1,721,056 research outputs found
SPO: A Secure and Performance-aware Optimization for MapReduce Scheduling
No full textMapReduce is a common framework that effectively processes multi-petabyte data in a distributed manner. Therefore, MapReduce is widely used in heterogeneous environments, such as cloud, to provide performance adequate for system needs. Despite the MapReduce benefits, tweaking the system configuration to achieve the maximum performance is still challenging and needs deep expertise. Besides, some new MapReduce security issues, which has not been well-addressed yet, are recently raised. In this paper, we present a performance-aware and secure framework, named SPO, to minimize the makespan of the tasks while considering task security constraints. Inspired by the HEFT algorithm, first, we introduce SPO, which proposes a two-stage static scheduler in Map and Reduce phases, respectively, to minimize makespan while considering network traffic. Plus, SPO∗ introduces a mathematical optimization model of the proposed scheduler aiming to estimate the system performance while considering security constraints with an error of less than 2%. The experimental results demonstrate that SPO outperforms Hadoop-stock in terms of makespan and network traffic by 29% and 31%, respectively, for the tasks running in heterogeneous environments
MapReduce: an infrastructure review and research insights
No full textIn the current decade, doing the search on massive data to find “hidden” and valuable information within it is growing. This search can result in heavy processing on considerable data, leading to the development of solutions to process such huge information based on distributed and parallel processing. Among all the parallel programming models, one that gains a lot of popularity is MapReduce. The goal of this paper is to survey researches conducted on the MapReduce framework in the context of its open-source implementation, Hadoop, in order to summarize and report the wide topic area at the infrastructure level. We managed to do a systematic review based on the prevalent topics dealing with MapReduce in seven areas: (1) performance; (2) job/task scheduling; (3) load balancing; (4) resource provisioning; (5) fault tolerance in terms of availability and reliability; (6) security; and (7) energy efficiency. We run our study by doing a quantitative and qualitative evaluation of the research publications’ trend which is published between January 1, 2014, and November 1, 2017. Since the MapReduce is a challenge-prone area for researchers who fall off to work and extend with, this work is a useful guideline for getting feedback and starting research
POSTER: An intelligent framework to parallelize hadoop phases
No full textHadoop-stock is a reliable, scalable, and open source implementation of the MapReduce framework to process data-intensive applications in a distributed and parallel environment. In a common environment between multiple users with various types of applications, due to the lower number of resources than the number of jobs, there will be multi-wave jobs. Shuffling as the longest phase of running a job has the most adverse effect (network traffic) on the job execution time. On one hand, due to the dependency of shuffle phase to reduce task, the shuffle phase could not start until the reduce task being scheduled. On the other hand, the static scheduling of reduce tasks results in loss of reduce slots. This paper presents our ongoing effort in the designing an intelligent service in which the sort/merge and shuffle phases are completely independent of map and reduce phases and could act in parallel with map and reduce phases. This parallelism mitigates the job completion time
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
CAST: Content-Aware STT-MRAM Cache Write Management for Different Levels of Approximation
Full text linkSpin transfer torque magnetic RAM (STT-MRAM) technology is one of the most promising alternative for static RAM (SRAM) for implementing on-chip memories. Compared with SRAMs, STT-MRAMs benefit from higher density and near-zero leakage power, nonetheless they impose high energy consumption for reliable write operations. However, in many applications, absolute data integrity is not required; thus, acting on the current applied in the write operations may represent a novel knob for disciplined approximate computing to obtain energy saving with a minimal quality loss in applications' outputs. This article proposes CAST, a hardware/software approach to adjust the energy/quality of write operations in STT-MRAM caches in multicore systems based on the content of requested write operations. CAST utilizes fine-grained cache-line-level actuation knobs with different levels of quality for individual write operations. This unique feature of STT-MRAMs allows to avoid interapplication actuation interference suffered by SRAMs, and makes the approach particularly suitable for systems running multiple applications with mixed accuracy sensitivity. Moreover, CAST exploits another peculiarity of STT-MRAMs represented by the asymmetry and transition-dependency of the write error rate, to further tune in a fine-grained manner the write current to achieve an additional energy saving, even in full-accurate applications. Our evaluations on workloads of full-approximate, mixed-criticality, and full-accurate applications demonstrate up to 57%, 34%, and 21% energy savings over a baseline STT-MRAM cache, respectively, with an acceptable quality of the generated outputs
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