the strong atomicity of HTM to actively monitor updates to critical kernel data structures. Then TxIntro can mount introspection to timely detect malicious tampering. To avoid fetching inconsistent kernel states for introspection, TxIntro uses HTM to add related synchronization states into the read set of the monitoring core and thus can easily detect potential inflight concurrent kernel updates. We have implemented and evaluated TxIntro based on Xen VMM on a commodity Intel Haswell machine that provides restricted transactional memory (RTM) support. To demonstrate the effectiveness of TxIntro, we implemented a set of kernel rootkit detectors using TxIntro. Evaluation results show that TxIntro is effective in detecting these rootkits, and is efficient in adding negligible performance overhead.

关键词： Kernel Monitoring Educational institutions Abstracts Single photon emission computed tomography Virtual machine monitors Continuous wavelet transforms

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Dynamic Multi-Agent Reinforcement Learning for Control Optimization

Dynamic Multi-Agent Reinforcement Learning for Control Optim...

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International Conference on Intelligent systems, Modelling and Simulation

作者： Derek Fagan Rene Meier Distributed Systems Group School of Computer Science and Statistics Trinity College Dublin Mobile Systems Group Department of Computer Science Lucerne University of Applied Sciences

ISBN: (纸本)9781479938599

In this paper we analyze the use of Reinforcement Learning (RL) in control optimization within dynamic multi-agent systems. RL is an effective algorithm for single agent optimization but performs less well in dynamic multi-agent environments. We investigate this principle based upon three of the most common RL algorithms. We also introduce a novel RL algorithm that excels in both single agent optimization and adaptation within multi-agent environments. This algorithm takes into account not only its own current state but also the current states of each of its significant neighbor agents so as to significantly increase performance within multi-agent systems. It employs a model driven approach to facilitate effective adaptation as well as policy-based methods to enable efficient action selection.

关键词： Multi-Agent Reinforcement Learning Control Optimization Multi-Agent systems

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Replication-Based Fault-Tolerance for Large-Scale Graph Processing

Replication-Based Fault-Tolerance for Large-Scale Graph Proc...

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International Conference on Dependable systems and Networks (DSN)

作者： Peng Wang Kaiyuan Zhang Rong Chen Haibo Chen Haibing Guan Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Department of Computer Science Shanghai Jiao Tong University

The increasing algorithm complexity and dataset sizes necessitate the use of networked machines for many graph-parallel algorithms, which also makes fault tolerance a must due to the increasing scale of machines. Unfortunately, existing large-scale graph-parallel systems usually adopt a distributed checkpoint mechanism for fault tolerance, which incurs not only notable performance overhead but also lengthy recovery time. This paper observes that the vertex replicas created for distributed graph computation can be naturally extended for fast in-memory recovery of graph states. This paper proposes Imitator, a new fault tolerance mechanism, that supports cheaply maintenance of vertex states by replicating vertex states to their replicas during normal message exchanges, and provides fast in-memory reconstruction of failed vertices from replicas in other machines. Imitator has been implemented by extending Hama, a popular open-source clone of Pregel. Evaluation shows that Imitator incurs negligible performance overhead (less than 5% for all cases) and can recover from failures of more than one million of vertices with less than 3.4 seconds.

关键词： Fault tolerance Fault tolerant systems computer crashes Checkpointing Synchronization Clustering algorithms Computational modeling

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Data Avenue: Remote Storage Resource Management in WS-PGRADE/gUSE

Data Avenue: Remote Storage Resource Management in WS-PGRADE...

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International Workshop on science Gateways (IWSG)

作者： Ákos Hajnal Zoltán Farkas Péter Kacsuk Laboratory of Parallel and Distributed Systems Hungarian Academy of Sciences Budapest Hungary Computer Science and Software Engineering Department University of Westminster London United Kingdom

State-of-the-art gateways are connected to several distributed computing infrastructures (DCIs) and are able to run jobs and workflows simultaneously in all those different DCIs. However, the flexibility of accessing data storages belonging to different DCIs is a missing feature of current gateways. SZTAKI (Institute for computer science and Control) has developed a Data Avenue Blacktop service and aLiferay-based Data Avenue port let that open the door for integrating such features into science gateways. The paper explains the design considerations of the Data Avenue Blacktop service and its usage scenarios in science gateways through the Data Avenue port let.

关键词： Conferences Logic gates

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Privacy-Aware Large-Scale Virological and Epidemiological Data Monitoring

Privacy-Aware Large-Scale Virological and Epidemiological Da...

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Annual IEEE Symposium on computer-Based Medical systems

作者： Constantinos Patsakis Michael Clear Paul Laird Athanasios Zigomitros Mélanie Bouroche Distributed Systems Group School of Computer Science and Statistics Dublin Ireland Greece & Department of Informatics University of Piraeus Greece

Modern mobile and wearable devices are enabling the realization of so-called ubiquitous computing. This provides citizens the technological means to contribute to urban management by becoming sensors within a smart city. Notwithstanding, the health sector is a very crucial factor for city management, imposing restrictions to the decisions directly or indirectly. The question that arises is given the current technological advances, could we collect health related data from citizens without violating their privacy? In this work we propose a methodology that can be used to allow citizens to send their data without disclosing their identity, while simultaneously enabling almost real-time urban-scale virological and epidemiological data monitoring.

关键词： Protocols Monitoring Smart phones Privacy Real-time systems Sensors Cities and towns

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