Abstract-We propose a novel framework for location detection with sensor networks, based on the theory of identifying codes. The key idea of this approach is to allow sensor coverage areas to overlap so that each resolvable position is covered by a unique set of sensors. In this setting, determining a sensor-placement with a minimum number of sensors is equivalent to constructing an optimal identifying code, an NPcomplete problem in general. We thus propose and analyze new polynomial-time algorithms for generating irreducible (but not necessarily optimal) codes for arbitrary topologies. Our algorithms incorporate robustness properties that are critically needed in harsh environments. We further introduce distributed versions of these algorithms, allowing sensors to self-organize and determine a (robust) identifying code without any central coordination. Through analysis and simulation, we show that our algorithms produce nearly optimal solutions for a wide range of parameters. In addition, we demonstrate a tradeoff between system robustness and the number of active sensors (which is related to the expected lifetime of the system). Finally, we present experimental results, obtained on a small testbed, that demonstrate the feasibility of our approach.

Abstract-The RTS/CTS mechanism is widely used in wireless networks in order to avoid packet collisions and, thus, achieve high throughput. In ad hoc networks, however, the current implementation of the RTS/CTS mechanism may lead to interdependencies so that nodes become unable to transmit any packets during long periods of time. This effect manifests itself in the form of congestion where, after a certain point, the network throughput decreases with increasing load instead of maintaining its peak value. In this paper, we describe and analyze this problem in detail and provide a backward-compatible solution, called RTS Validation. Our simulations show that this solution leads to a 60% gain in the peak throughput in addition to stabilizing the throughput at high load.

Abstract-We propose a new framework for providing robust location detection in emergency response systems, based on the theory of identifying codes. The key idea of this approach is to allow sensor coverage areas to overlap in such a way that each resolvable position is covered by a unique set of sensors. In this setting, determining a sensor-placement with a minimum number of sensors is equivalent to constructing an optimal identifying code, an NP-complete problem in general. We thus propose and analyze a new polynomial-time algorithm for generating irreducible codes for arbitrary topologies. We also generalize the concept of identifying codes to incorporate robustness properties that are critically needed in emergency networks and provide a polynomial-time algorithm to compute irreducible robust identifying codes. Through analysis and simulation, we show that our approach typically requires significantly fewer sensors than existing proximity-based schemes. Alternatively, for a fixed number of sensors, our scheme can provide robustness in the face of sensor failures or physical damage to the system.

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IEEE 802.11 wireless networks employ the so-called RTS/CTS mechanism in order to avoid DATA packet collisions. The main design assumption is that all the nodes in the vicinity of a sender and a receiver will hear the RTS or CTS packets, and defer their transmission appropriately. This assumption happens not to hold in general, even under perfect operating conditions. Often, neighboring nodes are "masked" by other on-going transmissions nearby and, hence, are unable to receive the RTS or CTS packets correctly. We refer to such nodes as masked nodes. In this paper, we describe the masked node problem and show scenarios leading to DATA packet collisions. We evaluate the impact of masked nodes through mathematical analysis and real experiments on a small IEEE 802.11 ad-hoc network.The analytical and experimental data closely match and reveal that the presence of a masked node in a network can result in an order of magnitude increase in DATA packet loss compared to a network without masked nodes. These results are further validated by extensive simulations on a large-scale network, which show that masked nodes also significantly affect delay and throughput performance. Therefore, masked nodes severely limit the effectiveness of the RTS/CTS mechanism in preventing performance degradation in wireless LANs.