5,707 research outputs found
Device-Centric Cooperation in Mobile Networks
The increasing popularity of applications such as video streaming in today's
mobile devices introduces higher demand for throughput, and puts a strain
especially on cellular links. Cooperation among mobile devices by exploiting
both cellular and local area connections is a promising approach to meet the
increasing demand. In this paper, we consider that a group of cooperative
mobile devices, exploiting both cellular and local area links and within
proximity of each other, are interested in the same video content. Traditional
network control algorithms introduce high overhead and delay in this setup as
the network control and cooperation decisions are made in a source-centric
manner. Instead, we develop a device-centric stochastic cooperation scheme. Our
device-centric scheme; DcC allows mobile devices to make control decisions such
as flow control, scheduling, and cooperation without loss of optimality. Thanks
to being device-centric, DcC reduces; (i) overhead; i.e., the number of control
packets that should be transmitted over cellular links, so cellular links are
used more efficiently, and (ii) the amount of delay that each packet
experiences, which improves quality of service. The simulation results
demonstrate the benefits of DcC
End-to-End Simulation of 5G mmWave Networks
Due to its potential for multi-gigabit and low latency wireless links,
millimeter wave (mmWave) technology is expected to play a central role in 5th
generation cellular systems. While there has been considerable progress in
understanding the mmWave physical layer, innovations will be required at all
layers of the protocol stack, in both the access and the core network.
Discrete-event network simulation is essential for end-to-end, cross-layer
research and development. This paper provides a tutorial on a recently
developed full-stack mmWave module integrated into the widely used open-source
ns--3 simulator. The module includes a number of detailed statistical channel
models as well as the ability to incorporate real measurements or ray-tracing
data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and
highly customizable, making it easy to integrate algorithms or compare
Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example.
The module is interfaced with the core network of the ns--3 Long Term Evolution
(LTE) module for full-stack simulations of end-to-end connectivity, and
advanced architectural features, such as dual-connectivity, are also available.
To facilitate the understanding of the module, and verify its correct
functioning, we provide several examples that show the performance of the
custom mmWave stack as well as custom congestion control algorithms designed
specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and
Tutorials (revised Jan. 2018
Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting
In a multihop wireless network, it is crucial but challenging to schedule
transmissions in an efficient and fair manner. In this paper, a novel
distributed node scheduling algorithm, called Local Voting, is proposed. This
algorithm tries to semi-equalize the load (defined as the ratio of the queue
length over the number of allocated slots) through slot reallocation based on
local information exchange. The algorithm stems from the finding that the
shortest delivery time or delay is obtained when the load is semi-equalized
throughout the network. In addition, we prove that, with Local Voting, the
network system converges asymptotically towards the optimal scheduling.
Moreover, through extensive simulations, the performance of Local Voting is
further investigated in comparison with several representative scheduling
algorithms from the literature. Simulation results show that the proposed
algorithm achieves better performance than the other distributed algorithms in
terms of average delay, maximum delay, and fairness. Despite being distributed,
the performance of Local Voting is also found to be very close to a centralized
algorithm that is deemed to have the optimal performance
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