504 research outputs found
Approximations and Bounds for (n, k) Fork-Join Queues: A Linear Transformation Approach
Compared to basic fork-join queues, a job in (n, k) fork-join queues only
needs its k out of all n sub-tasks to be finished. Since (n, k) fork-join
queues are prevalent in popular distributed systems, erasure coding based cloud
storages, and modern network protocols like multipath routing, estimating the
sojourn time of such queues is thus critical for the performance measurement
and resource plan of computer clusters. However, the estimating keeps to be a
well-known open challenge for years, and only rough bounds for a limited range
of load factors have been given. In this paper, we developed a closed-form
linear transformation technique for jointly-identical random variables: An
order statistic can be represented by a linear combination of maxima. This
brand-new technique is then used to transform the sojourn time of non-purging
(n, k) fork-join queues into a linear combination of the sojourn times of basic
(k, k), (k+1, k+1), ..., (n, n) fork-join queues. Consequently, existing
approximations for basic fork-join queues can be bridged to the approximations
for non-purging (n, k) fork-join queues. The uncovered approximations are then
used to improve the upper bounds for purging (n, k) fork-join queues.
Simulation experiments show that this linear transformation approach is
practiced well for moderate n and relatively large k.Comment: 10 page
Latency Bounds of Packet-Based Fronthaul for Cloud-RAN with Functionality Split
The emerging Cloud-RAN architecture within the fifth generation (5G) of
wireless networks plays a vital role in enabling higher flexibility and
granularity. On the other hand, Cloud-RAN architecture introduces an additional
link between the central, cloudified unit and the distributed radio unit,
namely fronthaul (FH). Therefore, the foreseen reliability and latency for 5G
services should also be provisioned over the FH link. In this paper, focusing
on Ethernet as FH, we present a reliable packet-based FH communication and
demonstrate the upper and lower bounds of latency that can be offered. These
bounds yield insights into the trade-off between reliability and latency, and
enable the architecture design through choice of splitting point, focusing on
high layer split between PDCP and RLC and low layer split between MAC and PHY,
under different FH bandwidth and traffic properties. Presented model is then
analyzed both numerically and through simulation, with two classes of 5G
services that are ultra reliable low latency (URLL) and enhanced mobile
broadband (eMBB).Comment: 6 pages, 7 figures, 3 tables, conference paper (ICC19
Low-Latency Millimeter-Wave Communications: Traffic Dispersion or Network Densification?
This paper investigates two strategies to reduce the communication delay in
future wireless networks: traffic dispersion and network densification. A
hybrid scheme that combines these two strategies is also considered. The
probabilistic delay and effective capacity are used to evaluate performance.
For probabilistic delay, the violation probability of delay, i.e., the
probability that the delay exceeds a given tolerance level, is characterized in
terms of upper bounds, which are derived by applying stochastic network
calculus theory. In addition, to characterize the maximum affordable arrival
traffic for mmWave systems, the effective capacity, i.e., the service
capability with a given quality-of-service (QoS) requirement, is studied. The
derived bounds on the probabilistic delay and effective capacity are validated
through simulations. These numerical results show that, for a given average
system gain, traffic dispersion, network densification, and the hybrid scheme
exhibit different potentials to reduce the end-to-end communication delay. For
instance, traffic dispersion outperforms network densification, given high
average system gain and arrival rate, while it could be the worst option,
otherwise. Furthermore, it is revealed that, increasing the number of
independent paths and/or relay density is always beneficial, while the
performance gain is related to the arrival rate and average system gain,
jointly. Therefore, a proper transmission scheme should be selected to optimize
the delay performance, according to the given conditions on arrival traffic and
system service capability
Collaborative Uploading in Heterogeneous Networks: Optimal and Adaptive Strategies
Collaborative uploading describes a type of crowdsourcing scenario in
networked environments where a device utilizes multiple paths over neighboring
devices to upload content to a centralized processing entity such as a cloud
service. Intermediate devices may aggregate and preprocess this data stream.
Such scenarios arise in the composition and aggregation of information, e.g.,
from smartphones or sensors. We use a queuing theoretic description of the
collaborative uploading scenario, capturing the ability to split data into
chunks that are then transmitted over multiple paths, and finally merged at the
destination. We analyze replication and allocation strategies that control the
mapping of data to paths and provide closed-form expressions that pinpoint the
optimal strategy given a description of the paths' service distributions.
Finally, we provide an online path-aware adaptation of the allocation strategy
that uses statistical inference to sequentially minimize the expected waiting
time for the uploaded data. Numerical results show the effectiveness of the
adaptive approach compared to the proportional allocation and a variant of the
join-the-shortest-queue allocation, especially for bursty path conditions.Comment: 15 pages, 11 figures, extended version of a conference paper accepted
for publication in the Proceedings of the IEEE International Conference on
Computer Communications (INFOCOM), 201
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
On the Role of Preemption for Timing Metrics in Coded Multipath Communication
Recent trends in communication networks have focused on Quality of Service
(QoS) requirements expressed through timing metrics such as latency or Age of
Information (AoI). A possible way to achieve this is coded multipath
communication: redundancy is added to a block of information through a robust
packet-level code, transmitting across multiple independent channels to reduce
the impact of blockages or rate fluctuation. The number of these links can grow
significantly over traditional two-path schemes: in these scenarios, the
optimization of the timing metrics is non-trivial, and latency and AoI might
require different settings. In particular, packet preemption is often the
optimal solution to optimize AoI in uncoded communication, but can
significantly reduce the reliability of individual blocks. In this work, we
model the multipath communication as a fork-join D/M/(K,N)/L queue, where K
blocks of information are encoded into N>K redundant blocks. We derive the
latency and Peak AoI (PAoI) distributions for different values of the queue
size L. Our results show that preemption is not always the optimal choice, as
dropping a late packet on one path might affect the reliability of the whole
block, and that minimizing the PAoI leads to poor latency performance.Comment: Submitted for publication to the IEEE Transactions on Communication
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