8,328 research outputs found
ShenZhen transportation system (SZTS): a novel big data benchmark suite
Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets
DiPerF: an automated DIstributed PERformance testing Framework
We present DiPerF, a distributed performance testing framework, aimed at
simplifying and automating service performance evaluation. DiPerF coordinates a
pool of machines that test a target service, collects and aggregates
performance metrics, and generates performance statistics. The aggregate data
collected provide information on service throughput, on service "fairness" when
serving multiple clients concurrently, and on the impact of network latency on
service performance. Furthermore, using this data, it is possible to build
predictive models that estimate a service performance given the service load.
We have tested DiPerF on 100+ machines on two testbeds, Grid3 and PlanetLab,
and explored the performance of job submission services (pre WS GRAM and WS
GRAM) included with Globus Toolkit 3.2.Comment: 8 pages, 8 figures, will appear in IEEE/ACM Grid2004, November 200
pTNoC: Probabilistically time-analyzable tree-based NoC for mixed-criticality systems
The use of networks-on-chip (NoC) in real-time safety-critical multicore systems challenges deriving tight worst-case execution time (WCET) estimates. This is due to the complexities in tightly upper-bounding the contention in the access to the NoC among running tasks. Probabilistic Timing Analysis (PTA) is a powerful approach to derive WCET estimates on relatively complex processors. However, so far it has only been tested on small multicores comprising an on-chip bus as communication means, which intrinsically does not scale to high core counts. In this paper we propose pTNoC, a new tree-based NoC design compatible with PTA requirements and delivering scalability towards medium/large core counts. pTNoC provides tight WCET estimates by means of asymmetric bandwidth guarantees for mixed-criticality systems with negligible impact on average performance. Finally, our implementation results show the reduced area and power costs of the pTNoC.The research leading to these results has received funding from the European Community’s Seventh Framework Programme [FP7/2007-2013] under the PROXIMA Project
(www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Mladen Slijepcevic is funded by the Obra Social Fundación la Caixa under grant Doctorado “la Caixa” - Severo Ochoa. Carles
Hern´andez is jointly funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been
partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer ReviewedPostprint (author's final draft
Design of an integrated airframe/propulsion control system architecture
The design of an integrated airframe/propulsion control system architecture is described. The design is based on a prevalidation methodology that uses both reliability and performance. A detailed account is given for the testing associated with a subset of the architecture and concludes with general observations of applying the methodology to the architecture
MR-BART: Multi-Rate Available Bandwidth Estimation in Real-Time
In this paper, we propose Multi-Rate Bandwidth Available in Real Time
(MR-BART) to estimate the end-to-end Available Bandwidth (AB) of a network
path. The proposed scheme is an extension of the Bandwidth Available in Real
Time (BART) which employs multi-rate (MR) probe packet sequences with Kalman
filtering. Comparing to BART, we show that the proposed method is more robust
and converges faster than that of BART and achieves a more AB accurate
estimation. Furthermore, we analyze the estimation error in MR-BART and obtain
analytical formula and empirical expression for the AB estimation error based
on the system parameters.Comment: 12 Pages (Two columns), 14 Figures, 4 Tables
Exact asymptotics for fluid queues fed by multiple heavy-tailed on-off flows
We consider a fluid queue fed by multiple On-Off flows with heavy-tailed
(regularly varying) On periods. Under fairly mild assumptions, we prove that
the workload distribution is asymptotically equivalent to that in a reduced
system. The reduced system consists of a ``dominant'' subset of the flows, with
the original service rate subtracted by the mean rate of the other flows. We
describe how a dominant set may be determined from a simple knapsack
formulation. The dominant set consists of a ``minimally critical'' set of
On-Off flows with regularly varying On periods. In case the dominant set
contains just a single On-Off flow, the exact asymptotics for the reduced
system follow from known results. For the case of several
On-Off flows, we exploit a powerful intuitive argument to obtain the exact
asymptotics. Combined with the reduced-load equivalence, the results for the
reduced system provide a characterization of the tail of the workload
distribution for a wide range of traffic scenarios
Collecting and Analyzing Failure Data of Bluetooth Personal Area Networks
This work presents a failure data analysis campaign on
Bluetooth Personal Area Networks (PANs) conducted on
two kind of heterogeneous testbeds (working for more than
one year). The obtained results reveal how failures distribution
are characterized and suggest how to improve the
dependability of Bluetooth PANs. Specically, we dene the
failure model and we then identify the most effective recovery
actions and masking strategies that can be adopted for
each failure. We then integrate the discovered recovery actions
and masking strategies in our testbeds, improving the
availability and the reliability of 3.64% (up to 36.6%) and
202% (referred to the Mean Time To Failure), respectively
GPS queues with heterogeneous traffic classes
We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic classes are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing (WFQ), have emerged as an important mechanism for achieving service differentiation in integrated networks. We derive the asymptotic workload behavior of the light-tailed class for the situation where its GPS weight is larger than its traffic intensity. The GPS mechanism ensures that the workload is bounded above by that in an isolated system with the light-tailed class served in isolation at a constant rate equal to its GPS weight. We show that the workload distribution is in fact asymptotically equivalent to that in the isolated system, multiplied with a certain pre-factor, which accounts for the interaction with the heavy-tailed class. Specifically, the pre-factor represents the probability that the heavy-tailed class is backlogged long enough for the light-tailed class to reach overflow. The results provide crucial qualitative insight in the typical overflow scenario
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