64 research outputs found
Elements for Response Time Statistics in ERP Transaction Systems
We present some measurements and ideas for response time statistics in ERP
systems. It is shown that the response time distribution of a given transaction
in a given system is generically a log-normal distribution or, in some
situations, a sum of two or more log-normal distributions. We present some
arguments for this form of the distribution based on heuristic rules for
response times, and we show data from performance measurements in actual
systems to support the log-normal form. Deviations of the log-normal form can
often be traced back to performance problems in the system. Consequences for
the interpretation of response time data and for service level agreements are
discussed.Comment: revtex, twocolumn, 8 pages, 13 figures. figures replaced by coloured
version
Characterizing Workload of Web Applications on Virtualized Servers
With the ever increasing demands of cloud computing services, planning and
management of cloud resources has become a more and more important issue which
directed affects the resource utilization and SLA and customer satisfaction.
But before any management strategy is made, a good understanding of
applications' workload in virtualized environment is the basic fact and
principle to the resource management methods. Unfortunately, little work has
been focused on this area. Lack of raw data could be one reason; another reason
is that people still use the traditional models or methods shared under
non-virtualized environment. The study of applications' workload in virtualized
environment should take on some of its peculiar features comparing to the
non-virtualized environment. In this paper, we are open to analyze the workload
demands that reflect applications' behavior and the impact of virtualization.
The results are obtained from an experimental cloud testbed running web
applications, specifically the RUBiS benchmark application. We profile the
workload dynamics on both virtualized and non-virtualized environments and
compare the findings. The experimental results are valuable for us to estimate
the performance of applications on computer architectures, to predict SLA
compliance or violation based on the projected application workload and to
guide the decision making to support applications with the right hardware.Comment: 8 pages, 8 figures, The Fourth Workshop on Big Data Benchmarks,
Performance Optimization, and Emerging Hardware in conjunction with the 19th
ACM International Conference on Architectural Support for Programming
Languages and Operating Systems (ASPLOS-2014), Salt Lake City, Utah, USA,
March 1-5, 201
KISS: Stochastic Packet Inspection Classifier for UDP Traffic
This paper proposes KISS, a novel Internet classifica- tion engine. Motivated by the expected raise of UDP traffic, which stems from the momentum of Peer-to-Peer (P2P) streaming appli- cations, we propose a novel classification framework that leverages on statistical characterization of payload. Statistical signatures are derived by the means of a Chi-Square-like test, which extracts the protocol "format," but ignores the protocol "semantic" and "synchronization" rules. The signatures feed a decision process based either on the geometric distance among samples, or on Sup- port Vector Machines. KISS is very accurate, and its signatures are intrinsically robust to packet sampling, reordering, and flow asym- metry, so that it can be used on almost any network. KISS is tested in different scenarios, considering traditional client-server proto- cols, VoIP, and both traditional and new P2P Internet applications. Results are astonishing. The average True Positive percentage is 99.6%, with the worst case equal to 98.1,% while results are al- most perfect when dealing with new P2P streaming applications
Performance evaluation of an open distributed platform for realistic traffic generation
Network researchers have dedicated a notable part of their efforts
to the area of modeling traffic and to the implementation of efficient traffic
generators. We feel that there is a strong demand for traffic generators
capable to reproduce realistic traffic patterns according to theoretical
models and at the same time with high performance. This work presents an open
distributed platform for traffic generation that we called distributed
internet traffic generator (D-ITG), capable of producing traffic (network,
transport and application layer) at packet level and of accurately replicating
appropriate stochastic processes for both inter departure time (IDT) and
packet size (PS) random variables. We implemented two different versions of
our distributed generator. In the first one, a log server is in charge of
recording the information transmitted by senders and receivers and these
communications are based either on TCP or UDP. In the other one, senders and
receivers make use of the MPI library. In this work a complete performance
comparison among the centralized version and the two distributed versions of
D-ITG is presented
Weibull mixture model to characterise end-to-end Internet delay at coarse time-scales
Traces collected at monitored points around the Internet contain representative
performance information about the paths their probes traverse. Basic measurement
attributes, such as delay and loss, are easy to collect and provide a means to
both build and validate empirical performance models. However, the task of analysis
and extracting performance conclusions from measurements remains challenging.
Ideally, performance modelling aims to find a set of self-contained parameters to
describe, summarise, profile and easy display network performance status at a time.
This can result in the provision of meaningful information to address applications in
fault and performance management, hence providing input to network provisioning,
traffic engineering and performance prediction.
In this work we present the Weibull Mixture Model, a method to characterise endto-
end network delay measurements within a few simple, accurate, representative and
handleable parameters using a finite combination of Weibull distributions, with all the
aforementioned benefits. The model parameters are related tomeaningful delay characteristics,
such as average peak and tail behaviour in a daily profile, and can be optimally
found using an iterative algorithm known as Expectation Maximisation. Studies on
such parameter evolution can reflect current workload status and all possible network
events impacting packet dynamics, with further applications in network management.
In addition, a self-sufficient procedure to implement the Weibull Mixture Model is
presented, along with a set of matching examples to real GPS synchronised measurements
taken across the Internet, donated by RIPE NCC
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