Silvija Kokalj-Filipovic

Doped fountain coding for minimum delay data collection in circular networks

This paper studies decentralized, Fountain and network-coding based strategies for facilitating data collection in circular wireless sensor networks, which rely on the stochastic diversity of data storage. The goal is to allow for a reduced delay collection by a data collector who accesses the network at a random position and random time. Data dissemination is performed by a set of relays which form a circular route to exchange source packets. The storage nodes within the transmission range of the routeiquests relays linearly combine and store overheard relay transmissions using random decentralized strategies. An intelligent data collector first collects a minimum set of coded packets from a subset of storage nodes in its proximity, which might be sufficient for recovering the original packets and, by using a message-passing decoder, attempts recovering all original source packets from this set. Whenever the decoder stalls, the source packet which restarts decoding is polled/doped from its original source node. The random-walk-based analysis of the decoding/doping process furnishes the collection delay analysis with a prediction on the number of required doped packets. The number of doped packets can be surprisingly small when employed with an Ideal Soliton code degree distribution and, hence, the doping strategy may have the least collection delay when the density of source nodes is sufficiently large. Furthermore, we demonstrate that network coding makes dissemination more efficient at the expense of a larger collection delay. Not surprisingly, a circular network allows for a significantly more (analytically and otherwise) tractable strategies relative to a network whose model is a random geometric graph.

ARQ with Doped Fountain Decoding

We analyze the benefits of an automatic repeat- request (ARQ) scheme employed in doped belief-propagation decoding for increasing the throughput of fountain encoded data transmissions. The proposed doping mechanism selects doping symbols randomly from the set of input symbols contributing to degree-two output symbols. Here an output symbol is the encoded symbol whose code-graph links to input symbols decoded thus far have been severed. This doping approach always ensures releasing of at least one output symbol, thus increasing the number of degree-one output symbols (the ripple). Using a random walk analysis, we study the belief propagation decoding with degree-two random doping for a fountain code with symbols drawn from an Ideal Soliton distribution. We show that the decoding process is a renewal process whereas the process starts all over afresh after each doping. The approximate interdoping process analysis revolves around a random walk model for the ripple size. We model the sequence of the ripple size increments (due to doping and/or decoding) as an iid sequence of shifted and truncated Poisson random variables. This model furnishes a prediction on the number of required doping symbols and, furthermore, the ARQ throughput cost analysis. We also find that the Ideal Soliton significantly outperforms the Robust Soliton distribution in our ARQ-doping scheme.

Decentralized fountain codes for minimum-delay data collection

This paper studies decentralized strategies for facilitating data collection in circular wireless sensor networks, which rely on the stochastic diversity of data storage. The goal is to allow for a reduced delay collection by a mobile data collector (MDC) who accesses the network at a random position and random time. We consider a two-phase data collection: the push phase is mechanized through source packet dissemination strategies based on network coding; the pull phase is based on polling of additional packets from their original source nodes. Dissemination is performed by a set of relays which form a circular route to exchange source packets. The storage nodes within the transmission range of the routeiquests relays linearly combine and store overheard relay transmissions. MDC first collects a set of packets in its physical proximity and, using a message-passing decoder, attempts recovering all original source packets from this set. Whenever the decoder stalls a source packet which restarts decoding is polled/doped from its original source. The number of doped packets can be surprisingly small and, hence, the push-pull doping strategy may have the least collection delay when the density of source nodes is sufficiently large. Furthermore, the Ideal Soliton fountain encoding is a good linear combining strategy at the storage nodes whenever doping is employed.

BeSpoken Protocol for Data Dissemination in Wireless Sensor Networks

For wireless sensor networks with many location- unaware nodes, we investigate a protocol, dubbed BeSpoken, that steers data transmissions along a straight path called a spoke. The protocol directs data transmissions by randomly selecting relays to retransmit data packets from crescent-shaped areas along the spoke axis. The resulting random walk of the spoke hop sequence may be modeled as a two dimensional Markov process. We propose design rules for protocol parameters that minimize energy consumption while ensuring that spokes propagate far enough and have a limited wobble with respect to the spoke axis.

Methods for Extracting V2V Propagation Models from Imperfect RSSI Field Data

We describe three in-field data collection efforts yielding a large database of RSSI values vs. time or distance from vehicles communicating with each other via DSRC. We show several data processing schemes we have devised to develop opportunistic Vehicle-to-Vehicle (V2V) propagation models from such data. The database is limited in several important ways, not least, the presence of a high noise floor that limits the distance over which good modeling is feasible. Another is the presence of interference from multiple active transmitters. Our methodology makes it possible to obtain, despite these limitations, accurate models of median path loss vs. distance, shadow fading, and fast fading caused by multipath. We aim not to develop a new V2V model, but to show the methods enabling such a model to be obtained from in-field RSSI data, without elaborate measurement design and the associated deployment cost. Finally, models based on field data allow for capturing the multiple effects of an increasing number of simultaneous V2V transceivers under typical extreme traffic scenarios.

EM-based channel estimation from crowd-sourced RSSI samples corrupted by noise and interference

We propose a method for estimating channel parameters from RSSI measurements and the lost packet count, which can work in the presence of losses due to both interference and signal attenuation below the noise floor. This is especially important in the wireless networks, such as vehicular, where propagation model changes with the density of nodes. The method is based on Stochastic Expectation Maximization, where the received data is modeled as a mixture of distributions (no/low interference and strong interference), incomplete (censored) due to packet losses. The PDFs in the mixture are log-Gamma, according to the commonly accepted model for wireless signal and interference power expressed in dBm. This approach leverages the loss count as additional information, hence outperforming maximum likelihood estimation, which does not use this information (ML-), for a small number of received RSSI samples. Hence, it allows inexpensive on-line channel estimation from ad-hoc collected data. The method also outperforms ML- on uncensored data mixtures, as ML- assumes that samples are from a single-mode PDF.

Random Walk Models for Geographic Data Propagation in Wireless Sensor Networks

For wireless sensor networks with many location-unaware nodes, we investigate a protocol, dubbed BeSpoken, that steers data transmissions along a straight path called a spoke. The protocol directs data transmissions by randomly selecting relays to retransmit data packets from crescent-shaped areas along the spoke axis. The packet retransmission by the selected relay constitutes a spoke hop. The current spoke direction at any given hop may deviate from the spoke axis. In this work, we model the current direction as a Markov modulated random walk, and offer protocol design guidelines which ensure that the deviation is limited.

Geographic data propagation in location-unaware wireless sensor networks: a two-dimensional random walk analysis

For wireless sensor networks with many location-unaware nodes, which can be modeled as a planar Poisson point process, we investigate a protocol, dubbed BeSpoken, which steers data transmissions along a straight path called a spoke. BeSpoken implements a simple, spatially recursive process, where a basic set of control packets and a data packet are exchanged repeatedly among daisy-chained relays that constitute the spoke. Hence, a data packet originated by the first relay makes a forward progress in the direction of the spoke. Despite the simplicity of the protocol engine, modeling the spoke process is a significant challenge. Bespoken directs data transmissions by randomly selecting relays to retransmit data packets from crescent-shaped areas along the spoke axis. The resulting random walk of the spoke hop sequence may be modeled as a two dimensional Markov process. Based on this model, we propose design rules for protocol parameters that minimize energy consumption while ensuring that spokes propagate far enough and have a limited wobble with respect to the spoke axis. The energy efficiency is demonstrated through simulations of the BeSpoken-based data search, and a comparison with the energy consumption of a search based on directed diffusion.

Can a packet walk straight through a field of randomly dying location-unaware wireless nodes?

A protocol, dubbed BeSpoken, steers data transmissions along a straight path called a spoke through a wireless sensor network with many location-unaware nodes. BeSpoken implements a simple, spatially recursive communication process, where a set of control packets and a data packet are exchanged among daisy-chained relays that constitute the spoke. It directs data transmissions by randomly selecting relays from crescent-shaped areas along the spoke axis created by intersecting transmission ranges of control and data packets. To specify design rules for protocol parameters that minimize energy consumption while ensuring that spokes propagate far enough and have a limited wobble with respect to the spoke axis, our model of the spoke propagation matches the protocol parameters to the density of network nodes, assuming that nodes are spatially distributed as a Poisson point process of known uniform intensity. To avoid this requirement, we propose and characterize an adaptive mechanism that ensures desired spoke propagation in a network of arbitrary density. This necessitates a qualitatively new protocol model used to evaluate the spoke propagation under both the basic and the adaptive protocol. The introduced adaptive mechanism repairs the spoke when the crescent-shaped area is empty which may occur in the case of network thinning and as a result of random or arbitrary sensor death. Our analytical and simulation results demonstrate that the adaptive BeSpoken creates longer spokes both in networks with uniform distribution of nodes and in networks with holes. In addition, the adaptive protocol is significantly less sensitive to changes in the distribution of network nodes and their density.