AMiBA Wideband Analog Correlator

A wideband analog correlator has been constructed for the Yuan-Tseh Lee Array for Microwave Background Anisotropy. Lag correlators using analog multipliers provide large bandwidth and moderate frequency resolution. Broadband IF distribution, backend signal processing and control are described. Operating conditions for optimum sensitivity and linearity are discussed. From observations, a large effective bandwidth of around 10 GHz has been shown to provide sufficient sensitivity for detecting cosmic microwave background variations.Comment: 28 pages, 23 figures, ApJ in press

Field-based branch prediction for packet processing engines

Network processors have exploited many aspects of architecture design, such as employing multi-core, multi-threading and hardware accelerator, to support both the ever-increasing line rates and the higher complexity of network applications. Micro-architectural techniques like superscalar, deep pipeline and speculative execution provide an excellent method of improving performance without limiting either the scalability or flexibility, provided that the branch penalty is well controlled. However, it is difficult for traditional branch predictor to keep increasing the accuracy by using larger tables, due to the fewer variations in branch patterns of packet processing. To improve the prediction efficiency, we propose a flow-based prediction mechanism which caches the branch histories of packets with similar header fields, since they normally undergo the same execution path. For packets that cannot find a matching entry in the history table, a fallback gshare predictor is used to provide branch direction. Simulation results show that the our scheme achieves an average hit rate in excess of 97.5% on a selected set of network applications and real-life packet traces, with a similar chip area to the existing branch prediction architectures used in modern microprocessors

Citywide Estimation of Traffic Dynamics via Sparse GPS Traces

Traffic congestion is a perpetual challenge in metropolitan areas around the world. The ability to understand traffic dynamics is thus critical to effective traffic control and management. However, estimation of traffic conditions over a large-scale road network has proven to be a challenging task for two reasons: first, traffic conditions are intrinsically stochastic; second, the availability and quality of traffic data vary to a great extent. Traditional traffic monitoring systems that exist mostly on major roads and highways are insufficient to recover the traffic conditions for an entire network. Recent advances in GPS technology and the resulting rich data sets offer new opportunities to improve upon such traditional means, by providing much broader coverage of road networks. Despite that, such data are limited by their spatial-temporal sparsity in practice. To address these issues, we have developed a novel framework to estimate travel times, traversed paths, and missing values over a large-scale road network using sparse GPS traces. Our method consists of two phases. In the first phase, we adopt the shortest travel time criterion based on Wardrop\u27s Principles in the map-matching process. With an improved traveltime allocation technique, we have achieved up to 52.5% relative error reduction in network travel times compared to a state-of-the-art method [1]. In the second phase, we estimate missing values using Compressed Sensing algorithm, thereby reducing the number of required measurements by 94.64%

Adaptive Resonance Theory

SyNAPSE program of the Defense Advanced Projects Research Agency (Hewlett-Packard Company, subcontract under DARPA prime contract HR0011-09-3-0001, and HRL Laboratories LLC, subcontract #801881-BS under DARPA prime contract HR0011-09-C-0001); CELEST, an NSF Science of Learning Center (SBE-0354378

Quantum sine-Gordon dynamics on analogue curved spacetime in a weakly imperfect scalar Bose gas

Using the coherent state functional integral expression of the partition function, we show that the sine-Gordon model on an analogue curved spacetime arises as the effective quantum field theory for phase fluctuations of a weakly imperfect Bose gas on an incompressible background superfluid flow when these fluctuations are restricted to a subspace of the single-particle Hilbert space. We consider bipartitions of the single-particle Hilbert space relevant to experiments on ultracold bosonic atomic or molecular gases, including, e.g., restriction to high- or low-energy sectors of the dynamics and spatial bipartition corresponding to tunnel-coupled planar Bose gases. By assuming full unitary quantum control in the low-energy subspace of a trapped gas, we show that (1) appropriately tuning the particle number statistics of the lowest-energy mode partially decouples the low- and high-energy sectors, allowing any low-energy single-particle wave function to define a background for sine-Gordon dynamics on curved spacetime and (2) macroscopic occupation of a quantum superposition of two states of the lowest two modes produces an analogue curved spacetime depending on two background flows, with respective weights continuously dependent on the corresponding weights of the superposed quantum states.Comment: 12 pages, 1 figur

Small-Packet Flows in Software Defined Networks: Traffic Profile Optimization

This paper proposes a method for optimizing bandwidth usage in Software Defined Networks (SDNs) based on OpenFlow. Flows of small packets presenting a high overhead, as the ones generated by emerging services, can be identified by the SDN controller, in order to remove header fields that are common to any packet in the flow, only during their way through the SDN. At the same time, several packets can be multiplexed together in the same frame, thus reducing the overall number of frames. The method can be useful for providing QoS while the packets are traversing the SDN. Four kinds of small-packet traffic flows are considered (VoIP, UDP and TCP-based online games, and ACKs from TCP flows). Both IPv4 and IPv6 are studied, and significant bandwidth savings (up to 68 % for IPv4 and 78 % for IPv6) can be obtained for the considered kinds of traffic. The optimization method is also applied to different public Internet traffic traces, and significant reductions in terms of packets per second are achieved. Results show that bandwidth consumption is also reduced, especially in those traces where the percentage of small packets is high. Regarding the effect on QoS, the additional delay can be kept very low (below 1 millisecond) when the throughput is high, but it may become significant for low- throughput scenarios. Thus, a trade-off between bandwidth saving and additional delay appears in those cases

Design, Analysis And Implementation Of Orthogonal Frequency Coding In Saw Devices Used For Spread Spectrum Tags And Sensors

SAW based sensors can offer wireless, passive operation in numerous environments and various device embodiments are employed for retrieval of the sensed data information. Single sensor systems can typically use a single carrier frequency and a simple device embodiment, since tagging is not required. In a multi-sensor environment, it is necessary to both identify the sensor and retrieve the sensed information. This dissertation presents the concept of orthogonal frequency coding (OFC) for applications to SAW sensor technology. OFC offers all advantages inherent to spread spectrum communications including enhanced processing gain and lower interrogation power spectral density (PSD). It is shown that the time ambiguity in the OFC compressed pulse is significantly reduced as compared with a single frequency tag having the same code length and additional coding can be added using a pseudo-noise (PN) sequence. The OFC approach is general and should be applicable to many differing SAW sensors for temperature, pressure, liquid, gases, etc. Device embodiments are shown and a potential transceiver is described. Measured device results are presented and compared with COM model predictions to demonstrate performance. Devices are then used in computer simulations of the proposed transceiver design and the results of an OFC sensor system are discussed

On Improving Automation by Integrating RFID in the Traceability Management of the Agri-Food Sector

Traceability is a key factor for the agri-food sector. RFID technology, widely adopted for supply chain management, can be used effectively for the traceability management. In this paper, a framework for the evaluation of a traceability system for the agri-food industry is presented and the automation level in an RFID-based traceability system is analyzed and compared with respect to traditional ones. Internal and external traceability are both considered and formalized, in order to classify different environments, according to their automation level. Traceability systems used in a sample sector are experimentally analyzed, showing that by using RFID technology, agri-food enterprises increase their automation level and also their efficiency, in a sustainable wa