Growing demands in heterogeneous utility computing systems in future cloud and high performance computing systems are driving the development of processor-hardware accelerator interconnects with greater performance, flexibility, and dynamism. Recent innovations in the field of utility computing have led to an emergence in the use of heterogeneous compute elements. By leveraging the computing advantages of hardware accelerators alongside typical general purpose processors, performance efficiency can be maximized. The network linking these compute nodes is increasingly becoming the bottleneck in these architectures, limiting the hardware accelerators to be restricted to localized computing. A high-bandwidth, agile interconnect is an imperative enabler for hardware accelerator delocalization in heterogeneous utility computing. A redesign of these systems' interconnect and architecture will be essential to establishing high-bandwidth, low-latency, efficient, and dynamic heterogeneous systems that can meet the challenges of next-generation utility computing. By leveraging an optics-based approach, this dissertation presents the design and implementation of optically-connected hardware accelerators (OCHA) that exploit the distance-independent energy dissipation and bandwidth density of photonic transceivers, in combination with the flexibility, efficiency and data parallelization offered by optical networks. By replacing the electronic buses with an optical interconnection network, architectures that delocalize hardware accelerators can be created that are otherwise infeasible. With delocalized optically-connected hardware accelerator nodes accessible by processors at run time, the system can alleviate the network latency issues plague current heterogeneous systems. Accelerators that would otherwise sit idle, waiting for it's master CPU to feed it data, can instead operate at high utilization rates, leading to dramatic improvements in overall system performance. This work presents a prototype optically-connect hardware accelerator module and custom optical-network-aware, dynamic hardware accelerator allocator that communicate transparently and optically across an optical interconnection network. The hardware accelerators and processor are optimized to enable hardware acceleration across an optical network using fast packet-switching. The versatility of the optical network enables additional performance benefits including optical multicasting to exploit the data parallelism found in many accelerated data sets. The integration of hardware acceleration, heterogeneous computing, and optics constitutes a critical step for both computing and optics. The massive data parallelism, application dependent-location and function, as well as network latency, and bandwidth limitations facing networks today complement well with the strength of optical communications-based systems. Moreover, ongoing efforts focusing on development of low-cost optical components and subsystems that are suitable for computing environment may benefit from the high-volume heterogeneous computing market. This work, therefore, takes the first steps in merging the areas of hardware acceleration and optics by developing architectures, protocols, and systems to interface with the two technologies and demonstrating areas of potential benefits and areas for future work. Next-generation heterogeneous utility computing systems will indubitably benefit from the use of efficient, flexible and high-performance optically connect hardware acceleration.

In the near future, objects equipped with heterogeneous devices such as sensors, actuators, and tags, will be able to interact with each other and cooperate to achieve common goals. These networks are termed the Internet of Things (IoT) and have applications in healthcare, smart buildings, assisted living, manufacturing, supply chain management, and intelligent transportation. The IoT vision is enabled by ubiquitous wireless communications and there are numerous resource allocation challenges to efficiently connect each device to the network. In this thesis, we study wireless resource allocation problems that arise in the IoT, namely in the areas of the energy harvesting tags, termed the Internet of Tags (IoTags), and in cellular networks (mobile and cognitive). First, we present our experience designing and developing Energy Harvesting Active Networked Tags (EnHANTs). The prototypes harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultra-low-power Ultra- Wideband Impulse Radio (UWB-IR) transceivers, and dynamically adapt their communications and networking patterns to the energy harvesting and battery states. Using our custom designed small scale testbed, we evaluate energy-adaptive networking algorithms spanning the protocol stack (link, network, and flow control). Throughout the evaluation of experiments, we highlight numerous phenomena which are typically difficult to capture in simulations and nearly impossible to model in analytical work. We believe that these lessons would be useful for the designers of many different types of energy harvesters and energy harvesting adaptive networks. Based on the lessons learned from EnHANTs, we present Power Aware Neighbor Discovery Asynchronously (Panda), a Neighbor Discovery (ND) protocol optimized for networks of energy harvesting nodes. To enable object tracking and monitoring applications for IoTags, Panda is designed to efficiently identify nodes which are within wireless communication range of one another. By accounting for numerous hardware constraints which are typically ignored (i.e., energy costs for transmission/reception, and transceiver state switching times/costs), we formulate a power budget to guarantee perpetual ND. Finally, via testbed evaluation utilizing Commercial Off-The-Shelf (COTS) energy harvesting nodes, we demonstrate experimentally that Panda outperforms existing protocols by a factor of 2-3x. We then consider Proportional Fair (PF) cellular scheduling algorithms for mobile users, These users experience slow-fading wireless channels while traversing roads, train tracks, bus routes, etc. We leverage the predicable mobility on these routes and present the Predictive Finite-horizon PF Scheduling ((PF)2S) Framework. We collect extensive channel measurement results from a 3G network and characterize mobility-induced channel state trends. We show that a user’s channel state is highly reproducible and leverage that to develop a data rate prediction mechanism. Our trace-based simulations of the (PF)2S Framework indicate that the framework can increase the throughput by 15%–55% compared to traditional PF schedulers, while improving fairness. Finally, we study fragmentation within a probability model of combinatorial structures. Our model does not refer to any particular application. Yet, it is applicable to dynamic spectrum access networks which can be used as the wireless access technology for numerous IoT applications. In dynamic spectrum access networks, users share the wireless resource and compete to transmit and receive data, and accordingly have specific bandwidth and residence-time requirements. We prove that the spectrum tends towards states of complete fragmentation. That is, for every request for j > 1 sub-channels, nearly all size-j requests are allocated j mutually disjoint sub-channels. In a suite of four theorems, we show how this result specializes for certain classes of request-size distributions. We also show that the delays in reaching the inefficient states of complete fragmentation can be surprisingly long. The results of this chapter provide insights into the fragmentation process and, in turn, into those circumstances where defragmentation is worth the cost it incurs.

Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. Here we present an integrated circuit-based electrochemical camera chip capable of simultaneous spatial imaging of multiple redox-active metabolites, called phenazines, produced by Pseudomonas aeruginosa PA14 colony biofilms. Imaging of mutants with various capacities for phenazine production reveals local patterns of phenazine distribution in the biofilms. Such integrated circuit-based techniques promise wide applicability in detecting redox-active species from diverse biological samples.

Thesis (M.S.) Massachusetts Institute of Technology. Dept. of Electrical Engineering, 1946. / Bibliography: leaf 60. / by Sidney Alden Wingate. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1938. / MICROFICHE COPY AVAILABLE IN ENGINEERING. / Includes bibliographical references (leaf 63). / by Albert Carruthers Hall. / M.S.

Computed tomography (CT) imaging provides a non-destructive means to examine the interior of an object which is a valuable tool in medical and security applications. The variety of materials seen in the security applications is higher than in the medical applications. Factors such as clutter, presence of dense objects, and closely placed items in a bag or a parcel add to the difficulty of the material recognition in security applications. Metal and dense objects create image artifacts which degrade the image quality and deteriorate the recognition accuracy. Conventional CT machines scan the object using single source or dual source spectra and reconstruct the effective linear attenuation coefficient of voxels in the image which may not provide the sufficient information to identify the occupying materials. In this dissertation, we provide algorithmic solutions to enhance CT material recognition. We provide a set of algorithms to accommodate different classes of CT machines. First, we provide a metal artifact reduction algorithm for conventional CT machines which perform the measurements using single X-ray source spectrum. Compared to previous methods, our algorithm is robust to severe metal artifacts and accurately reconstructs the regions that are in proximity to metal. Second, we propose a novel joint segmentation and classification algorithm for dual-energy CT machines which extends prior work to capture spatial correlation in material X-ray attenuation properties. We show that the classification performance of our method surpasses the prior work's result. Third, we propose a new framework for reconstruction and classification using a new class of CT machines known as spectral CT which has been recently developed. Spectral CT uses multiple energy windows to scan the object, thus it captures data across higher energy dimensions per detector. Our reconstruction algorithm extracts essential features from the measured data by using spectral decomposition. We explore the effect of using different transforms in performing the measurement decomposition and we develop a new basis transform which encapsulates the sufficient information of the data and provides high classification accuracy. Furthermore, we extend our framework to perform the task of explosive detection. We show that our framework achieves high detection accuracy and it is robust to noise and variations. Lastly, we propose a combined algorithm for spectral CT, which jointly reconstructs images and labels each region in the image. We offer a tractable optimization method to solve the proposed discrete tomography problem. We show that our method outperforms the prior work in terms of both reconstruction quality and classification accuracy.

Massachusetts Institute of Technology. Dept. of Electrical Engineering. Thesis. 1974. M.S. / MICROFICHE COPY ALSO AVAILABLE IN BARKER ENGINEERING LIBRARY. / Number 73 omitted in paging. / Includes bibliographical references. / M.S.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1961. / Vita. / Includes bibliographical references (leaves 171-175). / by John Paul Penhume. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1960. / Vita. / Includes bibliographical references (leaves 123-124). / by Frederic Richard Morgenthaler. / Ph.D.

Thesis (M.S.) Massachusetts Institute of Technology. Dept. of Electrical Engineering, 1955. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Bibliography: leaves [46-48]. / by Robert William Reichard. / M.S.