Results 1  10
of
17
Trusted Computer System Evaluation Criteria
 National Computer Security Center
, 1985
"... We develop a general model to estimate the throughput and goodput between arbitrary pairs of nodes in the presence of interference from other nodes in a wireless network. Our model is based on measurements from the underlying network itself and is thus more accurate than abstract models of RF propag ..."
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Cited by 61 (2 self)
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We develop a general model to estimate the throughput and goodput between arbitrary pairs of nodes in the presence of interference from other nodes in a wireless network. Our model is based on measurements from the underlying network itself and is thus more accurate than abstract models of RF propagation such as those based on distance. The seed measurements are easy to gather, requiring only O(N) measurements in an Nnode networks. Compared to existing measurementbased models, our model advances the state of the art in three important ways. First, it goes beyond pairwise interference and models interference among an arbitrary number of senders. Second, it goes beyond broadcast transmissions and models the more common case of unicast transmissions. Third, it goes beyond homogeneous nodes and models the general case of heterogeneous nodes with different traffic demands and different radio characteristics. Using simulations and measurements from two different wireless testbeds, we show that the predictions of our model are accurate in a wide range of scenarios.
A MeasurementBased Approach to Modeling Link Capacity in 802.11based Wireless Networks
 In To appear in ACM MOBICOM ’07
, 2007
"... We present a practical, measurementbased model that captures the effect of interference in 802.11based wireless LAN or mesh networks. The goal is to model capacity of any given link in the presence of any given number of interferers in a deployed network, carrying any specified amount of offered l ..."
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Cited by 52 (4 self)
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We present a practical, measurementbased model that captures the effect of interference in 802.11based wireless LAN or mesh networks. The goal is to model capacity of any given link in the presence of any given number of interferers in a deployed network, carrying any specified amount of offered load. Central to our modeling approach is a MAClayer model for 802.11 that is fed by PHYlayer models for deferral and packet capture behaviors, which in turn are profiled based on measurements. The target network to be evaluated needs only O(N) measurement steps to gather metrics for individual links that seed the models. We provide two solution approaches – one based on direct simulation (slow, but accurate) and the other based on analytical methods (faster, but approximate). We present elaborate validation results for a 12 node 802.11b mesh network using upto 5 interfering transmissions. We demonstrate, using as comparison points three simpler modeling approaches, that the accuracy of our approach is much better, predicting link capacities with errors within 10 % of the base channel datarate for about 90% of the cases.
Understanding Congestion Control in Multihop Wireless Mesh Networks
"... Complex interference in static multihop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair an ..."
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Cited by 25 (6 self)
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Complex interference in static multihop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multihop wireless mesh networks. First, we design an AIMDbased ratecontrol protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a nodelocal one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the maxmin rates for our topologies, while still being distributed and amenable to real implementation.
The Achievable Rate Region of 802.11Scheduled Multihop Networks
 IEEE/ACM TRANSACTIONS ON NETWORKING
"... In this paper, we characterize the achievable rate region for any 802.11scheduled static multihop network. To do so, we first characterize the achievable edgerate region, that is, the set of edge rates that are achievable on the given topology. This requires a careful consideration of the inter ..."
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Cited by 11 (4 self)
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In this paper, we characterize the achievable rate region for any 802.11scheduled static multihop network. To do so, we first characterize the achievable edgerate region, that is, the set of edge rates that are achievable on the given topology. This requires a careful consideration of the interdependence among edges, since neighboring edges collide with and affect the idle time perceived by the edge under study. We approach this problem in two steps. First, we consider twoedge topologies and study the fundamental ways by which they interact. Then, we consider arbitrary multihop topologies, compute the effect that each neighboring edge has on the edge under study in isolation, and combine to get the aggregate effect. We then use the characterization of the achievable edgerate region to characterize the achievable rate region. We verify the accuracy of our analysis by comparing the achievable rate region derived from simulations with the one derived analytically. We make a couple of interesting and somewhat surprising observations while deriving the rate regions. First, the achievable rate region with 802.11 scheduling is not necessarily convex. Second, the performance of 802.11 is surprisingly good. For example, in all the topologies used for model verification, the maxmin allocation under 802.11 is at least 64 % of the maxmin allocation under a perfect scheduler.
Online optimization of 802.11 mesh networks
 In Proc. of CoNEXT
, 2009
"... 802.11 wireless mesh networks are ubiquitous, but suffer from severe performance degradations due to poor synergy between the 802.11 CSMA MAC protocol and higher layers. Several solutions have been proposed that either involve significant modifications to the 802.11 MAC or legacy higher layer protoc ..."
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Cited by 4 (0 self)
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802.11 wireless mesh networks are ubiquitous, but suffer from severe performance degradations due to poor synergy between the 802.11 CSMA MAC protocol and higher layers. Several solutions have been proposed that either involve significant modifications to the 802.11 MAC or legacy higher layer protocols, or rely on 802.11 MAC models seeded with offline measurements performed during network downtime. We introduce a technique for online optimization of 802.11 wireless mesh networks using rate control at the network layer. The technique is based on a lightweight model that characterizes the feasible rates region of an operational 802.11 wireless mesh network. Unlike existing 802.11 modeling approaches, the parameters of this model can be estimated online, incur minimal overhead and can be realized using standard probing mechanisms at the network layer. Using analysis and extensive measurements over a wireless mesh network testbed, we validate the assumptions on which the model is built, and explain the principles behind the choice and estimation of its parameters. The benefits of the model and its solution in terms of fairness, throughput and stability are demonstrated operationally for a range of multihop topologies and configurations.
Neighborhoodcentric congestion control for multihop wireless mesh networks
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Optimal SINRbased Random Access
"... Abstract — Random access protocols, such as Aloha, are commonly modeled in wireless adhoc networks by using the protocol model. However, it is wellknown that the protocol model is not accurate and particularly it cannot account for aggregate interference from multiple interference sources. In this ..."
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Abstract — Random access protocols, such as Aloha, are commonly modeled in wireless adhoc networks by using the protocol model. However, it is wellknown that the protocol model is not accurate and particularly it cannot account for aggregate interference from multiple interference sources. In this paper, we use the more accurate physical model, which is based on the signaltointerferenceplusnoiseratio (SINR), to study optimizationbased design in wireless random access systems, where the optimization variables are the transmission probabilities of the users. We focus on throughput maximization, fair resource allocation, and network utility maximization, and show that they entail nonconvex optimization problems if the physical model is adopted. We propose two schemes to solve these problems. The first design is centralized and leads to the global optimal solution using a sumofsquares technique. However, due to its complexity, this approach is only applicable to smallscale networks. The second design is distributed and leads to a closetooptimal solution using the coordinate ascent method. This approach is applicable to mediumsize and largescale networks. Based on various simulations, we show that it is highly preferable to use the physical model for optimizationbased random access design. In this regard, even a suboptimal design based on the physical model can achieve a significantly better performance than an optimal design based on the inaccurate protocol model. I.
An experimental study of intercell interference effects on system performance in . . .
, 2008
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Throughput and fairness in random access networks
, 2006
"... Abstract — This paper present an throughput analysis of logutility and maxmin fairness. Assuming all nodes interfere with each other, completely or partially, logutility fairness significantly enhances the total throughput compared to maxmin fairness since the nodes should have the same throughpu ..."
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Cited by 1 (1 self)
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Abstract — This paper present an throughput analysis of logutility and maxmin fairness. Assuming all nodes interfere with each other, completely or partially, logutility fairness significantly enhances the total throughput compared to maxmin fairness since the nodes should have the same throughput in maxmin fairness. The improvement is enlarged especially when the effect of cumulated interference from multiple senders cannot be ignored. I. LOGUTILITY AND MAXMIN FAIRNESS In this paper, we focus on dense wireless networks using random access protocols such as 802.11 LANs in offices and urban residential areas. We mainly consider slottedAloha systems but our analysis is simply extended for CSMA/CS networks with a single carriersensing range. In typical urban residential networks, one or few terminals are located closely to their access point and tend to capture a strong signal. The dense distribution of the access points, however, enlarges the effect of cumulative interference on frame reception. For fair bandwidth allocation, there exist two famous fairness schemes: logutility [1] and maxmin fairness. Logutility or proportional fairness has been well known as a flexible and useful abstraction for multiplexing scarce resources among users and applications. Maxmin fairness, however, achieve the complete fair allocation, where all nodes have the same throughput. Consider all nodes are within the single interference range. That is, any overlapped transmissions from the nodes completely collides and that results in transmission errors. Let be the number of nodes. In this case, the nodes have the probability¡£ ¢ attempt in logutility fairness [2] and the throughput¤¦¥¨§ total is given by:
Performance Modeling of 802.11 Ad Hoc Networks with TimeVarying Carrier Sense Range and Physical Capture Capability
"... Abstract—In a slow fading environment, the carrier sense range is not constant, so there is not a constant set of hidden terminals for a mobile station. The probability of capture with a set of interferers is not a fixed value either, and it fundamentally affects the loss rate and throughput of the ..."
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Abstract—In a slow fading environment, the carrier sense range is not constant, so there is not a constant set of hidden terminals for a mobile station. The probability of capture with a set of interferers is not a fixed value either, and it fundamentally affects the loss rate and throughput of the whole network. We estimate the expectation of the capture probability in a single hop ad hoc network and incorporate it with our previously proposed model for 802.11 DCF that considers the timevarying nature of carrier sensing. The system throughput is then derived from an individual station’s point of view. The model is verified against simulations, and extensive numerical experiments are performed to demonstrate its application. I.