Infinite Capacity Research Articles

Open-circuit voltage photodetector architecture for infrared imagers

We theoretically and experimentally investigate the application of an open-circuit voltage photodetector (VocP) architecture for mid-wave infrared (MWIR, 3–5 μm) detection and imaging. In contrast to conventional reverse-bias (RB) operation of the diode, which generates a photocurrent that is proportional to the photon irradiance, we evaluate the potential of using unbiased diodes that generate an open-circuit voltage, VOC, under illumination. The predicted Noise Equivalent Differential Temperature (NEDT) of a VocP is inferior to conventional RB when we assume an infinite well capacity and fixed integration time, but the prediction reverses when the actual well capacity of a readout integrated circuit (ROIC) is taken into account. Therefore, for a focal plane array (FPA) with a ROIC, we predict superior NEDT for the VocP. To demonstrate this concept, we fabricated and tested a basic VocP unit-cell architecture by connecting the VOC anode of a MWIR photodiode to the gate of an n-type metal-oxide semiconductor transistor that is operated in sub-threshold. Very good agreement is obtained between the analytical model and the observed drain current of the transistor over three orders of photon irradiance (1015–1018 photons/sec-cm2). The decoupling of the diode photocurrent from the integration capacitor in the circuit leads to a lower dark current that allows for longer integration times and improved sensitivity. This potentially can have a great impact on the performance and functionality of FPAs, leading to FPAs with better NEDT at a higher operating temperature, wider dynamic range, and smaller pixel size leading to larger array formats.

Energy-efficient computation offloading strategy with tasks scheduling in edge computing

In mobile edge computing systems, the energy consumption and execution delay can be reduced dramatically by mobile edge computation offloading (MECO) . However, due to the limited computing capacity of edge cloud, an energy-efficient offloading strategy plays a significant role. In this paper, the offloading decision problem for multi-device edge computing systems based on time-division multiple access is studied. The scheduling of offloading devices at the edge cloud is considered when modelling the edge computing system. Then, the offloading decision problem is formulated as an energy consumption minimization problem with the constraint of latency tolerance. It is a mixed integer programming problem of NP-hardness. To address the problem, a Dynamic Programming-based Energy Saving Offloading (DPESO) algorithm is designed to obtain the offloading strategy including the offloading option, offloading sequence and transmission power. First, the MECO with infinite edge cloud capacity is solved by device classification and transmission power decision. Then, we sort and adjust the offloading devices to meet the latency tolerance for the MECO with finite edge cloud capacity. Finally, simulation results demonstrate that the DPESO algorithm achieves better energy efficiency than the baseline strategies and has good scalability.

Optimal Resource Allocation in Multihop Wireless Networks Relying on Energy Harvesting

In this letter, we propose a new backpressure-based optimal joint routing and congestion control scheme for wireless multihop networks operating solely on energy harvesting. Compared to previous works, we assume: i) different energy consumption for each commodity, and ii) energy is consumed when a node transmits, receives and produces traffic. We show that this requires infinite battery capacity for logarithmic utility functions and further improve the battery capacity computation. Finally, we show queue stability, while ensuring energy causality.

Physical Layer based Message Authentication with Secure Channel Codes

In this paper, we investigate physical (PHY) layer message authentication to combat adversaries with infinite computational capacity. Specifically, a PHY-layer authentication framework over a wiretap channel (W <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ; W <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) is proposed to achieve information theoretic security with the same key. We develop a theorem to reveal the requirements/conditions for the authentication framework to be information-theoretic secure for authenticating a polynomial number of messages in terms of n. Based on this theorem, we design an authentication protocol that can guarantee the security requirements, and prove its authentication rate can approach infinity when n goes to infinity. Furthermore, we design and implement a feasible and efficient message authentication protocol over binary symmetric wiretap channel (BSWC) by using Linear Feedback Shifting Register based (LFSR-based) hash functions and strong secure polar code. Through extensive simulations, it is demonstrated that the proposed protocol can achieve high authentication rate, with low time cost and authentication error rate.

BACKPRESSURE BASED TRAFFIC SIGNAL CONTROL CONSIDERING CAPACITY OF DOWNSTREAM LINKS

Congestion is a kind of expression of instability of traffic network. Traffic signal control keeping traffic network stable can reduce the congestion of urban traffic. In order to improve the efficiency of urban traffic network, this study proposes a decentralized traffic signal control strategy based on backpressure algorithm used in Wi-Fi mesh networks for packets routing. Backpressure based traffic signal control algorithm can stabilize urban traffic network and achieve maximum throughput. Based on original backpressure algorithm, the variant parameter and penalty function are considered to balance the queue differential and capacity of downstream links in urban traffic network. For each traffic phase of intersections, phase weight is computed using queue differential and capacity of downstream links, which fixed the deficiency of infinite queue capacity in original backpressure algorithm. It is proved that the extended backpressure traffic signal control algorithm can maintain stability of urban traffic network, and also can prevent queue spillback, so as to improve performance of whole traffic network. Simulations are carried out in Vissim using Vissim COM programming interface and Visual Studio development tools. Evaluation results illuminate that it can get better performance than the backpressure algorithm just based on queue length differential in average queue length and delay of traffic network.

Analysis of an M/PH/1 Retrial Queueing-Inventory System with Level Dependent Retrial Rate

We analyze a queueing-inventory system which can model airline and railway reservation systems. An arriving customer to an idle server joins for service immediately with exactly one item from inventory at the moment of service completion if there are some on-hand inventory, or else he accesses to a buffer of varying size (the buffer capacity varies and equals to the number of the items in the inventory with maximum size S). When the buffer overflows, the customer joins an orbit of infinite capacity with probability p or is lost forever with probability 1−p. Arrivals form a Poisson process, and service time has phase type distribution. The time between any two successive retrials of the orbiting customer is exponentially distributed with parameter depending on the number of customers in the orbit. In addition, the items have a common life time with exponentially distributed. Cancellation of orders is possible before their expiry and intercancellation times are assumed to be exponentially distributed. The stability condition and steady-state probability vector have been studied by Neuts–Rao truncation method using the theory of Level Dependent Quasi-Birth-Death (LDQBD) processes. Several stationary performance measures are also computed. Furthermore, we provide numerical illustration of the system performance with variation in values of underlying parameters and analyze an optimization problem.

A production inventory model with deteriorating items and retrial demands

This paper considers a single server perishable inventory system in which customers arrive in a homogeneous Poisson stream. The system has a production unit which produces a single item in an exponentially distributed time interval. At the time of arrival, a customer leads to service if the server is available with a positive level of inventory. Otherwise, the customer goes to a waiting place(orbit) of infinite capacity with pre-determined probability or exits the system with complementary probability. Each customer in the orbit tries to access the server in an exponentially distributed time interval. After every unsuccessful retrial, the customer returns to the orbit with a pre-allotted probability or is lost forever with complementary probability. An algorithmic solution to the problem is obtained using Matrix Analytic Method. The mean number of customer loss before and after entering the system, the rate of successful retrials among overall retrials and some other performance measures of the system are derived. The impacts of system parameters on different measures are numerically studied. A suitable cost function is constructed and the optimum control policy is numerically obtained.

New binary associative memory model based on the XOR operation

An associative memory is a special type of artificial neural network that has the purpose of store input patterns with their corresponding output patterns and efficiently recall a pattern from a noise-distorted version. Presented in this article is a new framework for constructing a binary associative memory model based on two new autoinverse operations called extended XOR/XNOR; these new operations are generated from the XOR/XNOR operations, respectively. Two types of associative memory are generated with this model: the max type (XOR-AM max), which is constructed with the maximum of the extended XOR operation, and the min type (XOR-AM min), which is constructed with the minimum of the extended XNOR operation. The XOR-AM max exhibits tolerance against the presence of patterns distorted by dilative noise, whereas the XOR-AM min exhibits tolerance against the presence of patterns distorted by erosive noise; both types of memory converge in a single step, use the same extended XOR/XNOR operator for learning and recalling phases, operate in heteroassociative and autoassociative modes, and show infinite storage capacity for the autoassociative mode. Finally, computer simulation results are presented for the new memories based on the extended XOR/XNOR (XOR-AM), which have better or equal performance compared to other associative memories. For the experiments with mixed noise, the conditions established by the kernel method proposed by Ritter for Morphological Associative Memories were conserved, and the solution algorithm proposed by Hattori for the construction of the kernel patterns of these memories was modified.

Delay-Optimal Policies in Partial Fork-Join Systems with Redundancy and Random Slowdowns

We consider a large distributed service system consisting of n homogeneous servers with infinite capacity FIFO queues. Jobs arrive as a Poisson process of rate λn/kn (for some positive constant kn and integer kn). Each incoming job consists of ???? identical tasks that can be executed in parallel, and that can be encoded into at least ???? ?replicas" of the same size (by introducing redundancy) so that the job is considered to be completed when any kn replicas associated with it finish their service. Moreover, we assume that servers can experience random slowdowns in their processing rate so that the service time of a replica is the product of its size and a random slowdown. First, we assume that the server slowdowns are shifted exponential and independent of the replica sizes. In this setting we show that the delay of a typical job is asymptotically minimized (as n - ∞) when the number of replicas per task is a constant that only depends on the arrival rate λ, and on the expected slowdown of servers. Second, we introduce a new model for the server slowdowns in which larger tasks experience less variable slowdowns than smaller tasks. In this setting we show that, under the class of policies where all replicas start their service at the same time, the delay of a typical job is asymptotically minimized (as n - ∞) when the number of replicas per task is made to depend on the actual size of the tasks being replicated, with smaller tasks being replicated more than larger tasks.

A Gestão Estratégica da Defesa: Novos Tempos, Novos Desafios

New times, new wars and new challenges. The three classic dimensions of the battlefield: land, naval and air no longer cover all aspects of conflict. To them was added the spatial dimension, cyberspace, the networked environment and an almost infinite capacity for storing information that allows the connection of the real battlefield with the virtual. The enemy may be a political, religious or terrorist faction. In the case of Brazil, the new demands of Brazilian society in the area of public security (Constabulary Function), aid for natural disasters, support for major events and specific demands such as Covid-19 are added. This study aims to present the impact that these challenges have generated on the Brazilian Armed Forces, with the purpose of contributing to a more efficient and effective management of the military apparatus in favor of society and the country's interests.

A Geo/Geo/1 Inventory Priority Queue with Self Induced Interruption

This paper considers discrete time (s, S) inventory Geo/Geo/1 priority queue formed by the customers’ induced interruption during service. An arriving customer enters into a high priority queue of infinite capacity. During his/her service, the service may be interrupted due to own reasons with some probability. The interrupted customer is moved to a lower priority queue of infinite capacity. An item in the inventory is supplied whenever a customer leaves from high priority queue after interrupting/completing the service. The customer in the lower priority queue is served according to preemptive priority discipline. Inter-arrival time, service time and lead time are considered to be geometrically distributed. We use the matrix analytic method to analyse the model. The necessary and sufficient condition for the stability of the system is obtained. The marginal distributions of both higher and lower priority queue lengths are studied. Numerical experiments are incorporated to draw special attention to the importance of the model.

Analysis of Retrial Queueing-Inventory System with Stock Dependent Demand Rate: (s, S) Versus (s, Q) Ordering Policies

Looking into the common real-life observation, particularly, the continuous time Markovian queueing inventory models with the demand rate depends on the on-hand inventory level. It may influence to gain more sale and profit of a particular item. According to this fact, we consider the demand rate of primary as well as retrial customers depending on the on-hand inventory level. An arriving primary customer finds the positive inventory, immediately they purchase an item with a rate depending on the present stock level and at the time of zero inventory, they will enter into the orbit of infinite capacity. The same assumption also holds for retrial customers if the inventory level(IL) is positive. Based on the ordering policies, we present two models: (i) (s, S) policy (ii) (s, Q) Policy. By applying Neut’s Matrix Geometric techniques, the system characteristics are computed under the steady state conditions and the numerical illustrations show the flexibility of the ordering polices in the proposed model.

Railway delay management with passenger rerouting considering train capacity constraints

Delay management for railways is concerned with the question of whether a train should wait for a delayed feeder train or depart on time. The answer should not only depend on the length of the delay but also consider other factors, such as capacity restrictions. We present an optimization model for delay management in railway networks that accounts for capacity constraints on the number of passengers that a train can effectively carry. While limited capacities of tracks and stations have been considered in delay management models, passenger train capacity has been neglected in the literature so far, implicitly assuming an infinite train capacity. However, even in open systems where no seat reservation is required and passengers may stand during the journey if all seats are occupied, physical space is naturally limited, and the number of standing seats is constrained for passenger safety reasons. We present a mixed-integer nonlinear programming formulation for the delay management problem with passenger rerouting and capacities of trains. Our model allows the rerouting of passengers missing their connection due to delays or capacity constraints. We linearize the model in exact and approximate ways and experimentally compare the different approaches with the solution of a reference model from the literature that neglects capacity constraints. The results demonstrate that there is a significant impact of considering train capacity restrictions in decisions to manage delays.

Delay-optimal Policies in Partial Fork-Join Systems with Redundancy and Random Slowdowns

We consider a large distributed service system consisting of n homogeneous servers with infinite capacity FIFO queues. Jobs arrive as a Poisson process of rate λn/k_n (for some positive constant λ and integer k_n). Each incoming job consists of k_n identical tasks that can be executed in parallel, and that can be encoded into at least k_n "replicas" of the same size (by introducing redundancy) so that the job is considered to be completed when any k_n replicas associated with it finish their service. Moreover, we assume that servers can experience random slowdowns in their processing rate so that the service time of a replica is the product of its size and a random slowdown. First, we assume that the server slowdowns are shifted exponential and independent of the replica sizes. In this setting we show that the delay of a typical job is asymptotically minimized (as $n\to\infty$) when the number of replicas per task is a constant that only depends on the arrival rate λ, and on the expected slowdown of servers. Second, we introduce a new model for the server slowdowns in which larger tasks experience less variable slowdowns than smaller tasks. In this setting we show that, under the class of policies where all replicas start their service at the same time, the delay of a typical job is asymptotically minimized (as n\to\infty) when the number of replicas per task is made to depend on the actual size of the tasks being replicated, with smaller tasks being replicated more than larger tasks.

Microgeometry-independent equation for measuring infinite dilution activity coefficients using gas-liquid chromatography with static-wall-coated open-tubular columns

Gas-liquid chromatography is an effective method to determine infinite dilution activity coefficients (γ∞). Wall-coated open-tubular (WCOT) column which offers more advantages over packed column should be a preferable column type; however, the small carrier gas flow rate and stationary phase amount in WCOT columns limit its application in the determination of γ∞. Mathematical strategy made some progress to avoid the quantification problem in the determination of γ∞ by static-wall-coated open-tubular (SWCOT) columns. However, the previously reported strategy was based on the assumption that SWCOT column was geometrically an ideal hollow cylinder, which indeed deviates from the reality. In this study, without that assumption, we derived a new microgeometry-independent equation by using the relationship between the hold-up volume (VM) and the volume of stationary phase (VL), and used it to measure the γ∞ of various organic solutes in two ionic liquids (ILs) 1‑butyl‑3-methylimidazolium dicyanamide and 1,3-dibutyronitrile-imidazolium bis((trifluoromethyl)sulfonyl)imide, both of which contain double cyano groups in the anion or cation. Phase loading study was adopted to eliminate the influence of interfacial adsorption to partition. The infinite dilution partial molar excess enthalpy, selectivity and capacity were directly calculated from the experimental γ∞ values, and the linear solvation energy relationship (LSER) model was used to characterize the specific properties of both ILs. This new established equation will promote the application of SWCOT columns in thermodynamic measurement and benefit the fast screening of novel solvents for chemical separation processes.

Effect of Vanadium (IV) Sulfate Particles Present in the Posolyte on the Anodic Current of a Vanadium Redox Flow Battery

Vanadium redox flow batteries (VRFB) are one of the most promising technologies for large scale energy conversion and storage (Cunha et al. 2014). Since it uses the same element in its four oxidation states (V(II)/V(III) and V(IV)/V(V) couples), its major advantage is the minimization of the cross-contamination problem observed in other RFBs. In addition, the fact that the electrolyte has an infinite regenerative capacity (Wang et al. 2015), makes this type of battery extremely rewarding on the economical point of view.However, their commercialization is hindered, among other reasons, by the limited quantity of stored energy (~ 40 kWh/m3), due to the low solubility of the vanadium salts (< 2 M), strongly influenced by the sulfuric acid concentration, generally used as supporting electrolyte: higher H2SO4 concentrations stabilize the V(V) species but decrease the solubility of the other salts (V(II), V(III) and V(IV)). Operating temperature also enhances the solubility of vanadium salts, inducing thereby an opposite behavior for the V(V) (solubility decreases with increasing temperatures) compared to the other valences. Therefore, the precipitation of vanadium species is considered to be an important problem for which a number of solutions has been proposed such as the use of a mixed H2SO4/HCl supporting electrolyte (Vijayakumar et al. 2013) and precipitation inhibitors (Skyllas-Kazacos et al. 2016). However, the understanding of the impact of the vanadium particles suspended in the electrolyte on the current was not yet addressed.Hence, the present work deals with the study of the impact of the presence of vanadium (IV) particles (VOSO4.5H2O powder) on the limiting current of the oxidation of V(IV) to V(V), using a classical three electrodes cell in which the working electrode is a rotating cylinder made of graphite. In addition, in order to insure an homogeneous distribution of the particles in the cell (avoid sedimentation), an additional stirring system, consisting of a cross-shaped stirrer is introduced at the bottom of the cell. Various kinds of measurements were achieved using a saturated V(IV) solution at 10 °C, in 3 M sulfuric acid: first, the effect of solid particles of VOSO4.5H2O powder was examined and then, comparatively the same experiments were performed using inert particles (glass spheres) having similar physical properties as the vanadium particles. In addition, the coupled effects of both the stirring provided from the rotating electrode and the stirring assured by the ‘cross-shaped stirrer’, on the magnitude of the current was also studied.The results show that the anodic limiting current of the V(IV) decreases, as the mass concentration of the solid particles increases. Higher apparent viscosity of the resulting mixture directly impacts the diffusion coefficient of the dissolved VO2+ species and limits the mass transfer. Moreover, the results do not show any positive effect of the presence of the solid particles (V(IV) or glass spheres) on the thickness of the diffusion layer (enhancement of the transfer of the dissolved VO2+ by some collisions between the solid particles and the electrode surface). Besides the study of the coupled effects of both stirring rates (electrode + additional stirrer) leads to some curious results on the evolution of the magnitude of the current, e.g. a ‘usual’ power law dependence until a complete independence, probably caused by a compensation of both motions in certain regimes. All these results were discussed.

Energy and memory-aware software pipelining streaming applications on NoC-based MPSoCs

In this article, we explore the problem of energy-aware scheduling of real-time applications modelled by conditional task graphs on NoC based MPSoC such that the total energy consumption is minimized. We propose a novel energy and memory-aware retiming conditional task graph (EMRCTG) approach that integrates task-level coarse-grained software pipelining with Dynamic Voltage and Frequency Scaling (DVFS). Our approach not only optimizes energy consumption but ensures that memory capacity constraints are satisfied. EMRCTG has two phases. In the first phase, we map tasks to processors, transform intra-period data dependencies into inter-period and generate a schedule by a Non-Linear Programming (NLP)-based algorithm assuming infinite memory capacity. The NLP-based algorithm assigns a continuous frequency and voltage to each task and each communication and uses a polynomial-time heuristic to transform the continuous frequencies and voltages to discrete frequencies and voltages. We analyse the memory consumption of the generated schedule and initiate schedule repair phase 2 if the memory capacity constraints violate. The schedule repair phase finds a set of nodes such that by reducing their retiming values the memory capacity constraints satisfy.We compare our approach against two existing approaches GeneS and JCCTS. GeneS is a genetic algorithm that first transforms the dependent task set into an independent task set and then collectively performs task mapping, ordering and voltage scaling. JCCTS is a mixed integer linear programming based approach that optimally removes inter-processor communication overhead. Our experimental result show that compared to the approach GeneS our approach can obtain an improvement in range of 1.6 to 18 percent and an average improvement of 11 percent. Compared to the approach JCCTS our approach can achieve an improvement in range of 9 to 42 percent and an average improvement of 26 percent.

Throughput Maximization With Energy Harvesting in UAV-Assisted Cognitive Mobile Relay Networks

In order to extend the communication coverage and improve system performance, the applications of unmanned aerial vehicles (UAVs) in wireless communications have attracted a lot of attention in the industry. In this paper, we propose a power control algorithm in energy harvesting (EH)-based cognitive mobile relay networks where an UAV is equipped with a decode-and-forward (DF) relay to cooperate the communication of secondary user (SU). Assuming that the only power source for SU transmitter with EH is a battery with infinite capacity, we solve a throughput maximization problem to optimize the transmit powers of SU and the mobile relay, subject to the causality constraint of energy usage at SU transmitter, the maximum transmit power constraint of the mobile relay, and the interference temperature (IT) constraint to protect the communication of primary user (PU). When formulating this throughput maximization problem, we adopt an offline scheme with deterministic settings. For simplicity, the original multi-variable optimization problem is transformed into a single variable optimization problem via the optimal throughput principle of the DF relaying communication system. Furthermore, we solve this new optimization problem via the Lagrange dual method, and we derive the closed-form expressions of the optimal solutions. The simulation results illustrate the optimized system performance that the optimal throughput of the secondary system can be achieved by the proposed dynamic power control algorithm.

Screening of ionic liquids for the extraction of biologically active compounds using emulsion liquid membrane: COSMO-RS prediction and experiments

Emulsion liquid membrane (ELM) is an effective way to recover and remove biologically active compounds, particularly drug molecules from hospital wastewater. Ionic liquid (IL)-assisted ELMs have recently been found to be efficient for recovery and removal of biologically active compounds owing to their excellent characteristics. However, the selection of potential ILs from the wide range of anion-cation combinations is quite challenging. To address this issue, the conductor-like screening model for real solvents (COSMO-RS) has emerged as a reliable tool to screen solvents based on a variety of fluid mixture properties. In this study, we screened ILs for the extraction of lactic acid as a model drug using COSMO-RS. Six cations and 20 anions were selected and combined to form 120 ILs, which were then assessed for recovery of lactic acid. The activity coefficient at infinite dilution, capacity, selectivity, performance index, and solvation energy values for all of the combinations were predicted, by which the effectiveness of each IL was evaluated. ILs without aromatic rings showed greater efficiencies than ILs containing aromatic rings. Moreover, the sulphate anion-cation combinations showed the highest capacities and selectivities. Overall, tetramethylammonium sulfate was found to be the best extractant for lactic acid. The COSMO-RS predictions were validated with experimental data, and the results showed a maximum difference of ~8.0 between the predicted and experimental values.

Dynamic Modeling for Resilience Measurement: NATO Resilience Decision Support Model

Despite its conceptual uncertainty, resilience is mostly about the measurement of capacity. Current studies confirm the importance of resilience measurement and the necessity to support policy makers with a measurement mechanism. A holistic approach considering the measurement of different resilience domains interactively and concurrently is the critical element in this endeavor. In parallel with the rise of popularity of resilience in international organizations, NATO has initiated a project with the objective to discover whether the resilience capacity of a country can be evaluated in a dynamic way via a prototype model execution. The implemented model running both baseline (without any shock) and extraordinary scenarios (with strategic shocks), clearly demonstrates its capacity to represent quantitatively the resilience related factors of a country in the complex operational environment. Moreover, the outputs of the model substantially comply with the resilience concept existing in the literature and NATO applications. One of the main strengths of the model is its almost infinite capacity to create various scenarios and make what-if analysis limited only by the current number of endogenous parameters of the model. It allows studying the secondary and the third order effects of events introduced in scenarios. The user interfaces (input and output dashboards) of the model help decision makers modify the values of selected endogenous parameters, see and compare the time-based values of the resilience factors, and doing so to evaluate risk related to the Area of Operations. Subject matter experts have validated the model and identified the main areas of improvement. The further development brings more countries to the model and implements an aggregation mechanism for output values of both resilience capacity and risk functions. The model will form the core of the NATO Resilience expert system.