Payone : incentive for epidemic protocol-based anonymity system

Anonymity systems maintain the anonymity of communicating nodes by camouflaging them, either with peer nodes generating dummy traffic or with peer nodes participating in the actual communication process. The probability of any adversary breaking down the anonymity of the communicating nodes is inversely proportional to the number of peer nodes participating in the network. Hence to maintain the anonymity of the communicating nodes, a large number of peer nodes are needed. Lack of peer availability weakens the anonymity of any large scale anonymity system. This work proposes PayOne, an incentive based scheme for promoting peer availability. PayOne aims to increase the peer availability by encouraging nodes to participate in the anonymity system by awarding them with incentives and thereby promoting the anonymity strength. Existing incentive schemes are designed for single path based approaches. There is no incentive scheme for multipath based or epidemic based anonymity systems. This work has been specifically designed for epidemic protocols and has been implemented over MuON, one of the latest entries to the area of multicasting based anonymity systems. MuON is a peer-to-peer based anonymity system which uses epidemic protocol for data dissemination. Existing incentive schemes involve paying every intermediate node that is involved in the communication between the initiator and the receiver. These schemes are not appropriate for epidemic based anonymity systems due to the incurred overhead. PayOne differs from the existing schemes because it involves paying a single intermediate node that participates in the network. The intermediate node can be any random node that participates in the communication and does not necessarily need to lie in the communication path between the initiator and the receiver. The light-weight characteristics of PayOne make it viable for large-scale epidemic based anonymity systems.

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.