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In connected autonomous vehicles (CAVs), the driving safety can be greatly deteriorated, in the presence of occlusions which are adverse to CAVs’ perception of region-of-interest (RoI). Collaborative perception on the basis the information sharing of occlusions among CAVs, in a real-time and accurate manner, provides a means of the occlusion-free RoI perception for safe driving. In this paper, we propose a novel framework of Collaborative Occlusion-free Perception (COFP) in CAVs, to regain the real-time and accurate occlusion awareness. The innovative COFP targets two goals: well-balanced computation resource allocation, as well as fast and high-quality RoI information fusion. Specifically, the resource allocation problem, with the objective of minimizing CAVs’ completion delay, is formulated as a multi-player continuous potential game and solved by a better response dynamics (BRD) algorithm. The RoI information fusion, with the objective of maximizing the overall object depiction quality, is formulated as a combinatorial optimization problem, and solved by a modified discrete salp swarm (MDSSA) algorithm. Experimental results show that the proposed COFP with 5 GHz computing power can achieve full occlusion awareness for CAVs with 69.61% completion time reduction and 19.03% fusion quality improvement, compared to the existing methods.

We consider the problem of task offloading and resource allocation in mobile edge computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile devices (MDs) may offload their tasks to edge servers based on the allocated computation (e.g., CPU/GPU cycles and storage) and wireless resources (e.g., bandwidth). However, these resources could not be effectively utilized unless an encouraging resource allocation scheme can be proposed. What’s worse, task offloading incurs additional MEC energy consumption, which inevitably violate the long-term MEC energy budget. Considering these two challenges, we propose an online joint offloading and resource allocation (JORA) framework under the long-term MEC energy constraint, aiming at guaranteeing the end-users’ QoE. To achieve this, we leverage Lyapunov optimization to exploit the optimality of the long-term QoE maximization problem. By constructing an energy deficit queue to guide energy consumption, the problem can be solved in a real-time manner. On this basis, we propose online JORA methods in both centralized and distributed manners. Furthermore, we prove that our proposed methods enable the achievement of the close-to-optimal performance while satisfying the long-term MEC energy constraint. In addition, we conduct extensive simulations and the results show superiority in performance over other methods.

Storage and memory systems for modern data analytics are heavily layered, managing shared persistent data, cached data, and nonshared execution data in separate systems such as a distributed file system like HDFS, an in-memory file system like Alluxio, and a computation framework like Spark. Such layering introduces significant performance and management costs. In this paper we propose a single system called Pangea that can manage all data---both intermediate and long-lived data, and their buffer/caching, data placement optimization, and failure recovery---all in one monolithic distributed storage system, without any layering. We present a detailed performance evaluation of Pangea and show that its performance compares favorably with several widely used layered systems such as Spark.

During this decade, artificial intelligence (AI) has established itself as a phenomenon in our daily life. It is one of the most important investment priorities and has been at the forefront of recent technological disruptions. New boundaries are being pushed daily, ranging from winning against the world’s best Go player to selfdriving and autopilot capabilities Startups and tech giants continue to forge ahead in applying AI in diverse domains spanning speech recognition, image classification, recommendation systems, and internet search. Colloquially, AI can be loosely described as a machine mimicking cognitive abilities that humans exhibit fundamentally such as learning and problem solving.

The use of green hydrogen to decarbonize the U.S. economy has been steadily gaining commercial interest as the cost and availability of renewable electricity decreases. At present, technologies can only take advantage of low electricity prices at low capacity factor, due to its intermittent availability, negatively impacting the economics. Reversible solid-oxide cell (r-SOC) based energy conversion systems can potentially solve this problem by producing power when electricity prices are high and hydrogen when they are low. However, the long-term operation of r-SOC systems has not been fully investigated compared to paired SOFC and SOEC units. This paper presents techno-economic results for two SOC-based hydrogen and power co-generation concepts. These technologies primarily generate hydrogen through solid oxide electrolysis but have the capacity to switch to power if signaled by the market. This operational flexibility provides a significant benefit to an electric grid with a growing share of variable renewable energy generation.

While the Internet promises a future for universally accessible and more intelligent healthcare, the privacy of patients, doctors, nurses, and healthcare providers is of greater concern today than ever. This special issue addresses two selected important topics involved in healthcare informatics and privacy.

This article presents a publishing system for efficiently creating dynamic Web content. Complex Web pages are constructed from simpler fragments. Fragments may recursively embed other fragments. Relationships between Web pages and fragments are represented by object dependence graphs. We present algorithms for efficiently detecting and updating Web pages affected after one or more fragments change. We also present algorithms for publishing sets of Web pages consistently; different algorithms are used depending upon the consistency requirements.Our publishing system provides an easy method for Web site designers to specify and modify inclusion relationships among Web pages and fragments. Users can update content on multiple Web pages by modifying a template. The system then automatically updates all Web pages affected by the change. Our system accommodates both content that must be proofread before publication and is typically from humans as well as content that has to be published immediately and is typically from automated feeds.We discuss some of our experiences with real deployments of our system as well as its performance. We also quantitatively present characteristics of fragments used at a major deployment of our publishing system including fragment sizes, update frequencies, and inclusion relationships.

Contemporary Web sites typically consist of front–end Web servers, application servers, and back-end information systems such as database servers. There has been limited research on how to provide overload control and service differentiation for the back-end systems. In this paper we propose an architecture called tiered service (TS) for these purposes. In TS, there are several heterogeneous back-end systems to serve the Web applications. The Web applications communicate with a routing intermediary to intelligently route the queries to the appropriate back-end servers based on various policies such as client profiles and server load. In our system the back ends may store different qualities of data; lower quality data typically requires less overhead to serve. The main contributions of this paper include (i) a tiered content replication scheme that replicates tiered qualities of data on heterogeneous back ends with different capacity to satisfy clients with diverse requirements for latency and quality of data, and (ii) an application-transparent query routing architecture that automatically routes the queries to the appropriate back ends. The architecture was implemented in our test bed, and its performance was benchmarked. The experimental results demonstrate that TS offers significant performance improvement.

The delivery of multimedia over the Internet is affected by adverse network conditions such as high packet loss rate and long delay. This paper aims at mitigating such effects by leveraging client-side caching proxies. We present a novel cache architecture and associated cache management algorithms that turn edge caches into accelerators of streaming media delivery. This architecture allows partial caching of media objects and joint delivery from caches and origin servers. Most importantly, the caching algorithms are both network-aware and stream-aware; they take into account the popularity of streaming media objects, their bit rate requirements, and the available bandwidth between clients and servers. Using Internet bandwidth models derived from proxy cache logs and measured over real Internet paths, we have conducted extensive simulations to evaluate the performance of various cache management algorithms. Our experiments demonstrate that network-aware caching algorithms can significantly reduce startup delay and improve stream quality. Our experiments also show that partial caching is particularly effective when bandwidth variability is not very high.

Quantification of heart valve leaflet deformation during the cardiac cycle is essential in understanding normal and pathological valvular function, as well as in the design of replacement heart valves. Due to the technical complexities involved, little work to date has been performed on dynamic valve leaflet motion. We have developed a novel experimental method utilizing a noncontacting structured laser-light projection technique to investigate dynamic leaflet motion. Using a simulated circulatory loop, a matrix of 150–200 laser light points were projected over the entire leaflet surface. To obtain unobstructed views of the leaflet surface, a stereo system of high-resolution boroscopes was used to track the light points at discrete temporal points during the cardiac cycle. The leaflet surface at each temporal point was reconstructed in three dimensions, and fit using our biquintic hermite finite element approach (Smith et al., Ann. Biomed. Eng.26:598–611, 2001). To demonstrate our approach, we utilized a bovine pericardial bioprosthetic heart valve, which revealed regions of complex flexural deformation and substantially different shapes during the opening and closing phases. In conclusion, the current method has high spatial and temporal resolution and can reconstruct the entire surface of the cusp simultaneously. Because it is completely noncontacting, this approach is applicable to studies of fatigue and bioreactor technology for tissue engineered heart valves. © 2001 Biomedical Engineering Society. PAC01: 8719Hh, 8780-y, 4262Be, 8719St

Numerous studies show that miss ratios at forward proxies are typically at least 40–50%. This paper proposes and evaluates a new approach for improving the throughput of Web proxy systems by reducing the overhead of handling cache misses. Namely, we propose to front-end a Web proxy with a high performance node that filters the requests, processing the misses and forwarding the hits and the new cacheable content to the proxy. Requests are filtered based on hints of the proxy cache content. This system, called Proxy Accelerator, achieves significantly better communications performance than a traditional proxy system. For instance, an accelerator can be built as an embedded system optimized for communication and HTTP processing, or as a kernel-mode HTTP server. Scalability with the Web proxy cluster size is achieved by using several accelerators. We use analytical models, trace-based simulations, and a real implementation to study the benefits and the implementation tradeoffs of this new approach. Our results show that a single proxy accelerator node in front of a 4-node Web proxy can improve the cost-performance ratio by about 40%. Hint-based request filter implementation choices that do not affect the overall hit ratio are available. An implementation of the hint management module integrated in Web proxy software is presented. Experimental evaluation of the implementation demonstrates that the associated overheads are very small.

In this paper we develop a general methodology for characterizing the access patterns of Web server requests based on a time‐series analysis of finite collections of observed data from real systems. Our approach is used together with the access logs from the IBM Web site for the Olympic Games to demonstrate some of its advantages over previous methods and to construct a particular class of benchmarks for large‐scale heavily‐accessed Web server environments. We then apply an instance of this class of benchmarks to analyze aspects of large‐scale Web server performance, demonstrating some additional problems with methods commonly used to evaluate Web server performance at different request traffic intensities.

The fuel cell program at the United States Department of Energy (DOE) National Energy Technology Laboratory (NETL) is focused on the development of low-cost, highly efficient, and reliable fossil-fuel-based solid oxide fuel cell (SOFC) power systems that can generate environmentally friendly electric power with at least 90% carbon capture. NETL’s SOFC technology development roadmap is aligned with near-term market opportunities in the distributed generation sector to validate and advance the technology while paving the way for utility-scale natural gas (NG)- and coal-derived synthesis gas-fueled applications via progressively larger system demonstrations. The present study represents a part of a series of system evaluations being carried out at NETL to aid in prioritizing technological advances along research pathways to the realization of utility-scale SOFC systems, a transformational goal of the fuel cell program. In particular, the system performance of utility-scale NG fuel cell (NGFC) systems with and without carbon dioxide (CO2) capture is presented. The NGFC system analyzed features an external auto-thermal reformer (ATR) feeding the fuel to the SOFC system consisting of planar anode-supported SOFC with separated anode and cathode off-gas streams. In systems with CO2 capture, an air separation unit (ASU) is used to provide the oxygen for the ATR and for the combustion of unutilized fuel in the SOFC anode exhaust along with a CO2 purification unit to provide a nearly pure CO2 stream suitable for transport for usage in enhanced oil recovery (EOR) operations or for storage in underground saline formations. Remaining thermal energy in the exhaust gases is recovered in a bottoming steam Rankine cycle while supplying any process heat requirements. A reduced order model (ROM) developed at the Pacific Northwest National Laboratory (PNNL) is used to predict the SOFC performance. The ROM, while being computationally effective for system studies, provides other detailed information about the state of the stack, such as the internal temperature gradient, generally not available from simple performance models often used to represent the SOFC. Such additional information can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall system reliability. The NGFC system performance was analyzed by varying salient system parameters, including the percent of internal (to the SOFC module) NG reformation—ranging from 0 to 100%—fuel utilization, and current density. The impact of advances in underlying SOFC technology on electrical performance was also explored.

Numerical models for design and optimization of fuel cell-based power generation systems require an accurate representation of the SOFC stack performance over a wide range of operating conditions. Response surface techniques were used with detailed SOFC stack model results to create a computationally efficient reduced order model (ROM) of the stack that retains desirable information about its internal state, which can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall reliability. A tool was developed to randomly sample selected input parameters, obtain stack solutions for these sampled cases, perform regression to obtain response surfaces for stack performance and other metrics of interest, and export the response surfaces as a ROM. The ROM was then successfully implemented in an Aspen Plus® system model for a natural gas fuel cell (NGFC) power system. Additional work to characterize the ROM’s approximation error is ongoing.

The thermal, electrical, and fluid flow fields associated with a Siemens Power Generation Inc., Stationary Fuel Cells, flattened tubular high power density (HPD) solid oxide fuel cell (SOFC) were investigated comprehensively in a previous study. The present computational investigation is the subsequent part of an ongoing numerical pursuit at Siemens of an optimized cell geometry, commercialization of SOFC technology being the ultimate objective. A Delta type HPD cell featuring eight air channels was investigated and compared with a flattened tubular HPD cell. The computational models were developed using the commercial computational fluid dynamics software FLUENT 6.2 along with its SOFC user defined routine to model the electrochemical effects. The SOFC model parameters were derived from experimental data. The cathode, the anode, and the interconnection layers of the cell were resolved in the model and all modes of heat transfer, conduction, convection, and radiation were included. The resulting electrical performance and the thermal hydraulic characteristics of the cells for fully reformed natural gas fuel flow (reformed external to the cell) are presented and discussed. It was clear from these studies that the Delta HPD cell has distinct advantages over the flattened HPD cell in terms of system electrical performance as well as power density.

The thermal, electrical, and fluid flow fields associated with a Siemens Power Generation Inc., Stationary Fuel Cells, flattened tubular high power density (HPD) solid oxide fuel cell (SOFC) were investigated comprehensively in a previous study. The present computational investigation is the subsequent part of an ongoing numerical pursuit at Siemens of an optimized cell geometry, commercialization of SOFC technology being the ultimate objective. A Delta type HPD cell featuring eight air channels was investigated and compared with a flattened tubular HPD cell. The computational models were developed using the commercial computational fluid dynamics software FLUENT 6.2 along with its SOFC user defined routine to model the electrochemical effects. The SOFC model parameters were derived from experimental data. The cathode, the anode, and the interconnection layers of the cell were resolved in the model and all modes of heat transfer, conduction, convection, and radiation were included. The resulting electrical performance and the thermal hydraulic characteristics of the cells for fully reformed natural gas fuel flow (reformed external to the cell) are presented and discussed. It was clear from these studies that the Delta HPD cell has distinct advantages over the flattened HPD cell in terms of system electrical performance as well as power density.