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检索条件"任意字段=14th International Symposium on Algorithms and Data Structures, WADS 2015"

共 67 条记录，以下是11-20 订阅

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Scalable Infrastructures for data in Motion 14

Scalable Infrastructures for Data in Motion

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14th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing (CCGrid)

作者： Ediger, David McColl, Rob Poovey, Jason Campbell, Dan Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9781479927845

Analytics applications for reporting and human interaction with big data rely upon scalable frameworks for data ingest, storage, and computation. Batch processing of analytic workloads increases latency of results and can perform redundant computation. In real-world applications, new data points are continuously arriving and a suite of algorithms must be updated to reflect the changes. Reducing the latency of re-computation by keeping algorithms online and up-to-date enables fast query, experimentation, and drill-down. In this paper, we share our experiences designing and implementing scalable infrastructure around NoSQL databases for social media analytics applications. We propose a new heterogeneous architecture and execution model for streaming data applications that focuses on throughput and modularity.

关键词： Servers Algorithm design and analysis databases Clustering algorithms data structures Computational modeling Media

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Minimizing data Access Latencies via Virtual Machine Placement Method in datacenter 14

Minimizing Data Access Latencies via Virtual Machine Placeme...

引用

14th international symposium on Pervasive Systems, algorithms and Networks (I-SPAN) / 11th international Conference on Frontier of Computer Science and Technology (FCST) / 3rd international symposium of Creative Computing (ISCC)

作者： Zhang, Xinyan Zhang, Yong Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China Liaoning Normal Univ Sch Comp & Informat Technol Dalian Peoples R China

ISBN: (纸本)9781538608401

the processing framework of large-scale data is becoming a major concern due to an explosive growth of data intensive applications in the cloud environment, such as MapReduce/Hadoop architecture. Many virtual machines (VMs) are used for processing large-scale data of cloud applications. therefore, the total completion time of a task is an important index to evaluate the cloud performance. the access latency between nodes is one of the key factors affecting the task completion time for computing-intensive applications. Additionally, minimizing total access time can reduce the overall bandwidth cost of running the job. this paper proposes an optimization model focused on optimizing VMs placement so as to minimize the total data access latency where the data sets have been located. According to the proposed model, our VMs optimization problem is linear programming. therefore, we obtain the optimum solution of our model by the branch-and-bound algorithm that its time complexity is O(2(NM)) (where N is the number of the data nodes and M is the number of VMs). Simultaneously, we also present a greedy algorithm, which has O(NM) of time complexity, to solve our model. Finally, the simulation results show that all of the solutions of our model are superior to existing models and close to the optimal value.

关键词： datacenter greedy algorithm virtual machine branch-and-bound algorithm

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Polylogarithmic fully retroactive priority queues via hierarchical checkpointing 14th

Polylogarithmic fully retroactive priority queues via hierar...

引用

14th international symposium on algorithms and data structures, wads 2015

作者： Demaine, Erik D. Kaler, Tim Liu, Quanquan Sidford, Aaron Yedidia, Adam MIT CSAIL CambridgeMA United States

ISBN: (纸本)9783319218397

Since the introduction of retroactive data structures at SODA 2004 [1], a major open question has been the difference between partial retroactivity (where updates can be made in the past) and full retroactivity (where queries can also be made in the past). In particular, for priority queues, partial retroactivity is possible in O(logm) time per operation on a m-operation timeline, but the best previously known fully retroactive priority queue has cost Θ(√ mlogm) time per operation. We address this open problem by providing a general logarithmicoverhead transformation from partial to full retroactivity called "hierarchical checkpointing," provided that the given data structure is "time-fusible" (multiple structures with disjoint timespans can be fused into a timeline supporting queries of the present). As an application, we construct a fully retroactive priority queue which can insert an element, delete the minimum element, and find the minimum element, at any point in time, in O(log2 m) amortized time per update and O(log2 mlog logm) time per query, using O(mlogm) space. Our data structure also supports the operation of determining the time at which an element was deleted in O(log2 m) time. © Springer international Publishing Switzerland 2015.

关键词： data structures

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Finding pairwise intersections inside a query range 14th

Finding pairwise intersections inside a query range

引用

14th international symposium on algorithms and data structures, wads 2015

作者： De Berg, Mark Gudmundsson, Joachim Mehrabi, Ali D. Department of Computer Science TU Eindhoven Eindhoven Netherlands School of IT University of Sydney Sydney Australia

ISBN: (纸本)9783319218397

We study the following problem: preprocess a set O of objects into a data structure that allows us to efficiently report all pairs of objects from O that intersect inside an axis-aligned query range Q. We present data structures of size O(n polylog n) and with query time O((k + 1) polylog n), where k is the number of reported pairs, for two classes of objects in the plane: axis-aligned rectangles and objects with small union complexity. For the 3-dimensional case where the objects and the query range are axis-aligned boxes in 3, we present a data structure of size O(n √ n polylog n) and query time O((√ n + k) polylog n). When the objects and query are fat, we obtain O((k +1) polylog n) query time using O(n polylog n) storage. © Springer international Publishing Switzerland 2015.

关键词： data structures

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High-performance Hardware Accelerators for Sorting and Managing Priorities

High-performance Hardware Accelerators for Sorting and Manag...

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14th IEEE international symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Sklyarov, Valery Skliarova, Iouliia Mihhailov, Dmitri Sudnitson, Alexander Univ Aveiro DETI IEETA P-3800 Aveiro Portugal Tallinn Univ Technol Dept Comp Engn Tallinn Estonia

ISBN: (纸本)9781424497560

the paper describes the hardware implementation and optimization of algorithms that process tree-like data structures which are needed for numerous practical applications in such areas as databases, embedded systems, and networks requiring priority management. the emphasis is done on applications that involve fast processing of new incoming data items, such as resorting. Parallelism is achieved by constructing N binary trees (N>1) and applying concurrent operations to N trees at the same time with the aid of N communicating processing modules. It is shown that the considered technique can efficiently be combined with sorting networks, which gives new potentialities for optimization. Modeling in software, experiments with FPGA-based circuits on different computing platforms, and comparisons with the other known methods demonstrate that the performance is increased significantly. It is also shown that the proposed algorithms are easily scalable.

关键词： tree-like data structures fast resorting managing priorities hierarchical FSMs parallelization sorting networks

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Supporting Queries and Analyses of Large-Scale Social Media data with Customizable and Scalable Indexing Techniques over NoSQL databases 14

Supporting Queries and Analyses of Large-Scale Social Media ...

引用

14th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing (CCGrid)

作者： Gao, Xiaoming Qiu, Judy Indiana Univ Sch Informat & Comp Bloomington IN 47405 USA

ISBN: (纸本)9781479927845

Social media data analysis demonstrates two special characteristics in Big data processing. First, most analyses focus on data subsets related to specific social events or activities instead of the whole dataset. Second, analysis workflows consist of multiple stages, and algorithms applied in each stage may use different computation and communication patterns depending on processing frameworks. this paper presents our efforts in supporting the data storage and processing requirements for such characteristics. To achieve efficient queries about target data subsets, we propose a general customizable and scalable indexing framework that can be built over distributed NoSQL databases. this framework allows users to define suitable customized index structures for their query patterns against social media data, and supports scalable indexing of both historical and streaming data. We implement this framework on HBase, and name it IndexedHBase. Starting from IndexedHBase, we build a distributed analysis stack based on YARN to support analysis algorithms using different processing frameworks, such as Hadoop MapReduce, Harp, and Giraph. this analysis stack is used to host the Truthy social media data observatory, and we have applied the customized index structures in supporting both query evaluation and sophisticated analysis algorithms. Performance tests show that our solutions outperform implementations using both direct raw data scans and current indexing mechanisms in existing NoSQL databases.

关键词： Social media data analysis customizable and scalable indexing NoSQL databases YARN

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Enabling self-management of component-based high-performance scientific applications 05

Enabling self-management of component-based high-performance...

引用

14th IEEE international symposium on High Performance Distributed Computing

作者： Liu, H Parashar, M Rutgers State Univ Dept Elect & Comp Engn Appl Software Syst Lab Piscataway NJ 08854 USA

ISBN: (纸本)0780390377

Emerging high-performance parallel/distributed scientific applications and environments are increasingly large, dynamic and complex. As a result, it requires programming systems that enable the applications to detect and dynamically respond to changing requirements, state and execution context by adapting their computational behaviors and interactions. In this paper, we present such a programming system that extends the Common Component Architecture to enable self-management of component-based scientific applications. the programming system separates and categorizes operational requirements of scientific applications, and allows them to be specified and enforced at runtime through re-configuration, optimization and healing of individual components and the application. Two scientific simulations are used to illustrate the system and its self-managing behaviors. A performance evaluation is also presented.

关键词： Application software Component architectures Partitioning algorithms Runtime US Department of Energy Software systems Extraterrestrial phenomena data structures Adaptive mesh refinement Prototypes

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A Parallel Method for Scalable Anonymization of Transaction data 14

A Parallel Method for Scalable Anonymization of Transaction ...

引用

IEEE 14th international symposium on Parallel and Distributed Computing (ISPDC)

作者： Memon, Neelam Loukides, Grigorios Shao, Jianhua Cardiff Univ Sch Comp Sci & Informat Cardiff CF10 3AX S Glam Wales

ISBN: (纸本)9781467371483

Transaction data, such as market basket or diagnostic data, contain sensitive information about individuals. Such data are often disseminated widely to support analytic studies. this raises privacy concerns, as the confidentiality of individuals must be protected. Anonymization is an established methodology to protect transaction data, which can be applied using different algorithms. RBAT is an algorithm for anonymzitng transaction data that has many desirable features. these include flexible specification of privacy requirements and the ability to preserve data utility well. However, like most anonymization methods, RBAT is a sequential algorithm that is not scalable to large datasets. this limits the applicability of RBAT in practice. To address this issue, in this paper, we develop a parallel version of RBAT using MapReduce. We partition the data across a cluster of computing nodes and implement the key operations of RBAT in parallel. Our experimental results show that scalable anonymization of large transaction datasets can be achieved using MapReduce and our method can scale nearly linear to the number of processing nodes.

关键词： Anonymization Distributed algorithms Generalization MapReduce Parallel Method Parallel Processing Privacy Scalability Top-Down Method

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A Framework for Vehicle Routing Approximation Schemes in Trees 1

引用

16th international algorithms and data structures symposium (wads)

作者： Becker, Amariah Paul, Alice Brown Univ Comp Sci Dept Providence RI 02912 USA Brown Univ Data Sci Initiat Providence RI 02912 USA

ISBN: (数字)9783030247669

ISBN: (纸本)9783030247669;9783030247652

We develop a general framework for designing polynomial-time approximation schemes (PTASs) for various vehicle routing problems in trees. In these problems, the goal is to optimally route a fleet of vehicles, originating at a depot, to serve a set of clients, subject to various constraints. For example, in MINIMUM MAKESPAN VEHICLE ROUTING, the number of vehicles is fixed, and the objective is to minimize the longest distance traveled by a single vehicle. Our main insight is that we can often greatly restrict the set of potential solutions without adding too much to the optimal solution cost. this simplification relies on partitioning the tree into clusters such that there exists a near-optimal solution in which every vehicle that visits a given cluster takes on one of a few forms. In particular, only a small number of vehicles serve clients in any given cluster. By using these coarser building blocks, a dynamic programming algorithm can find a near-optimal solution in polynomial time. We show that the framework is flexible enough to give PTASs for many problems, including MINIMUM MAKESPAN VEHICLE ROUTING, DISTANCE-CONSTRAINED VEHICLE ROUTING, CAPACITATED VEHICLE ROUTING, and SCHOOL BUS ROUTING, and can be extended to the multiple depot setting.

关键词： Approximation algorithms Vehicle routing Rooted tree cover

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Fast and simple connectivity in graph timelines 14th

Fast and simple connectivity in graph timelines

引用

14th international symposium on algorithms and data structures, wads 2015

作者： Karczmarz, Adam LĄcki, Jakub University of Warsaw Warszawa Poland

ISBN: (纸本)9783319218397

In this paper we study the problem of answering connectivity queries about a graph timeline. A graph timeline is a sequence of undirected graphs G1,..., Gt on a common set of vertices of size n such that each graph is obtained from the previous one by an addition or a deletion of a single edge. We present data structures, which preprocess the timeline and can answer the following queries: - forall(u, v, a, b) - does the path u → v exist in each of Ga,..., Gb? - exists(u, v, a, b) - does the path u → v exist in any of Ga,..., Gb? - forall2(u, v, a, b) - do there exist two edge-disjoint paths connecting u and v in each of Ga,..., Gb? We show data structures that can answer forall and forall2 queries in O(log n) time after preprocessing in O(m + t log n) time. Here by m we denote the number of edges that remain unchanged in each graph of the timeline. For the case of exists queries, we show how to extend an existing data structure to obtain a preprocessing/query trade-off of 〈O(m + min(nt, t2-α)),O(tα)〉 and show a matching conditional lower bound. © Springer international Publishing Switzerland 2015.

关键词： data structures

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