27,248 research outputs found
Queuing Theoretic Analysis of Power-performance Tradeoff in Power-efficient Computing
In this paper we study the power-performance relationship of power-efficient
computing from a queuing theoretic perspective. We investigate the interplay of
several system operations including processing speed, system on/off decisions,
and server farm size. We identify that there are oftentimes "sweet spots" in
power-efficient operations: there exist optimal combinations of processing
speed and system settings that maximize power efficiency. For the single server
case, a widely deployed threshold mechanism is studied. We show that there
exist optimal processing speed and threshold value pairs that minimize the
power consumption. This holds for the threshold mechanism with job batching.
For the multi-server case, it is shown that there exist best processing speed
and server farm size combinations.Comment: Paper published in CISS 201
Tars: Timeliness-aware Adaptive Replica Selection for Key-Value Stores
In current large-scale distributed key-value stores, a single end-user
request may lead to key-value access across tens or hundreds of servers. The
tail latency of these key-value accesses is crucial to the user experience and
greatly impacts the revenue. To cut the tail latency, it is crucial for clients
to choose the fastest replica server as much as possible for the service of
each key-value access. Aware of the challenges on the time varying performance
across servers and the herd behaviors, an adaptive replica selection scheme C3
is proposed recently. In C3, feedback from individual servers is brought into
replica ranking to reflect the time-varying performance of servers, and the
distributed rate control and backpressure mechanism is invented. Despite of
C3's good performance, we reveal the timeliness issue of C3, which has large
impacts on both the replica ranking and the rate control, and propose the Tars
(timeliness-aware adaptive replica selection) scheme. Following the same
framework as C3, Tars improves the replica ranking by taking the timeliness of
the feedback information into consideration, as well as revises the rate
control of C3. Simulation results confirm that Tars outperforms C3.Comment: 10pages,submitted to ICDCS 201
Admission Control and Scheduling for High-Performance WWW Servers
In this paper we examine a number of admission control and scheduling protocols for high-performance web servers based on a 2-phase policy for serving HTTP requests. The first "registration" phase involves establishing the TCP connection for the HTTP request and parsing/interpreting its arguments, whereas the second "service" phase involves the service/transmission of data in response to the HTTP request. By introducing a delay between these two phases, we show that the performance of a web server could be potentially improved through the adoption of a number of scheduling policies that optimize the utilization of various system components (e.g. memory cache and I/O). In addition, to its premise for improving the performance of a single web server, the delineation between the registration and service phases of an HTTP request may be useful for load balancing purposes on clusters of web servers. We are investigating the use of such a mechanism as part of the Commonwealth testbed being developed at Boston University
Coding for Fast Content Download
We study the fundamental trade-off between storage and content download time.
We show that the download time can be significantly reduced by dividing the
content into chunks, encoding it to add redundancy and then distributing it
across multiple disks. We determine the download time for two content access
models - the fountain and fork-join models that involve simultaneous content
access, and individual access from enqueued user requests respectively. For the
fountain model we explicitly characterize the download time, while in the
fork-join model we derive the upper and lower bounds. Our results show that
coding reduces download time, through the diversity of distributing the data
across more disks, even for the total storage used.Comment: 8 pages, 6 figures, conferenc
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