Varying Response Ratio Priority: A Preemptive CPU Scheduling Algorithm (VRRP)

In present era, one of the most important resources of computer machine is CPU. With the increasing number of application, there exist a large number of processes in the computer system at the same time. Many processes in system simultaneously raise a challenging circumstance of managing the CPU in such a manner that the CPU utilization and processes execution gets optimal performance. The world is still waiting for most efficient algorithm which remains a challenging issue. In this manuscript, we have proposed a new algorithm Progressively Varying Response Ratio Priority a preemptive CPU scheduling algorithm based on the Priority Algorithm and Shortest Remaining Time First. In this scheduling algorithm, the priority is been calculated and the processes with high priority get CPU first or next. For new process, the priority of it becomes equal to inverse of burst time and for the old processes the priority calculation takes place as a ratio of waiting time and remaining burst time. The objective is to get all the processes executed with minimum average waiting time and no starvation. Experiment and comparison show that the VRRP outperforms other CPU scheduling algorithms. It gives better evaluation results in the form of scheduling criteria. We have used the deterministic model to compare the different algorithms.

Chronically Evaluated Highest Instantaneous Priority Next: A Novel Algorithm for Processor Scheduling

This paper proposes a novel chronically evaluated highest instantaneous priority next processor scheduling algorithm. The currently existing algorithms like first come first serve, shortest job first, round-robin, shortest remaining time first, highest response ratio next and varying response ratio priority algorithm have some problems associated with them. Some of them can lead to endless waiting or starvation and some of them like round-robin has problem of too many context switches and high waiting time associated with them. In the proposed algorithm, we have taken care of all such problems. As the novel algorithm is capable of achieving as good results as shortest remaining time first algorithm and also it will never lead to starvation.

Broadcast Scheduling Strategy Based on the Priority of Real-Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel, scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels. In order to meet the requirement of real-time data disseminating and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.

Two-stage scheduling algorithm based on priority table for clusters with inaccurate system parameters

A new two-stage soft real-time scheduling algorithm based on priority table was proposed for task dispatch and selection in cluster systems with inaccurate parameters. The inaccurate characteristics of the system were modeled through probability analysis. By taking into account the multiple important system parameters, including task deadline, priority, session integrity and memory access locality, the algorithm is expected to achieve high quality of service. Lots of simulation results collected under different load conditions demonstrate that the algorithm can not only effectively overcome the inaccuracy of the system state, but also optimize the task rejected ratio, value realized ratio, differentiated service guaranteed ratio, and session integrity ensured ratio with the average improvement of 3.5%, 5.8%, 7.6% and 5. 5%, respectively. Compared with many existing schemes that cannen deal with the inaccurate parameters of the system, the proposed scheme can achieve the best system performance by carefully adjusting scheduling probability. The algorithm is expected to be promising in systems with soft real-time scheduling requirement such as E-commerce applications.

Peer priority based data scheduling algorithm in P2P streaming system

In order to solve the problem that the existing data scheduling algorithm cannot make full use of neighbors' bandwidth resources when allocating data request among several senders in the multisender based P2P streaming system,a peer priority based scheduling algorithm is proposed.The algorithm calculates neighbors' priority based on peers' historical service evaluation as well as how many wanted data that the neighbor has.The data request allocated to each neighbor is adjusted dynamically according to the priority when scheduling.Peers with high priority are preferred to allocate more data request.Experiment shows the algorithm can make full use of neighbors' bandwidth resources to transmit data to reduce server pressure effectively and improve system scalability.

High Performance Priority Packets Scheduling Mechanism for Big Data in Smart Cities

Today,Internet of Things(IoT)is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities.Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio,energy efficiency,end-to-end delays etc.However,traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics.In big data smart cities applications which need fast packets transmission ratio such as sending priority packets to hospitals for an emergency case,an efficient schedulingmechanism ismandatory which is the main concern of this paper.In this paper,we overcome the shortcoming issues of the traditional scheduling algorithms that are utilized in big data smart cities emergency applications.Transmission information about the priority packets between the source nodes(i.e.,people with emergency cases)and the destination nodes(i.e.,hospitals)is performed before sending the packets in order to reserve transmission channels and prepare the sequence of transmission of theses priority packets between the two parties.In our proposed mechanism,Software Defined Networking(SDN)with centralized communication controller will be responsible for determining the scheduling and processing sequences for priority packets in big data smart cities environments.In this paper,we compare between our proposed Priority Packets Deadline First scheduling scheme(PPDF)with existing and traditional scheduling algorithms that can be used in urgent smart cities applications in order to illustrate the outstanding network performance parameters of our scheme such as the average waiting time,packets loss rates,priority packets end-to-end delay,and efficient energy consumption.

Novel radar dwell scheduling algorithm based on pulse interleaving

The problem of scheduling radar dwells in multifunction phased array radar systems is addressed. A novel dwell scheduling algorithm is proposed. The whole scheduling process is based on an online pulse interleaving technique. It takes the system timing and energy constraints into account. In order to adapt the dynamic task load, the algorithm considers both the priorities and deadlines of tasks. The simulation results demonstrate that compared with the conventional adaptive dwell scheduling algorithm, the proposed one can improve the task drop rate and system resource utility effectively.

NEW NONSTANDARD JOB SHOP SCHEDULING ALGORITHM

Considering the complex constraint between operations in nonstandard job shop scheduling problem （NJSSP）, critical path of job manufacturing tree is determined according to priority scheduling function constructed. Operations are divided into dependent operations and independent operations with the idea of subsection, and corresponding scheduling strategy is put forward according to operation characteristic in the segment and the complementarities of identical function machines. Forward greedy rule is adopted mainly for dependent operations to make operations arranged in the right position of machine selected, then each operation can be processed as early as possible, and the total processing time of job can be shortened as much as possible. For independent operations optimum scheduling rule is adopted mainly, the inserting position of operations will be determined according to the gap that the processing time of operations is subtracted from idle time of machine, and the operation will be inserted in the position with minimal gap. Experiments show, under the same conditions, the result that operations are scheduled according to the object function constructed, and the scheduling strategy adopted is better than the result that operations are scheduled according to efficiency scheduling algorithm.

Study on scheduling algorithm for multiple handling requests of single automated guided vehicles

To solve the problem of small amount of machining centers in small and medium flexible manufacture systems(FMS), a scheduling mode of single automated guided vehicle(AGV) is adopted to deal with multiple transport requests in this paper. Firstly, a workshop scheduling mechanism of AGV is analyzed and a mathematical model is established using Genetic Algorithm. According to several sets of transport priority of AGV, processes of FMS are encoded, and fitness function, selection, crossover, and variation methods are designed. The transport priority which has the least impact on scheduling results is determined based on the simulation analysis of Genetic Algorithm, and the makespan, the longest waiting time, and optimal route of the car are calculated. According to the actual processing situation of the workshop, feasibility of this method is verified successfully to provide an effective solution to the scheduling problem of single AGV.

Improved differential evolution algorithm for resource-constrained project scheduling problem

An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be evaluated.To investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected heuristics.The results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.

Scheduler Algorithm for Multi-Class Switch with Priority Threshold

The requirement for guaranteed Quality of Service (QoS) have become very essential since there are numerous network base application is available such as video conferencing, data streaming, data transfer and many more. This has led to the multi-class switch architecture to cater for the needs for different QoS requirements. The introduction of threshold in multi-class switch to solve the starvation problems in loss sensitive class has increased the mean delay for delay sensitive class. In this research, a new scheduling architecture is introduced to improve mean delay in delay sensitive class when the threshold is active. The proposed architecture has been simulated under uniform and non-uniform traffic to show performance of the switch in terms of mean delay. The results show that the proposed architecture has achieved better performance as compared to Weighted Fair Queueing (WFQ) and Priority Queue (PQ).

A real-time fault-tolerant scheduling algorithm with low dependability cost in on-board computer system

To make the on-board computer system more dependable and real-time in a satellite, an algorithm of the fault-tolerant scheduling in the on-board computer system with high priority recovery is proposed in this paper. This algorithm can schedule the on-board fault-tolerant tasks in real time. Due to the use of dependability cost, the overhead of scheduling the fault-tolerant tasks can be reduced. The mechanism of the high priority recovery will improve the response to recovery tasks. The fault-tolerant scheduling model is presented simulation results validate the correctness and feasibility of the proposed algorithm.

考虑电动汽车优先级需求的两阶段优化调度策略

随着光伏发电渗透率的升高,光伏出力的不确定性会影响电网的安全稳定运行。而利用电动汽车(EV)移动储能的特性可以实现EV和光伏的协同增效。本文基于EV能量调度的灵活性,构建了考虑用户充电需求的EV两阶段优化调度模型:在日前预调度阶段,建立光伏的就地消纳偏差最小、EV充电完成率最大、EV用户出行成本最小的多目标优化函数,并引入充放电系数对EV的充电行为进行优化;在实时调度阶段,负荷聚合商结合各时段EV的实际充电需求,根据调度优先级对优化后的充放电系数修正,保证EV充电的公平性,制定出最优的充放电策略。通过综合考虑EV用户对于充电完成度和充电成本的不同需求,对不同充电模式、不同权重系数进行分析,同时考虑了用户改变充电需求的情况,验证本文所提策略在降低光伏消纳偏差量、满足用户充电需求方面具有明显效果。

考虑柔性设备加工能力的综合调度算法

现有柔性综合调度研究中,没有考虑设备系统的协同加工能力,从而降低了设备系统高密加工和快速加工能力。针对此问题,文章将柔性设备可进行加工的工序数作为优化对象、以竞争资源较为紧张的设备资源为优化要素,提出了考虑柔性设备加工能力的综合调度算法(ISA-CPCFE):首先,采用优先调度层级较高与加工时长较短的工序的策略,提高了工序并行调度的力度;其次,提出一种最小化调度标尺与动态调整柔性设备优先级的策略,进一步提高了设备紧凑调度的力度。最后,将ISA-CPCFE算法与基于剪枝分层、基于设备驱动、基于实际路径、基于逆序层优先的算法进行对比实验。结果表明:ISA-CPCFE算法实现了复杂产品加工时间更短、柔性设备系统整体利用率更高的优化目标,调度效果更优。

抢占式调度问题的PPTA模型与验证方法

优先级用于解决诸如在资源共享和安全设计等方面的冲突,已经成为实时系统设计中不可或缺的一部分.对于引入优先级的实时系统,每个任务都会被分配优先级,这就导致低优先级的任务在运行时可能会被高优先级的任务抢占资源,进而给实时系统带来抢占式调度问题.现有研究,缺乏一种可以直观表示任务的优先级以及任务之间的依赖关系的建模及自动验证方法.为此,提出抢占式优先级时间自动机(PPTA)并引入抢占式优先级时间自动机网络(PPTAN).首先,通过在时间自动机上添加变迁的优先级来表示任务的优先级,再利用变迁将具有依赖关系的任务相关联,从而可以利用PPTA建模带有优先级的实时任务.在时间自动机上添加阻塞位置,进而利用PPTAN建模优先级抢占式调度问题.其次,提出基于模型的转换方法,将抢占式优先级时间自动机映射到自动验证工具UPPAAL中.最后,通过建模多核多任务实时系统实例并与其他模型进行对比,说明所提模型不仅适用于建模优先级抢占式调度问题并可对其进行准确验证分析.

基于MEC服务器优先服务的路侧单元MAC层调度策略

针对多接入边缘计算(MEC)服务器高可靠、低时延和大数据量的数据传输要求,基于无冲突接入、优先级架构和弹性服务技术,提出一种适用于车辆边缘计算场景下的媒体访问控制(MAC)调度策略。所提策略由车联网(IoV)路侧单元(RSU)集中协调信道接入权,优先确保车载网络中车载通信单元(OBU)与MEC服务器之间的链路传输质量,以及时传输车辆到网络(V2N)业务数据;同时,对本地OBU之间的业务采取弹性服务方式,增强密集车辆接入时应急消息传输的可靠性。首先,构建调度策略的排队分析模型;其次,根据各时刻系统状态变量的无后效性特点建立嵌入式马尔可夫链,并通过概率母函数的分析方法对系统进行理论分析,得到MEC服务器通信单元和OBU的平均排队队长、平均等待时延和RSU查询周期等关键指标的精确解析表达式。计算机仿真实验结果表明,统计分析结果与理论计算结果一致,所提调度策略在高负载情况下能够提高IoV的稳定性和灵活性。

面向算力制造全流程的企业园区算力网络系统和关键技术

数字经济催生算力需求突飞猛进,企业数字化转型依赖算力资源和相关应用。围绕算力制造全流程解析的四大类算力应用,提出企业园区算力网络的系统架构,并基于此构建覆盖研发云、办公云、生产云和终端云的四个子系统,进而建立围绕三大技术创新的企业园区算力网络系统。文章还首次提出算力制造的核心竞争力问题等价于这些应用使用算力的效率和成本问题,而唯有在资源和运营上实施双重定制,才能实现资源利用的极致效率和运营服务的极致体验,从而达成算力制造的降本提效目标。该系统和关键技术在运营商和企业合作项目开展试点验证,结果表明,在改善应用体验和算力资源效率上取得显著成效,成为算力服务器竞争力的关键因素。

天津港大港港区LNG双泊位联合运行通航管理方案

为满足北方地区冬季LNG高峰期保供目标,部分渤海沿海港口在同一港池内规划布置双LNG泊位。鉴于双泊位联合运营下的LNG船舶关联性强且操纵难度高的特点,有必要对LNG双泊位联合运行进行调度管理方案研究。以国内首座正式投产运营的LNG双泊位为例,基于船舶操纵模拟仿真方法,通过分析LNG船舶航行对航道通航效率影响及相邻泊位联动性,提出双泊位运营下的LNG船进出港优先级。在此基础上,结合LNG双泊位运营特点和通航管理规则,制定近期和远期不同阶段的船舶联合调度组织模式。研究结论可为单港池LNG双泊位的通航管理提供决策依据。

嵌入式多核系统中的实时混合任务调度算法

针对由周期任务和零星任务形成的实时混合任务集进行合理调度问题,文中提出了一种基于零松弛度边界公平(Boundary Fair until Zero Laxity,BFZL)的实时混合任务算法。该算法在改进边界公平(Improved Boundary Fair,I-BF)实时混合任务算法基础上,通过引入最小松弛度优先(Least Laxity First,LLF)算法中的松弛度参数来改进判定任务的优先级,并提出基于松弛度与启发式策略相结合的启发式算法改进任务的分配策略。实验结果表明,BFZL算法能够满足系统实时性,并达到了算法优化目的。通过数据对比分析可知,该算法相比于原始算法,零星任务的平均响应时间降低了约26%,上下文切换减少了约28%,迁移减少了约50%。该算法在调度开销方面也具有一定优势。