42 research outputs found
Approximate performance analysis of generalized join the shortest queue routing
In this paper we propose a highly accurate approximate performance analysis
of a heterogeneous server system with a processor sharing service discipline
and a general job-size distribution under a generalized join the shortest queue
(GJSQ) routing protocol. The GJSQ routing protocol is a natural extension of
the well-known join the shortest queue routing policy that takes into account
the non-identical service rates in addition to the number of jobs at each
server. The performance metrics that are of interest here are the equilibrium
distribution and the mean and standard deviation of the number of jobs at each
server. We show that the latter metrics are near-insensitive to the job-size
distribution using simulation experiments. By applying a single queue
approximation we model each server as a single server queue with a
state-dependent arrival process, independent of other servers in the system,
and derive the distribution of the number of jobs at the server. These
state-dependent arrival rates are intended to capture the inherent correlation
between servers in the original system and behave in a rather atypical way.Comment: 16 pages, 5 figures -- version 2 incorporates minor textual change
Separation of timescales in a two-layered network
We investigate a computer network consisting of two layers occurring in, for
example, application servers. The first layer incorporates the arrival of jobs
at a network of multi-server nodes, which we model as a many-server Jackson
network. At the second layer, active servers at these nodes act now as
customers who are served by a common CPU. Our main result shows a separation of
time scales in heavy traffic: the main source of randomness occurs at the
(aggregate) CPU layer; the interactions between different types of nodes at the
other layer is shown to converge to a fixed point at a faster time scale; this
also yields a state-space collapse property. Apart from these fundamental
insights, we also obtain an explicit approximation for the joint law of the
number of jobs in the system, which is provably accurate for heavily loaded
systems and performs numerically well for moderately loaded systems. The
obtained results for the model under consideration can be applied to
thread-pool dimensioning in application servers, while the technique seems
applicable to other layered systems too.Comment: 8 pages, 2 figures, 1 table, ITC 24 (2012
Self-* overload control for distributed web systems
Unexpected increases in demand and most of all flash crowds are considered
the bane of every web application as they may cause intolerable delays or even
service unavailability. Proper quality of service policies must guarantee rapid
reactivity and responsiveness even in such critical situations. Previous
solutions fail to meet common performance requirements when the system has to
face sudden and unpredictable surges of traffic. Indeed they often rely on a
proper setting of key parameters which requires laborious manual tuning,
preventing a fast adaptation of the control policies. We contribute an original
Self-* Overload Control (SOC) policy. This allows the system to self-configure
a dynamic constraint on the rate of admitted sessions in order to respect
service level agreements and maximize the resource utilization at the same
time. Our policy does not require any prior information on the incoming traffic
or manual configuration of key parameters. We ran extensive simulations under a
wide range of operating conditions, showing that SOC rapidly adapts to time
varying traffic and self-optimizes the resource utilization. It admits as many
new sessions as possible in observance of the agreements, even under intense
workload variations. We compared our algorithm to previously proposed
approaches highlighting a more stable behavior and a better performance.Comment: The full version of this paper, titled "Self-* through self-learning:
overload control for distributed web systems", has been published on Computer
Networks, Elsevier. The simulator used for the evaluation of the proposed
algorithm is available for download at the address:
http://www.dsi.uniroma1.it/~novella/qos_web
Towards Autonomic Service Provisioning Systems
This paper discusses our experience in building SPIRE, an autonomic system
for service provision. The architecture consists of a set of hosted Web
Services subject to QoS constraints, and a certain number of servers used to
run session-based traffic. Customers pay for having their jobs run, but require
in turn certain quality guarantees: there are different SLAs specifying charges
for running jobs and penalties for failing to meet promised performance
metrics. The system is driven by an utility function, aiming at optimizing the
average earned revenue per unit time. Demand and performance statistics are
collected, while traffic parameters are estimated in order to make dynamic
decisions concerning server allocation and admission control. Different utility
functions are introduced and a number of experiments aiming at testing their
performance are discussed. Results show that revenues can be dramatically
improved by imposing suitable conditions for accepting incoming traffic; the
proposed system performs well under different traffic settings, and it
successfully adapts to changes in the operating environment.Comment: 11 pages, 9 Figures,
http://www.wipo.int/pctdb/en/wo.jsp?WO=201002636
An architecture of internet based data processing based on multicast and anycast protocols
Most of the current web-based application systems suffer from poor performance and costly heterogeneous accessing. Distributed or replicated strategies can alleviate the problem in some degree, but there are still some problems of the distributed or replicated model, such as data synchronization, load balance, and so on. In this paper, we propose a novel architecture for Internet-based data processing system based on multicast and anycast protocols. The proposed architecture breaks the functionalities of existing data processing system, in particular, the database functionality, into several agents. These agents communicate with each other using multicast and anycast mechanisms. We show that the proposed architecture provides better scalability, robustness, automatic load balance, and performance than the current distributed architecture of Internet-based dataprocessing.<br /
Patia: Adaptive distributed webserver (A position paper)
This paper introduces the Patia Adaptive Webserver architecture, which is distributed and consists of semi-autonomous agents called FLYs. The FLY carries with it the set of rules and adaptivity policies required to deliver the data to the requesting client. Where a change in the FLY’s external environment could affect performance, it is the FLY’s responsibility to change the method of delivery (or the actual object being delivered). It is our conjecture that the success of today’s multimedia websites in terms of performance lies in the architecture of the underlying servers and their ability to adapt to changes in demand and resource availability, as well as their ability to scale. We believe that the distributed and autonomous nature of this system are key factors in achieving this.
ADAPTIVE FRAMWORK FOR DATA DISTRIBUTION IN CLOUD-ELASTIC SERVER ARCHITECTURE
ABSTRACT The increasing quantity of information to be processed and store in a data center and cloud also, th
Методи оптимізації розподілу навантаження
Considered most widespread methods of load distribution for the WEB-server, which enhance their performance and productivity and ensure their continuous operationРассмотрены наиболее распространенные методы распределения нагрузки для WEB-сервере, которые повышают их быстродействие и производительность и обеспечивают их непрерывную работуРозглянуто найбільш розповсюдженні методи розподілу навантаження для WEB-сервері, які підвищують їх швидкодію та продуктивність і забезпечують їх безперервну робот