2,451 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
Performance Modelling and Optimisation of Multi-hop Networks
A major challenge in the design of large-scale networks is to predict and optimise the
total time and energy consumption required to deliver a packet from a source node to a
destination node. Examples of such complex networks include wireless ad hoc and sensor
networks which need to deal with the effects of node mobility, routing inaccuracies, higher
packet loss rates, limited or time-varying effective bandwidth, energy constraints, and the
computational limitations of the nodes. They also include more reliable communication
environments, such as wired networks, that are susceptible to random failures, security
threats and malicious behaviours which compromise their quality of service (QoS) guarantees.
In such networks, packets traverse a number of hops that cannot be determined
in advance and encounter non-homogeneous network conditions that have been largely
ignored in the literature. This thesis examines analytical properties of packet travel in
large networks and investigates the implications of some packet coding techniques on both
QoS and resource utilisation.
Specifically, we use a mixed jump and diffusion model to represent packet traversal
through large networks. The model accounts for network non-homogeneity regarding
routing and the loss rate that a packet experiences as it passes successive segments of a
source to destination route. A mixed analytical-numerical method is developed to compute
the average packet travel time and the energy it consumes. The model is able to capture
the effects of increased loss rate in areas remote from the source and destination, variable
rate of advancement towards destination over the route, as well as of defending against
malicious packets within a certain distance from the destination. We then consider sending
multiple coded packets that follow independent paths to the destination node so as to
mitigate the effects of losses and routing inaccuracies. We study a homogeneous medium
and obtain the time-dependent properties of the packet’s travel process, allowing us to
compare the merits and limitations of coding, both in terms of delivery times and energy
efficiency. Finally, we propose models that can assist in the analysis and optimisation
of the performance of inter-flow network coding (NC). We analyse two queueing models
for a router that carries out NC, in addition to its standard packet routing function. The
approach is extended to the study of multiple hops, which leads to an optimisation problem
that characterises the optimal time that packets should be held back in a router, waiting
for coding opportunities to arise, so that the total packet end-to-end delay is minimised
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