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resource-saving scheduling scheme for centralized target tracking in multiple radar system under automatic blanket jamming

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Chinese Journal of Aeronautics 2024年第5期37卷 349-362页

作者： Zhengjie LI Yujie WEI Junwei XIE Haowei ZHANG Yu TIAN Air and Missile Defense College Air Force Engineering UniversityXi’an 710051China Air Force Xi’an Flying College Xi’an 710300China Air and Missile Defense Institute Air Force Research InstituteBeijing 100085China School of Economics and Management Beihang UniversityBeijing 100191China

This paper investigates the problem of Joint Radar Node Selection and Power Allocation(JRNSPA)in the Multiple Radar System(MRS)in the blanket jamming environment.Each radar node independently tracks moving target and subsequently transmits the raw observation data to the fusion center,which formulates a centralized tracking network structure.In order to establish a practical blanket jamming environment,we suppose that each target carries the self-defense jammer which automatically implements blanket jamming to the radar nodes that exceed the preset interception probability.Subsequently,the Predicted Conditional Cramer-Rao Lower Bound(PC-CRLB)is derived and utilized as the tracking accuracy criterion.Aimed at ensuring both the tracking performance and the Low Probability of Intercept(LPI)performance,the resource-saving scheduling model is formulated to minimize the transmit power consumption while meeting the requirements of tracking accuracy.Finally,the Modified Zoutendijk Method Of Feasible Directions(MZMFD)-based two-stage solution technique is adopted to solve the formulated non-convex optimization model.Simulation results show the effectiveness of the proposed JRNSPA scheme.

关键词： Multiple Radar System(MRS) Centralized target tracking resource scheduling Blanket jamming Low Probability of Intercept(LPI)

A multi-resource scheduling scheme of Kubernetes for IIoT

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Journal of Systems Engineering and Electronics 2022年第3期33卷 683-692页

作者： ZHU Lin LI Junjiang LIU Zijie ZHANG Dengyin Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China

With the rapid development of data applications in the scene of Industrial Internet of Things(IIoT),how to schedule resources in IIoT environment has become an urgent problem to be solved.Due to benefit of its strong scalability and compatibility,Kubernetes has been applied to resource scheduling in IIoT scenarios.However,the limited types of resources,the default scheduling scoring strategy,and the lack of delay control module limit its resource scheduling performance.To address these problems,this paper proposes a multi-resource scheduling(MRS)scheme of Kubernetes for IIoT.The MRS scheme dynamically balances resource utilization by taking both requirements of tasks and the current system state into consideration.Furthermore,the experiments demonstrate the effectiveness of the MRS scheme in terms of delay control and resource utilization.

关键词： Industrial Internet of Things(IIoT) Kubernetes resource scheduling time delay

Metaheuristic Based resource scheduling Technique for Distributed Robotic Control Systems

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Computer Systems Science & Engineering 2022年第8期42卷 795-811页

作者： P.Anandraj S.Ramabalan Department of Computer Science and Engineering E.G.S.Pillay Engineering CollegeNagapattinam611002India Department of Mechanical Engineering E.G.S.Pillay Engineering CollegeNagapattinam611002India

The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently.The distributed robotic control system can be used in real time for resolving various challenges such as localization,motion controlling,mapping,route planning,etc.The distributed robotic control system can manage different kinds of heterogenous devices.Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements.For instance,scheduling of resources(such as communication channel,computation unit,robot chassis,or sensor input)to the various system components turns out to be an essential requirement for completing the tasks on time.Therefore,resource scheduling is necessary for ensuring effective execution.In this regard,this paper introduces a novel chaotic shell game optimization algorithm(CSGOA)for resource scheduling,known as the CSGOA-RS technique for the distributed robotic control system environment.The CSGOA technique is based on the integration of the chaotic maps concept to the SGO algorithm for enhancing the overall performance.The CSGOA-RS technique is designed for allocating the resources in such a way that the transfer time is minimized and the resource utilization is increased.The CSGOA-RS technique is applicable even for the unpredicted environment where the resources are to be allotted dynamically based on the early estimations.For validating the enhanced performance of the CSGOA-RS technique,a series of simulations have been carried out and the obtained results have been examined with respect to a selected set of measures.The resultant outcomes highlighted the promising performance of the CSGOA-RS technique over the other resource scheduling techniques.

关键词： Distributed robotic control system resource scheduling load balancing resource utilization metaheuristics shell game optimization

Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network

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Frontiers of Information Technology & Electronic Engineering 2024年第5期25卷 685-700页

作者： Yuexia FU Jing WANG Lu LU Qinqin TANG Sheng ZHANG China Mobile Research Institute Beijing 100053China Purple Mountain Laboratories Nanjing 211111China China Mobile Communications Corporation Beijing 100033China

Under the development of computing and network convergence,considering the computing and network resources of multiple providers as a whole in a computing force network(CFN)has gradually become a new trend.However,since each computing and network resource provider(CNRP)considers only its own interest and competes with other CNRPs,introducing multiple CNRPs will result in a lack of trust and difficulty in unified scheduling.In addition,concurrent users have different requirements,so there is an urgent need to study how to optimally match users and CNRPs on a many-to-many basis,to improve user satisfaction and ensure the utilization of limited resources.In this paper,we adopt a reputation model based on the beta distribution function to measure the credibility of CNRPs and propose a performance-based reputation update model.Then,we formalize the problem into a constrained multi-objective optimization problem and find feasible solutions using a modified fast and elitist non-dominated sorting genetic algorithm(NSGA-II).We conduct extensive simulations to evaluate the proposed algorithm.Simulation results demonstrate that the proposed model and the problem formulation are valid,and the NSGA-II is effective and can find the Pareto set of CFN,which increases user satisfaction and resource utilization.Moreover,a set of solutions provided by the Pareto set give us more choices of the many-to-many matching of users and CNRPs according to the actual situation.

关键词： Computing force network resource scheduling Performance-based reputation User satisfaction

Fuzzy Control Based resource scheduling in IoT Edge Computing

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Computers, Materials & Continua 2022年第6期71卷 4855-4870页

作者： Samah Alhazmi Kailash Kumar Soha Alhelaly College of Computing and Informatics Saudi Electronic UniversityRiyadhKingdom of Saudi Arabia

Edge Computing is a new technology in Internet of Things(IoT)paradigm that allows sensitive data to be sent to disperse devices quickly and without delay.Edge is identical to Fog,except its positioning in the end devices is much nearer to end-users,making it process and respond to clients in less time.Further,it aids sensor networks,real-time streaming apps,and the IoT,all of which require high-speed and dependable internet access.For such an IoT system,resource scheduling Process(RSP)seems to be one of the most important tasks.This paper presents a RSP for Edge Computing(EC).The resource characteristics are first standardized and normalized.Next,for task scheduling,a Fuzzy Control based Edge resource scheduling(FCERS)is suggested.The results demonstrate that this technique enhances resource scheduling efficiency in EC and Quality of Service(QoS).The experimental study revealed that the suggested FCERS method in this work converges quicker than the other methods.Our method reduces the total computing cost,execution time,and energy consumption on average compared to the baseline.The ES allocates higher processing resources to each user in case of limited availability of MDs;this results in improved task execution time and a reduced total task computation cost.Additionally,the proposed FCERS m 1m may more efficiently fetch user requests to suitable resource categories,increasing user requirements.

关键词： IoT edge computing resource scheduling task scheduling fuzzy control

resource scheduling scheme with QoS support in two-hop relay-enhanced OFDMA systems

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The Journal of China Universities of Posts and Telecommunications 2010年第4期17卷 26-30页

作者： LIU Wei ,JI Hong,LI Ting School of Information and Telecommunication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China School of Information and Telecommunication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

As the system performance is obviously improved by introducing the concept of relay into the traditional orthogonal frequency division multiple access （OFDMA） systems, resource scheduling in relay-enhanced OFDMA systems is worthy of being studied carefully. To solve the optimization problem of achieving the maximum throughput while satisfying the quality of service （QoS） and guaranteeing the fairness of users, a novel resource scheduling scheme with QoS support for the downlink of two-hop relay-enhanced OFDMA systems is proposed. The proposed scheme, which is considered both in the first time sub-slot between direct link users and relay stations, and the second time sub-slot among relay link users, takes QoS support into consideration, as well as the system throughput and the fairness for users. Simulation results show that the proposed scheme has good performance in maximizing system throughput and guaranteeing the performance in the service delay and the data loss rate.

关键词： relay OFDMA QoS resource scheduling

Multi-objective resource optimization scheduling based on iterative double auction in cloud manufacturing

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Advances in Manufacturing 2019年第4期7卷 374-388页

作者： Zhao-Hui Liu Zhong-Jie Wang Chen Yang College of Electronics and Information Engineering Tongji UniversityShanghai 201804People's Republic of China College of Engineering Science and Technology Shanghai Ocean UniversityShanghai 201306People's Republic of China

Cloud manufacturing is a new kind of networked manufacturing model.In this model,manufacturing resources are organized and used on demand as marketoriented services.These services are highly uncertain and focus on users.The information between service demanders and service providers is usually incomplete.These challenges make the resource scheduling more difficult.In this study,an iterative double auction mechanism is proposed based on game theory to balance the individual benefits.resource demanders and providers act as buyers and sellers in the auction.resource demanders offer a price according to the budget,the delivery time,preference,and the process of auction.Meanwhile,resource providers ask for a price according to the cost,maximum expected profit,optimal reservation price,and the process of auction.A honest quotation strategy is dominant for a participant in the auction.The mechanism is capable of guaranteeing the economic benefits among different participants in the market with incomplete information.Furthermore,the mechanism is helpful for preventing harmful market behaviors such as speculation,cheating,etc.Based on the iterative double auction mechanism,manufacturing resources are optimally allocated to users with consideration of multiple objectives.The auction mechanism is also incentive compatibility.

关键词： Cloud manufacturing resource scheduling Multi-objective optimization Iterative double auction Incentive compatibility

A user-oriented resource scheduling method for improving agile software pattern in cloud environment

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Journal of Central South University 2016年第11期23卷 2906-2916页

作者：龙飞杨昌荣辉桂李建方 School of Information Management Wuhan University Department of Economics and Management Changsha University College of Computer Science and Electronic Engineering Hunan University

The crowdsourcing, as a service pattern in cloud environment, usually aims at the cross-disciplinary cooperation and creating value together with customers and becomes increasingly prevalent. Software process, as a kind of software development and management strategy, is defined as a series of activities implemented by software life cycle and provides a set of rules for various phases of the software engineering to achieve the desired objectives. With the current software development cycle getting shorter, facing more frequent needs change and fierce competition, a new resource management pattern is proposed to respond to these issues agilely by introducing the crowdsourcing service to agile software development for pushing the agility of software process. Then, a user-oriented resource scheduling method is proposed for rational use of various resources in the process and maximizing the benefits of all parties. From the experimental results, the proposed pattern and resources scheduling method reduces greatly the resource of project resource manager and increases the team resource utilization rate, which greatly improves the agility of software process and delivers software products quickly in crowdsourcing pattern.

关键词： resource scheduling agile software development project resource manager(PRM) individual resource provider(IRP)-

An Optimized resource scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes

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Computers, Materials & Continua 2020年第2期62卷 713-729页

作者： Yinghang Jiang Qi Liu Williams Dannah Dandan Jin Xiaodong Liu Mingxu Sun Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China School of Computing Edinburgh Napier UniversityEdinburgh EH105DTUK School of Electrical Engineering University of JinanChinaand Centre for Health Sciences ResearchUniversity of SalfordSalfordGreater ManchesterM54WTUK

Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes.“Straggling”tasks,however,have a serious impact on task allocation and scheduling in a Hadoop system.Speculative Execution(SE)is an efficient method of processing“Straggling”Tasks by monitoring real-time running status of tasks and then selectively backing up“Stragglers”in another node to increase the chance to complete the entire mission early.Present speculative execution strategies meet challenges on misjudgement of“Straggling”tasks and improper selection of backup nodes,which leads to inefficient implementation of speculative executive processes.This paper has proposed an Optimized resource scheduling strategy for Speculative Execution(ORSE)by introducing non-cooperative game schemes.The ORSE transforms the resource scheduling of backup tasks into a multi-party non-cooperative game problem,where the tasks are regarded as game participants,whilst total task execution time of the entire cluster as the utility function.In that case,the most benefit strategy can be implemented in each computing node when the game reaches a Nash equilibrium point,i.e.,the final resource scheduling scheme to be obtained.The strategy has been implemented in Hadoop-2.x.Experimental results depict that the ORSE can maintain the efficiency of speculative executive processes and improve fault-tolerant and computation performance under the circumstances of Normal Load,Busy Load and Busy Load with Skewed Data.

关键词： Distributed computing speculative execution resource scheduling non-cooperative game theory