New Algorithms for Resource Reclaiming from Precedence Constrained Tasks in Multiprocessor Real-Time Systems

The scheduling of tasks in multiprocessor real-time systems has attracted many researchers in the recent past. Tasks in these systems have deadlines to be met, and most of the real-time scheduling algorithms use worst case computation times to schedule these tasks. Many resources will be left unused if the tasks are dispatched purely based on the schedule produced by these scheduling algorithms, since most of the tasks will take less time to execute than their respective worst case computation times. Resource reclaiming refers to the problem of reclaiming the resources left unused by a real-time task when it takes less time to execute than its worst case computation time. In this paper, we propose two algorithms to reclaim these resources from real-time tasks that are constrained by precedence relations and resource requirements, in shared memory multiprocessor systems. We introduce a notion called a restriction vector for each task which captures its resource and precedence constraints with other tasks. This will help not only in the efficient implementation of the algorithms, but also in obtaining an improvement in performance over the reclaiming algorithms proposed in earlier work [[2]]. We compare our resource reclaiming algorithms with the earlier algorithms and, by experimental studies, show that they reclaim more resources, thereby increasing the guarantee ratio (the ratio of the number of tasks guaranteed to meet their deadlines to the number of tasks that have arrived), which is the basic requirement of any resource reclaiming algorithm. From our simulation studies, we demonstrate that complex reclaiming algorithms with high reclaiming overheads do not lead to an improvement in the guarantee ratio.     

Non-proportional loading in sequentially linear analysis for 3D stress states

Sequentially linear analysis (SLA), a non-incremental-iterative approach towards finite element simulation of quasi-brittle materials, is based on sequentially identifying a critical integration point in the model, to reduce its strength and stiffness, and the associated critical load multiplier (λ_crit), to scale the linear analysis results. In this article, two novel methods are presented to enable SLA simulations for non-proportional loading situations in a three-dimensional fixed smeared crack framework. In the first approach, the cubic function in the load multiplier is analytically solved for real roots using trigonometric solutions or the Cardano method. In the second approach, the load multiplier is expressed as a function of the inclination of a potential damage plane and is deduced using a constrained optimization approach. The first method is preferred over the second for the validation studies due to computational efficiency and accuracy reasons. A three-point bending beam test, with and without prestress, and an RC slab tested in shear, with and without axial loads, are used as benchmarks. The proposed solution method shows good agreement with the experiments in terms of force-displacement curves and damage evolution.     

Influence of different conducting substrates on magnetic properties of electrodeposited Ni–Fe thin films

Electrodeposition of Ni–Fe soft magnetic alloy on copper and stainless steel substrates was performed in chloride bath. The deposition parameters such as current density, pH, temperature and deposition time have been investigated. From the investigation the optimized deposition parameters were current density 3.5 mA/cm², pH 3, temperature 30 °C and deposition time 15 min. The Ni–Fe magnetic alloys deposited on copper and stainless steel substrates under optimized deposition parameters are subjected to various characterizations. The structural and surface morphology of the Ni–Fe films were detected by using X-ray diffractogram (XRD) and scanning electron microscope (SEM) respectively. The constituents in the films were determined by energy dispersive X-ray spectroscopy (EDAX) technique. The magnetic properties such as the coercivity (H_c) and saturation magnetization of the films were studied with the help of vibrating sample magnetometer (VSM). From the magnetic studies it is concluded that the grain size are create a considerable impact on magnetic behavior of the films on both the substrates. The films prepared on stainless steel substrate of 0.1 M concentration at optimized deposition parameters exhibits higher coercivity (5010 Oe) which seems to be ideal for magnetic sensor applications.     

Solution combustion synthesis of layered LiNi0.5Mn0.5O2 and its characterization as cathode material for lithium-ion cells

LiNi_0.5Mn_0.5O₂, a promising cathode material for lithium-ion batteries, is synthesized by a novel solution-combustion procedure using acenaphthene as a fuel. The powder X-ray diffraction (XRD) pattern of the product shows a hexagonal cell with a = 2.8955 Å and c = 14.1484 Å. Electron microscopy investigations indicate that the particles are of sub-micrometer size. The product delivers an initial discharge capacity of 161 mAh g⁻¹ between 2.5 and 4.6 V at a 0.1 C rate and could be subjected to more than 50 cycles. The electrochemical activity is corroborated with cyclic voltammetric (CV) and electrochemical impedance data. The preparative procedure presents advantages such as a low cation mixing, sub-micron particles and phase purity.     

Evaluation of mechanical properties of hybrid Al7009 nanocomposite

ABSTRACT

Hybrid nanocomposites are prepared by Al7009 aluminum alloy as base material,graphite and nano magnesium oxide (MgO) as reinforcements. Stir casting processes are used for preparation of hybrid nanocomposite, the percentage of graphite is fixed at 1 wt.% and nano magnesium oxide is varied for 1%, 2%, and 3% by weight and the specimens are named as A (pure), B (1% graphite and 1% MgO), C (1% graphite and 2% MgO), and D (1% graphite and 3% MgO). Evaluation of mechanical properties such as compressive strength, hardness, density, and impact strength behavior of hybrid Al7009 nano aluminum composites are analyzed. From the experimental results, the compressive strength and hardness of hybrid nanocomposite increases up to 2% wt of nano MgO particles and then the value decreases for 3% wt of nano MgO particles. Density increases from the specimens A to C with an increase in percentage of reinforcement in the matrix phase and then it decreases for specimen D. With respect to toughness highest value of 4.4 Jis obtained for sample D and the increase in percentage was 62.9 when compared to sample A, it was 37.5% when compared to specimen B and 12.8% when compared to specimen C.     

Numerical investigations of hydrogen and air mixture with vortex tube and duct combinations

Hydrogen gas stands as a renewable energy fuel for the transportation sector. The hydrogen to air ratio is an essential factor in deciding the combustion and therefore the thermal efficiency of an internal combustion engine. In this study, the mixing of hydrogen and air is considered among the four geometrical configurations. These cases are considered from the simple duct and vortex tube which induces an additional swirl inside a cylinder. The approach of the study involves the meshing and computation of mass, momentum and energy equations by finite volume method. After the convergence of results, mixture ratio is analyzed with the velocity components and vorticity variables. The ratio of hydrogen to air is found to vary between 8 and 35 among the cases considered. The desired ratio could be obtained from the combination of vortex tube and plain duct configurations. Stratification of mixture is found to be significant from the gradient of velocity components in this study.     

A new distributed route selection approach for channelestablishment in real-time networks

We propose a new distributed route selection approach, called parallel probing, for real-time channel establishment in a point-to-point network. The existing distributed routing algorithms fall into two major categories: preferred neighbor based or flooding based. The preferred neighbor approach offers a better call acceptance rate, whereas the flooding approach is better in terms of call setup time and routing distance. The proposed approach attempts to combine the benefits of both preferred neighbor and flooding approaches in a way to improve all the three performance metrics simultaneously. This is achieved by probing k different paths in parallel, for a channel, by employing different heuristics on each path. Also, the proposed approach uses a notion called intermediate destinations (IDs), which are subset of nodes along the least-cost path between source and destination of a call, in order to reduce the excessive resource reservations while probing for a channel by releasing unused resources between IDs and initiating parallel probes at every ID. Further, it has the flexibility of adapting to different load conditions by its nature of using different heuristics in parallel, and hence, a path found for a channel would have different segments (a segment is a path between two successive IDs), and each of these segments would very well be selected by different heuristics. The effectiveness of the proposed approach has been studied through simulation for well-known network topologies for a wide range of quality-of-service and traffic parameters. The simulation results reveal that the average call acceptance rate offered by the proposed route-selection approach is better than that of both the flooding and preferred neighbor approaches, and the average call setup time and routing distance offered by it are very close to that of the flooding approach     

An efficient dynamic scheduling algorithm for multiprocessorreal-time systems

Many time-critical applications require predictable performance and tasks in these applications have deadlines to be met. In this paper, we propose an efficient algorithm for nonpreemptive scheduling of dynamically arriving real-time tasks (aperiodic tasks) in multiprocessor systems. A real-time task is characterized by its deadline, resource requirements, and worst case computation time on p processors, where p is the degree of parallelization of the task. We use this parallelism in tasks to meet their deadlines and, thus, obtain better schedulability compared to nonparallelizable task scheduling algorithms. To study the effectiveness of the proposed scheduling algorithm, we have conducted extensive simulation studies and compared its performance with the myopic scheduling algorithm. The simulation studies show that the schedulability of the proposed algorithm is always higher than that of the myopic algorithm for a wide variety of task parameters     

Effect of structural evolution and surface morphological changes on the electrochemical response of an FeNbAlMnCuSiB alloy

The electrochemical response of a soft magnetic FeNbAlMnCuSiB alloy was studied through different stages of devitrification. The structural evolution including appearance of a nanocrystalline phase and intermetallics, and accompanying surface topographical changes were studied and correlated to the electrochemical behavior of this alloy. The electrochemical behavior was not directly related to changes in surface roughness but it was very responsive to the structural changes, particularly to the formation of the nanocrystalline phase and to the precipitation of Fe₇Nb₆ phase. There was a progressive passivation breakdown with the appearance of crystalline phases on annealing.