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FAM: A frame aggregation based method to infer the load level in IEEE 802.11 networks
Abstract
In many environments, connected devices are exposed to and must choose between multiple Wi-Fi networks. However, the procedure for selecting an access point is still based on simple criteria that consider the device to be unique in the network. In particular, the network load is not taken into account even though it is a key parameter for the quality of service and experience.
In this paper, we investigate how an unmodified vanilla device could estimate the load of a network in the user space with no interventions from the access points. In this regard, we propose a novel and practical method, FAM (Frame Aggregation based Method). It leverages the frame aggregation mechanism introduced in recent IEEE 802.11 amendments to estimate the network load through its channel busy time fraction. FAM combines an active probing technique to measure the actual packet aggregation and Markovian models that provide the expected rate as a function of the volume and nature of the traffic on the network. We validate the effectiveness of FAM against both ns-3 simulations and test-bed experiments under several scenarios. Results show that our method FAM is able to infer the network load with a granularity based on six different levels of network loads for the considered scenarios.
... For this scenario, the impact of the aggregation size on the throughput and the latency is evaluated. In [6], an algorithm is proposed to evaluate the network load from the current frame aggregation level (the mean number of frames aggregated in a jumbo frame). The algorithm is based on a Markov chain that models a service discipline where each jumbo frame systematically includes the oldest frame of the transmission buffer (the first frame in the FIFO order). ...
Aggregation and Orthogonal Frequency Division Multiple Access (OFDMA) are two fundamental features allowing access points and stations to benefit from the high physical transmission rates of the recent WiFi standards. They aim to pool frames with a unique overhead (mainly the physical header and the acknowledgment) to mitigate its impact on the throughput. Natural implementations of these features lead to nonFIFO (First In, First Out) service disciplines that may generate unfairness between frames. In this paper, we evaluate three stateless service disciplines that require a low level of resources (computation and memory). We prove that when OFDMA does not introduce additional delay, one of these greedy algorithms minimizes the overhead. Whereas this service discipline maximizes the system capacity, it generates strong unfairness between the stations. Instead, the two other algorithms may offer a good trade-off between capacity and fairness. These algorithms are evaluated through a theoretical framework and simulations that replay actual Wi-Fi traces.
We propose in this paper an algorithm for available bandwidth estimation in mobile ad hoc networks and its integration into a conventional routing protocol like AODV for improving the rate-adaptive video streaming. We have introduced in our approach a local estimation of the available bandwidth as well as a prediction of the consumed bandwidth. This information allows video application to adjust its transmission rate avoiding network congestion. We conducted a performance evaluation of our solution through simulation experiments using two network scenarios. In the simulation study, transmission of video streams encoded with the H.264/MPEG-4 advanced video coding standard was evaluated. The results reveal performance improvements in terms of packet loss, delay and PSNR.
The estimation of the available bandwidth (av_bw) between two end nodes through the Internet, is an area that has motivated researchers around the world in the last twenty years, to have faster and more accurate tools; Due to the utility it has in various network applications; Such as routing management, intrusion detection systems and the performance of transport protocols. Different tools use different estimation techniques but generally only analyze the three most used metrics as av_bw, relative error and estimation time. This work expands the information regarding the evaluation literature of the current Available Bandwidth Estimation Tools (ABET's), where they analyze the estimation techniques, metrics, different generation tools of cross-traffic and evaluation testbed; Concentrating on the techniques and estimation methodologies used, as well as the challenges faced by open-source tools in high-performance networks of 10 Gbps or higher.
The knowledge of bandwidth in communication networks can be useful in various applications. Some popular examples are validation of service level agreements, traffic engineering and capacity planning support, detection of congested or underutilized links, optimization of network route selection, dynamic server selection for downloads and visualizing network topologies, to name just a few. Following these various motivations, a variety of bandwidth estimation techniques and tools have been proposed in the last decade and still, several new ones are currently being introduced. They all show a wide spectrum of different assumptions, characteristics, advantages and limitations. In this paper, the bandwidth estimation literature is reviewed, with focus on introducing four specific bandwidth-related metrics including capacity, available bandwidth, achievable throughput and bulk transfer capacity (BTC); describing the main characteristics, strengths and weaknesses of major bandwidth estimation techniques as well as classifying the respective tool implementations. Also, the fundamental challenges, practical issues and difficulties faced by designing and implementing bandwidth estimation techniques are addressed.
According to the amendment 5 of the IEEE 802.11 standard, 802.11n still uses the distributed coordination function (DCF) access method as mandatory function in access points and wireless stations (essentially to assure compatibility with previous 802.11 versions). This article provides an accurate two dimensional Markov chain model to investigate the throughput performance of IEEE 802.11n networks when frame aggregation and block acknowledgements (Block-ACK) schemes are adopted. Our proposed model considered packet loss either from collisions or channel errors. Further, it took anomalous slots and the freezing of backoff counter into account. The contribution of this work was the analysis of the DCF performance under error-prone channels considering both 802.11n MAC schemes and the anomalous slot in the backoff process. To validate the accuracy of our proposed model, we compared its mathematical simulation results with those obtained using the 802.11n DCF in the network simulator (NS-2) and with other analytical models investigating the performance of 802.11n DCF. Simulation results proved the accuracy of our model.
Packet dispersion techniques have been commonly used to estimate bandwidth in wired networks. However, current packet dispersion techniques were developed for wired network environments and can provide inaccurate results in wireless networks due to wireless capacity variability over short time scales. This paper develops an analytical model to investigate packet dispersion behavior in wireless networks. The packet dispersion model is validated using both an extended ns-2 simulator that includes 802.11 MAC layer rate adaptation and wireless 802.11b testbed measurements. Utilizing the model, this study shows that packet dispersion measures effective capacity and achievable throughput of wireless networks instead of the maximum capacity as in wired networks. Additionally, mean and variance of packet dispersion in IEEE 802.11 wireless networks is analyzed while considering the impact of channel conditions such as packet size, link rate, bit error rate and RTS/CTS
Bandwidth estimation techniques seek to provide an accurate estimation of available bandwidth such that network applications can adjust their behavior accordingly. However, most current techniques were designed for wired networks and produce relatively inaccurate results and long convergence times on wireless networks where capacity can vary dramatically. This paper presents a new wireless bandwidth estimation tool, WBest, designed for fast, non-intrusive, accurate estimation of available bandwidth in IEEE 802.11 networks. WBest is a two-stage algorithm: 1) a packet pair technique estimates the effective capacity over a flow path where the last hop is a wireless LAN (WLAN); and 2) a packet train technique estimates achievable throughput to infer the available bandwidth. WBest parameters are optimized given the tradeoffs of accuracy, intrusiveness and convergence time. The advantage of WBest stems from avoiding a search algorithm to detect the available bandwidth by statistically detecting the available fraction of the effective capacity to mitigate estimation delay and the impact of random wireless channel errors. WBest is implemented and evaluated on an 802.11 wireless testbed. Comparisons with other available bandwidth estimation tools shows WBest to have higher accuracy, lower intrusiveness and faster convergence times. Thus, WBest demonstrates the potential for improving the performance of applications that need bandwidth estimation, such as multimedia streaming, on wireless networks.
The IEEE 802.11n standard aims at providing a data transmission rate of up to 600 Mbps. The frame aggregation techniques of IEEE 802.11n MAC layer play an important role in the enhancement of channel utilization. In this paper, we investigate the effect of IEEE 802.11n frame aggregation for two aggregation mechanisms: MAC protocol data unit aggregation (A-MPDU) and MAC service data unit aggregation (A-MSDU). We propose an analytical model based on an enhanced discrete time Markov chain (DTMC) model in order to describe the post- backoff behavior due to frame aggregation, and then evaluate the throughput performance. Analytical results based on the mathematical model are verified through simulation. The throughput performance of the A-MSDU mechanism outperforms the A-MPDU mechanism as the frame aggregation size becomes larger under an error-free environment. In addition, the throughput performance is significantly improved as the frame aggregation size increases.
The packet pair mechanism has been shown to be a reliable method to measure the bottleneck link capacity on a network path, but its use for measuring available bandwidth is more challenging. In this paper, we use modeling, measurements, and simulations to better characterize the interaction between probing packets and the competing network traffic. We first construct a simple model to understand how competing traffic changes the probing packet gap for a single-hop network. The gap model shows that the initial probing gap is a critical parameter when using packet pairs to estimate available bandwidth. Based on this insight, we present two available bandwidth measurement techniques, the initial gap increasing (IGI) method and the packet transmission rate (PTR) method. We use extensive Internet measurements to show that these techniques estimate available bandwidth faster than existing techniques such as Pathload, with comparable accuracy. Finally, using both Internet measurements and ns simulations, we explore how the measurement accuracy of active probing is affected by factors such as the probing packet size, the length of probing packet train, and the competing traffic on links other than the tight link.
In this paper we develop a novel model-based technique, the Delphi algorithm, for inferring the instantaneous volume of competing cross-traffic across an end-to-end path. By using only end-to-end measurements, Delphi avoids the need for data collection within the Internet. Unique to the algorithm is an efficient exponentially spaced probing packet train and a parsimonious multifractal parametric model for the cross-traffic that captures its multiscale statistical properties (including long-range dependence) and queuing behavior. The algorithm is adaptive; it requires no a priori traffic statistics and effectively tracks changes in network conditions. ns (network simulator) experiments reveal that Delphi gives accurate cross-traffic estimates for higher link utilization levels while at lower utilizations it over-estimates the cross-traffic. Also, when Delphi's single bottleneck assumption does not hold it over-estimates the cross-traffic.
This paper presents pathChirp, a new active probing tool for estimating the available bandwidth on a communication network path. Based on the concept of "self-induced congestion," pathChirp features an exponential flight pattern of probes we call a chirp. Packet chips offer several significant advantages over current probing schemes based on packet pairs or packet trains. By rapidly increasing the probing rate within each chirp, pathChirp obtains a rich set of information from which to dynamically estimate the available bandwidth. Since it uses only packet interarrival times for estimation, pathChirp does not require synchronous nor highly stable clocks at the sender and receiver. We test pathChirp with simulations and Internet experiments and find that it provides good estimates of the available bandwidth while using only a fraction of the number of probe bytes that current stateof -the-art techniques use.
Optimization of the association between wireless stations and access points (APs) has shown its effectiveness to improve the overall performance of wireless LAN. Most of the previous works do not consider the latest amendments of the IEEE 802.11 standard. The main challenges are to propose models that take into account recent enhancements such as spatial multiplexing (MIMO) at the physical layer and frame aggregation mechanism at the MAC layer. To assess these new features, we derive an association optimization approach based on a new metric, named Hypothetical Busy Time Fraction (H-BTF), that combines the classical Busy Time Fraction (BTF) and the frame aggregation mechanism. This metric is based on local measurements like throughput demand and frame error rate for each station. The model estimates the H-BTF of each AP for any configuration and is thus able to predict H-BTF for other association scheme. Association is then optimized to minimize the load of the busiest APs. This load balancing between APs aims to satisfy stations with regard to their throughput demands. Numerical evaluations performed with the network simulator ns-3 have shown the accuracy of the proposed approach for a large set of scenarios and a significant benefit for the stations in terms of throughput and satisfaction.
Software Defined Networking (SDN) is an emerging paradigm that is expected to revolutionize computer networks. Methods for measuring Quality of Service (QoS) parameters such as bandwidth utilization, packet loss, and delay have been recently introduced in literature for SDN-based scenarios, but they required almost invariably a completely different approach with respect to traditional network environments, thus facing new challenges and exploiting new opportunities. An important dynamic path characteristic is Available Bandwidth (ABW), that has strong impact on a wide range of applications, but is a metric very hard to estimate with traditional approaches. In this paper we focus our analysis on ABW measurement based on messages in the OpenFlow protocol. We present both analytical results and experimental evaluation (in Mininet emulation and using Floodlight, OpenDaylight and ONOS controllers) of measurement error due to network delay between the SDN switches and the controller. Based on our results we propose to extend the OpenFlow protocol with a local timestamping mechanism, providing and discussing two different implementations of this feature. The presented analysis and the proposed extension of OpenFlow protocol are not restricted to ABW, and can benefit measurement of other network metrics in SDN.
We consider for the first time available bandwidth estimation (ABE) in the context of 802.11n, which is fast replacing the legacy 802.11a/b/g networks. We experimentally show that the frame aggregation (FA) feature of 802.11n is the dominant one among 802.11n features affecting the ABE. Using an indoor 802.11n wireless testbed, we compare three ABE tools (WBest, DietTopp and pathChirp) in various cross-traffic scenarios. We find that FA significantly hurts the accuracy of all ABE tools; DietTopp and pathChirp are relatively more robust than WBest. Because faster available bandwidth estimation and less intrusiveness are desirable properties of any ABE tool and WBest satisfies them relatively better than the other two tools, we conduct an in-depth investigation into the harmful effect of FA on ABE using WBest. This in turn led us to come up with two key design principles to counter FA effects: (1) treating aggregated probes as one jumbo probe; and (2) generating a larger number of probes. We then develop an enhanced version of WBest termed WBest+ that incorporates these principles. Our evaluation shows that the new version is effective in achieving accurate ABE in the presence of FA.
While many theoretical and simulation works have already highlighted the potential gain of cognitive radio, several technical issues still have to be evaluated and overcome from an experimental viewpoint. Our team is currently developing a new experimental facility remotely accessible and dedicated to this problem. CorteXlab is developed in the framework of a nationwide French program Future Internet of Things which proposes a federated and competitive infrastructure. The Cor-teXlab facility offers a 167m2 EM shielded room and integrates a set of 22 USRP from National Instrument, 16 picoSDR nodes from Nutaq and 42 IoT-Lab wireless sensor nodes from Hikob. CorteXlab is built on the network architecture developed for the SensLAB testbed and exploits the free and open-source toolkit GNU-radio. All nodes are remotely accessible through a software interface called Minus. The demo presented at Infocom describes the facility and shows the process a user should follow to deploy his own experiment. Two typical scenarios involving several nodes are built and deployed live. The first scenario is based on IEEE 802.15.4 communication between two picoSDR nodes. The second scenario is dealing with an avoiding-interference use case where the previous two picoSDRs are communicating while a cognitive MIMO-OFDM transceiver running on one picoSDR must avoid interference with them.
For active, probing-based bandwidth measurements performed on top of the unifying IP layer, it may seem reasonable to expect the measurement problem in wireless networks to be no different than the one in wired networks. However, in networks with 802.11 wireless bottleneck links we show that this is not the case. The results from the experiments presented in this paper show that the measured available bandwidth is dependent on the probe packet size (contrary to what is observed in wired networks). Another equally important finding is that the measured link capacity, using the well known TOPP model, is dependent on the probe packet size and on the cross-traffic intensity. The underlying reasons for the observed differences are analyzed by incorporating the characteristics of 802.11 wireless networks into the TOPP model. The extended model is applicable to other end-to-end bandwidth measurement methods as well, such as BART, Pathload and PTR.
The popularity of multimedia streaming services via wireless networks presents major challenges in the management of network bandwidth. One challenge is to quickly and precisely estimate the available bandwidth for the decision of streaming rates of layered and scalable multimedia services. Previous works based on wired networks are too burdensome to be applied to multimedia applications in wireless networks. In this paper, a new method, IdleGap, is suggested to estimate the available bandwidth of a wireless LAN based on the information from a low layer in the protocol stack. We use a network simulation tool, NS-2, to evaluate our new method with various range of cross traffic and observation times. Our simulation results show that IdleGap accurately estimates the available bandwidth for all ranges of cross traffic (100Kbps ~ 1Mbps) with a very short observation time of 10 seconds.
Quality of Service (QoS) support in IEEE 802.11-based ad hoc networks relies on the networks’ ability to estimate the available bandwidth on a given link. However, no mechanism has been standardized to accurately evaluate this resource. This remains one of the main issues open to research in this field. This paper proposes an available bandwidth estimation approach which achieves more accurate estimation when compared to existing research. The proposed approach differentiates the channel busy caused by transmitting or receiving from that caused by carrier sensing, and thus improves the accuracy of estimating the overlap probability of two adjacent nodes’ idle time. Simulation results testify the improvement of this approach when compared with well known bandwidth estimation methods in the literature.
We present a network friendly bandwidth measurement method, TOPP,
that is based on active probing and includes analysis by segmented
regression. This method can estimate two complementing available
bandwidth metrics in addition to the link bandwidth of the congested
link. Contrary to traditional packet pair estimates of the bottleneck
link bandwidth, our estimate is not limited by the rate at which we can
inject probe packets into the network. We also show that our method is
able to detect bottlenecks that are invisible to methods such as the
C-probe. Further more, we describe scenarios where our analysis method
is able to calculate bandwidth estimates for several congested hops
based on a single end-to-end probe session
Available bandwidth estimation is useful for route selection in overlay networks, QoS verification, and tra#c engineering. Recent years have seen a surge in interest in available bandwidth estimation. A few tools have been proposed and evaluated in simulation and over a limited number of Internet paths, but there is still great uncertainty in the performance of these tools over the Internet at large.
The available bandwidth of a network path P is the maximum throughput that P can provide to a flow, without reducing the throughput of the cross traffic in P . We have developed an endto -end active measurement tool, called pathload, that estimates the available bandwidth of a network path. The basic idea in pathload is that the one-way delays of a periodic packet stream show increasing trend, when the stream rate is larger than the available bandwidth. In this paper, we describe pathload in detail, and show some experimental results that illustrate the tool's accuracy.
Available bandwidth vs. achievable throughput measurements in 4G mobile networks
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