4,564 research outputs found
Rigorous and Practical Proportional-fair Allocation for Multi-rate Wi-Fi
Recent experimental studies confirm the prevalence of the widely known performance anomaly
problem in current Wi-Fi networks, and report on the severe network utility degradation caused by
this phenomenon. Although a large body of work addressed this issue, we attribute the refusal of
prior solutions to their poor implementation feasibility with off-the-shelf hardware and their impre-
cise modelling of the 802.11 protocol. Their applicability is further challenged today by very high
throughput enhancements (802.11n/ac) whereby link speeds can vary by two orders of magnitude.
Unlike earlier approaches, in this paper we introduce the first rigorous analytical model of 802.11
stations’ throughput and airtime in multi-rate settings, without sacrificing accuracy for tractability.
We use the proportional-fair allocation criterion to formulate network utility maximisation as a con-
vex optimisation problem for which we give a closed-form solution. We present a fully functional
light-weight implementation of our scheme on commodity access points and evaluate this extensively
via experiments in a real deployment, over a broad range of network conditions. Results demonstrate
that our proposal achieves up to 100% utility gains, can double video streaming goodput and reduces
TCP download times by 8x
A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs
This paper considers proportional fairness amongst ACs in an EDCA WLAN for
provision of distinct QoS requirements and priority parameters. A detailed
theoretical analysis is provided to derive the optimal station attempt
probability which leads to a proportional fair allocation of station
throughputs. The desirable fairness can be achieved using a centralised
adaptive control approach. This approach is based on multivariable statespace
control theory and uses the Linear Quadratic Integral (LQI) controller to
periodically update CWmin till the optimal fair point of operation. Performance
evaluation demonstrates that the control approach has high accuracy performance
and fast convergence speed for general network scenarios. To our knowledge this
might be the first time that a closed-loop control system is designed for EDCA
WLANs to achieve proportional fairness
Energy management in communication networks: a journey through modelling and optimization glasses
The widespread proliferation of Internet and wireless applications has
produced a significant increase of ICT energy footprint. As a response, in the
last five years, significant efforts have been undertaken to include
energy-awareness into network management. Several green networking frameworks
have been proposed by carefully managing the network routing and the power
state of network devices.
Even though approaches proposed differ based on network technologies and
sleep modes of nodes and interfaces, they all aim at tailoring the active
network resources to the varying traffic needs in order to minimize energy
consumption. From a modeling point of view, this has several commonalities with
classical network design and routing problems, even if with different
objectives and in a dynamic context.
With most researchers focused on addressing the complex and crucial
technological aspects of green networking schemes, there has been so far little
attention on understanding the modeling similarities and differences of
proposed solutions. This paper fills the gap surveying the literature with
optimization modeling glasses, following a tutorial approach that guides
through the different components of the models with a unified symbolism. A
detailed classification of the previous work based on the modeling issues
included is also proposed
Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges
With the rapid development of marine activities, there has been an increasing
number of maritime mobile terminals, as well as a growing demand for high-speed
and ultra-reliable maritime communications to keep them connected.
Traditionally, the maritime Internet of Things (IoT) is enabled by maritime
satellites. However, satellites are seriously restricted by their high latency
and relatively low data rate. As an alternative, shore & island-based base
stations (BSs) can be built to extend the coverage of terrestrial networks
using fourth-generation (4G), fifth-generation (5G), and beyond 5G services.
Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs.
Despite of all these approaches, there are still open issues for an efficient
maritime communication network (MCN). For example, due to the complicated
electromagnetic propagation environment, the limited geometrically available BS
sites, and rigorous service demands from mission-critical applications,
conventional communication and networking theories and methods should be
tailored for maritime scenarios. Towards this end, we provide a survey on the
demand for maritime communications, the state-of-the-art MCNs, and key
technologies for enhancing transmission efficiency, extending network coverage,
and provisioning maritime-specific services. Future challenges in developing an
environment-aware, service-driven, and integrated satellite-air-ground MCN to
be smart enough to utilize external auxiliary information, e.g., sea state and
atmosphere conditions, are also discussed
Maximising the Utility of Enterprise Millimetre-Wave Networks
Millimetre-wave (mmWave) technology is a promising candidate for meeting the
intensifying demand for ultra fast wireless connectivity, especially in
high-end enterprise networks. Very narrow beam forming is mandatory to mitigate
the severe attenuation specific to the extremely high frequency (EHF) bands
exploited. Simultaneously, this greatly reduces interference, but generates
problematic communication blockages. As a consequence, client association
control and scheduling in scenarios with densely deployed mmWave access points
become particularly challenging, while policies designed for traditional
wireless networks remain inappropriate. In this paper we formulate and solve
these tasks as utility maximisation problems under different traffic regimes,
for the first time in the mmWave context. We specify a set of low-complexity
algorithms that capture distinctive terminal deafness and user demand
constraints, while providing near-optimal client associations and airtime
allocations, despite the problems' inherent NP-completeness. To evaluate our
solutions, we develop an NS-3 implementation of the IEEE 802.11ad protocol,
which we construct upon preliminary 60GHz channel measurements. Simulation
results demonstrate that our schemes provide up to 60% higher throughput as
compared to the commonly used signal strength based association policy for
mmWave networks, and outperform recently proposed load-balancing oriented
solutions, as we accommodate the demand of 33% more clients in both static and
mobile scenarios.Comment: 22 pages, 12 figures, accepted for publication in Computer
Communication
Resource management in QoS-aware wireless cellular networks
2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost
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