Cross-layer design for wireless sensor relay networks

In recent years, the idea of wireless sensor networks has gathered a great deal of attention. A distributed wireless sensor network may have hundreds of small sensor nodes. Each individual sensor contains both processing and communication elements and is designed in some degree to monitor the environmental events specified by the end user of the network. Information about the environment is gathered by sensors and delivered to a remote collector. This research conducts an investigation with respect to the energy efficiency and the cross-layer design in wireless sensor networks. Motivated by the multipath utilization and transmit diversity capability of space-time block codes (STBC), a new energy efficient cooperative routing algorithm using the STBC is proposed. Furthermore, the steady state performance of the network is analyzed via a Markov chain model. The proposed approach in this dissertation can significantly reduce the energy consumption and improve the power efficiency. This work also studies the application of differential STBC for wireless multi-hop sensor networks over fading channels. Using differential STBC, multiple sensors are selected acting as parallel relay nodes to receive and relay collected data. The proposed technique offers low complexity, since it does not need to track or estimate the time-varying channel coefficients. Analysis and simulation results show that the new approach can improve the system performance. This dissertation models the cooperative relay method for sensor networks using a Markov chain and an M/G/1 queuing system. The analytical and simulation results indicate system improvements in terms of throughput and end-to-end delay. Moreover, the impact of network resource constraints on the performance of multi-hop sensor networks with cooperative relay is also investigated. The system performance under assumptions of infinite buffer or finite buffer sizes is studied, the go through delay and the packet drop probability are improved compared to traditional single relay method. Moreover, a packet collision model for crucial nodes in wireless sensor networks is introduced. Using such a model, a space and network diversity combining (SNDC) method is designed to separate the collision at the collector. The network performance in terms of throughput, delay, energy consumption and efficiency are analyzed and evaluated

Master of Science

thesisThe 2012 Great Utah Shakeout highlighted the necessity for increased coordination in the collection and sharing of spatial data related to disaster response during an event. Multiple agencies must quickly relay scientific and damage observations between teams in the field and command centers. Spatial Data Infrastructure (SDI) is a framework that directly supports information discovery and access and use of the data in decision making processes. An SDI contains five core components: policies, access networks, data handling facilities, standards, and human resources needed for the effective collection, management, access, delivery, and utilization of spatial data for a specific area. Implementation of an SDI will increase communication between agencies, field-based reconnaissance teams, first responders, and individuals in the event of a disaster. The increasing popularity of location-based mobile social networks has led to spatial data from these sources being used in the context of managing disaster response and recovery. Spatial data acquired from social networks, or Volunteer Geographic Information (VGI), could potentially contribute thousands of low-cost observations to aid in damage assessment and recovery efforts that may otherwise be unreported. The objective of this research is to design and develop an SDI to allow the incorporation of VGI, professional Geographic Information System (GIS) layers, a mobile application, and scientific reports to aid in the disaster management process. A secondary goal is to assess the utility of the resulting SDI. The end result of combining the three systems (e.g., SDE, a mobile application, and VGI), along with the network of relevant users, is an SDI that improves the volume, quality, currency, accuracy, and access to vital spatial and scientific information following a hazard event

Crystallization in large wireless networks

We analyze fading interference relay networks where M single-antenna source-destination terminal pairs communicate concurrently and in the same frequency band through a set of K single-antenna relays using half-duplex two-hop relaying. Assuming that the relays have channel state information (CSI), it is shown that in the large-M limit, provided K grows fast enough as a function of M, the network "decouples" in the sense that the individual source-destination terminal pair capacities are strictly positive. The corresponding required rate of growth of K as a function of M is found to be sufficient to also make the individual source-destination fading links converge to nonfading links. We say that the network "crystallizes" as it breaks up into a set of effectively isolated "wires in the air". A large-deviations analysis is performed to characterize the "crystallization" rate, i.e., the rate (as a function of M,K) at which the decoupled links converge to nonfading links. In the course of this analysis, we develop a new technique for characterizing the large-deviations behavior of certain sums of dependent random variables. For the case of no CSI at the relay level, assuming amplify-and-forward relaying, we compute the per source-destination terminal pair capacity for M,K converging to infinity, with K/M staying fixed, using tools from large random matrix theory.Comment: 30 pages, 6 figures, submitted to journal IEEE Transactions on Information Theor