Discrete-Rate Adaptation and Selection in Energy Harvesting Wireless Systems

In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.

Electrospun SnSb Crystalline Nanoparticles inside Porous Carbon Fibers as a High Stability and Rate Capability Anode for Rechargeable Batteries

In an electrochemical alloying reaction, the electroactive particles become mechanically unstable owing to large volume changes occurring as a result of high amounts of lithium intake. This is detrimental for long-term battery performance. Herein, a novel synthesis approach to minimize such mechanical instabilities in tin particles is presented. An optimal one-dimensional assembly of crystalline single-phase tin-antimony (SnSb) alloy nanoparticles inside porous carbon fibers (abbreviated SnSb-C) is synthesized for the first time by using the electrospinning technique (employing non-oxide precursors) in combination with a sintering protocol. The ability of antimony to alloy independently with lithium is beneficial as it buffers the unfavorable volume changes occurring during successive alloying/dealloying cycles in Sn. The SnSb-C assembly provides nontortuous (tortuosity coefficient, =1) fast conducting pathways for both electrons and ions. The presence of carbon in SnSb-C completely nullifies the conventional requirement of other carbon forms during cell electrode assembly. The SnSb-C exhibited remarkably high electrochemical lithium stability and high specific capacities over a wide range of currents (0.2-5Ag(-1)). In addition to lithium-ion batteries, it is envisaged that SnSb-C also has potential as a noncarbonaceous anode for other battery chemistries, such as sodium-ion batteries.

Optimal Linear Glauber Model

Contrary to the actual nonlinear Glauber model, the linear Glauber model (LGM) is exactly solvable, although the detailed balance condition is not generally satisfied. This motivates us to address the issue of writing the transition rate () in a best possible linear form such that the mean squared error in satisfying the detailed balance condition is least. The advantage of this work is that, by studying the LGM analytically, we will be able to anticipate how the kinetic properties of an arbitrary Ising system depend on the temperature and the coupling constants. The analytical expressions for the optimal values of the parameters involved in the linear are obtained using a simple Moore-Penrose pseudoinverse matrix. This approach is quite general, in principle applicable to any system and can reproduce the exact results for one dimensional Ising system. In the continuum limit, we get a linear time-dependent Ginzburg-Landau equation from the Glauber's microscopic model of non-conservative dynamics. We analyze the critical and dynamic properties of the model, and show that most of the important results obtained in different studies can be reproduced by our new mathematical approach. We will also show in this paper that the effect of magnetic field can easily be studied within our approach; in particular, we show that the inverse of relaxation time changes quadratically with (weak) magnetic field and that the fluctuation-dissipation theorem is valid for our model.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

A Fast and Fault-Tolerant Distributed Algorithm for Near-Optimal TDMA Scheduling in WSNs

The time division multiple access (TDMA) based channel access mechanisms perform better than the contention based channel access mechanisms, in terms of channel utilization, reliability and power consumption, specially for high data rate applications in wireless sensor networks (WSNs). Most of the existing distributed TDMA scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA scheduling algorithms is to improve the channel utilization by generating a schedule of smaller length. But, they usually take longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a novel scheme for TDMA scheduling in WSNs, which can generate a compact schedule similar to static scheduling algorithms, while its runtime performance can be matched with those of dynamic scheduling algorithms. Furthermore, the proposed distributed TDMA scheduling algorithm has the capability to trade-off schedule length with the time required to generate the schedule. This would allow the developers of WSNs, to tune the performance, as per the requirement of prevalent WSN applications, and the requirement to perform re-scheduling. Finally, the proposed TDMA scheduling is fault-tolerant to packet loss due to erroneous wireless channel. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA schedule. Simulation results show that the proposed algorithm generates a compact schedule in a very less time.

Sum Secrecy Rate in Multicarrier DF Relay Beamforming

In this paper, we study sum secrecy rate in multicarrier decode-and-forward relay beamforming. We obtain the optimal source power and relay weights on each subcarrier which maximize the sum secrecy rate. For a given total power on a given subcarrier k, P-0(k), we reformulate the optimization problem by relaxing the rank-1 constraint on the complex positive semidefinite relay weight matrix, and solve using semidefinite programming. We analytically prove that the solution to the relaxed optimization problem is indeed rank 1. We show that the subcarrier secrecy rate, R-s (P-0(k)), is a concave function in total power P-0(k) if R-s (P-0(k)) > 0 for any P-0(k) > 0. Numerical results show that the sum secrecy rate with optimal power allocation across subcarriers is more than the sum secrecy rate with equal power allocation. We also propose a low complexity suboptimal power allocation scheme which outperforms equal power allocation scheme.

Campaigning in Heterogeneous Social Networks: Optimal Control of SI Information Epidemics

We study the optimal control problem of maximizing the spread of an information epidemic on a social network. Information propagation is modeled as a susceptible-infected (SI) process, and the campaign budget is fixed. Direct recruitment and word-of-mouth incentives are the two strategies to accelerate information spreading (controls). We allow for multiple controls depending on the degree of the nodes/individuals. The solution optimally allocates the scarce resource over the campaign duration and the degree class groups. We study the impact of the degree distribution of the network on the controls and present results for Erdos-Renyi and scale-free networks. Results show that more resource is allocated to high-degree nodes in the case of scale-free networks, but medium-degree nodes in the case of Erdos-Renyi networks. We study the effects of various model parameters on the optimal strategy and quantify the improvement offered by the optimal strategy over the static and bang-bang control strategies. The effect of the time-varying spreading rate on the controls is explored as the interest level of the population in the subject of the campaign may change over time. We show the existence of a solution to the formulated optimal control problem, which has nonlinear isoperimetric constraints, using novel techniques that is general and can be used in other similar optimal control problems. This work may be of interest to political, social awareness, or crowdfunding campaigners and product marketing managers, and with some modifications may be used for mitigating biological epidemics.

Reference Points and Optimal Management in Stochastic Age-Structured Fisheries Models

The purpose of this article is to characterize dynamic optimal harvesting trajectories that maximize discounted utility assuming an age-structured population model, in the same line as Tahvonen (2009). The main novelty of our study is that uses as an age-structured population model the standard stochastic cohort framework applied in Virtual Population Analysis for fish stock assessment. This allows us to compare optimal harvesting in a discounted economic context with standard reference points used by fisheries agencies for long term management plans (e.g. Fmsy). Our main findings are the following. First, optimal steady state is characterized and sufficient conditions that guarantees its existence and uniqueness for the general case of n cohorts are shown. It is also proved that the optimal steady state coincides with the traditional target Fmsy when the utility function to be maximized is the yield and the discount rate is zero. Second, an algorithm to calculate the optimal path that easily drives the resource to the steady state is developed. And third, the algorithm is applied to the Northern Stock of hake. Results show that management plans based exclusively on traditional reference targets as Fmsy may drive fishery economic results far from the optimal.

The study of Indian shrimp larvae feeding by enriched rotifer with vitamin C and unsaturated fatty acid (epa, dha) and its effects on growth factors, survival rate and environmental stresses

In this experiment, the feeding of Indian white shrimp larvae by unenriched rotifers (treatment 1) and enriched with highly unsaturated fatty acid (treatment 2) and highly unsaturated fatty acid along with vitamin C (treatment 3) on the growth factors, survival and resistance against salinity and formalin stress tests were studied and their differences with control treatment including newly hatched Artemia nauplii is compared. In this the study four treatments in a completely randomized design with 3 replicates per treatment were used. Farming of shrimp larvae of Zoea II to postlarvae 5 was done in 20 liter plastic bucket. Present results indicated that growth factors and survival rate of stage Zoea II to postlarvae 1 in treatments 1, 2 and 3 improve rather than control in which this case was due to optimal size rotifer rather than Artemia nauplii. Also, treatments 2 and 3 feeding with oil liver cod emulsion enriched rotifer have the highest concentration of DHA (mg/g DW) and the ratio DHA/EPA in which due to have shown the highest growth factors and a significant difference (P<0.05) with treatments 1 and control. The highest survival at stage PL1 were observed in treatment 3 that was enriched with ascorbyl palmitate in which have to the synergistic properties of vitamin C rather than treatments 2, 1 and control and showed a significant difference (P<0.05). But in stage PL5 the highest amount of growth and survival rates were related to control treatment which showed a significant difference (P<0.05) with other treatments that control has higher size rather than treatments 1, 2 and 3. Also, among experiment treatments that the two treatments 2 and 3 due to enrichment had higher growth and survival rates compared with treatment 1 in which their differences have also been significant (P<0.05). In the case of stress tests, results indicated that the highest survival rate has been reported when specimens were offered a diet containing high levels of highly unsaturated fatty acids with vitamin C. So that in stage PL1 in the salinity stress tests 10 and 20 ppt the highest survival rate was observed in treatment 3. As for the second, treatment 2 showed a significant difference (P<0.05) with treatment 3. It is worth mentioning that treatment 3 showed a higher survival rate compared to treatment 2 due to the synergistic properties of vitamin C. The difference between these two treatments with treatment 1 and control was also significant. No significant difference was observed in formalin stress test 100 ppm in this stage between treatments 3 and 2 which shows the highest survival rate. But their difference with treatments 1 and control was significant (P<0.05). Also, in stage PL5 in the salinity stress tests 10 and 20 ppt the highest survival rate was observed in treatment 3 which showed no significant difference (P<0.05) with control treatment. While their difference in the amount of survival rate with treatment 1 and 2 was significant (P<0.05). In this stage, the highest observed survival rate in formalin stress test 100 ppm included treatments control, 3 and 2 among which there were no significant differences (P<0.05). While the difference between these three treatments with treatment 1 was significant.

High epitaxial growth rate of 4H-SiC using TCS as silicon precursor

High homoepitaxial growth of 4H-SiC has been performed in a home-made horizontal hot wall CVD reactor on n-type 4H-SiC 8 degrees off-oriented substrates in the size of 10 mm x 10 mm, using trichlorosilane (TCS) as silicon precursor source together with ethylene as carbon precursor source. Cross-section Scanning Electron Microscopy (SEM), Raman scattering spectroscopy and Atomic Force Microscopy (AFM) were used to determine the growth rate, structural property and surface morphology, respectively. The growth rate reached to 23 mu m/h and the optimal epilayer was obtained at 1600 degrees C with TCS flow rate of 12 seem in C/Si of 0.42, which has a good surface morphology with a low Rms of 0.64 nm in 10 mu mx10 mu m area.

Comparison of photobioreactors and optimal light regime for rapid vegetative propagation of transgenic Undaria pinnatifida gametophytes

BACKGROUND: Previously, tachyplesin gene (tac) has been successfully transferred into Undaria pinnatifida gametophytes using the method of microprojectile bombardment transformation. The objectives of this study were to compare and evaluate the performance of bubble-column and airlift bioreactors to determine a preferred configuration of bioreactor for vegetative propagation of transgenic U. pinnatifida gametophytes, and to then investigate the influence of light on vegetative propagation of these gametophytes, including incident light intensity, photoperiod and light quality to resolve the problems of rapid vegetative propagation within the selected bioreactor. RESULTS: Experimental results showed that final dry cell density in the airlift bioreactor was 12.7% higher than that in the bubble-column bioreactor under the optimal aeration rate of 1.2 L air min(-1) L-1 culture. And a maximum final dry cell density of 2830 mg L-1 was obtained within the airlift bioreactor using blue light at 40 mu mol m(-2) s(-1) with a light/dark cycle of 14/10 (h). Polymerase chain reaction (PCR) analysis indicated that genes (bar and tac) were not lost during rapid vegetative propagation within the airlift bioreactor. CONCLUSION: The airlift bioreactor was shown to be much more suitable for rapid vegetative propagation of transgenic U. pinnatifida gametophytes than the bubble-column bioreactor in the laboratory. The use of blue light allows improvement of vegetative propagation of transgenic U. pinnatifida gametophytes. (C) 2009 Society of Chemical Industry

Size dependence of biomass spectra and abundance spectra: the optimal distributions

Based on the hypothesis of self-optimization, we derive four models of biomass spectra and abundance spectra in communities with size-dependent metabolic rates. In Models 1 and 2, the maximum diversity of population abundance in different size classes subject to the constraints of constant mean body mass and constant mean respiration rate is assumed to be the strategy for ecosystems to organize their size structure. In Models 3 and 4, the organizing strategy is defined as the maximum diversity of biomass in different size classes without constraints on mean body mass and subject to the constant mean specific respiration rate of all individuals, i.e. the average specific respiration rate over all individuals of a community or group, which characterizes the mean rate of energy consumption in a community. Models 1 and 2 generate peaked distributions of biomass spectral density whereas Model 3 generates a fiat distribution. In Model 4, the distributions of biomass spectral density and of abundance spectral density depend on the Lagrangian multipler (lambda (2)). When lambda (2) tends to zero or equals zero, the distributions of biomass spectral density and of abundance spectral density correspond to those from Model 3. When lambda (2) has a large negative value, the biomass spectrum is similar to the empirical fiat biomass spectrum organized in logarithmic size intervals. When lambda (2) > 0, the biomass spectral density increases with body mass and the distribution of abundance spectral density is an unimodal curve. (C) 2001 Elsevier Science B.V. All rights reserved.

Three-dimensional bubble clusters : Shape, packing, and growth rate

Cox, S.J., and Graner, F. (2004) Three-dimensional bubble clusters: shape, packing and growth-rate. Physical review. E, Statistical, nonlinear, and soft matter physics . 69:031409.

Statistic Rate Monotonic Scheduling

In this paper we present Statistical Rate Monotonic Scheduling (SRMS), a generalization of the classical RMS results of Liu and Layland that allows scheduling periodic tasks with highly variable execution times and statistical QoS requirements. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. The feasibility test for SRMS ensures that using SRMS' scheduling algorithms, it is possible for a given periodic task set to share a given resource (e.g. a processor, communication medium, switching device, etc.) in such a way that such sharing does not result in the violation of any of the periodic tasks QoS constraints. The SRMS scheduling algorithm incorporates a number of unique features. First, it allows for fixed priority scheduling that keeps the tasks' value (or importance) independent of their periods. Second, it allows for job admission control, which allows the rejection of jobs that are not guaranteed to finish by their deadlines as soon as they are released, thus enabling the system to take necessary compensating actions. Also, admission control allows the preservation of resources since no time is spent on jobs that will miss their deadlines anyway. Third, SRMS integrates reservation-based and best-effort resource scheduling seamlessly. Reservation-based scheduling ensures the delivery of the minimal requested QoS; best-effort scheduling ensures that unused, reserved bandwidth is not wasted, but rather used to improve QoS further. Fourth, SRMS allows a system to deal gracefully with overload conditions by ensuring a fair deterioration in QoS across all tasks---as opposed to penalizing tasks with longer periods, for example. Finally, SRMS has the added advantage that its schedulability test is simple and its scheduling algorithm has a constant overhead in the sense that the complexity of the scheduler is not dependent on the number of the tasks in the system. We have evaluated SRMS against a number of alternative scheduling algorithms suggested in the literature (e.g. RMS and slack stealing), as well as refinements thereof, which we describe in this paper. Consistently throughout our experiments, SRMS provided the best performance. In addition, to evaluate the optimality of SRMS, we have compared it to an inefficient, yet optimal scheduler for task sets with harmonic periods.

Optimal Scheduling of Secondary Content for Aggregation in Video-on-Demand Systems

Dynamic service aggregation techniques can exploit skewed access popularity patterns to reduce the costs of building interactive VoD systems. These schemes seek to cluster and merge users into single streams by bridging the temporal skew between them, thus improving server and network utilization. Rate adaptation and secondary content insertion are two such schemes. In this paper, we present and evaluate an optimal scheduling algorithm for inserting secondary content in this scenario. The algorithm runs in polynomial time, and is optimal with respect to the total bandwidth usage over the merging interval. We present constraints on content insertion which make the overall QoS of the delivered stream acceptable, and show how our algorithm can satisfy these constraints. We report simulation results which quantify the excellent gains due to content insertion. We discuss dynamic scenarios with user arrivals and interactions, and show that content insertion reduces the channel bandwidth requirement to almost half. We also discuss differentiated service techniques, such as N-VoD and premium no-advertisement service, and show how our algorithm can support these as well.