Optimization Task Scheduling Using Cooperation Search Algorithm for Heterogeneous Cloud Computing Systems

Cloud computing has taken over the high-performance distributed computing area,and it currently provides on-demand services and resource polling over the web.As a result of constantly changing user service demand,the task scheduling problem has emerged as a critical analytical topic in cloud computing.The primary goal of scheduling tasks is to distribute tasks to available processors to construct the shortest possible schedule without breaching precedence restrictions.Assignments and schedules of tasks substantially influence system operation in a heterogeneous multiprocessor system.The diverse processes inside the heuristic-based task scheduling method will result in varying makespan in the heterogeneous computing system.As a result,an intelligent scheduling algorithm should efficiently determine the priority of every subtask based on the resources necessary to lower the makespan.This research introduced a novel efficient scheduling task method in cloud computing systems based on the cooperation search algorithm to tackle an essential task and schedule a heterogeneous cloud computing problem.The basic idea of thismethod is to use the advantages of meta-heuristic algorithms to get the optimal solution.We assess our algorithm’s performance by running it through three scenarios with varying numbers of tasks.The findings demonstrate that the suggested technique beats existingmethods NewGenetic Algorithm(NGA),Genetic Algorithm(GA),Whale Optimization Algorithm(WOA),Gravitational Search Algorithm(GSA),and Hybrid Heuristic and Genetic(HHG)by 7.9%,2.1%,8.8%,7.7%,3.4%respectively according to makespan.

Flexible artificial vision computing system based on FeOx optomemristor for speech recognition

With the advancement of artificial intelligence,optic in-sensing reservoir computing based on emerging semiconductor devices is high desirable for real-time analog signal processing.Here,we disclose a flexible optomemristor based on C_(27)H_(30)O_(15)/FeOx heterostructure that presents a highly sensitive to the light stimuli and artificial optic synaptic features such as short-and long-term plasticity(STP and LTP),enabling the developed optomemristor to implement complex analogy signal processing through building a real-physical dynamic-based in-sensing reservoir computing algorithm and yielding an accuracy of 94.88%for speech recognition.The charge trapping and detrapping mediated by the optic active layer of C_(27)H_(30)O_(15) that is extracted from the lotus flower is response for the positive photoconductance memory in the prepared optomemristor.This work provides a feasible organic−inorganic heterostructure as well as an optic in-sensing vision computing for an advanced optic computing system in future complex signal processing.

System Support for Parallel Computing on Heterogeneous Networks of Workstations

Abstract In this paper, we introduce several on-going research projects to support parallel and distribut,ed computing on heterogeneous networks of workstations (NOW) in the High Performance Computing and Software Lahoratory at the University of Texas at San Antonio. The projects at aiming at addressing three technical issues. First, the factors of heterogeneity and time-sharing effects make traditional performance models/metrics for homogeneous computing performance measurement and evaluation not. suitable for bet.erogeneous computing. We develop practical models and metrics which quantify. the heterogeneity of networks and characterize the performance effects. Second, in order to perform parallel computation effectively, special system support is necessary. We are developing system schemes for heterogeneity management, process scheduling and efficient communications. Finally, to provide insight into system performance, we are developing two types of supporting tools : a graphical instrumentation monitor to aid users in investigating performance problems and in determining the most effective way of exploiting the NOW systems, and a trace-driven simulator to test and compare different system management and scheduling schemes.

Programming for scientific computing on peta-scale heterogeneous parallel systems

Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.

Intelligent Dynamic Heterogeneous Redundancy Architecture for IoT Systems

The conventional dynamic heterogeneous redundancy(DHR)architecture suffers from the security threats caused by the stability differences and similar vulnerabilities among the executors.To overcome these challenges,we propose an intelligent DHR architecture,which is more feasible by intelligently combining the random distribution based dynamic scheduling algorithm(RD-DS)and information weight and heterogeneity based arbitrament(IWHA)algorithm.In the proposed architecture,the random distribution function and information weight are employed to achieve the optimal selection of executors in the process of RD-DS,which avoids the case that some executors fail to be selected due to their stability difference in the conventional DHR architecture.Then,through introducing the heterogeneity to restrict the information weights in the procedure of the IWHA,the proposed architecture solves the common mode escape issue caused by the existence of multiple identical error output results of similar vulnerabilities.The experimental results characterize that the proposed architecture outperforms in heterogeneity,scheduling times,security,and stability over the conventional DHR architecture under the same conditions.

Multiple Tin Compounds Modified Carbon Fibers to Construct Heterogeneous Interfaces for Corrosion Prevention and Electromagnetic Wave Absorption

Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is considered an effective means to achieve high-efficiency EMW absorption.However,interface modulation engineering has not been fully discussed and has great potential in the field of EMW absorption.In this study,multi-component tin compound fiber composites based on carbon fiber(CF)substrate were prepared by electrospinning,hydrothermal synthesis,and high-temperature thermal reduction.By utilizing the different properties of different substances,rich heterogeneous interfaces are constructed.This effectively promotes charge transfer and enhances interfacial polarization and conduction loss.The prepared SnS/SnS_(2)/SnO_(2)/CF composites with abundant heterogeneous interfaces have and exhibit excellent EMW absorption properties at a loading of 50 wt%in epoxy resin.The minimum reflection loss(RL)is−46.74 dB and the maximum effective absorption bandwidth is 5.28 GHz.Moreover,SnS/SnS_(2)/SnO_(2)/CF epoxy composite coatings exhibited long-term corrosion resistance on Q235 steel surfaces.Therefore,this study provides an effective strategy for the design of high-efficiency EMW absorbing materials in complex and harsh environments.

Effects of connected automated vehicle on stability and energy consumption of heterogeneous traffic flow system

With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Nanograting‑Based Dynamic Structural Colors Using Heterogeneous Materials

Dynamic structuralcolors can change in response todifferent environmental stimuli.This ability remains effectiveeven when the size of the speciesresponsible for the structural coloris reduced to a few micrometers,providing a promising sensingmechanism for solving microenvironmentalsensing problems inmicro-robotics and microfluidics.However, the lack of dynamicstructural colors that can encoderapidly, easily integrate, and accuratelyreflect changes in physical quantities hinders their use in microscale sensing applications. Herein, we present a 2.5-dimensionaldynamic structural color based on nanogratings of heterogeneous materials, which were obtained by interweaving a pH-responsive hydrogelwith an IP-L photoresist. Transverse gratings printed with pH-responsive hydrogels elongated the period of longitudinal grating in the swollenstate, resulting in pH-tuned structural colors at a 45° incidence. Moreover, the patterned encoding and array printing of dynamic structuralcolors were achieved using grayscale stripe images to accurately encode the periods and heights of the nanogrid structures. Overall, dynamicstructural color networks exhibit promising potential for applications in information encryption and in situ sensing for microfluidic chips.

Protein arginine methyltransferase-6 regulates heterogeneous nuclear ribonucleoprotein-F expression and is a potential target for the treatment of neuropathic pain

Protein arginine methyltransferase-6 participates in a range of biological functions,particularly RNA processing,transcription,chromatin remodeling,and endosomal trafficking.However,it remains unclear whether protein arginine methyl transferase-6 modifies neuropathic pain and,if so,what the mechanisms of this effect.In this study,protein arginine methyltransferase-6 expression levels and its effect on neuropathic pain were investigated in the spared nerve injury model,chronic constriction injury model and bone cancer pain model,using immunohistochemistry,western blotting,immunoprecipitation,and label-free proteomic analysis.The results showed that protein arginine methyltransferase-6 mostly co-localized withβ-tubulinⅢin the dorsal root ganglion,and that its expression decreased following spared nerve injury,chronic constriction injury and bone cancer pain.In addition,PRMT6 knockout(Prmt6~(-/-))mice exhibited pain hypersensitivity.Furthermore,the development of spared nerve injury-induced hypersensitivity to mechanical pain was attenuated by blocking the decrease in protein arginine methyltransferase-6 expression.Moreover,when protein arginine methyltransferase-6 expression was downregulated in the dorsal root ganglion in mice without spared nerve injury,increased levels of phosphorylated extracellular signal-regulated kinases were observed in the ipsilateral dorsal horn,and the response to mechanical stimuli was enhanced.Mechanistically,protein arginine methyltransferase-6 appeared to contribute to spared nerve injury-induced neuropathic pain by regulating the expression of heterogeneous nuclear ribonucleoprotein-F.Additionally,protein arginine methyltransfe rase-6-mediated modulation of hete rogeneous nuclear ribonucleoprotein-F expression required amino atids 319 to 388,but not classical H3R2 methylation.These findings indicated that protein arginine methyltransferase-6 is a potential therapeutic target fo r the treatment of peripheral neuro pathic pain.

Design and Implementation of a Heterogeneous Database System over the Intranet

Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction management and parallel query over the Intranet Methods In the designing and implementation of HDBUS two important concepts heterogeneous tables join. Results and Conclu- tion The first concept can be used to process the parallel query of multiple database server, the second one is the key technology of heterogeneous is the key technology of heterogeneous distribute database.

Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

Silicon-based optoelectronic heterogeneous integration for optical interconnection

The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.

Carboniferous-Early Permian heterogeneous distribution of porous carbonate reservoirs in the Central Uplift of the South Yellow Sea Basin and its hydrocarbon potential analysis

Mesozoic-Palaeozoic marine carbonate rocks are crucial hydrocarbon reservoirs in the Central Uplift area of the South Yellow Sea Basin(SYSB).Due to the scarcity of boreholes and the significant heterogeneity of carbonate reservoirs,the distribution of porous carbonate reservoirs and their related key controlling factors remain unclear.In this study,factors affecting the distribution of porous Carboniferous-Early Permian carbonate reservoirs in the SYSB were investigated through seismic inversion and isotope analysis.The log-seismic characteristics of porous carbonate reservoirs,sensitive lithology parameters,and physical property parameters were extracted and analyzed.The pre-stack simultaneous inversion technique was applied to predict the lithology and physical properties of porous carbonate reservoirs.Moreover,the sedimentary of carbonate was analyzed using isotopes of carbon,oxygen,and strontium.The results show that porous carbonate reservoirs are mainly developed in the open platform sediments with porosities of 3%-5%and are mainly distributed in the paleo-highland(Huanglong Formation and Chuanshan Formation)and the slope of paleo-highland(Hezhou Formation).The porous carbonate reservoirs of the Qixia Formation are only locally developed.In addition,the negativeδ13C excursions indicate a warm and humid tropical climate with three sea-level fluctuations in the study area from the Carboniferous to Early Permian.The favorable conditions for developing porous carbonate rocks include the sedimentary environment and diagenetic process.The primary pore tends to form in high-energy environments of the paleo-highland,and the secondary pore is increased by dissolution during the syngenetic or quasi-syngenetic period.According to the hydrocarbon potential analysis,the Late Ordovician Wufeng Formation and Lower Silurian Gaojiabian Formation are the source rocks in the high-maturity-over-maturity stage,the Carboniferous-Lower Permian carbonate is the good reservoirs,and the Late Permian Longtan-Dalong Formation is the stable seal,ensuring a huge hydrocarbon accumulation potential in SYSB.The methods proposed in this study can be applied to other carbonate-dominated strata worldwide.

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

This paper aims to solve large-scale and complex isogeometric topology optimization problems that consumesignificant computational resources. A novel isogeometric topology optimization method with a hybrid parallelstrategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equationsolving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency ofCPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload betweenCPU and GPU. To illustrate the advantages of the proposedmethod, three benchmark examples are tested to verifythe hybrid parallel strategy in this paper. The results show that the efficiency of the hybrid method is faster thanserial CPU and parallel GPU, while the speedups can be up to two orders of magnitude.

High performance heterogeneous embedded computing: a review

As increasingly widening gap of computing demand and performance in embedded computing domain,heterogeneous computing architecture which delivers better performance as well as lower power in limited size is gaining more and more attention. At first,the heterogeneous computing model is presented. And the different tightly coupled single chip heterogeneous architectures and their application domain are introduced. Then,task partitioning methods are described. Several programming model technology are analyzed and discussed. Finally,main challenges and future perspective of High Performance Embedded Computing(HPEC) are summarized.

Undrained bearing capacity of obliquely-eccentrically loaded shallow foundations overlying a heterogeneous and inherently anisotropic clay deposit

Clay deposits typically exhibit significant degrees of heterogeneity and anisotropy in their strength and stiffness properties.Such non-monotonic responses can significantly impact the stability analysis and design of overlying shallow foundations.In this study,the undrained bearing capacity of shallow foundations resting on inhomogeneous and anisotropic clay layers subjected to oblique-eccentric combined loading is investigated through a comprehensive series of finite element limit analysis(FELA)based on the well-established lower-bound theorem and second-order cone programming(SOCP).The heterogeneity of normally consolidated(NC)clays is simulated by adopting a well-known general model of undrained shear strength increasing linearly with depth.In contrast,for overconsolidated(OC)clays,the variation of undrained shear strength with depth is considered to follow a bilinear trend.Furthermore,the inherent anisotropy is accounted for by adopting different values of undrained shear strength along different directions within the soil medium,employing an iterative-based algorithm.The results of numerical simulations are utilized to investigate the influences of natural soil heterogeneity and inherent anisotropy on the ultimate bearing capacity,failure envelope,and failure mechanism of shallow foundations subjected to the various combinations of vertical-horizontal(V-H)and vertical-moment(V-M)loads.

Energy-Optimal and Delay-Bounded Computation Offloading in Mobile Edge Computing with Heterogeneous Clouds

By Mobile Edge Computing(MEC), computation-intensive tasks are offloaded from mobile devices to cloud servers, and thus the energy consumption of mobile devices can be notably reduced. In this paper, we study task offloading in multi-user MEC systems with heterogeneous clouds, including edge clouds and remote clouds. Tasks are forwarded from mobile devices to edge clouds via wireless channels, and they can be further forwarded to remote clouds via the Internet. Our objective is to minimize the total energy consumption of multiple mobile devices, subject to bounded-delay requirements of tasks. Based on dynamic programming, we propose an algorithm that minimizes the energy consumption, by jointly allocating bandwidth and computational resources to mobile devices. The algorithm is of pseudo-polynomial complexity. To further reduce the complexity, we propose an approximation algorithm with energy discretization, and its total energy consumption is proved to be within a bounded gap from the optimum. Simulation results show that, nearly 82.7% energy of mobile devices can be saved by task offloading compared with mobile device execution.

Joint Resource Allocation Using Evolutionary Algorithms in Heterogeneous Mobile Cloud Computing Networks

The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.

Fast weighting method for plasma PIC simulation on GPU-accelerated heterogeneous systems

Particle-in-cell (PIC) method has got much benefits from GPU-accelerated heterogeneous systems.However,the performance of PIC is constrained by the interpolation operations in the weighting process on GPU (graphic processing unit).Aiming at this problem,a fast weighting method for PIC simulation on GPU-accelerated systems was proposed to avoid the atomic memory operations during the weighting process.The method was implemented by taking advantage of GPU's thread synchronization mechanism and dividing the problem space properly.Moreover,software managed shared memory on the GPU was employed to buffer the intermediate data.The experimental results show that the method achieves speedups up to 3.5 times compared to previous works,and runs 20.08 times faster on one NVIDIA Tesla M2090 GPU compared to a single core of Intel Xeon X5670 CPU.