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A multi-stack module consisting of a number of stacks connected in series and parallel serves as a basis for installation of MW-scale vanadium flow battery system in grid storage applications. Due to the existence of stack-to-stack variation in resistance, the module performance can be notably limited by an inappropriate module layout that magnifies the impact of stack resistance variation through series and parallel connections. To understand the layout effect on performance, an in-depth investigation is conducted for an eight-stack 250 kW module in this study. Based on experimental measurements, the correlation of module layout to performance is firstly revealed on both the 250 kW module and a laboratory mini-module. Subsequently, 35 different layouts are specified for the 250 kW module and their performance is fully evaluated by means of development of dynamic models for the module. Simulation results prove that the module charging capacity can be effectively improved by grouping stacks with similar resistances into the same branch and be further promoted by optimizing the flow rate for the stack with the largest resistance. The present study offers not only mechanistic insights into the importance of module layout but a cost-effective way to evaluate the module performance as well.

We presented a new method to measure the topological charge (TC) of the vortex beam (VB) by use a Shack-Hartmann wavefront sensor with sector microlens array (SMLA). The SMLA is circularly symmetric, which perfectly corresponds to helical phase and ring intensity of the VB. On the focal plane, there are spot array with circular distribution due to the special arrangement of the SMLA. In this letter, we also analyzed the error, and concluded that the error of the outer ring is smaller. As a result, we only employed the data of the outermost ring. This method easily can obtain the sign and magnitude of the TC by calculating offset direction and offset of the spots respectively. The simulation results show that our method can determine large TCs and has high accuracy. While this method has a simple structure and can be used in optical communications in the future.

WANs are often over-provisioned to accommodate worst-case operating conditions, with many links typically running at only around 30% capacity. In this paper, we show that in-network congestion management can play an important role in increasing network utilization. To mitigate the effects of in-network congestion caused by rapid variations in traffic demand, we propose using high-frequency traffic control (HFTraC) algorithms that exchange real-time flow rate and buffer occupancy information between routers to dynamically coordinate their link-service rates. We show that the design of such dynamic link-service rate policies can be cast as a distributed optimal control problem that allows us to systematically explore an enlarged design space of in-network congestion management algorithms. This also provides a means of quantitatively comparing different controller architectures: we show, perhaps surprisingly, that centralized control is not always better. We implement and evaluate HFTraC in the face of rapidly varying UDP and TCP flows and in combination with AQM algorithms. Using a custom experimental testbed, a Mininet emulator, and a production WAN, we show that HFTraC leads to up to 66% decreases in packet loss rates at high link utilizations as compared to FIFO policies.

During the operation of vanadium redox flow battery, the cell stack can suffer from electrolyte leakage and material failure that significantly affect the overall performance of the battery, provided that the stack is improperly designed and assembled. In order to manufacture more reliable battery stacks without undergoing electrolyte leakage and mechanical failure, the stress distributions on all key components of the stack need to be known. In this study, three-dimensional mechanical models are developed to perform simulation analyses on stress distribution for the cell stacks. Stress distributions on key cell components under specified sealing gasket designs, assembling forces and number of cells in a stack are investigated for the single cell and multi-cell stacks, while potential material failure and damage for the stack components are also analyzed in accordance with maximum stress criterion and von Mises yield criterion depending on the material of the components. Simulations results successfully demonstrate the stress distribution and magnitude in specified stack design and assembly condition, and highlight the importance of mechanical analyses in developing flow battery stacks with superior sealing and mechanical performance for long-term use.

Multipath TCP (MPTCP) can improve overall throughput of an end-to-end connection by leveraging different network paths. However, the heterogeneity of these paths can significantly hamper MPTCP’s performance. In this paper, we propose to send acknowledgments (ACKs) along the lowest-latency path. This can help improve the performance of MPTCP when subflow throughput is constrained by packet loss by reacting to loss events faster. An active probing module is also developed to dynamically select the lowest-latency path against the potential change of path condition. Experiments demonstrate that overall throughput improvement generally ranges from 10% to 50%.

Collaborative filtering (CF) is among the most effective techniques for recommendations. However, it suffers from data sparsity and cold-start issue. One solution is to incorporate the side information and the other is to learn knowledge from relevant domains. In this paper, we consider both aspects and propose a generic deep transfer collaborative filtering (DTCF) architecture, which integrates collective matrix factorization and deep transfer learning. We exhibit one instantiation of our architecture by employing non-negative matrix tri-factorization and stacked denoising autoencoder (SDAE) in both source and target domains. Deep learning copes with both the ratings’ statistic characteristics and the side information to generate effective latent representations. Matrix tri-factorization produces private latent factors linked with per SDAE and common latent factors connected with different domains. Extensive experimental results on real datasets exhibit a superiority of our approach in comparison to state-of-the-art works.

Full commercialization of vanadium flow batteries requires a high current density operation. However, this can be only realized when associated large polarizations of the cell are properly reduced. Of all the cell components, the porous electrode plays a critical role in determining cell polarizations since it directly relates to each of the polarizations. Despite that, an in-depth understanding of electrode compression impact on polarizations of a flow cell is still limited in literature. In this work, a quantitatively experimental study to unveil the electrode compression impact on each of the polarizations as well as the performance of a vanadium flow cell is conducted by employing a symmetric cell configuration. Four different compression ratios are investigated by both ex-situ characterizations and in-situ symmetric cell tests, which successfully reveal its influence on activation, ohmic and concentration polarizations at varied operating current densities. Charge-discharge cycling tests further prove the significance of electrode compression to both efficiency and discharge capacity, while also delivering an optimal compression ratio for the investigated flow cell. Such a quantitative analysis not only promotes a deep understanding of the importance of electrode compression to cell performance, but is also of vital importance for stack design and optimization in practice.

The crosstalk of orbital angular momentum（OAM）modes is one of the most important issues for free-space optical (FSO) communication. We theoretically derive a crosstalk model for Laguerre-Gaussian (LG) vortex beams propagating in turbulent atmosphere. The calculated crosstalk of different OAM modes in different turbulence by analytical expression is consistent with experimental measurements. Both theoretical and experimental results reveal that the crosstalk of high order LG vortex beams is more obvious in atmospheric turbulence. Different from the numerical calculation of the integral expression of the previous studies, this analytical expression can directly and quantitatively characterize the crosstalk and the law of different topological charges in vortex beams. Based on this analytical expression, the crosstalk widths of vortex beams with different topological charges can be calculated accurately, so that the optimal sets of OAM modes can be found more easily under each atmospheric turbulence condition.

Flow batteries are being increasingly deployed in grid-scale energy storage applications. However, long-term operation of flow batteries still suffers from a different extent of capacity decay. While the effects of ion diffusion and side reactions on capacity degradation have been identified and further minimized by improvement in materials, the mechanism of volumetric transfer and its influence in capacity still receive insufficient attentions that impedes further capacity optimizations for flow batteries. In order to gain an in-depth understanding of volumetric transfer mechanism in flow batteries, six different types of flow batteries are adopted in this study and further classified in accordance with electrolyte viscosities for investigations. Experimental results show that a net volumetric transfer in a conventional flow battery highly depends on viscosity values of the two half-cell electrolytes and is virtually towards the half-cell possessing a smaller electrolyte viscosity. For flow batteries with a mixed electrolyte in both half-cells, moreover, cycling tests further demonstrate a zero net transfer under similar viscosity measurements of both half-cell electrolytes. Unraveling the viscosity impact on volumetric transfer is greatly beneficial to facilitate deeper understandings of transport phenomena in flow batteries, which can contribute to realize long-term flow battery operation with a superior capacity retention.

Several cloud or data-parallel applications involve coflow scheduling, which controls a set of flows under the same semantic meaning with a common goal. Due to such common goal, optimizing each flow using the standard flow scheduling approaches does not necessarily lead to good coflow performance. Therefore, numerous methods and systems are proposed to focus on coflow scheduling problem.However, the current coflow scheduling designs are based on simple heuristics or observations. The absence of the optimum makes it hard to adjudge their absolute effectiveness. In this work, we derive the optimal solution to the coflow deadline satisfaction problem (CDS), which maximizes the number of satisfied coflow deadlines, from a mixed integer linear program formulation.We further show that CDS is not only NP-hard to solve but also intractable to approximate with a fixed approximation ratio (unless P=NP). As such, the use of heuristics is justified. We then develop optimization-based methods to approach the problem offline and online. The proposed methods are simulated and compared against the optimum, along with some state-of-the-art designs, and the results suggest that our methods are much closer to the optimum than the existing ones, especially when we have more room to schedule.

This paper analyzes fast adaptive traffic engineering from a feedback control perspective. We provide a model that characterizes the system parameters' effects on the performance of the dynamic routing system. This allows quantitative analysis of adaptive traffic engineering control laws and its design parameter choices. We then specialize the general framework in two representative network topologies and derive the stability conditions for their dynamic routing systems. Experiments are carried out to compare against our theoretical predictions considering two forms of adaptive traffic engineering control law as examples. Together they provide systematic insights on the relations among several network factors and the intrinsic tradeoff among different network control objectives.

In this paper we propose a platform that optimizes the available end-to-end throughput in real time through overlay networks. With the knowledge the network topology and conditions, it strives to achieve the optimal end-to-end throughput by exploring the last-mile diversity. It allows the flexible and responsive per-end-user selection of the edge node for the overlay networks, and thus can fast recover from network failures and performance degradation. We present our design of the end-to-end throughput optimization system with detailed discussion of each component including dynamic routing engine, performance monitor and information exchange. Our experimental results from a real-world deployment show that compared to the performance-oblivious routing, it not only brings up to 5 times throughput gains in the presence of 0.05% loss, but also improves 20% throughput when facing delay increase in the original path.

We present HALO, the first link-state routing solution with hop-by-hop packet forwarding that minimizes the cost of carrying traffic through packet-switched networks. At each node $u$ , for every other node $t$ , the algorithm independently and iteratively updates the fraction of traffic destined to $t$ that leaves $u$ on each of its outgoing links. At each iteration, the updates are calculated based on the shortest path to each destination as determined by the marginal costs of the network's links. The marginal link costs used to find the shortest paths are in turn obtained from link-state updates that are flooded through the network after each iteration. For stationary input traffic, we prove that HALO converges to the routing assignment that minimizes the cost of the network. Furthermore, we observe that our technique is adaptive, automatically converging to the new optimal routing assignment for quasi-static network changes. We also report numerical and experimental evaluations to confirm our theoretical predictions, explore additional aspects of the solution, and outline a proof-of-concept implementation of HALO.

Hand posture recognition (HPR) is quite a challenging task, due to both the difficulty in detecting and tracking hands with normal cameras and the limitations of traditional manually selected features. In this article, we propose a two-stage HPR system for Sign Language Recognition using a Kinect sensor. In the first stage, we propose an effective algorithm to implement hand detection and tracking. The algorithm incorporates both color and depth information, without specific requirements on uniform-colored or stable background. It can handle the situations in which hands are very close to other parts of the body or hands are not the nearest objects to the camera and allows for occlusion of hands caused by faces or other hands. In the second stage, we apply deep neural networks (DNNs) to automatically learn features from hand posture images that are insensitive to movement, scaling, and rotation. Experiments verify that the proposed system works quickly and accurately and achieves a recognition accuracy as high as 98.12%.

In vanadium redox flow batteries (VFB), the power of the battery is determined by the number of cells in the stack. Serial and parallel layouts are commonly adopted interactively to suit the designed power demand. The bipolar stack design inevitably introduces shunt currents bypassing into the common manifolds in the stack and thereby resulting in a parasitic loss of power and energy. During standby, shunt current and its associated internal discharge reactions can generate heat and increase stack temperature, potentially leading to thermal precipitation in the positive half-cell. This study aims to investigate the effect of shunt current on stack efficiency and temperature variation during standby periods for a 40-cell stack. Dynamic models based on mass balance, energy balance and electrical circuit are developed for simulations and the results provide an insight into stack performance that will aid in optimising stack design and suitable cooling strategies for the VFB.

Many network flows nowadays, especially in a data center environment, have associated deadlines by which they must be fully transmitted. Nevertheless, traditional transport protocols such as TCP, focus on concepts like throughput and fairness, and do not aim to satisfy flow deadlines. Motivated by this limitation, several alternative transport designs and solutions have been recently proposed. These approaches generally achieve a better performance in terms of the number of satisfied deadlines and are usually built upon various heuristics. In contrast to these previous works, this article approaches the problem directly from an optimization perspective. We first prove that the problem belongs to the class of NP-hard problems that do not even admit a constant ratio approximation solution (unless P=NP), and formulate it as a mixed integer-linear optimization program. Then, using linear programming approximations, we further develop offline and online optimization-based rate control algorithms to approach the problem. Flow-level simulation results indicate that the proposed algorithms can be near-optimal, and hence they can be served as benchmarks against which other solutions to this problem can be evaluated. We additionally performed simulations incorporating such real network features as deployment delays and packet-level granularity to evaluate the performance of the proposed algorithms in a more realistic environment.

Binary data in 1T1C or 2T2C non-volatile ferroelectric random access memories, which are represented by the polarization charges of switching and non-switching events, are retrieved when a reading current pulse exceeds the sense amplifier threshold for discrimination of nonswitching pulses, and a reset pulse is required after the destructive readout. Downscaling the dimensions of such memory cells reduces the measurable polarization charge proportional to the capacitor area, and data are no longer detected reliably in high-density memories. The nondestructive readout of the binary information is possible from the high- and low-conductance bipolar switching of a ferroelectric diode under two opposite poling fields, where the direction of the diode effect switches with polarization reversal. Our study of BiFeO3 thin-film capacitors shows measured polarization-modulated diode currents for encoding information within high-density memories. We used two in-plane nano-electrodes fabricated on the film surface in gaps of a few tens of nanometers. As an in-plane field is applied antiparallel to the domain orientation above a coercive field, the partial domains near the film surface layer are switched firstly to form conductive charged walls with respect to the underlying unswitched bulk matrix, so that we can observed an “on” current from current-voltage loops. As the switching field is high enough, the underlying domains throughout the whole film thickness are switched. In this case, there was no charged domain wall, and thus, we observed an “off” current. Both “on” and “off” currents with the ratio of 100 are stable over laboratory time with write cycles larger than 2×105 and write time as short as 10 ns, which provide the proof of ferro-resistive switching and independent adjustments of ferroelectricity and conductivity in a single-phase ferroelectric in promotion of the integration density of the memory with high performance.

We propose high-frequency traffic control (HFTraC), a rate control scheme that coordinates the transmission rates and buffer utilizations in routers network-wide at fast timescale. HFTraC can effectively deal with traffic demand fluctuation by utilizing available buffer space in routers network-wide, and therefore lead to significant performance improvement in terms of tradeoff between bandwidth utilization and queueing delay. We further note that the performance limit of HFTraC is determined by the network architecture used to implement it. We provide trace-driven evaluation of the performance of HFTraC implemented in the proposed architectures that vary from fully centralized to completely decentralized.

A ferroelectric-resistive random access memory consisting of a conductive BiFeO3 epitaxial thin film with a unipolar diode current modulated by electric polarization orientation is reported. This device has a memory that lasts for months, a sufficiently high on current and on/ off ratio to permit ordinary sense amplifiers to measure "1" or " 0", and is fully compatible with complementary metal- oxide semiconductor processing.

This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones.

Software defined networking (SDN) establishes a separation between the control plane and the data plane, allowing network intelligence and state to be centralized -- in this way the underlying network infrastructure is hidden from the applications. This is in stark contrast to existing distributed networking architectures, in which the control and data planes are vertically combined, and network intelligence and state, as well as applications, are distributed throughout the network. It is also conceivable that some elements of network functionality be implemented in a centralized manner via SDN, and that other components be implemented in a distributed manner. Further, distributed implementations can have varying levels of decentralization, ranging from myopic (in which local algorithms use only local information) to coordinated (in which local algorithms use both local and shared information). In this way, myopic distributed architectures and fully centralized architectures lie at the two extremes of a broader hybrid software defined networking (HySDN) design space.Using admission control as a case study, we leverage recent developments in distributed optimal control to provide network designers with tools to quantitatively compare different architectures, allowing them to explore the relevant HySDN design space in a principled manner. In particular, we assume that routing is done at a slower timescale, and seek to stabilize the network around a desirable operating point despite physical communication delays imposed by the network and rapidly varying traffic demand. We show that there exist scenarios for which one architecture allows for fundamentally better performance than another, thus highlighting the usefulness of the approach proposed in this paper.

Middleboxes are special network devices that perform various functions such as enabling security and efficiency. SDN-based routing approaches in networks with middleboxes need to address resource constraints, such as memory in the switches and processing power of middleboxes, and traversal constraint where a flow must visit the required middleboxes in a specific order. In this work we propose a solution based on MultiPoint-To-Point Trees (MPTPT) for routing traffic in SDN-enabled networks with consolidated middleboxes. We show both theoretically and via simulations that our solution significantly reduces the number of routing rules in the switches, while guaranteeing optimum throughput and meeting processing requirements. Additionally, the underlying algorithm has low complexity making it suitable in dynamic network environment.

It has been proved theoretically that a network with heterogeneous congestion control algorithms that react to different congestion signals can have multiple equilibrium points. In this paper, we demonstrate this experimentally using TCP Reno and Vegas/FAST. We also show that any desired inter-protocol fairness is in principle achievable by an appropriate choice of Vegas/FAST parameter, and that intra-protocol fairness among flows within each protocol is unaffected by the presence of the other protocol except for a reduction in effective link capacities. Dummynet experiments and ns-2 simulations are presented to verify these results.

A recently proposed active queue management, CHOKe, is stateless, simple to implement, yet surprisingly effective in protecting TCP from UDP flows. We present an equilibrium model of TCP/CHOKe. We prove that, provided the number of TCP flows is large, the UDP bandwidth share peaks at (e+1)/sup -1/=0.269 when UDP input rate is slightly larger than link capacity, and drops to zero as UDP input rate tends to infinity. We clarify the spatial characteristics of the leaky buffer under CHOKe that produce this throughput behavior. Specifically, we prove that, as UDP input rate increases, even though the total number of UDP packets in the queue increases, their spatial distribution becomes more and more concentrated near the tail of the queue, and drops rapidly to zero toward the head of the queue. In stark contrast to a nonleaky FIFO buffer where UDP bandwidth shares would approach 1 as its input rate increases without bound, under CHOKe, UDP simultaneously maintains a large number of packets in the queue and receives a vanishingly small bandwidth share, the mechanism through which CHOKe protects TCP flows.

A recently proposed active queue management, CHOKe, aims to protect TCP from UDP flows. Simulations have shown that as UDP rate increases, its bandwidth share initially rises but eventually drops. We derive an approximate model of CHOKe and show that, provided the number of TCP flows is large, the UDP bandwidth share peaks at (e+1) -1 = 0.269 when the UDP input rate is slightly larger than the link capacity, and drops to zero as UDP input rate tends to infinity, regardless of the TCP algorithm.

Active end-to-end available bandwidth estimation is intrusive, expensive, inaccurate, and does not work well with bursty cross traffic or on high capacity links. Yet, it is important for designing high performant networked systems, improving network protocols, building distributed systems, and improving application performance. In this paper, we present minProbe which addresses unsolved issues that have plagued available bandwidth estimation. As a middlebox, minProbe measures and estimates available bandwidth with high-fidelity, minimal-cost, and in userspace; thus, enabling cheaper (virtually no overhead) and more accurate available bandwidth estimation. MinProbe performs accurately on high capacity networks up to 10 Gbps and with bursty cross traffic. We evaluated the performance and accuracy of minProbe over a wide-area network, the National Lambda Rail (NLR), and within our own network testbed. Results indicate that minProbe can estimate available bandwidth with error typically no more than 0.4 Gbps in a 10 Gbps network.

We consider the network-layer problem of avoiding congestion while reconfiguring the routing paths. We formulate a flow-based and a switch-based model. For the flow-based model, we demonstrate that an optimal sequence of minimum update steps could always be found when the dependency graph is acyclic. For the switch-based model, we find a way to translate a feasible flow-based sequence to a feasible switch-based sequence subject to a tree topology constraint on the routing paths.

ZrO2 thin film with suitable dielectric constant for MFIS FET's application was prepared by novel metal-organic-decomposition (MOD) method. The dielectric constants of the thin film laid between 10 and 30 and increased with the development of the crystallinity. The magnitude of the leakage current of the thin film with thickness of 27nm and 35nm was 1E-5 and 1E-7 A/cm2 respectively when 5V bias voltage was applied. The C-V characteristics show a memory window of 2.5V for a sweep voltage from -5V to +5V. It indicates that the thin film could satisfy the requirement of MFIS structure.

PbZr0.52Ti0.48O3 thin film prepared by metal-organic decomposition method was chemically etched by utilizing HF/HNO3 solution. Typical semiconductor processes were used to pattern the film. The dependence of the conformity of pattern transfer on the microstructure of the film was studied. The results showed that the etching rates were different between the islands of the grains and the surrounding areas within the film. The film with small grains is favored for pattern transfer of fidelity. The dimension of the islands of grains contributes greatly to the tolerance of patterned features. Tolerance of 2 μm has been achieved to fulfill the need of usage in microelectromechanical systems.

In the network layer, an internet service provider controls the traffic across an autonomous system by load balancing via traffic engineering and by varying the offered traffic of the users via feedback signals. In the transport layer, users send traffic into the network using the TCP protocol, which adjusts offered traffic according to the received feedback. We investigate how feedback and current traffic engineering practice interact with congestion control under the network utility maximization framework. We show that the current interaction is stable, increases network utility, but does not necessarily improve the traffic engineering objective. The mismatch in outcome and incentives prompt us for a more holistic view using game theory. With suitable modification of the feedback, we show that the interaction converges to a socially optimal solution for users running either primal or dual algorithms. We further show that the results hold even when traffic engineering is performed at any irregular intervals. More generally, we show via heterogeneous feedback the same optimality result for a mix of users running primal and dual algorithms.

The development of open electricity markets has led to a decoupling between the market clearing procedure that defines the power dispatch and the security analysis that enforces predefined stability margins. This gap results in market inefficiencies introduced by corrections to the market solution to accommodate stability requirements. In this paper we present an optimal power flow formulation that aims to close this gap. First, we show that the pseudospectral abscissa can be used as a unifying stability measure to characterize both poorly damped oscillations and voltage stability margins. This leads to two novel optimization problems that can find operation points which minimize oscillations or maximize voltage stability margins, and make apparent the implicit tradeoff between these two stability requirements. Finally, we combine these optimization problems to generate a dynamics-aware optimal power flow formulation that provides voltage as well as small signal stability guarantees.

Current intra-domain routing protocols like OSPF and IS-IS use link-state routing algorithms with hop-by-hop forwarding that sacrifice traffic engineering performance for ease of implementation and management. Though optimal traffic engineering algorithms exist, they tend to be either not link-state algorithms or to require source routing - characteristics that make them difficult to implement. As the focus of this paper, we introduce HALO, the first optimal link-state routing algorithm with hop-by-hop forwarding, where link weights can be calculated locally. Furthermore, our solution can adapt to changing traffic patterns automatically. The optimality of the algorithm is proved theoretically and also verified numerically.

This paper examines synchronization of computer clocks connected via a data network and proposes a skewless algorithm to synchronize them. Unlike existing solutions, which either estimate and compensate the frequency difference (skew) among clocks or introduce offset corrections that can generate jitter and possibly even backward jumps, our algorithm achieves synchronization without these problems. We first analyze the convergence property of the algorithm and provide necessary and sufficient conditions on the parameters to guarantee synchronization. We then implement our solution on a cluster of IBM BladeCenter servers running Linux and study its performance. In particular, both analytically and experimentally, we show that our algorithm can converge in the presence of timing loops. This marks a clear contrast with current standards such as NTP and PTP, where timing loops are specifically avoided. Furthermore, timing loops can even be beneficial in our scheme. For example, it is demonstrated that highly connected subnetworks can collectively outperform individual clients when the time source has large jitter. It is also experimentally demonstrated that our algorithm outperforms other well-established software-based solutions such as the NTPv4 and IBM Coordinated Cluster Time (IBM CCT)., to appear in ICNP13

Peer-to-peer (P2P) file distribution is a scalable way to disseminate content to a wide audience. For a P2P network, one fundamental performance metric is the average time needed to deliver a certain file to all peers, which in general depends on the topology of the network and the scheduling of transmissions. Despite its apparent importance, how to minimize average finish time remains an open question even for a fully- connected network. This is mainly due to the analytical challenges that come with the combinatorial structures of the problem. In this paper, by using the water-filling technique, we determine how each peer should use its capacity to sequentially minimize the file download times in an upload-constrained P2P network. Furthermore, it is argued that this scheduling also potentially minimizes average finish time for the network. This result not only provides fundamental insight to scheduling in such P2P systems, but also can serve as a benchmark to evaluate practical algorithms and illustrate the scalability of P2P networks.

Peer-to-peer (P2P) file distribution is a scalable way to disseminate content to a wide audience. This paper presents an algorithm by which download times are sequentially minimized; that is, the first peer's download time is minimized, and subsequent peers' times are minimized conditional on their predecessors' times being minimized. This objective gives robustness to the file distribution in the case that the network may be partitioned. It is also an important step towards the natural objective of minimizing the average download time, which is made challenging by the combinatorial structure of the problem. This optimality result not only provides fundamental insight to scheduling in such P2P systems, but also can serve as a benchmark to evaluate practical algorithms and illustrate the scalability of P2P networks.

This paper reverse engineers backoff-based random-access MAC protocols in ad-hoc networks. We show that the contention resolution algorithm in such protocols is implicitly participating in a non-cooperative game. Each link attempts to maximize a selfish local utility function, whose exact shape is reverse engineered from the protocol description, through a stochastic subgradient method in which the link updates its persistence probability based on its transmission success or failure. We prove that existence of a Nash equilibrium is guaranteed in general. The minimum amount of backoff aggressiveness needed for uniqueness of Nash equilibrium and convergence of the best response strategy are established as a function of user density. Convergence properties and connection with the best response strategy are also proved for variants of the stochastic-subgradient-based dynamics of the game. Together with known results in reverse engineering TCP and BGP, this paper completes the recent efforts in reverse engineering the main protocols in layers 2-4.

A novel 2D nanometer edge contact type cell for phase change RAM is manufactured, in which the active area can be controlled mainly by the thickness of both bottom electrode film and the GST film. The high resistive GST is indispensable to minimize the writing current and threshold voltage of PCRAM. The GST resistivity can be increased effectively by doping nitrogen and the nitrogen-doped film is first used in the novel 2D nanometer structure successfully for reducing the threshold voltage application. It is found the phase change from FCC to hexagonal structure is suppressed by nitrogen doping, while 3 stable resistance states is first found in the resistivity-annealling temperature curve for the film by sputtering method, which might be used in multilevel PCRAM.

This paper studies how to design a stabilizing AQM in supporting TCP (Transmission Control Protocol) with arbitrary delays. For the well-known AIMD (Additive Increase Multiplicative Decrease) dynamic model of TCP, our study shows that we can compensate for arbitrary delays explicitly by applying a modified virtual queue dynamics that makes the equilibrium queuing delay zero. This study also verifies that a simplified AQM AVQ (Adaptive Virtual Queue) is the state-feedback control for the AIMD model based on the virtual queue dynamics.

The design of a general-purpose parallel interface based on CPLD is described. As a result, system design can be simplified by using a parallel interface circuit that is composed of CPLDs in an embedded system. Flexibility is another advantage. The module method has been used in the design, so the design procedure becomes simpler and more efficient. It also has reusable performance.

Path loss for non-line-of-sight (NLOS) propagation in urban streets with a low base station antenna is simulated. Typical path loss curves are shown to be characterized by three,slopes and two break points. The path loss exponents for each part at different frequency are calculated. The frequency and the road width's effects on path loss are discussed. An explanation for the results is also included in this paper.

Time resolution of multipath delay profiles measured by using the autocorrelation of a pseudonoise (PN) code sequence is generally limited by the chip rate of the PN code sequence. In this paper, we proposed a simple method to improve the time resolution of delay profiles measured by the PN correlation method. The effectiveness of this method is demonstrated by an indoor wireless propagation experiment using circularly polarized wave at 900 MHz, and the number of multipath is given unambiguously.

7th International ASIC Conference Organized by SSCS-Shanghai and Fudan University SSCS-Shanghai and Fudan University jointly organized the 7th International ASIC Conference (ASICON), which took place on 26-29 October, 2007 in Guilin, China. Held seven times since 1994 and sponsored by IEEE, the Institution of Engineering & Technology (IET), and the Chinese Institute of Electronics (CIE), the conference provides a forum for researchers, students, and engineers working in the fields of SOC/VLSI circuit design.

The self‐aligned titanium silicide device technology has been studied by using NH3 plasma assisted thermal annealing and ion implant through titanium metal or silicide film. Enhanced surface nitridation of titanium by activated species suppresses lateral silicide growth and oxide contamination. NH3 plasma assisted annealing can be used as an effective method to form TiSi2 and activate implanted dopant. P+N junction and P channel metal–oxide–semiconductor field‐effect transistor can be produced by boron implant through Ti metal or its silicide and the NH3 plasma assisted thermal annealing.