Energy efficiency modelling for IEEE 802.11a distribution coordination function system without finite retry limits

Use of IEEE 802.11 wireless local area networks (WLANs) as an extension to existing wired networks, offering both mobility and portability in a residential or office environment, is growing at an unprecedented rate. One of the critical limitations of current WLANs is the limited energy storage of mobile devices, and the design of energy-efficient protocols for WLANs has therefore become an area of intensive research. An analytical framework to study the energy consumption and energy efficiency of IEEE 802.11a WLANs is proposed. The energy consumption by considering the interactions between IEEE 802.11a PHY and MAC layers is modelled. Simulation results demonstrate that the theoretical model is accurate in predicting the energy efficiency over a wide range of scenarios. In addition, the effects of different PHY and MAC layer parameters on energy efficiency of IEEE 802.11a WLANs are investigated, as are the effects of different parameters on energy efficiency.     

APON接入系统分布式分层调度算法

分析了APON中MAC子层的算法特点，按照不同的QoS需求把ATM的各类业务重新作了划分，提出了适合于APON系统的分布式分层调试方式。分布式分层调度方式对需调度的信息进行了聚合，并能十分容易地嵌入各种公平调度算法。通过仿真，证明了该调度方式能有效地保证服务质量。同时由于采用了分层调度，减少了各ONU与OLT之间的信息交互开销。     

Integrating tactical and operational decisions in fixed job scheduling

Two different problems are introduced in this article to handle capacity and scheduling decisions simultaneously in the fixed job scheduling framework. The combined fixed job scheduling (CFJS) problem integrates these decisions assuming fixed costs for the usage of identical parallel machines, whereas the working time determination (WTD) problem involves unit-time operating or rental costs. Mathematical models for both problems are presented along with the worst case time complexities. While an exact polynomial-time algorithm is proposed for the CFJS problem, a heuristic algorithm is developed for the WTD problem as it is shown to be strongly NP hard. Computational experiments are carried out for evaluating the performance of the algorithms. The results reveal that the solutions by the exact algorithm for the CFJS problem are much faster than a state-of-the-art commercial solver, particularly for large instances. For the WTD problem, the developed heuristic provides high-quality solutions in very short computation times.     

A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

One of the most effective technology for the 5G mobile communications is Device-to-device (D2D) communication which is also called terminal pass-through technology. It can directly communicate between devices under the control of a base station and does not require a base station to forward it. The advantages of applying D2D communication technology to cellular networks are: It can increase the communication system capacity, improve the system spectrum efficiency, increase the data transmission rate, and reduce the base station load. Aiming at the problem of co-channel interference between the D2D and cellular users, this paper proposes an efficient algorithm for resource allocation based on the idea of Q-learning, which creates multi-agent learners from multiple D2D users, and the system throughput is determined from the corresponding state-learning of the Q value list and the maximum Q action is obtained through dynamic power for control for D2D users. The mutual interference between the D2D users and base stations and exact channel state information is not required during the Q-learning process and symmetric data transmission mechanism is adopted. The proposed algorithm maximizes the system throughput by controlling the power of D2D users while guaranteeing the quality-of-service of the cellular users. Simulation results show that the proposed algorithm effectively improves system performance as compared with existing algorithms.     

Cross-layer design for tree-type routing and level-based centralised scheduling in IEEE 802.16 based wireless mesh networks

Infrastructure wireless mesh network, also named as mesh router, is one key topology for the next generation wireless networking. In this work, the performance optimisation for the infrastructure wireless mesh network is presented and the sub-optimum solution mechanism is investigated. A cross-layer design for tree-type routing, level-based centralised scheduling and distributed power control theme is proposed as the sub-optimum solution strategy. The cross-layer design relies on the channel information and the distributed transmission power control in the physical layer, and the wireless scheduling in the medium access control (MAC) layer, as well as the routing selection mechanism in the MAC upper layer. In this work, a modified distributed power control algorithm is proposed first. In addition, a tree-type routing construction algorithm for centralised scheduling is presented to improve the network throughput by jointly considering interference and hop-count to construct the routing tree. Simulation results show that the proposed cross-layer design strategy can effectively improve the network throughput performance, decrease the power consumption and achieve better performances.     

Flow shop rescheduling under different types of disruption

Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimise the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand, and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.     

Deployment of Polar Codes for Mission-Critical Machine-Type Communication Over Wireless Networks

Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack. In this paper, an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission system. To achieve this aim, we analyzed and compared the channel coding performance of convolutional codes (CCs), low-density parity-check (LDPC) codes, and polar codes in wireless network on the condition of short data packet transmission. The Viterbi decoding algorithm (VA), logarithmic belief propagation (Log-BP) algorithm, and cyclic redundancy check (CRC) successive cancellation list (SCL) (CRC-SCL) decoding algorithm were adopted to CC, LDPC codes, and polar codes, respectively. Consequently, a new PHY layer for mcMTC has been proposed. The reliability of the proposed approach has been validated by simulation in terms of Bit error rate (BER) and packet error rate (PER) vs. signal-to-noise ratio (SNR). The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER = 10⁻⁵ or even better with the implementation of polar codes. The results also show that the general-purpose wireless networks are prominent in providing short packet mcMTC with the modification needed.     

A logistics scheduling model: scheduling and transshipment for two processing centers

Logistics scheduling refers to problems in which decisions on job scheduling and transportation are integrated into a single framework. A logistics scheduling model for two processing centers that are located in different cities is presented. Each processing center has its own customers. When the demand in one processing center exceeds its processing capacity, it is possible to use part of the capacity of the other processing center subject to a job transshipment delay. Such a coordinated scheduling situation can be modeled as a parallel-machine scheduling problem with transshipment between the machines. We study problems with different objective functions and constraints, and propose various algorithms to solve these problems. Discussions on the benefits and incentives for the coordinated approach are presented.     

Adaptive opportunistic fair scheduling in power-controlled code division multiple access systems

The authors treat the multiuser scheduling problem for practical power-controlled code division multiple access (CDMA) systems under the opportunistic fair scheduling (OFS) framework. OFS is an important technique in wireless networks to achieve fair and efficient resource allocation. Power control is an effective resource management technique in CDMA systems. Given a certain user subset, the optimal power control scheme can be derived. Then the multiuser scheduling problem refers to the optimal user subset selection at each scheduling interval to maximise certain metric subject to some specific physical-layer constraints. The authors propose discrete stochastic approximation algorithms to adaptively select the user subset to maximise the instantaneous total throughput or a general utility. Both uplink and downlink scenarios are considered. They also consider the time-varying channels where the algorithm can track the time-varying optimal user subset. Simulation results to show the performance of the proposed algorithms in terms of the throughput/ utility maximisation, the fairness, the fast convergence and the tracking capability in time-varying environments are presented.     

Dynamic Algorithms for Input-Output Planning of Work-Station Loading

The central problem in manufacturing planning is to reconcile due dates with schedule dates. Conventional (static) scheduling methods utilize expected process times, constant work station capacities, and technological sequencing to develop schedule dates, which rarely match planned due dates. A different approach, input-output control, is based upon throughput times (wait plus process), variable work station capacity, and lead times (from input to output) to try to match scheduled output dates with due dates. This paper presents several dynamic programming and transportation-type algorithms for determining optimal output level profiles under restrictions of permissible work station capacity levels and wait queue sizes.     

Environmental-impact reduction through simultaneous design, scheduling, and operation

Processing facilities are normally designed with sufficient flexibility to handle nominal variations. When the process features planned changes in feedstock and products, scheduling is often used to optimize process operation. Proper scheduling may be limited to existing design or may entail retrofitting. Traditionally, economic objectives have served as the primary drivers for the design, retrofitting, and scheduling of industrial processes. Once a base design and scheduling plan have been established, environmental issues are addressed in many cases as an afterthought. As a result of this sequential approach, valuable synergisms and tradeoffs of economic and environmental objectives are often missed. The objective of this study is to develop a new approach to design and scheduling with economic and environmental objectives. Specifically, this study introduces a systematic framework and the associated mathematical formulation for simultaneous process design and scheduling while simultaneously addressing economic and environmental objectives. Therefore, this study establishes two types of proper tradeoffs (a) between design and scheduling and (b) between economic and environmental objectives. The environmental issues pertaining to the parameterized process retrofitting, scheduling, and operation strategies are simultaneously considered along with the environmental impact of these changes. An optimization formulation is developed for the case of project schedule while allowing design retrofitting changes that include new environmental units and modification of design and operating conditions in the process (without new process units). Also, a process model with the appropriate level of relevant details is included in the formulation. The projected schedule is discretized to allow for a multiperiod formulation with algebraic equations. The resulting framework identifies opportunities for synergism between the economic and environmental objectives. It also determines points of diminishing return beyond which tradeoffs between economic and environmental objectives are established. The devised procedure is illustrated with a case study on an oil refinery with scheduling of different products and the design of an environmental system that addresses NO _x emission.     

Multi-rate power-controlled link scheduling for mesh broadband wireless access networks

The problem of multi-rate power-controlled collision-free scheduling in spatial time division multiple access (STDMA) wireless mesh networks is formulated as a mathematical program utilising cross layer information. As these mixed integer linear programs are intractable (NP-hard problems), optimal collision-free schedules can be found only for topologies consisting of a few nodes. To this end, approximation algorithms that are based on linear programming relaxation and randomised rounding are studied. The proposed framework, which aims to maximise the spatial timeslot reuse under predefined signal-to-interference noise ratio thresholds, is suitable for providing centralised scheduling in the mesh mode of the IEEE 802.16 standard. Performance aspects of the approximation algorithms under different scenarios are investigated.     

A two-user approximation-based transmit beamforming for physical-layer multicasting in mobile cellular downlink systems

Multicast has been known as an efficient transmission technique for group-oriented applications such as multi-party video conferencing, video streaming for paid users, online gaming, and social networking. In this paper, we investigate physical-layer multicasting in mobile cellular downlink systems, where the antennas at base station are employed to transmit common signals to multiple users simultaneously. A central design problem of downlink physical-layer multicasting is the search for the optimal beamforming vector that maximizes the multicast rate. Traditionally, the problem has been formulated as a quadratically constrained quadratic programming problem and shown to be NP-hard in general. In this paper, starting from examining the Karush–Kuhn–Tucker stationary conditions, a new method based on two-user approximation is proposed for the search for the optimal beamforming vector. The method is able to achieve a much higher multicast rate than the existing methods and provides an attractive trade-off between performance and complexity, especially for the case of using a large number of antennas. Using a large number of antennas at base station, also known as the large-scale multiple-input and multiple-output technique, has been regarded widely as one of the most promising technologies to increase system capacity, coverage, and user throughput for future generations of mobile cellular systems.     

复杂型面智能生产单元任务−刀具联合动态调度策略

以复杂型面智能生产单元为背景,针对多机器的任务?刀具联合动态调度问题展开研究。通过分析复杂型面智能生产单元的作业流程和特征,建立任务?刀具联合调度问题的数学模型。结合通过对问题进行过程分解的方式构建一种组合规则调度算法生产框架,并通过在框架中嵌入启发式规则的方式生成72种组合规则算法。设计大量的算例测试集,通过对比、分析72种算法在差异化环境配置下的仿真结果,对比不同系统指标下算法的表现情况,发现基于FNOP规则构建的算法在75%的场景中均能取得较优的求解质量。研究成果为车间生产管理人员制定任务?刀具调度策略提供一定指导作用。     

生物计算网格中的在线调度技术研究

研究了在异构网格环境下的生物应用集成,定义了服务的提供者、部署者和使用者三种用户角色,设计了网格环境下的服务和资源整合机制,重点实现了用户管理以及作业调度控制等功能.根据计算资源的异构特点,设计了多种启发式调度算法.考虑到生物计算应用的不同类型,提出了自适应调度算法,该算法根据应用的特点动态选择启发式调度算法.实验表明,非阻塞调度优于阻塞调度方式;自适应调度算法比静态的在线调度算法有更好的性能,而在异构的网络中,带宽优先调度算法的性能比其他静态调度算法性能更好.     

基于仿真的生产计划鲁棒性问题研究

针对多品种小批量的单元化生产环境,基于Plant Simulation平台构建JobShop的鲁棒性调度仿真模型,模型采用预调度和再调度结合框架,通过单元层和设备层的层次化管理算法,实现了计划质量鲁棒性和解的鲁棒性的系统目标.实验表明,算法的应用可得到鲁棒性好的计划,松弛时间的优化分配方法可为确定性调度提供实验支持.     

Game-theoretic medium access control protocol for wireless sensor networks

In the traditional medium access control (MAC) protocols for wireless sensor networks (WSNs), energy consumption is traded for throughput and delay. However, in future WSNs, throughput and delay performance had better not be sacrificed for energy conservation. Here first, an incompletely cooperative game-theoretic heuristic-based constraint optimisation framework is introduced to achieve the goals of throughput, delay and energy conservation simultaneously. Then a simplified game-theoretic MAC (G-MAC) protocol is presented, which can be easily implemented in WSNs. Simulation results show that compared with two typical MAC protocols for WSNs, sensor MAC and timeout MAC, G-MAC can increase system throughput, and decrease delay and packet-loss-rate, while maintaining relatively low energy consumption.     

A model to examine the effect of loading conditions on scheduling rules in a job shop environment

Although a great deal of research has been carried out in the field of job scheduling this has generally been directed towards examining the benefits of particular rules and presenting improved algorithms. This paper examines how real job shop problems can be modelled and available scheduling rules examined for particular capacity loading conditions. A model of a medium-size production job shop is developed and it is shown that, for their particular shop layout and job mix, the performance and ranking of particular rules with respect to certain criteria, change with shop conditions. The model developed can easily be applied to a wide range of job shop situations and once performance charts have been produced for those scheduling rules available, they can be used to aid the existing scheduling system whether manual or computer based.     

Simultaneous versus sequential loading and scheduling of flexible assembly systems

A monolithic and a hierarchical approach is presented for loading and scheduling in a general flexible assembly system and a flexible assembly line. The system is made up of a set of assembly stations of various types each with limited working space and is capable of simultaneously producing a mix of product types. The objective is to determine an assignment of assembly tasks to stations and an assembly schedule for all products so as to complete the products in a minimum time. In the monolithic approach loading and scheduling decisions are made simultaneously. In the hierarchical approach, however, first the station workloads are balanced by solving the loading problem, and then detailed assembly schedule is determined for prefixed task assignments and assembly routes by solving a standard job-shop problem. Mixed integer programming formulations are presented for simultaneous and for sequential loading and scheduling. Loading and scheduling with alternative or with single task assignments are considered. Numerical examples are included to illustrate and compare the two approaches proposed.