AIB-OR: Improving Onion Routing Circuit Construction Using Anonymous Identity-Based Cryptosystems

The rapid growth of Internet applications has made communication anonymity an increasingly important or even indispensable security requirement. Onion routing has been employed as an infrastructure for anonymous communication over a public network, which provides anonymous connections that are strongly resistant to both eavesdropping and traffic analysis. However, existing onion routing protocols usually exhibit poor performance due to repeated encryption operations. In this paper, we first present an improved anonymous multi-receiver identity-based encryption (AMRIBE) scheme, and an improved identity-based one-way anonymous key agreement (IBOWAKE) protocol. We then propose an efficient onion routing protocol named AIB-OR that provides provable security and strong anonymity. Our main approach is to use our improved AMRIBE scheme and improved IBOWAKE protocol in onion routing circuit construction. Compared with other onion routing protocols, AIB-OR provides high efficiency, scalability, strong anonymity and fault tolerance. Performance measurements from a prototype implementation show that our proposed AIB-OR can achieve high bandwidths and low latencies when deployed over the Internet.     

A neural circuit model for changing the amount of information maintained in short-term memory depending on stimuli relationships

We propose a neural circuit model of changes in amount of information maintained in short-term memory depending on stimuli relationships. The relationships between stimuli are represented by the synchronous firings of overlapping neuronal groups for semantically related stimuli and the excitatory mutual connections for semantically unrelated but simultaneously presented stimuli. We conduct computer simulations to confirm our proposed neural circuit model. The resultant numbers of stored informational input patterns are almost consistent with the maximum numbers in the psychological experiments for both semantically related and unrelated stimuli. This agreement with the psychological experiments suggests that the structure and informational representation of the proposed model are appropriate.     

A recursion model for cellular production/assembly systems

This article presents an efficient algorithm for applying the recursion modeling approach to describe the transient operation of cellular production/assembly systems that incorporate features such as finite buffers, job-shop routing, lot sequencing, and material handling. Tests evaluate the approximation method relative to number of machines at a station, capacity of input/output buffers, degree of balance among station processing times, and sequencing rule. Furthermore, the method is demonstrated in application to a hypothetical industrial setting that involves the assembly of electronic circuit cards in a facility composed of several cells. All tests indicate that the method gives accurate estimates of transient performance within reasonable runtime. In comparison with earlier recursion models, this research incorporates a number of new features (see list above), improves the accuracy of approximation, and facilitates implementation with a new, more efficient algorithm.     

Performance Evaluation of Deflection Routing in Optical IP Packet-Switched Networks

In previous papers [5,6], an optical switch architecture was proposed to handle variable-length packets such as IP datagrams, based on an AWG device to route packets and equipped with a fiber delay-line stage as optical input buffer. Unfortunately, extensive simulations of optical networks built with switches of this type showed that considerable buffering capability would be required in order to achieve acceptable performance. In this work, therefore, we studied the effectiveness of packet deflection as a mean for solving packet contentions on outputs of optical switches. Optical transport networks were simulated, evaluating the performance of packet deflection routing, based on a traffic model adherent to real IP traffic measurements. Full-mesh and wheel network topologies have been considered, comparing results to assess deflection effectiveness. Our simulation results show that deflection routing leads to satisfying performance even using buffers with limited size. Furthermore, the average delivery delay does not suffer heavy penalty from packet deflection, even under heavy traffic conditions.     

Circuit Model of Fano Resonance on Tetramers,Pentamers, and Broken Symmetry Pentamers

This paper presents the representation circuit model for Fano resonance of plasmonic nanoparticles in the optical domain. An intuitive explanation is provided for the physical nature of Fano resonance based on the three-level quantum system, and the Fano resonance effects of three basic nanoparticle arrangements, namely tetramer, pentamer, and symmetry broke pentamer are discussed. A coupling capacitor is calculated as an equivalent component in the proposed circuit model in order to describe the coupling effect between subradiant and superradiant mode in the Fano resonance. The circuit impedances of tetramer, pentamer, and broken symmetry pentamer are simulated, with resultant circuit models in agreement with the calculated results based on S-parameters.     

Influence of the first amplifier stage in MEA systems on extracellular signal shapes

Recording of extracellular signals with planar metal microelectrodes (ME) has already been presented more than 30 years ago. To date, microelectrode array (MEA) systems are able to measure extracellular signals at about 64 sites, simultaneously. This enables monitoring of electrical activity of many cells in a large area. The extracellular recording technique has become a widely used method for neurological, toxicological or pharmacological studies. It already proved its potential to supplement the classical methods in electrophysiology. The interpretation of the recorded signal shapes in order to extract electrophysiological meaningful data--however--is still under discussion. In this article, we analyse the preamplifier circuit for extracellular recording of cardiac myocyte signals. We use a circuit model for the cell-electrode contact including the first amplification stage. In test experiments, we observe different signal shapes, when different shunt resistors are introduced at the input of the preamplifier. According to the frequency spectra of the recordings, we evaluate the transfer function between the source signal and the readout signal. As a result of our studies, an optimum readout electronics for originally, preserved extracellular signal shapes is proposed. Our amplifier design will be most valuable, if the use of small microelectrodes with high input impedances for in vitro as well as for in vivo experiments is desired.     

A nonlinear autoregressive Volterra model of the Hodgkin–Huxley equations

We propose a new variant of Volterra-type model with a nonlinear auto-regressive (NAR) component that is a suitable framework for describing the process of AP generation by the neuron membrane potential, and we apply it to input-output data generated by the Hodgkin–Huxley (H–H) equations. Volterra models use a functional series expansion to describe the input-output relation for most nonlinear dynamic systems, and are applicable to a wide range of physiologic systems. It is difficult, however, to apply the Volterra methodology to the H–H model because is characterized by distinct subthreshold and suprathreshold dynamics. When threshold is crossed, an autonomous action potential (AP) is generated, the output becomes temporarily decoupled from the input, and the standard Volterra model fails. Therefore, in our framework, whenever membrane potential exceeds some threshold, it is taken as a second input to a dual-input Volterra model. This model correctly predicts membrane voltage deflection both within the subthreshold region and during APs. Moreover, the model naturally generates a post-AP afterpotential and refractory period. It is known that the H–H model converges to a limit cycle in response to a constant current injection. This behavior is correctly predicted by the proposed model, while the standard Volterra model is incapable of generating such limit cycle behavior. The inclusion of cross-kernels, which describe the nonlinear interactions between the exogenous and autoregressive inputs, is found to be absolutely necessary. The proposed model is general, non-parametric, and data-derived.     

Sequential and Parallel Meta-Heuristics for Solving the Single Row Routing Problem

The design of multi-layer printed circuit boards is vital in the construction of complex electronic systems. Wire routing is a crucial step in the overall design process, which can be decomposed into a number of single row routing (SRR) problems. This paper proposes an approach to solve the SRR problem based on parallel meta-heuristics. The development of this technique involves the design of an encoding strategy that allows all possible routings to be uniquely represented and the derivation of cost functions that maximizes the quality of the developed solutions. Further, parallelization of the proposed approach is attempted to improve the computational efficiency. The different stages of the development are backed by experiments to show the pros and cons of the sequential and parallel implementations.     

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.     

Graded,Dynamically Routable Information Processing with Synfire-Gated Synfire Chains

Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Recently experimental evidence has been presented suggesting that neural information is encoded and transferred in packets, i.e., in stereotypical, correlated spiking patterns of neural activity. Due to their relevance to coherent spiking, synfire chains are one of the main theoretical constructs that have been appealed to in order to describe coherent spiking and information transfer phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited the classical synfire chain’s ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by streaming input, processes the input, then makes a decision based on the processed information and shuts itself down.     

Crossed and Locked Quotes in a Multi-Market Simulation

Financial markets are often fragmented, introducing the possibility that quotes in identical securities may become crossed or locked. There are a number of theoretical explanations for the existence of crossed and locked quotes, including competition, simultaneous actions, inattentiveness, fee structure and market access. In this paper, we perform a simulation experiment designed to examine the effect of simple order routing procedures on the properties of a fragmented market consisting of a single security trading in two independent limit order books. The quotes in the two markets are connected solely by the routing decision of the market participants. We report on the health of the consolidated market as measured by the duration of crossed and locked states, as well as the spread and the volatility of transaction prices in the consolidated market. We aim to quantify exactly how the prevalence of order routing among a population of market participants affects properties of the consolidated market. Our model contributes to the zero-intelligence literature by treating order routing as an experimental variable. Additionally, we introduce a parsimonious heuristic for limit order routing, allowing us to study the effects of both market order routing and limit order routing. Our model refines intuition for the sometimes subtle relationships between the prevalence of order routing and various market measures. Our model also provides a benchmark for more complex agent-based models.     

Dynamic Source Routing Strategy for Two-Level Flows on Scale-Free Networks

Packets transmitting in real communication networks such as the Internet can be classified as time-sensitive or time-insensitive. To better support the real-time and time-insensitive applications, we propose a two-level flow traffic model in which packets are labeled as level-1 or level-2, and those with level-1 have higher priority to be transmitted. In order to enhance the traffic capacity of the two-level flow traffic model, we expand the global dynamic routing strategy and propose a new dynamic source routing which supports no routing-flaps, high traffic capacity, and diverse traffic flows. As shown in this paper, the proposed dynamic source routing can significantly enhance the traffic capacity and quality of time-sensitive applications compared with the global shortest path routing strategy.     

Equivalent Circuit Method Analysis of Graphene-Metamaterial (GM) Absorber

This paper presents an effective method to model and analyze graphene-metamaterial (GM) absorbers by using an equivalent circuit model. A reliable and closed formula to describe the absorption mechanism of the GM structure was derived from this approach. With the obtained expressions, the effect of the graphene chemical potential on the absorber’s resonance frequency is able to be predicted. In order to verify this proposed equivalent circuit method, an absorber consists of metamaterial and graphene was simulated and the physical mechanism was well explained. This method provides an effective way to analyze multilayered GM absorbers for the future.     

Modeling,analysis and simulation of ant-based network routing protocols

Using the metaphor of swarm intelligence, ant-based routing protocols deploy control packets that behave like ants to discover and optimize routes between pairs of nodes. These ant-based routing protocols provide an elegant, scalable solution to the routing problem for both wired and mobile ad hoc networks. The routing problem is highly nonlinear because the control packets alter the local routing tables as they are routed through the network. We mathematically map the local rules by which the routing tables are altered to the dynamics of the entire networks. Using dynamical systems theory, we map local protocol rules to full network performance, which helps us understand the impact of protocol parameters on network performance. In this paper, we systematically derive and analyze global models for simple ant-based routing protocols using both pheromone deposition and evaporation. In particular, we develop a stochastic model by modeling the probability density of ants over the network. The model is validated by comparing equilibrium pheromone levels produced by the global analysis to results obtained from simulation studies. We use both a Matlab simulation with ideal communications and a QualNet simulation with realistic communication models. Using these analytic and computational methods, we map out a complete phase diagram of network behavior over a small multipath network. We show the existence of both stable and unstable (inaccessible) routing solutions having varying properties of efficiency and redundancy depending upon the routing parameters. Finally, we apply these techniques to a larger 50-node network and show that the design principles acquired from studying the small model network extend to larger networks.     

Energy-aware routing considering load balancing for SDN: a minimum graph-based Ant Colony Optimization

Software-Defined Network (SDN) technology is a network management approach that facilitates a high level of programmability and centralized manageability. By leveraging the control and data plane separation, an energy-aware routing model could be easily implemented in the networks. In the present paper, we propose a two-phase SDN-based routing mechanism that aims at minimizing energy consumption while providing a certain level of QoS for the users’ flows and realizing the link load balancing. To reduce the network energy consumption, a minimum graph-based Ant Colony Optimization (ACO) approach is used in the first phase. It prunes and optimizes the network tree by turning unnecessary switches off and providing an energy-minimized sub-graph that is responsible for the network existing flows. In the second phase, an innovative weighted routing approach is developed that guarantees the QoS requirements of the incoming flows and routes them so that to balance the loads on the links. We validated our proposed approach by conducting extensive simulations on different traffic patterns and scenarios with different thresholds. The results indicate that the proposed routing method considerably minimizes the network energy consumption, especially for congested traffics with mice-type flows. It can provide effective link load balancing while satisfying the users’ QoS requirements.

     

Route Optimization for Mobile IP

Route Optimization has been designed within the IETF to ameliorate the problem of triangle routing, a routing artifact introduced by Mobile IP's requirement to route packets destined for a mobile node by way of its home network. In this article, we describe the current protocol specification for the Route Optimization protocol, concentrating on design decisions and justifications. Once the basic mechanisms are explained, we show how they are applied to enable foreign agents to offer smooth handoffs for mobile nodes, and describe the security operations that enable reliable operation of this handoff between foreign agents with which a mobile node has no pre-existing security relationship. This revised version was published online in August 2006 with corrections to the Cover Date.     

A cellular mechanism for prepulse inhibition

In prepulse inhibition (PPI), startle responses to sudden, unexpected stimuli are markedly attenuated if immediately preceded by a weak stimulus of almost any modality. This experimental paradigm exposes a potent inhibitory process, present in nervous systems from invertebrates to humans, that is widely considered to play an important role in reducing distraction during the processing of sensory input. The neural mechanisms mediating PPI are of considerable interest given evidence linking PPI deficits with some of the cognitive disorders of schizophrenia. Here, in the marine mollusk Tritonia diomedea, we describe a detailed cellular mechanism for PPI--a combination of presynaptic inhibition of startle afferent neurons together with distributed postsynaptic inhibition of several downstream interneuronal sites in the startle circuit.     

Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms

The organization of order picking operations is one of the most critical issues in warehouse management. In this paper, novel tabu search (TS) algorithms integrated with a novel clustering algorithm are proposed to solve the order batching and picker routing problems jointly for multiple-cross-aisle warehouse systems. A clustering algorithm that generates an initial solution for the TS algorithms is developed to provide fast and effective solutions to the order-batching problem. Unlike most common picker routing heuristics, we model the routing problem of pickers as a classical TSP and propose efficient Nearest Neighbor+Or-opt and Savings+2-Opt heuristics to meet the specific features for the problem. Various problem instances including the number of orders, weight of items, and picking coordinates are generated randomly, and detailed numerical experiments are carried out to evaluate the performances of the proposed methods. In conclusion, the TS algorithms come out to be the most efficient methods in terms of solution quality and computational efficiency.     

A logical circuit for the regulation of fission yeast growth modes

Growth of fission yeast at the ends of its cylindrical cells switches from a monopolar to a bipolar mode, before it ceases during mitosis and cell division. Here we assume that these growth modes correspond to three stable states of an underlying regulatory circuit, which is a relatively simple and to a large degree autonomous subsystem of an otherwise complex cellular control system. We develop a switch-like logical circuit based on three elements defined as binary variables. Effects of circuit variables on each other are expressed in terms of logical operations. We analyse this circuit for its behavior ("phenotypes") after removing single or multiple operations ("mutants"). Known fission yeast polarity mutants such as those defective in the switch to bipolar growth can be classified based on these predicted 'phenotypes'. Differences in growth patterns between daughter cells in different bipolar growth mutants are also predicted by the circuit model. The model presented here should provide a useful framework to guide future experiments into mechanisms of cellular polarity. This paper illustrates the usefulness of simple logical circuits to describe and dissect features of complex regulatory processes such as the fission yeast growth patterns in both wild type and mutant cells.