Flexible Congestion Management for Error Reduction in Wireless Sensor Networks

The dissertation is concerned with the efficient resolution of data congestion on wireless sensor networks (WSNs). WSNs are of increasing relevance due to their applications in automation, industrial processes, natural-disaster detection, weather prediction, and climate monitoring. In large WSNs where measurements are periodically made at each node in the network and sent in a multi-hop fashion via the network tree to a single base-station node, the volume of data at a node may exceed the transmission capabilities of the node. This type of congestion can negatively impact data accuracy when packets are lost in transmission. We propose flexible congestion management for sensor networks (FCM) as a data-collection scheme to reduce network traffic and minimize the error resulting from data-volume reduction. FCM alleviates all congestion by lossy data fusion, encourages opportunistic fusion with an application-specific distortion tolerance, and balances network traffic. We consider several data-fusion methods including the k-means algorithm and two forms of adaptive summarization. Additional fusion is allowed when like data may be fused with low error up to some limit set by the user of the data-collection application on the network. Increasing the error limit tends to reduce the overall traffic on the network at the cost of data accuracy. When a node fuses more data than is required to alleviate congestion, its siblings are notified that they may increase the sizes of their transmissions accordingly. FCM is further improved to re-balance the network traffic of subtrees such that subtrees whose measurements have lower variance may decrease their output rates while subtrees whose measurements have higher variance may increase their output rates, while still addressing all congestion in the network. We verify the effectiveness of FCM with extensive simulations

Demographic variability among subpopulations of two coastal fishes around the South Island of New Zealand

Understanding the spatial structure of populations including variability in reproductive biology among subpopulations is a key objective in fisheries ecology. The aim of the present study was to identify the small scale (<10 km) population structure of blue cod (Parapercis colias) and sea perch (Helicolenus percoides) along the Otago coast and Fiordland to understand key processes that may have resulted in important demographic structure among subpopulations. Here, comparisons of size structure of blue cod among coastal and offshore regions of the Otago coast were used to estimate the biological consequences of size truncation. Populations strongly truncated towards smaller individuals were observed in coastal regions of likely higher fishing pressure. These truncated populations likely produced several orders of magnitude fewer eggs per capita than those with larger, older mature individuals. The result was a highly structured population with areas of low reproductive output and areas of higher reproductive output in close proximity, or a source-sink population. Similarly, the spatial structure of sea perch populations was investigated over larger scales. Here, intraspecific differences in morphology, growth, and isotopic signature were found among sea perch populations from Otago shelf compared to inner and outer coast regions in Fiordland. These results suggested that sea perch formed discrete subpopulations or stocks of fish in each region. The spatial population structure was most likely linked to habitat type, with distinct morphology, growth and isotopic signature associated with inner fjord and outer coastal sites. Further, maternal characteristics of sea perch from the Otago shelf including age, length, weight and condition were used to predict oil globule volume, notochord length and growth rate of cohorts of larvae. The results indicated that larger, older females produced offspring with larger energetic reserves, and likely better survivorship, than offspring from smaller, younger females. The investigations demonstrated important links between size and age structure and spatial population structure of two heavily exploited coastal fishes. The results have important implications for understanding population dynamics and the likely response of structured populations to exploitation or spatial management

Magnetic Tunnel Junction-Based On-Chip Microwave Phase and Spectrum Analyzer

A magnetic tunnel junction (MTJ)-based microwave detector is proposed and investigated. When the MTJ is excited by microwave magnetic fields, the relative angle between the free layer and pinned layer alternates, giving rise to an average resistance change. By measuring the average resistance change, the MTJ can be utilized as a microwave power sensor. Due to the nature of ferromagnetic resonance, the frequency of an incident microwave is directly determined. In addition, by integrating a mixer circuit, the MTJ-based microwave detector can also determine the relative phase between two microwave signals. Thus, the MTJbased microwave detector can be used as an on-chip microwave phase and spectrum analyzer

Tunnel barrier enhanced voltage signals generated by magnetization precession of a single ferromagnetic layer

We report the electrical detection of magnetization dynamics in an Al/AlOx/Ni80Fe20/Cu tunnel junction, where a Ni80Fe20 ferromagnetic layer is brought into precession under the ferromagnetic resonance (FMR) conditions. The dc voltage generated across the junction by the precessing ferromagnet is enhanced about an order of magnitude compared to the voltage signal observed when the contacts in this type of multilayered structure are ohmic. We discuss the relation of this phenomenon to magnetic spin pumping and speculate on other possible underlying mechanisms responsible for the enhanced electrical signal

Electric-Field-Induced Mott Insulating States in Organic Field-Effect Transistors

We consider the possibility that the electrons injected into organic field-effect transistors are strongly correlated. A single layer of acenes can be modelled by a Hubbard Hamiltonian similar to that used for the kappa-(BEDT-TTF)(2)X family of organic superconductors. The injected electrons do not necessarily undergo a transition to a Mott insulator state as they would in bulk crystals when the system is half-filled. We calculate the fillings needed for obtaining insulating states in the framework of the slave-boson theory and in the limit of large Hubbard repulsion, U. We also suggest that these Mott states are unstable above some critical interlayer coupling or long-range Coulomb interaction.Comment: 9 pages, 7 figure