Results 1 - 10
of
64
The Changing Usage of a Mature Campus-wide Wireless Network
- In Proceedings of ACM MOBICOM
, 2004
"... Wireless Local Area Networks (WLANs) are now commonplace on many academic and corporate campuses. As "Wi-Fi" technology becomes ubiquitous, it is increasingly important to understand trends in the usage of these networks. ..."
Abstract
-
Cited by 322 (12 self)
- Add to MetaCart
(Show Context)
Wireless Local Area Networks (WLANs) are now commonplace on many academic and corporate campuses. As "Wi-Fi" technology becomes ubiquitous, it is increasingly important to understand trends in the usage of these networks.
Access and Mobility of Wireless PDA Users
"... In this paper, we analyze the mobility patterns of users of wireless handheld PDAs in a campus wireless network using an 11 week trace of wireless network activity. Our study has three goals. First, we characterize the high-level mobility and access patterns of handheld PDA users and compare these c ..."
Abstract
-
Cited by 142 (4 self)
- Add to MetaCart
(Show Context)
In this paper, we analyze the mobility patterns of users of wireless handheld PDAs in a campus wireless network using an 11 week trace of wireless network activity. Our study has three goals. First, we characterize the high-level mobility and access patterns of handheld PDA users and compare these characteristics to previous workload mobility studies focused on laptop users. Second, we develop two wireless network topology models for use in wireless mobility studies: an evolutionary topology model based on user proximity and a campus waypoint model that serves as a trace-based complement to the random waypoint model. Finally, we use our wireless network topology models as a case study to evaluate ad-hoc routing algorithms on the network topologies created by the access and mobility patterns of users of modern wireless PDAs.
Analyzing the mac-level behavior of wireless networks in the wild.
- In ACM SIGCOMM Computer Communication Review
, 2006
"... ..."
(Show Context)
Measurement-based characterization of 802.11 in a hotspot setting
- in Proc. of ACM E-WIND workshop (held with SIGCOMM), 2005
"... Abstract – We analyze wireless measurements taken during the SIGCOMM 2004 conference to understand how well 802.11 operates in real deployments. We find that the overhead of 802.11 is high, with only 40 % of the transmission time spent in sending orig-inal data. Most of the remaining time is consume ..."
Abstract
-
Cited by 88 (3 self)
- Add to MetaCart
(Show Context)
Abstract – We analyze wireless measurements taken during the SIGCOMM 2004 conference to understand how well 802.11 operates in real deployments. We find that the overhead of 802.11 is high, with only 40 % of the transmission time spent in sending orig-inal data. Most of the remaining time is consumed by retransmis-sions due to packet losses that are caused by both contention and transmission errors. Our analysis also shows that wireless nodes adapt their transmission rates with an extremely high frequency. We comment on the difficulties and opportunities of working with wireless traces, rather than the wired traces of wireless activity that are presently more common.
Flow Scheduling for End-host Multihoming
- In Proceedings of IEEE INFOCOM
, 2006
"... Fueled by the competing DSL and Cable technologies, residential broadband access has seen a significant spread in availability to the point that many users have a choice from several ISPs. At the same time, 802.11 networks have spread rapidly in the residential area, and it is common for neighbors t ..."
Abstract
-
Cited by 46 (3 self)
- Add to MetaCart
(Show Context)
Fueled by the competing DSL and Cable technologies, residential broadband access has seen a significant spread in availability to the point that many users have a choice from several ISPs. At the same time, 802.11 networks have spread rapidly in the residential area, and it is common for neighbors to be able to access each other's wireless routers. End-users can leverage this diversity to improve their Internet connectivity at no additional cost by pooling all available Internet connections, both their own and their neighbors' via wireless. In this paper we present our design and evaluation of flow scheduling algorithms in PERM, a framework for practical end-host multihoming. PERM scheduler employs automated on-line analysis of the endusers ' networking behaviors, and exploits the recognized patterns to achieve high-performance scheduling at flow level. We verify our models of end-user's network traffic with large residential TCP traces. Based on these models we propose algorithms for scalable pre-probing and hybrid flow scheduling. Intensive experiments in our prototype testbed show that PERM scheduler reduces the latency by up to 50% for light-volume flows, and reduces the mean transmission time of heavy-volume flows by nearly 28% and 62% compared with a single Cable or DSL connection respectively. The PERM scheduler also out-performs algorithms for enterprise multihoming by up to 15% and 27% in mean transmission time for light- and heavy-volume flows respectively.
Understanding link-layer behavior in highly congested ieee 802.11b wireless networks
- In Proceedings of ACM SIGCOMM Workshop E-WIND
, 2005
"... The growing deployment and concomitant rise in wireless network usage necessitates the comprehensive understanding of its behavior. More importantly, as networks grow in size and number of users, congestion in the wireless portion of the network is likely to increase. We believe there is a strong ne ..."
Abstract
-
Cited by 43 (4 self)
- Add to MetaCart
(Show Context)
The growing deployment and concomitant rise in wireless network usage necessitates the comprehensive understanding of its behavior. More importantly, as networks grow in size and number of users, congestion in the wireless portion of the network is likely to increase. We believe there is a strong need to understand the intricacies of the wireless portion of a congested network by interpreting information collected from the network. Congestion in a wireless network can be best analyzed by studying the transmission of frames at the link layer. To this end, we use vicinity sniffing techniques to analyze the link layer in an operational IEEE 802.11b wireless network. In this paper, we discuss how congestion in a network can be estimated using point-to-point link reliability. We then show how link reliability is correlated with the behavior of link-layer properties such as frame retransmissions, frame sizes, and data rates. Based on the results from these correlations, our hypothesis is that the performance of the link layer in congested networks can be improved by (1) sending smaller frames, and/or (2) using higher data rates with a fewer number of frames sent.
Characterizing flows in large wireless data networks
- In Proceedings of ACM MOBICOM
, 2004
"... ..."
(Show Context)
Understanding Congestion in IEEE 802.11b Wireless Networks
- In Proceedings of the 2005 Internet Measurement Conference
, 2005
"... The growing popularity of wireless networks has led to cases of heavy utilization and congestion. In heavily utilized wireless networks, the wireless portion of the network is a major performance bottleneck. Understanding the behavior of the wireless portion of such networks is critical to ensure th ..."
Abstract
-
Cited by 36 (4 self)
- Add to MetaCart
(Show Context)
The growing popularity of wireless networks has led to cases of heavy utilization and congestion. In heavily utilized wireless networks, the wireless portion of the network is a major performance bottleneck. Understanding the behavior of the wireless portion of such networks is critical to ensure their robust operation. This understanding can also help optimize network performance. In this paper, we use link layer information collected from an operational, large-scale, and heavily utilized IEEE 802.11b wireless network deployed at the 62 nd Internet Engineering Task Force (IETF) meeting to study congestion in wireless networks. We motivate the use of channel busy-time as a direct measure of channel utilization and show how channel utilization along with network throughput and goodput can be used to define highly congested, moderately congested, and uncongested network states. Our study correlates network congestion and its effect on link-layer performance. Based on these correlations we find that (1) current rate adaptation implementations make scarce use of the 2 Mbps and 5.5 Mbps data rates, (2) the use of Request-to-Send/Clear-to-Send (RTS–CTS) prevents nodes from gaining fair access to a heavily congested channel, and (3) the use of rate adaptation, as a response to congestion, is detrimental to network performance. 1
Model T++: An Empirical Joint Space-Time Registration Model
- In Proceedings of ACM MOBIHOC
, 2006
"... We present an empirical registration model derived from the WLAN registration patterns of the mobile users. There exist models that accurately describe individually the spatial and temporal aspects of user registration, and demonstrate the importance of this modeling. The main distinction of the new ..."
Abstract
-
Cited by 26 (0 self)
- Add to MetaCart
We present an empirical registration model derived from the WLAN registration patterns of the mobile users. There exist models that accurately describe individually the spatial and temporal aspects of user registration, and demonstrate the importance of this modeling. The main distinction of the new model from the previous empirical models is that we are able to formulate the inter-dependence of space and time explicitly by a set of few equations. Our extensive studies of the WLAN traces indicate that a simple but proper notion of popularity gradient suffices to capture the correlation across space and time. Indeed, when locations (i.e., AP coverage area) are differentiated with respect to the number of visits they are receiving (i.e., AP popularity), the time spent at each location i before user moves from i to k turns out to be closely related to the difference of popularity between locations i and k. This observation led to the design of a joint time-space registration model (referred to as Model T++) that builds upon the Model T, which itself models only the space aspect of the registration, but is derived from the same campus WiFi network. As part of the process of generating a joint space-time model, we further extend spatial aspects of the Model T. We evaluate our model using various metrics against a random walk model as well as the Model T by superimposing location independent time series on these space-only registration models. Our results suggest that with a slight increase in the model complexity, our joint time-space registration model is able to better capture the real network registration than the independent time models. Model T++ can be easily integrated into both WLAN and multi-hop wireless mesh network simulations that require realistic registration models.
Model T: an empirical model for user registration patterns in a campus wireless LAN
- In the 11th Annual International Conference on Mobile Computing and Networking
, 2005
"... We derive an empirical model for spatial registration patternsofmobileusersastheymovewithinacampuswireless local area network (WLAN) environment and register at different access points. Such a model can be very useful in a variety of simulation studies of the performance of mobile wireless systems, ..."
Abstract
-
Cited by 25 (0 self)
- Add to MetaCart
(Show Context)
We derive an empirical model for spatial registration patternsofmobileusersastheymovewithinacampuswireless local area network (WLAN) environment and register at different access points. Such a model can be very useful in a variety of simulation studies of the performance of mobile wireless systems, such as that of resource management and mobility management protocols. We base the model on extensive experimental data from a campus WiFi LAN installation, representing traces from about 6000 users over a period of about 2 years. We divide the empirical data available to us into training and test data sets, develop the model based on the training set, and evaluate it against the test set. The model shows that user registration patterns exhibit a distinct hierarchy, and that WLAN access points (APs) can be clustered based on registration patterns. Cluster size distributions are highly skewed, as are intra-cluster transition probabilities and trace lengths, which can all be modeled well by the heavy-tailed Weibull distribution. The fraction of popular APs in a cluster, as a function of cluster size, can be modeled by exponential distributions. There is general similarity across hierarchies, in that inter-cluster registration patterns tend to have the same characteristics and distributions as intra-cluster patterns. We generate synthetic traces for intra-cluster transitions, inter-cluster transitions, and complete traces, and compare them against the corresponding traces from the test set. We define a set of metrics that evaluate how well the model captures the empirical features it is trying to represent. We find that the synthetic traces agree very well with the test set in terms of the metrics. We also compare the model to a simple modified random waypoint model as a baseline, and show the latter is not at all representative of the real data. The user of the model has the opportunity to use it as is, or can modify model parameters, such as the degree of randomness in registration patterns. We close with a brief discussion of further work to refine and extend the model.
