Dynamic resource allocation tor multimedia services in mobilecommunication environments

As demand for networked multimedia applications is increasing rapidly, it is important to provide these services in mobile communication environments. In this paper, we identify system requirements for base stations in order to support multimedia services. These requirements include supporting concurrent connections for multiple users, allocation of resources dynamically to satisfy diverse resource requirements for multimedia applications, and reallocation of resources during handoff incurred by user movement or newly generated calls. These requirements can be used to design an interface between land-based and mobile environments to handle one of the most challenging issues in multimedia communication: enforcing interstream and intrastream synchronizations. We propose two quality of presentation (QOP) parameters for evaluating the quality of mobile multimedia connections, and analyze the validity of these requirements     

多业务多用户OFDM系统中的资源快速分配方案

本文提出了多用户OFDM系统下行链路中的一种快速实用的资源分配算法.该算法以最大化系统吞吐量为目的,同时满足CBR(固定速率)和VBR(可变速率)用户的QoS(服务质量)要求.算法使用分组代替迭代计算,摒弃复杂的子载波交换操作,以极低的复杂度实现了等功率下的自适应子载波分配和比特加载.本文在选择性衰落信道下对算法进行评估,并与[6]中的算法比较.仿真表明,该算法可以在更低的复杂度D(KN log N 2KN)下实现与[6]同样的吞叶量.     

基于能效和异构服务的密集家庭小区资源分配

密集家庭小区网络提高了网络容量,同时也严重增大了网络的能耗。为了提高家庭基站网络的能效,针对密集家庭小区场景,联合考虑家庭用户的异构服务、电路功率、网络的跨层干扰,提出了最大化家庭用户总能效的资源分配算法,利用Dinkelbach理论和拉格朗日对偶分解理论,求解了该优化问题的闭式解,并分析了算法复杂度。仿真结果表明,所提的资源分配算法具有更高的网络能效,比已有资源分配算法的能效提高了约20%。     

Prioritized resource allocation for stressed networks

Overloads that occur during times of network stress result in blocked access to all users, independent of importance. These overloads can occur because of degraded resource availability or abnormally high demand. Public broadband networks must dynamically recognize some multimedia connections as having greater importance than others and allocate resources accordingly. A new approach to connection admission control is proposed that uses an upper limit policy to optimize the admission of connections based on the weighted sum of blocking across traffic classes. This results in a simple algorithm suitable for multimedia and packet networks. This work is also the first to demonstrate that the use of an upper limit policy is superior to traditional approaches of adding extra capacity or partitioning capacity, both in terms of the amount of resources required and sensitivity to load variations. An upper limit policy can also be deployed much faster when a large overload occurs from a disaster event     

Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

Recently, the deployment of novel smart network concepts, such as the Internet of things (IoT) or machine‐to‐machine communication, has gained more attention owing to its role in providing communication among various smart devices. The IoT involves a set of IoT devices (IoTDs) such as actuators and sensors that communicate with IoT applications via IoT gateways without human intervention. The IoTDs have different traffic types with various delay requirements, and we can classify them into two main groups: critical and massive IoTDs. The fundamental promising technology in the IoT is the advanced long‐term evolution (LTE‐A). In the future, the number of IoTDs attempting to access an LTE‐A network in a short period will increase rapidly and, thus, significantly reduce the performance of the LTE‐A network and affect the QoS required by variant IoT traffic. Therefore, efficient resource allocation is required. In this paper, we propose a priority‐based allocation scheme for multiclass service in IoT to efficiently share resources between critical and massive IoTD traffic based on their specific characteristics while protecting the critical IoTDs, which have a higher priority over the massive IoTDs. The performance of the proposed scheme is analyzed using the Geo/G/1 queuing system focusing on QoS guarantees and resource utilization of both critical and massive IoTDs. The distribution of service time of the proposed system is determined and, thus, the average waiting and service times are derived. The results indicate that the performance of the massive IoTDs depends on the data traffic characteristics of the critical IoTDs. Furthermore, the results emphasize the importance of the system delay analysis and demonstrate its effects on IoT configurations.     

Cluster-based resource allocation mechanism for Femtocell network

A based-cluster resource allocation mechanism was proposed for suppressing interference between Femtocell and Macrocell in Macro-Femto network.The mechanism included three parts,FBS was put in disjoint clusters by graph theory and convex optimization,then a sub-channel allocation algorithm was adopted to assign sub-channel to the FUE and MUE based on fairness of rate.In the end,power allocation was performed by using distributed algorithm.Simulation results show that the proposed mechanism effectively suppresses cross-tier and co-tier interference in the Macro-Femto network,improves the average rate,meanwhile satisfies the requirements of fairness of rate,which makes users more satisfied.     

Real-time resource allocation for LEO satellite constellations

The paper addresses the need of controling the access of terminals with guaranteed ressources on the high dynamic systems offered by LEO satellite constellations. A call-access-control scheme that guarantees the reservation of permanent resources of satellite constellations in $O(\sqrt(n)\hbox{log}(n))The paper addresses the need of controling the access of terminals with guaranteed ressources on the high dynamic systems offered by LEO satellite constellations. A call-access-control scheme that guarantees the reservation of permanent resources of satellite constellations in time, where n is the number of user present in the system, is described. A tradeoff between computational time of call-access-control and optimization of the use of the spectrum is identified. Some experimental results are presented.

Jér?me GaltierEmail:

     

Distributed resource allocation schemes

In this article, we discuss distributed resource allocation schemes in which each transmitter determines its allocation autonomously, based on the exchange of interference prices. These schemes have been primarily motivated by the common model for spectrum sharing in which a user or service provider may transmit in a designated band provided that they abide by certain rules (e.g., a standard such as 802.11). An attractive property of these schemes is that they are scalable, i.e., the information exchange and overhead can be adapted according to the size of the network.     

基于天线波束成形的OFDMA系统的自适应资源分配

对正交频分复用接入系统在多用户多天线传输情况下的自适应资源分配策略进行了研究,提出了一种基于天线波束成形的,包括动态子载波分配、自适应调制、比特加载的无线资源分配方案.算法的优化设计目标是在满足总的恒定传输比特数和误比特率性能要求的情况下,使得系统总的发射功率最小.仿真结果表明,由于多天线阵列增益和多用户分集增益,系统整体性能得到了明显的优化.     

Computational models and resource allocation for supercomputers

There are several different architectures used in supercomputers, with differing computational models. These different models present a variety of resource allocation problems that must be solved. The computational needs of a program must be cast in terms of the computational model supported by the supercomputer, and this must be done in a way that makes effective use of the machine's resources. This is the resource allocation problem. The computational models of available supercomputers and the associated resource allocation techniques are surveyed. It is shown that many problems and solutions appear repeatedly in very different computing environments. Some case studies are presented, sowing concrete computational models and the allocation strategies used     

毫微微小区中一种基于分组的资源分配方法

为有效解决毫微微小区间( Femtocell)干扰,采用分布式方式对毫微微小区进行资源管理。首先,对毫微微接入点( FAPs)进行分组。基于Lingo数学建模的思想,提出了一种解决分组优化问题的算法。该算法在使用分支定界算法寻找最优解的同时,通过建立单纯形表剪去偏离最优解方向的分支;其次,每组选择一个簇头为本组内FAPs分配资源,为此,提出了新的子信道分配方法,该方法根据干扰指示矩阵修正子信道分配的情况。仿真结果表明：和其他算法相比,提出的算法不仅能找到分组优化问题的最优解,并且效率更高;另外,提出的资源分配算法不仅减小了用户间干扰,而且提高了户间速率公平。     

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage, Heterogeneous Network (HetNet) has attracted the attention of many scholars in recent years. Additionally, with the introduction of the Non-Orthogonal Multiple Access (NOMA) technology, the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource, which makes the NOMA-assisted HetNet a hot topic. However, traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains, which is impractical for practical HetNets due to the impact of channel delays and random perturbation. To further improve energy utilization and system robustness, in this paper, we investigate a robust resource allocation problem to maximize the total Energy Efficiency (EE) of Small-Cell Users (SCUs) in NOMA-assisted HetNets under imperfect channel state information. By considering bounded channel uncertainties, the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users, the maximum transmit power of small base station, the Resource Block (RB) assignment, and the quality of service requirement of each SCU. The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method. A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation. Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.     

Cross-layer wireless resource allocation

A fundamental problem in networking is the allocation of limited resources among the users of the network. In a traditional layered network architecture, the resource to be allocated at the medium access control (MAC) and network layers utilizes communication links, viewed as "bit pipes" that deliver data at a fixed rate with occasional random errors. Though this separation has many advantages, there is a growing awareness that this simple bit-pipe view is inadequate, particularly in the context of modern wireless data networks. In this article, several basic cross-layer resource allocation problems for wireless fading channels are considered. The article focuses on the characterization of fundamental performance limits while taking into account both network layer QoS and physical layer performance.     

Efficient spectrum allocation for personal communications services

Principal features of personal communications service (PCS), namely, ubiquity, portability, and integration of voice and data, are examined, highlighting some issues affecting the spectrum choices before today's policymakers. Spectrum issues are discussed, focusing on two tools for promoting efficient spectrum use: the use of generic service definitions and band assignment     

用于资源动态预留的航天测控资源配置优化算法

针对航天测控资源配置优化问题这类约束条件繁杂且数量众多的组合优化问题,提出了可用于资源动态预留的航天测控资源配置优化算法。具体来讲,考虑测控设备和航天器执行任务的唯一性约束以及时间窗口冲突约束,建立了基于原子型任务调度的0-1整数规划模型;设计了能将实际需求和求解算法进行解耦的求解框架,并基于最大化利用测控资源的思想获得了可回溯的并行最佳优先搜索算法。仿真结果表明,所提算法达到了能在国内东部、西部、南部和北部四大测控区域中更加均衡地动态预留出更多、更重要测控设备的资源配置优化效果。     

使用对偶分解的MU-CoMP-JT联合资源分配

在MU-Co MP-JT(Multi-User Coordinated Multiple-Points Joint Transmission)联合资源分配问题中,传统的迫零预编码矩阵会使得每根天线发送功率互不相同,当Co MP节点发射功率仅满足总功率约束时性能损失不明显,而当Co MP节点分布在不同的地理位置时将受到单节点功率约束,这势必会降低系统功率利用率。为了进一步提升系统吞吐量,基于对偶分解理论提出了一种联合预编码优化的资源分配算法。该算法以最大化用户权重速率为目标,将原优化问题分解成若干个优化的子问题,不同子问题对应不同接收天线数的联合优化问题。当子信道的发送天线数大于接收天线数时,通过多次迭代计算得到预编码矩阵,并且预编码矩阵会随着拉格朗日因子的变化而变化。仿真结果表明所提联合预编码优化的联合资源分配算法能够明显提升系统吞吐量,且提高天线功率利用效率。     

一种多业务交换机的分区资源分配方法

文章首先介绍了多业务交换机的多个国际标准化组织提出的参考模型,并在此基础上针对各模型中的主要问题之一即交换机的分区问题阐述了其实现模型.文章最后针对分区中最为复杂的分区方式即动态分区,提出了一种算法和实现方案。     

一种MIMO系统中的新型资源分配算法

本文提出了一种MIMO(Multi-Input and Multi-Output)系统中的新型自适应调制和功率分配算法,在奇异值分解的基础上通过注水算法进行功率分配,此后根据所分配的功率与信道状态信息来确定自适应调制的门限及相应的调制阶数,并在自适应调制后通过功率修正因子来弥补常见算法中功率不能得到有效利用的问题,仿真结果表明该算法可以得到较高的频谱效率.     

A sustainable genetic algorithm for satellite resource allocation

A hybrid genetic algorithm (GA) is used to schedule tasks for a satellite, which can be modeled as a robot whose task is to retrieve objects from a two-dimensional field. The objective is to find a schedule that maximizes the value of objects retrieved. Typical of the real-world tasks to which this corresponds is the scheduling of ground contacts for a communications satellite. An important feature of our application is that the amount of time available for running the scheduler is not necessarily known in advance. This requires that the scheduler produce reasonably good results after a short period but that it also continue to improve its results if allowed to run for a longer period. We satisfy this requirement by developing what we call a sustainable GA.     

基于扩展自动机的服务组合静态与动态验证方法

针对目前Web服务组合研究中缺少对定量属性的验证以及在服务运行过程中缺乏对出现异常时的故障处理等问题,提出了一种基于扩展有限自动机的Web服务组合静态与动态验证方法。该方法首先对有限自动机进行扩展,建立了一个可以描述数据及时间等信息的Web服务组合形式化模型;基于该模型,采用计算树逻辑(CTL)描述相关属性,并利用模型检测工具UPPAAL对Web服务组合的行为属性、时间属性以及数据属性等进行了验证;最后结合所建立的诊断模型,给出了一种能够对Web服务组合运行过程中出现异常时进行有效处理的错误诊断算法。