1,850 research outputs found
Enhancing IEEE 802.11MAC in congested environments
IEEE 802.11 is currently the most deployed wireless local area networking standard. It uses carrier sense multiple access with collision avoidance (CSMA/CA) to resolve contention between nodes. Contention windows (CW) change dynamically to adapt to the contention level: Upon each collision, a node doubles its CW to reduce further collision risks. Upon a successful transmission, the CW is reset, assuming that the contention level has dropped. However, the contention level is more likely to change slowly, and resetting the CW causes new collisions and retransmissions before the CW reaches the optimal value again. This wastes bandwidth and increases delays. In this paper we analyze simple slow CW decrease functions and compare their performances to the legacy standard. We use simulations and mathematical modeling to show their considerable improvements at all contention levels and transient phases, especially in highly congested environments
A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks
One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has
attracted the researchers' consideration is congestion control. Accordingly,
many algorithms have been proposed to alleviate the congestion problem,
although it is hard to find an appropriate algorithm for applications and
safety messages among them. Safety messages encompass beacons and event-driven
messages. Delay and reliability are essential requirements for event-driven
messages. In crowded networks where beacon messages are broadcasted at a high
number of frequencies by many vehicles, the Control Channel (CCH), which used
for beacons sending, will be easily congested. On the other hand, to guarantee
the reliability and timely delivery of event-driven messages, having a
congestion free control channel is a necessity. Thus, consideration of this
study is given to find a solution for the congestion problem in VANETs by
taking a comprehensive look at the existent congestion control algorithms. In
addition, the taxonomy for congestion control algorithms in VANETs is presented
based on three classes, namely, proactive, reactive and hybrid. Finally, we
have found the criteria in which fulfill prerequisite of a good congestion
control algorithm
Beyond Geometry : Towards Fully Realistic Wireless Models
Signal-strength models of wireless communications capture the gradual fading
of signals and the additivity of interference. As such, they are closer to
reality than other models. However, nearly all theoretic work in the SINR model
depends on the assumption of smooth geometric decay, one that is true in free
space but is far off in actual environments. The challenge is to model
realistic environments, including walls, obstacles, reflections and anisotropic
antennas, without making the models algorithmically impractical or analytically
intractable.
We present a simple solution that allows the modeling of arbitrary static
situations by moving from geometry to arbitrary decay spaces. The complexity of
a setting is captured by a metricity parameter Z that indicates how far the
decay space is from satisfying the triangular inequality. All results that hold
in the SINR model in general metrics carry over to decay spaces, with the
resulting time complexity and approximation depending on Z in the same way that
the original results depends on the path loss term alpha. For distributed
algorithms, that to date have appeared to necessarily depend on the planarity,
we indicate how they can be adapted to arbitrary decay spaces.
Finally, we explore the dependence on Z in the approximability of core
problems. In particular, we observe that the capacity maximization problem has
exponential upper and lower bounds in terms of Z in general decay spaces. In
Euclidean metrics and related growth-bounded decay spaces, the performance
depends on the exact metricity definition, with a polynomial upper bound in
terms of Z, but an exponential lower bound in terms of a variant parameter phi.
On the plane, the upper bound result actually yields the first approximation of
a capacity-type SINR problem that is subexponential in alpha
Experimental Evaluation of Large Scale WiFi Multicast Rate Control
WiFi multicast to very large groups has gained attention as a solution for
multimedia delivery in crowded areas. Yet, most recently proposed schemes do
not provide performance guarantees and none have been tested at scale. To
address the issue of providing high multicast throughput with performance
guarantees, we present the design and experimental evaluation of the Multicast
Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to
channel conditions and stability, which is essential for multimedia
applications. MuDRA relies on feedback from some nodes collected via a
light-weight protocol and dynamically adjusts the rate adaptation response
time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150
nodes shows that MuDRA outperforms other schemes and supports high throughput
multicast flows to hundreds of receivers while meeting quality requirements.
MuDRA can support multiple high quality video streams, where 90% of the nodes
report excellent or very good video quality
Experimental Evaluation of Wireless Mesh Networks: A Case Study and Comparison
Price of WiFi devices has decreased dramatically in recent years, while new standards, as 802.11n, have multiplied its performance. This has fostered the deployment of Wireless Mesh networks (WMN), putting into practice concepts evolved from more than a decade of research in Ad Hoc networks. Nevertheless, evolution of WMN it is in its infancy, as shows the growing and diverse number of scenarios where WMN are being deployed. In these paper we analyze a particular case study of a Wireless Community Mesh Network, and we compare it with a selected experimental WMN studies found in the literature
Designing Wireless Broadband Access for Energy Efficiency: Are Small Cells the Only Answer?
The main usage of cellular networks has changed from voice to data traffic,
mostly requested by static users. In this paper, we analyze how a cellular
network should be designed to provide such wireless broadband access with
maximal energy efficiency (EE). Using stochastic geometry and a detailed power
consumption model, we optimize the density of access points (APs), number of
antennas and users per AP, and transmission power for maximal EE. Small cells
are of course a key technology in this direction, but the analysis shows that
the EE improvement of a small-cell network saturates quickly with the AP
density and then "massive MIMO" techniques can further improve the EE.Comment: Published at Small Cell and 5G Networks (SmallNets) Workshop, IEEE
International Conference on Communications (ICC), 6 pages, 5 figures, 1 tabl
A reinforcement learning-based link quality estimation strategy for RPL and its impact on topology management
Over the last few years, standardisation efforts are consolidating the role of the Routing Protocol for Low-Power and Lossy Networks (RPL) as the standard routing protocol for IPv6-based Wireless Sensor Networks (WSNs). Although many core functionalities are well defined, others are left implementation dependent. Among them, the definition of an efficient link-quality estimation (LQE) strategy is of paramount importance, as it influences significantly both the quality of the selected network routes and nodesâ\u80\u99 energy consumption. In this paper, we present RL-Probe, a novel strategy for link quality monitoring in RPL, which accurately measures link quality with minimal overhead and energy waste. To achieve this goal, RL-Probe leverages both synchronous and asynchronous monitoring schemes to maintain up-to-date information on link quality and to promptly react to sudden topology changes, e.g. due to mobility. Our solution relies on a reinforcement learning model to drive the monitoring procedures in order to minimise the overhead caused by active probing operations. The performance of the proposed solution is assessed by means of simulations and real experiments. Results demonstrated that RL-Probe helps in effectively improving packet loss rates, allowing nodes to promptly react to link quality variations as well as to link failures due to node mobility
- …