We present a tool to estimate the interference between nodes and links in a live wireless network by passive monitoring of wireless traffic. This tool does not require any controlled experiments, injection of probe traffic in the network, or even access to the network nodes. Our approach requires deploying multiple sniffers across the network to capture wireless traffic traces. These traces are then analyzed using a machine learning approach to infer the carrier-sense relationship between network nodes. This coupled with an estimation of collision probabilities helps us to deduce the interference relationships. We also demonstrate an important application of this tool-detection of selfish carrier-sense behavior. This is based on identifying any asymmetry in carrier-sense behavior between node pairs and finding multiple witnesses to raise confidence. We evaluate the effectiveness of the tool for both the applications using extensive experiments and simulation. Experimental and simulation results demonstrate that the proposed approach of estimating interference relations is significantly more accurate than simpler heuristics and quite competitive with active measurements. We also validate the approach in a real Wireless LAN environment. Evaluations using a real testbed as well as ns2 simulation studies demonstrate excellent detection ability of the selfish behavior. On the other hand, the metric of selfishness used to estimate selfish behavior matches closely with actual degree of selfishness observed.

Service-Oriented Architectures (SOAs) are increasingly being used for designing and building large-scale networked and distributed systems. Catering to the complex and dynamically varying needs of business applications/clients, these systems must usually be realized by dynamically composing a variety of network-available services. Evaluation of large-scale SOAs, particularly on dynamic network platforms, such as Mobile Ad-hoc Networks (MANETs), is a non-trivial problem that requires not only a correct modeling of SOAs and the network platform, but also their relationships. This paper describes a new tool - SOAMANET - to design and rapidly synthesize simulations for the experimental evaluation of SOAs on MANET platforms. With its modeling techniques and analysis capabilities, SOAMANET allows simulation-based and system execution-based analysis of dynamic SOA and/or MANET designs and implementations.

Wireless interference is the major cause of degradation of capacity in 802.11 wireless networks. We present an approach to estimate the interference between nodes and links in a live wireless network by passive monitoring of wireless traffic. This does not require any controlled experiments, injection of probe traffic in the network, or even access to the network nodes. Our approach requires deploying multiple sniffers across the network to capture wireless traffic traces. These traces are then analyzed to infer the interference relations between nodes and links. We model the 802.11 MAC as a Hidden Markov Model (HMM), and use a machine learning approach to learn the state transition probabilities in this model using the observed trace. This coupled with an estimation of collision probabilities helps us to deduce the interference relationships. We show the effectiveness of this method against simpler heuristics, and also a profiling-based method that requires active measurements. Experimental results demonstrate that the proposed approach is significantly more accurate than heuristics and quite competitive with active measurements. We also validate the approach in a real WLAN environment.

With the proliferation of WiFi technology, many WiFi networks are accessible from vehicles on the road making vehicular WiFi access realistic. However, several challenges exist: long latency to establish connection to a WiFi access point (AP), lossy link performance, and frequent disconnections due to mobility. We argue that people drive on familiar routes frequently, and thus the mobility and connectivity related information along their drives can be predicted with good accuracy using historical information – such as GPS tracks with timestamps, RF fingerprints, and link and network-layer addresses of visible APs. We exploit such information to develop new handoff and data transfer strategies. The handoff strategy reduces the connection establishment latency and also uses pre-scripted handoffs triggered by change in vehicle location. The data transfer strategy speeds up download performance by using prefetching on the APs yet to be encountered. Experimental performance evaluation reveals that the predictability of mobility and connectivity is high enough to be useful in such protocols. In our experiments with a vehicular client accessing road-side APs, the handoff strategy improves download performance by roughly a factor of 2 relative to the state-of-the-art. The data transfer strategy further improves this performance by another factor of 2.5.

In this work, we address the issue of unrealistic simulations of wireless networks using a measurement-based approach. The idea is to use empirical modeling using measurement data as a mechanism to model physical layer behavior. We demonstrate the power of this approach for 802.11-based networks using ns2, a packet-level network simulator. Specifically, we develop two versions of the ns2 simulator that model the wireless physical layer with different levels of fidelity. In both versions, the deferral and reception model are built using measurements. For propagation modeling, one version uses direct measurements and the other uses an empirically derived model. In validation experiments with a 12-node mesh testbed, both these versions were found to be reasonably accurate (85 percentile errors within about 10% of the capacity) relative to regular simulations (85 percentile errors within 50% of capacity).

We study the problem of supporting VoIP calls in a wireless mesh network. Specifically, we propose solutions for call admission control (CAC) and route selection for VoIP calls. Call admission decisions must evaluate how the capacity of the mesh network is utilized by the existing calls. We address this issue via a measurement-based modeling effort to model mutual interference between wireless links. The modeling approach evaluates whether capacity constraints (or, required QoS metrics) will be satisfied if a new call is admitted with a given route. Evaluations with a 6-node 802.11a testbed demonstrate excellent accuracy of the model and thus also the CAC performance. We address the issue of route selection by also using a modeling approach that considers models of transmission and interference ranges to develop a polynomial-time algorithm to search for feasible routes. This problem takes exponential time for wireless networks without such modeling. In addition to studying feasibility, we study several routing metrics such as shortest feasible path and maximum residual feasible path. Finally, we develop a new method for routing using call statistics that uses prior calling patterns to avoid potentially critical links. We evaluate the performance of these route selection techniques via extensive simulations and demonstrate the superiority of using max residual feasible path over simply shortest feasible path, and routing using call statistics over max residual feasible path.

We present a practical, measurement-based model that captures the effect of interference in 802.11-based 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 MAC-layer model for 802.11 that is fed by PHY-layer 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.

We consider the problem of supporting VoIP calls over a wireless mesh network. We particularly consider the call admission control (CAC) decision problem for VoIP calls on a mesh network. The goal of the call admission decision is to maintain the quality of VoIP calls as given by the R-score measure. In this work, we define a notion of interference capacity model that can be efficiently used to design a CAC algorithm. We show through extensive simulation of 802.11 mesh using ns-2, that our CAC performs well in multi-hop scenarios. Specifically, the proposed CAC provides less than 20% incorrect decisions for different sizes of a multihop linear topology.

In this paper we design and evaluate Ganges, a wireless mesh network architecture that can efficiently transport real-time video streams from multiple sources to a central monitoring station. Video quality suffers from deterioration in the presence of bursty network losses and due to packets missing their playback deadline. Ganges spatially separates the paths to reduce inter-flow contention. It finds out a fair rate allocation for the different video sources. The wireless routers in the mesh network implement several optimizations in order to reduce the end-to-end delay variation. Ganges improves the network capacity by over 10-15% over a shortest path tree, and improves the video picture quality by 7-10 dB

In the recent past, there has been a tremendous increase in the popularity of VoIP services as a result of huge growth in broadband access. The same voice-over-Internet protocol (VoIP) service poses new challenges when deployed over a wireless mesh network, while enabling users to make voice calls using WiFi phones. Packet losses and delay due to interference in a multiple-hop mesh network with limited capacity can significantly degrade the end-to-end VoIP call quality. In this work, we discuss the basic requirements for efficient deployment of VoIP services over a mesh network. We present and evaluate practical optimizing techniques that can enhance the network capacity, maintain the VoIP quality and handle user mobility efficiently. Extensive experiments conducted on a real testbed and ns-2 provide insights into the performance issues and demonstrate the level of improvement that can be obtained by the proposed techniques. Specifically, we find that packet aggregation along with header compression can increase the number of supported VoIP calls in a multihop network by 2-3 times. The proposed fast path switching is highly effective in maintaining the VoIP quality. Our fast handoff scheme achieves almost negligible disruption during calls to roaming clients

P2P file sharing protocol and ad hoc wireless routing protocol share many intriguing similarities even though they are motivated on totally different basis. The goal of P2P file sharing system such as KaZaa is to locate a set of servers that contain a given file and disseminate it efficiently. The key problem of an ad hoc network routing protocol is to determine which route to take to reach a given remote host. P2P file sharing application on mobile ad hoc network (MANET) has gained more momentum as shown in the research of recent years. One natural way is to implement P2P application and ad hoc routing at different layers they belong to. In this paper, we argue that instead of stacking one on the top of the other, more work needs to be done to make both P2P file sharing protocol and MANET routing protocol interact with each other. We extract the commonalities of these two and design a common query/response framework on which ad hoc network routing and P2P file sharing are integrated seamlessly. The extensive experiments show that our strategy performs better than the layered approach in terms of traffic, average delay and packet delivery ratio.

We have designed and evaluated iMesh, an infrastructure-mode 802.11-based mesh network. IEEE 802.11 access points double as routers making the network architecture completely transparent to mobile clients, who view the network as a conventional wireless LAN. Layer-2 handoffs between access points trigger routing activities inside the network, which can be thought of as layer-3 handoffs. We describe the design rationale and a testbed implementation of iMesh. We present results related to the handoff performance. The results demonstrate excellent handoff performance, the overall latency varying between 50-100 ms, depending on different layer-2 techniques, even when a five-hop long route update is needed. Various performance measurements also demonstrate the clear superiority of a flat routing scheme relative to a more traditional, Mobile IP-like scheme to handle layer-3 handoff.