119,415 research outputs found
When Queueing Meets Coding: Optimal-Latency Data Retrieving Scheme in Storage Clouds
In this paper, we study the problem of reducing the delay of downloading data
from cloud storage systems by leveraging multiple parallel threads, assuming
that the data has been encoded and stored in the clouds using fixed rate
forward error correction (FEC) codes with parameters (n, k). That is, each file
is divided into k equal-sized chunks, which are then expanded into n chunks
such that any k chunks out of the n are sufficient to successfully restore the
original file. The model can be depicted as a multiple-server queue with
arrivals of data retrieving requests and a server corresponding to a thread.
However, this is not a typical queueing model because a server can terminate
its operation, depending on when other servers complete their service (due to
the redundancy that is spread across the threads). Hence, to the best of our
knowledge, the analysis of this queueing model remains quite uncharted.
Recent traces from Amazon S3 show that the time to retrieve a fixed size
chunk is random and can be approximated as a constant delay plus an i.i.d.
exponentially distributed random variable. For the tractability of the
theoretical analysis, we assume that the chunk downloading time is i.i.d.
exponentially distributed. Under this assumption, we show that any
work-conserving scheme is delay-optimal among all on-line scheduling schemes
when k = 1. When k > 1, we find that a simple greedy scheme, which allocates
all available threads to the head of line request, is delay optimal among all
on-line scheduling schemes. We also provide some numerical results that point
to the limitations of the exponential assumption, and suggest further research
directions.Comment: Original accepted by IEEE Infocom 2014, 9 pages. Some statements in
the Infocom paper are correcte
Unsplittable Load Balancing in a Network of Charging Stations Under QoS Guarantees
The operation of the power grid is becoming more stressed, due to the
addition of new large loads represented by Electric Vehicles (EVs) and a more
intermittent supply due to the incorporation of renewable sources. As a
consequence, the coordination and control of projected EV demand in a network
of fast charging stations becomes a critical and challenging problem.
In this paper, we introduce a game theoretic based decentralized control
mechanism to alleviate negative impacts from the EV demand. The proposed
mechanism takes into consideration the non-uniform spatial distribution of EVs
that induces uneven power demand at each charging facility, and aims to: (i)
avoid straining grid resources by offering price incentives so that customers
accept being routed to less busy stations, (ii) maximize total revenue by
serving more customers with the same amount of grid resources, and (iii)
provide charging service to customers with a certain level of
Quality-of-Service (QoS), the latter defined as the long term customer blocking
probability. We examine three scenarios of increased complexity that gradually
approximate real world settings. The obtained results show that the proposed
framework leads to substantial performance improvements in terms of the
aforementioned goals, when compared to current state of affairs.Comment: Accepted for Publication in IEEE Transactions on Smart Gri
Efficient memory management in VOD disk array servers usingPer-Storage-Device buffering
We present a buffering technique that reduces video-on-demand server memory requirements in more than one order of magnitude. This technique, Per-Storage-Device Buffering (PSDB), is based on the allocation of a fixed number of buffers per storage device, as opposed to existing solutions based on per-stream buffering allocation. The combination of this technique with disk array servers is studied in detail, as well as the influence of Variable Bit Streams. We also present an interleaved data placement strategy, Constant Time Length Declustering, that results in optimal performance in the service of VBR streams. PSDB is evaluated by extensive simulation of a disk array server model that incorporates a simulation based admission test.This research was supported in part by the National R&D Program of Spain, Project Number TIC97-0438.Publicad
Electric Power Allocation in a Network of Fast Charging Stations
In order to increase the penetration of electric vehicles, a network of fast
charging stations that can provide drivers with a certain level of quality of
service (QoS) is needed. However, given the strain that such a network can
exert on the power grid, and the mobility of loads represented by electric
vehicles, operating it efficiently is a challenging problem. In this paper, we
examine a network of charging stations equipped with an energy storage device
and propose a scheme that allocates power to them from the grid, as well as
routes customers. We examine three scenarios, gradually increasing their
complexity. In the first one, all stations have identical charging capabilities
and energy storage devices, draw constant power from the grid and no routing
decisions of customers are considered. It represents the current state of
affairs and serves as a baseline for evaluating the performance of the proposed
scheme. In the second scenario, power to the stations is allocated in an
optimal manner from the grid and in addition a certain percentage of customers
can be routed to nearby stations. In the final scenario, optimal allocation of
both power from the grid and customers to stations is considered. The three
scenarios are evaluated using real traffic traces corresponding to weekday rush
hour from a large metropolitan area in the US. The results indicate that the
proposed scheme offers substantial improvements of performance compared to the
current mode of operation; namely, more customers can be served with the same
amount of power, thus enabling the station operators to increase their
profitability. Further, the scheme provides guarantees to customers in terms of
the probability of being blocked by the closest charging station. Overall, the
paper addresses key issues related to the efficient operation of a network of
charging stations.Comment: Published in IEEE Journal on Selected Areas in Communications July
201
Clockwise: a mixed-media file system
This paper presents Clockwise, a mixed-media file system. The primary goal of Clockwise is to provide a storage architecture that supports the storage and retrieval of best-effort and real-time file system data. Clockwise provides an abstraction called a dynamic partition that groups lists of related (large) blocks on one or more disks. Dynamic partitions can grow and shrink in size and reading or writing of dynamic partitions can be scheduled explicitly. With respect to scheduling, Clockwise uses a novel strategy to pre-calculate schedule slack time and it schedules best-effort requests before queued real-time requests in this slack tim
- …