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MSWiM 2017 - Proceedings of the 20th ACM international conference on Modeling, Analysis and Simulation of Wireless and Mobile systems

MSWiM 2017 - Proceedings of the 20th ACM International Confe...

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20th ACM international conference on Modeling, Analysis and Simulation of Wireless and Mobile systems, MSWiM 2017

ISBN: (纸本)9781450351645

the proceedings contain 42 papers. the topics discussed include: QoS-aware task offloading in distributed cloudlets with virtual network function services;hardening opportunistic HIP;serial in-network processing for large stationary wireless sensor networks;joint user association and backhaul routing for green 5G mesh millimeterwave backhaul networks;reverse engineering human mobility in large-scale natural disasters;semi-blind interference prediction in wireless networks;rate-compatible transmission schemes based on parallel concatenated punctured polar codes;live synthesis of vehicle-sourced data over 4G LTE;providing computing services through mobile devices in a collaborative way - a fog computing case study;an uncertain continuous collaborative users finding algorithm for location privacy protection;provisioning and management of internet of things applications: open issues and insights;DADCA: an efficient distributed algorithm for aerial data collection from wireless sensors networks by UAVs;lifetime-aware data collection using a mobile sink in WSNs with unreachable regions;experimental study of packet loss in a UWB sensor network for aircraft;and Acrux: indoor localization without strings.

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Large files, small writes, and pNFS 06

Large files, small writes, and pNFS

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20th Annual international conference on Supercomputing, ICS 2006

作者： Hildebrand, Dean Ward, Lee Honeyman, Peter Center for Information Technology Integration University of Michigan Scalable Computing Systems Department Sandia National Laboratories

ISBN: (纸本)1595932828

Workload characterization studies highlight the prevalence of small and sequential data requests in scientific applications. parallel file systems excel at large data transfers but sometimes at the expense of small I/O performance. pNFS is an NFSv4.1 high-performance enhancement that provides direct storage access to parallel file systems while preserving NFSv4 operating system and hardware platform independence. this paper demonstrates that distributed file systems can increase write throughput to parallel data stores - -regardless of file size - -by overcoming parallel file system inefficiencies. We also show how pNFS can improve the overall write performance of parallel file systems by using direct, parallel I/O for large write requests and a distributed file system for small write requests. We describe our pNFS prototype and present experiments demonstrating the performance improvements. Copyright (c) 2006 ACM.

关键词： File organization

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A Preliminary Model for Optimal Load Distribution in Heterogeneous Smart Environments 20

A Preliminary Model for Optimal Load Distribution in Heterog...

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IEEE 20th international conference on High Performance Switching and Routing (HPSR)

作者： Garcia, Jordi Aguilo, Francesc Simo, Ester Zaragoza, Marisa Masip-Bruin, Xavi Lu, Yunsong Prieto-Gonzalez, Andres Molinas-Ramon, Joan UPC BarcelonaTech Adv Network Architectures Lab CRAAX Vilanova I La Geltru 08800 Spain Huawei Technol Santa Clara CA 95050 USA

ISBN: (纸本)9781728116860

Smart cities are becoming popular and, with them, a plethora of resources is emerging turning into a massive concentration of computing devices. In such environments, the deployment of a smart resources management system is envisioned as an extraordinary opportunity to provide almost unlimited computing and networking capabilities obtained by putting together a vast set of nearby devices, hence offering high performance computing while benefiting from low latency networking. In this scenario, where millions of highly heterogeneous devices are available, a key challenge is to select the set of devices suited the most to carry out some specific tasks. In this paper, we present a performance estimation model intended to find an optimal solution for load distribution over massive heterogeneous systems, considering the effects of both, distributed computing and network overhead. the current implementation is in a preliminary stage, considering only fully parallel applications. Trials conducted considering several hardware configurations, with either homogeneous or heterogeneous systems, show the fact that the predicted performance matches the one obtained by the experimental executions with an almost negligible deviation. these initial results encourage us to continue developing the model for more complex and realistic applications.

关键词： Computational modeling Load modeling Task analysis Urban areas Performance evaluation Cloud computing Optimization

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20th international conference on parallel Processing, Euro-Par 2014

20th International Conference on Parallel Processing, Euro-P...

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20th international conference on parallel Processing, Euro-Par 2014

ISBN: (纸本)9783319098722

the proceedings contain 68 papers. the special focus in this conference is on Support tools environments, Performance prediction and evaluation, Scheduling and load balancing, High performance architectures and compilers, parallel and distributed data management, Grid, Cluster and cloud computing, Green high performance computing, distributed systems and algorithms, parallel and distributed programming, parallel numerical algorithms, Multicore and manycore programming, theory and algorithms for parallel computation and High performance networks and communication. the topics include: MPI trace compression using event flow graphs;customized scalable tracing with in-situ data analysis;performance measurement and analysis of transactional memory and speculative execution on IBM blue Gene/Q;an open-source management framework for cloud applications;modeling and simulation of a dynamic task-based runtime system for heterogeneous multi-core architectures;modeling the impact of reduced memory bandwidth on HPC applications;finding the important basic blocks in multithreaded programs;optimization and trade-off analysis for time, energy and resource usage;performance prediction and evaluation of parallel applications in KVM, Xen, and VMware;per-task DRAM energy metering in multicore systems;characterizing the performance-energy tradeoff of small ARM cores in HPC computation;finding efficient queue setup using high-resolution simulations;a progressively pessimistic scheduler for software transactional memory;a queueing theory approach to pareto optimal bags-of-tasks scheduling on clouds;scheduling/placement approach for task-graphs on heterogeneous architecture;energy-aware multi-organization scheduling problem;energy efficient scheduling of mapreduce jobs and switchable scheduling for runtime adaptation of optimization.

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Coherence-based coordinated checkpointing for software distributed shared memory systems

Coherence-based coordinated checkpointing for software distr...

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20th international conference on distributed computing systems (ICDCS 2000)

作者： Kongmunvattana, Angkul Tanchatchawal, Santipong Tzeng, Nian-Feng Univ of Louisiana at Lafayette Lafayette United States

Fault-tolerant techniques that can cope with system failures in software distributed shared memory (SDSM) are essential for creating productive and highly available parallel computing environments on clusters of workstations. In this paper, we propose a new, efficient coordinated checkpointing technique, called coherence-based coordinated checkpointing (CCC), for SDSM. Our CCC minimizes both the checkpointing overhead during failure-free execution and the cost of recovery from failures by leveraging existing coherence information maintained by SDSM. In the presence of system failures, it allows SDSM to recovery from the most recent checkpoint, saving the re-computation time. We have performed experiments on a cluster of eight Sun Ultra-5 workstations, comparing our CCC technique against both simple coordinated checkpointing (SCC) and incremental coordinated checkpointing (ICC) techniques by actually implementing these techniques in TreadMarks, a state-of-the-art SDSM system. the experimental results demonstrate that our CCC technique consistently outperforms both SCC and ICC techniques. In particular, our technique increases the execution time slightly by 0.5% to 4% for a 2-minute checkpointing interval during failure-free execution, while SCC and ICC techniques result in the execution time overhead of 4% to 100% and 3% to 64%, respectively, for the same checkpointing interval.

关键词： parallel processing systems

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Privacy-Protected Blockchain System 20

Privacy-Protected Blockchain System

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20th IEEE international conference on Mobile Data Management (IEEE MDM)

作者： Zhong, Ping Zhong, Qikai Mi, Haibo Zhang, Shigeng Xiang, Yang Cent S Univ Changsha Hunan Peoples R China Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

ISBN: (纸本)9781728133638

the blockchain uses a decentralized consensus mechanism to maintain the books in an immutable way, which ensures the blockchain smart contract system highly secure. In existing blockchain systems, all user information is disclosed in the blockchain. However, currently users begin to pay more and more attention to personal privacy, therefore the future blockchain smart contract system needs not only to keep immutability but also to protect user privacy. To achieve this goal, in this paper we propose a Privacy-Protected Blockchain System, where all data is encrypted within a controllable period of time. Although the data is visible from a historical perspective, our design can effectively protect user privacy and against deceivers, making the system more secure and healthy.

关键词： Blockchain Smart contracts Encryption Data privacy Privacy Peer-to-peer computing

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A holistic stream partitioning algorithm for distributed stream processing systems 20

A holistic stream partitioning algorithm for distributed str...

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20th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2019

作者： Li, Kejian Liu, Gang Lu, Minhua Guangdong Province Key Laboratory of Popular High Performance Computers Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Biomedical Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9781728126166

the performances of modern distributed stream processing systems are critically affected by the distribution of the load across workers. Skewed data streams in real world are very common and pose a great challenge to these systems, especially for stateful applications. Key splitting, which allows a single key to be routed to multiple workers, is a great idea to achieve good balance of load in the cluster. However, it comes with the cost of increased memory consumption and computation overhead as well as network communication. In this paper, we present a new definition of metric to model the cost of key splitting for intra-operator parallelism in stream processing systems and provide a novel perspective to reduce replication factor while keeping both overall load imbalance and processing latency low. Similar to previous work, our approach treats the head and the tail of the distribution differently in order to reduce memory requirements. For the head, it uses our proposed notion of regional load imbalance to decide dynamically whether to make one more worker responsible for the heavy hitter or not. For the tail, it simply uses hash partitioning to keep the size of the routing table for the head as small as possible. Extensive experimental evaluation demonstrates that our approach provides superior performance compared to the state-of-the-art partitioning algorithms in terms of load imbalance, replication factor and latency over different levels of skewed stream distributions. © 2019 IEEE.

关键词： distributed parameter control systems

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Accelerating the HMMER sequence analysis suite using conventional processors

Accelerating the HMMER sequence analysis suite using convent...

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20th international conference on Advanced Information Networking and Applications

作者： Walters, John Paul Qudah, Bashar Chaudhary, Vipin Wayne State Univ Inst Comp Sci Detroit MI 48202 USA Wayne State Univ Elect & Comp Engn Detroit MI 48202 USA

ISBN: (纸本)0769524664

Due to the ever-increasing size of sequence databases it has become clear that faster techniques must be employed to effectively perform biological sequence analysis in a reasonable amount of time. Exploiting the inherent parallelism between sequences is a common strategy. In this paper we enhance both the fine-grained and course-grained parallelism within the HMMER [2] sequence analysis suite. Our strategies are complementary to one another and, where necessary, can be used as drop-in replacements to the strategies already provided within HMMER. We use conventional processors (Intel Pentium IV Xeon) as well as the freely available MPICH parallel programming environment [1]. Our results show that the MPICH implementation greatly outperforms the PVM HMMER implementation, and our SSE2 implementation also lends greater computational power at no cost to the user.

关键词： parallel processing systems

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Deterministic optimal routing for two heterogeneous parallel servers

Deterministic optimal routing for two heterogeneous parallel...

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20th international conference on distributed computing systems (ICDCS 2000)

作者： Oida, Kazumasa Shinjo, Kazumasa ATR Adaptive Communications Research Lab Kyoto Japan

this paper describes the characteristics of an optimal routing that assigns each arriving packet to one of two heterogeneous parallel servers. the characteristics are derived from numerical solutions to a routing problem, which finds an optimal routing that minimizes the average packet delay under the condition that the input traffic is completely deterministic. Four characteristics are presented. (1) Under light or moderate traffic, the average packet delay of the optimal routing is almost the same as that of the join the shortest delay (JSD) policy. (2) As traffic becomes heavier, the optimal routing more often uses the fix queue based on size (FS) policy. (3) Under heavy traffic, the optimal routing assigns small packets to a slower server. (4) As the ratio of the two servers' service rates C1/C2 (C1 &le C2) decreases, under lighter traffic the optimal routing uses the FS policy. A new adaptive routing policy based on these four characteristics outperforms the JSD policy.

关键词： Mobile computing

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parallelization of the Array Method Using OpenMP 20th

Parallelization of the Array Method Using OpenMP

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20th Mexican international conference on Artificial Intelligence (MICAI)

作者： Velarde Martinez, Apolinar Inst Tecnol El Llano Aguascalientes Carretera Aguascalientes San Luis PotosiKm 18 Aguascalientes Aguascalientes Mexico

ISBN: (纸本)9783030898205;9783030898199

Shared memory programming and distributed memory programming, are the most prominent ways of parallelize applications requiring high processing times and large amounts of storage in High Performance computing (HPC) systems;parallel applications can be represented by parallel Task Graphs (PTG) using Directed Acyclic Graphs (DAGs). the scheduling of PTGs in HPCS is considered a NP-Complete combinatorial problem that requires large amounts of storage and long processing times. Heuristic methods and sequential programming languages have been proposed to address this problem. In the open access paper: Scheduling in Heterogeneous distributed computing systems Based on Internal Structure of parallel Tasks Graphs with Meta-Heuristics, the Array Method is presented, this method optimizes the use of Processing Elements (PE) in a HPCS and improves response times in scheduling and mapping resource with the use of the Univariate Marginal Distribution Algorithm (UMDA);Array Method uses the internal characteristics of PTGs to make task scheduling;this method was programmed in the C language in sequential form, analyzed and tested with the use of algorithms for the generation of synthetic workloads and DAGs of real applications. Considering the great benefits of parallel software, this research work presents the Array Method using parallel programming with OpenMP. the results of the experiments show an acceleration in the response times of parallel programming compared to sequential programming when evaluating three metrics: waiting time, makespan and quality of assignments.

关键词： parallel Task Graphs (PTG) High Performance computing (HPC) systems Scheduling tasks Univariate Marginal Distribution Algorithm (UMDA) Array method

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