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.     

Online combinatorial based mechanism for MEC network resource allocation

In this paper, the resource allocation problem for mobile edge computing (MEC) network is discussed. We focus on the design of online resource allocation strategy by considering the time‐varying demands of the combinatorial resources for the mobile users. To handle this issue, at first, a time splitting‐based online allocation mechanism is introduced. Then, for a given resource allocation period of the time splitting, a combinatorial auction mechanism for the combination resources allocation is proposed. We further prove that the proposed combinatorial auction is both individual rational and incentive‐compatible, and which can bring a higher revenue to the service provider. In order to verify the performance of the proposed mechanism, a variable‐relaxed‐based performance‐bound algorithm and a greedy optimization‐based suboptimal algorithm are presented for comparison purpose. Finally, the performance of these proposed algorithms are testified by numerical simulations, which confirm the analysis results.     

Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network

In order to alleviate the energy consumption problem caused by the increasing number of Internet of things (IoT) nodes,an energy-efficient (EE) maximization based resource allocation algorithm was proposed for multi-carrier wireless-powered backscatter communication network.Firstly,a multivariable and nonlinear resource allocation model was formulated to jointly optimize transmit power,transmission time,reflection coefficient,and energy-harvesting allocation coefficient,where the maximum transmit power constraint of the power station and the minimum harvested energy constraint at the backscatter device were considered.Then,the original non-convex optimization problem was transformed into a convex one which was solved by using Dinkelbach’s method and the variable substitution approach.Furthermore,the analytical solution of the resource allocation problem was obtained based on Lagrange dual theory.Simulation results verify that the proposed algorithm has better EE by comparing it with the existing algorithm under pure backscatter mode and algorithm under the harvested-then-transmit mode.     

Designing scalable on-demand policy-based resource allocation in IP networks

Today, the policy-based management approach is recognized as an efficient solution to simplify the complex task of managing and controlling networks. To this end, the IETF has introduced a reference framework to build PBM systems. However, this framework only addresses the provisioning of relatively long validity period services based on pre-defined service level agreements. Furthermore, very little work addresses the scalability properties of the instantiation of this framework in a real network. This work aims to extend the IETF PBM framework in order to support dynamic provisioning of short term services (end system signaling) as well as an instantiation scheme that is scalable (distributed provisioning of edge routers). This instantiation scheme is based on the distribution of the provisioning process while keeping centralized only the parts that involve critical resources, that is, the bandwidth brokerage. The performance properties of the proposed scheme are then demonstrated throughout both extensive experimentation and a short analytical study. The results of this work are intended to be used as a guideline to help network operators to design scalable PBM system in order to offer to their customers services with QoS assurance in an on-demand basis.     

Energy efficiency resource allocation based on spectrum-power tradeoff in distributed satellite cluster network

Wireless Networks - Distributed satellite cluster network is a novel structure in spatial information network. This paper investigates the spectrum-power tradeoff algorithm for distributed...     

Improved resource allocation strategy in SU-CoMP network

Coordinated multi-point transmission and reception (CoMP) for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple access (OFDMA) systems. Two prevalent approaches in SU-CoMP are coordinated scheduling (CS) and joint processing (JP). Although JP in SU-CoMP has been proved to achieve a great link performance improvement for the cell-edge user, efficient resource allocation (RA) on the system level is quite needed. However, so far limited work has been done considering JP, and most existing schemes achieved the improvement of cell-edge performance at cost of the cell-average performance degradation compared to the single cell RA. In this paper, a two-phase strategy is proposed for SU-CoMP networks. CS and JP are combined to improve both cell-edge and cell-average performance. Compared to the single cell RA, simulation results demonstrate that, the proposed strategy leads to both higher cell-average and cell-edge throughput.     

Computation energy efficiency maximization based resource allocation scheme in wireless powered mobile edge computing network

For wireless powered mobile edge computing (MEC) network,a system computation energy efficiency (CEE) maximization scheme by considering the limited computation capacity at the MEC server side was proposed.Specifically,a CEE maximization optimization problem was formulated by jointly optimizing the computing frequencies and execution time of the MEC server and the edge user(EU),the transmit power and offloading time of each EU,the energy harvesting time and the transmit power of the power beacon.Since the formulated optimization problem was a non-convex fractional optimization problem and hard to solve,the formulated problem was firstly transformed into a non-convex subtraction problem by means of the generalized fractional programming theory and then transform the subtraction problem into an equivalent convex problem by introducing a series of auxiliary variables.On this basis,an iterative algorithm to obtain the optimal solutions was proposed.Simulation results verify the fast convergence of the proposed algorithm and show that the proposed resource allocation scheme can achieve a higher CEE by comparing with other schemes.     

C-RAN架构中适用于干扰消除的资源分配机制

针对在C-RAN( Clean-Radio Access Network)架构无线网络中的干扰消除机制会带来背景噪声放大的问题,利用C-RAN架构网络的集中式处理,从而可以对全网络系统求解干扰。在定义网络背景噪声放大因子的基础上,将网络中背景噪声放大的最小化问题建立为以资源分配集合为可行空间、以最小化背景噪声放大因子为目标函数的最优化数学模型,并给出了利用遗传算法进行求解的方法,在此基础上设计了资源分配的机制。对该机制的仿真结果表明：将此机制应用到C-RAN构架网络中,能有效降低误码率,提升网络中用户公平性和吞吐量。     

车联网中网络切片资源分配方案

为了满足车联网中不同应用的服务质量(Quality of Service, QoS)要求,提出了一种基于网络切片技术的车联网频谱资源分配方案。该方案考虑数据接入控制,通过联合优化频谱资源块(Resource Block, RB)分配和车辆信号发射功率控制,在安全服务切片低时延高可靠性的约束下,最大化信息娱乐服务切片的平均和吞吐量。将车联网资源管理建模为一个混合整数随机优化问题,利用李雅普诺夫(Lyapunov)优化理论将该优化问题分解为接入控制和RB分配与功率控制两个子问题,并分别对其进行求解,得到每个时隙的接入控制和资源分配方案。仿真结果表明,所提出的资源分配方案能够有效提高信息娱乐服务切片的平均和吞吐量,并且可以通过调整引入的控制参数值来实现吞吐量和时延的动态平衡。同时,与已有方案相比,该方案具有更好的时延性能。     

A resource allocation and cell association algorithm for energy efficiency in HetNets

Aiming at further improving the energy efficiency of system while meeting the data rate requirement of the users, in this paper, a network energy efficiency optimization problem by jointly optimizing the resource allocation of macrocells and small cells is formulated and proven to be an NP‐hard problem, which cannot be worked out by direct methods in polynomial time. Considering the effectiveness of the modified particle swarm optimization (MPSO) algorithm, an MPSO‐based resource allocation and cell association algorithm is employed to solve the proposed joint optimization problem where the frequency resource partitioning of the macrocells, the transmission power, and the cell‐association bias of the small cells are jointly optimized. During the implementation of the optimization algorithm, the cell association alters with the transmission power and cell‐association bias adjustment, and the small cells where there are no active users associating with them will be turned off. The data rate requirement of the users is an indispensable metric in the communication system. Taking no account of the data rate requirement of the users, the frequency resource partitioning and cell association alteration will deteriorate the data rate of a few of users. Under such circumstances, we take the users' data rate requirement as a constraint of the joint optimization problem. The system level simulation results show that, by jointly optimizing the resource allocation of macrocells and small cells while guaranteeing the users' data rate requirement, the energy efficiency and system throughput can be further improved, and energy consumption can be further reduced.     

网络虚拟化中动态资源分配算法研究

针对网络虚拟化中资源分配问题,提出一种动态的资源分配算法。算法根据物理节点平均负载差异度,结合当前物理网络容忍的节点负载差异动态地进行虚拟节点迁移,并通过综合影响因子为虚拟节点选择合适的目标宿主,减少虚拟节点迁移对物理链路带宽和虚拟链路时延的影响。仿真实验表明,该算法能使物理节点上的负载分布均衡,同时对时延和带宽的影响较小。     

Quality-focused resource allocation for resilient 5G network

Photonic Network Communications - The upcoming 5G cellular wireless network brings new challenges and problematic issues in providing services with different quality of service (QoS) requirements...     

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。     

无线mesh网络中可信协同信道资源分配策略

为了有效提升无线mesh网络信道资源的利用率和网络服务质量,提出基于可信协同的信道资源分配策略.针对节点自适应特点,引入博弈理论、建立节点的信誉机制以实现节点可信协同并优化信道分配结果.仿真实验分别对节点服务等级、网络收益结果作相应评价.实验结果发现节点服务等级对节点网络收益有直接影响,当协同服务等级达到3时,网络收益状况最佳,此时节点跳数与服务等级呈协同关系;对比经典协同算法,在相同网络拓扑环境下,可信协同信道资源分配策略分别是UACRR算法、DMP-MBA算法的1.04倍、1.069倍,明显占优.     

超密集网络中基于能效最优的资源分配算法

为了实现超密集网络中的绿色通信,提出一种基于能效最优的资源分配算法。首先,在考虑用户服务质量（quality of service,QoS）需求和干扰容限的情况下,建立最大化网络能效的优化问题。其次,为了降低求解原问题的计算复杂度,采用柯西不等式将原优化问题进行松弛,从而转化为非合作博弈问题。进而,在满足最大最小公平（max-min fairness,MMF）准则的情况下,提出一种分布式能效最优算法（distributed EE maximization algorithm,DEMA）。仿真结果表明,所提算法较传统算法可以更好地兼顾系统的能效和吞吐量性能。     

LTE-A多小区中继网络两跳速率匹配资源分配算法

针对中继网络的两跳特性,提出一种多小区中继网络两跳速率匹配资源分配算法。首先,在第一个子时隙内各小区独立地为小区中所有用户分配子载波,并根据子载波分配结果,建立基于非合作博弈的功率分配模型;然后,由第一跳资源分配结果对第二跳速率匹配,自适应地为中继分配资源以满足边缘用户的速率需求。仿真结果表明,该算法在满足边缘用户速率需求的前提下,进一步提高了中心用户的吞吐量,同时降低了系统的发射功率,从而提升了系统性能。     

中继蜂窝网络中动态无线资源分配方案

提出一种中继蜂窝网络中基于动态复用分割的无线资源分配方案。该方案在所设计的帧结构基础上,从时间域和频率域进行联合的资源分配。其基本思想是通过小区间的协作使频带资源可以最有效的复用来提高系统性能。仿真结果论证了该方案在小区容量方面可以获得较大的增益。     

An elastic resource allocation algorithm enabling wireless network virtualization

Following the wired network virtualization, virtualization of wireless networks becomes the next step aiming to provide network or infrastructure providers with the ability to manage and control their networks in a more dynamic fashion. The benefit of the wireless mobile network virtualization is a more agile business model where virtual mobile network operators (MNOs) can request and thus pay physical MNOs in a more pay‐as‐you‐use manner. This paper presents some resource allocation algorithms for joint network virtualization and resource allocation of wireless networks. The overall algorithm involves the following two major processes: firstly, to virtualize a physical wireless network into multiple slices, each representing a virtual network, and secondly, to carry out physical resource allocation within each virtual network (or slice). In particular, the paper adopts orthogonal frequency division multiplexing (OFDM) as its physical layer to achieve more efficient resource utilization. Therefore, the resource allocation is conducted in terms of sub‐carriers. Although the motivation and algorithm design are based on IEEE 802.16 or WiMAX networks, the principle and algorithmic essence are also applicable to other OFDM access‐based wireless networks. The aim was to achieve the following design goals: virtual network isolation and resource efficiency. The latter is measured in terms of network throughput and packet delivery ratio. The simulation results show that the aforementioned goals have been achieved. Copyright © 2012 John Wiley & Sons, Ltd.