Showing papers by "Samir R. Das published in 2009"

Predictive methods for improved vehicular WiFi access

Abstract: 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.

Variable radii connected sensor cover in sensor networks

Abstract: One of the useful approaches to exploit redundancy in a sensor network is to keep active only a small subset of sensors that are sufficient to cover the region required to be monitored The set of active sensors should also form a connected communication graph, so that they can autonomously respond to application queries and/or tasks Such a set of active sensors is known as a connected sensor cover, and the problem of selecting a minimum connected sensor cover has been well studied when the transmission radius and sensing radius of each sensor is fixed In this article, we address the problem of selecting a minimum energy-cost connected sensor cover, when each sensor node can vary its sensing and transmission radius; larger sensing or transmission radius entails higher energy costFor the aforesaid problem, we design various centralized and distributed algorithms, and compare their performance through extensive experiments One of the designed centralized algorithms (called CGA) is shown to perform within an O(log n) factor of the optimal solution, where n is the size of the network We have also designed a localized algorithm based on Voronoi diagrams which is empirically shown to perform very close to CGA and, due to its communication-efficiency, results in significantly prolonging the network lifetime We also extend the aforementioned algorithms to incorporate fault tolerance In particular, we show how to extend the algorithms to address the minimum energy-cost connected sensor k-cover problem, in which every point in the query region needs to be covered by at least k distinct active sensors The CGA preserves the approximation bound in this case We also propose a localized topology control scheme to preserve k-connectivity, and use it to extend the Voronoi-based approach to computing a minimum energy-cost k1-connected k2-cover We study the performance of our proposed algorithms through extensive simulations

Wireless link scheduling under a graded SINR interference model

Abstract: In this paper, we revisit the wireless link scheduling problem under a graded version of the SINR interference model. Unlike the traditional thresholded version of the SINR model, the graded SINR model allows use of "imperfect links", where communication is still possible, although with degraded performance (in terms of data rate or PRR). Throughput benefits when graded SINR model is used instead of thresholded SINR model to schedule transmissions have recently been shown in an experimental testbed. Here, we formally define the wireless link scheduling problem under the graded SINR model, where we impose an additional constraint on the minimum quality of the usable links, (expressed as an SNR threshold βQ). Then, we present an approximation algorithm for this problem, which is shown to be within a constant factor from optimal. We also present a more practical greedy algorithm, whose performance bounds are not known, but which is shown through simulation to have much better average performance than the approximation algorithm. Furthermore, we investigate, through both simulation and implementation on an experimental testbed, the tradeoff between the minimum link quality threshold βQ and the resulting network throughput.

Physical Interference Modeling for Transmission Scheduling on Commodity WiFi Hardware

Abstract: The demand for capacity in WiFi networks is driving a new look at transmission scheduling-based link layers. One basic issue here is the use of accurate interference models to drive transmission scheduling algorithms. However, experimental work in this space has been limited. In this work, we use commodity WiFi hardware (specifically, 802.11a) for a comprehensive study of interference modeling for transmission scheduling on a mesh network setup. We focus on the well-known physical interference model for its realism. We propose use of the "graded" version of the model where feasibility of a link is probabilistic, as opposed to using the more traditional "thresholded" version, where feasibility is binary. We show experimentally that the graded model is significantly more accurate (80 percentile error 0.2 vs. 0.55 for thresholded model). We develop transmission scheduling experiments using greedy scheduling algorithms for the evacuation model for both interference models. We also develop similar experiments for optimal scheduling performance for the simplified one-shot scheduling. The scheduling experiments demonstrate clearly superior performance for the graded model, often by a factor of 2. We conclude by promoting use of this model for scheduling studies.

Understanding Channel and Interface Heterogeneity in Multi-channel Multi-radio Wireless Mesh Networks

Abstract: Multi-channel multi-radio architectures have been widely studied for 802.11-based wireless mesh networks to address the capacity problem due to wireless interference. They all utilize channel assignment algorithms that assume all channels and radio interfaces to be homogeneous. However, in practice, different channels exhibit different link qualities depending on the propagation environment for the same link. Different interfaces on the same node also exhibit link quality variations due to hardware differences and required antenna separations. We present a detailed measurement study of these variations using two mesh network testbeds in two different frequency bands --- 802.11g in 2.4GHz band and 802.11a in 5GHz band. We show that the variations are significant and `non-trivial' in the sense that the same channel does not perform well for all links in a network, or the same interface does not perform well for all interfaces it is paired up with for each link. We also show that using the channel-specific link quality information in a candidate channel assignment algorithm improves its performance more than 3 times on average.