Labeling algorithm and its fairness analysis for autonomous system

A kind of packet labeling algorithm for autonomous system is introduced. The fairness of the algorithm for each traffic stream in the integrated-services is analyzed. It is shown that the rate of each stream in the integrated-services would converge to a stable value if the transmittfing or forwarding rates converge to that of the receiving exponentially.

THE INNER-SYSTEM LABELING ALGORITHM AND ITS FAIRNESS ANALYSIS

On the basis of inner-system labeling signaling used in the integrated access system,a kind of inner-system labeling algorithm is introduced in this paper, and the fairness of the algorithm for each traffic stream in the integrated-services is analyzed. The base of this algorithm is Class of Services (CoS), and each packet entering the relative independent area (an autonomous system) would be labeled according to the service type or Quality of Service (QoS) in demand,and be scheduled and managed within the system (the system can be enlarged if conforming to the same protocol). The experimental results show that each of the stream rate in the integratedservices would converge to a stable value if the rates of transmitting converge to that of the receiving exponentially, that is, the effective traffic of each stream would be fair.

EFRED: Enhancement of Fair Random Early Detection Algorithm

Quality of Service (QoS) generally refers to measurable like latency and throughput, things that directly affect the user experience. Queuing (the most popular QoS tool) involves choosing the packets to be sent based on something other than arrival time. The Active queue management is important subject to manage this queue to increase the effectiveness of Transmission Control Protocol networks. Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, Random Early Detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. One of these enhancements of RED is FRED or Fair Random Early Detection attempts to deal with a fundamental aspect of RED in that it imposes the same loss rate on all flows, regardless of their bandwidths. FRED also uses per-flow active accounting, and tracks the state of active flows. FRED protects fragile flows by deterministically accepting flows from low bandwidth connections and fixes several shortcomings of RED by computing queue length during both arrival and departure of the packet. Unlike FRED, we propose a new scheme that used hazard rate estimated packet dropping function in FRED. We call this new scheme Enhancement Fair Random Early Detection. The key idea is that, with EFRED Scheme change packet dropping function, to get packet dropping less than RED and other AQM algorithms like ARED, REM, RED, etc. Simulations demonstrate that EFRED achieves a more stable throughput and performs better than current active queue management algorithms due to decrease the packets loss percentage and lowest in queuing delay, end to end delay and delay variation (JITTER).

Dynamic bandwidth allocation algorithm for full-band utilization

To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized （DFBU） allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth （up to full-bandwidth） while the performance of fairness and QoS requirement is still guaranteed.

Ship hull plate processing surface fairing with constraints based on B-spline

The problem of ship hull plate processing surface fairing with constraints based on B-spline is solved in this paper. The algorithm for B-spline curve fairing with constraints is one of the most common methods in plane curve fairing. The algorithm can be applied to global and local curve fairing. It can constrain the perturbation range of the control points and the shape variation of the curve, and get a better fairing result in plane curves. In this paper, a new fairing algorithm with constraints for curves and surfaces in space is presented. Then this method is applied to the experiments of ship hull plate processing surface. Finally numerical results are obtained to show the efficiency of this method.

Scheduling Algorithm for Multimedia Services in IEEE 802.16e OFDM System

Based on five scheduling types and their QoS requirements defined in IEEE 802.16e specification, this paper proposes a new scheduring algorithm for non-real-time or real-time multimedia services. Taking the performances of efficiency, fairness and complexity into consideration, the proposed algorithm enhances the efficiency of air interface resource at the expense of the short-time unfairness, but ensures the long-time fairness. Moreover, the proposed algorithm introduces an efficient QoS assurance mechanism, which implements the functions of congestion control, queuing management and traffic management. The simulation results based on a simplified traffic model show that the proposed algorithm guarantees better performances of efficiency and fairness than conventional algorithms, without increasing the algorithm complexity. Especially on the occasion of heavy-traffic requirement, the performance of efficiency and fairness can be improved by 50% at most.

Schedule algorithm for mitigating inter-cell interference based on orthogonal complement space

In order to avoid severe performance degradation led by the inter-cell interference (ICI) in orthogonal frequency division multiple access (OFDMA) systems with a frequency reused factor (FRF) of 1,distributed schedule algorithm (DS-OCS) and distributed proportional fairness schedule algorithm (DPFS-OCS) based on orthogonal complement space (OCS) were proposed. The first right and left singular vectors of the channel that the user experienced were selected as the transmitting and receiving beamforming vectors. An interference space was spanned by the left singular vectors of the entire interference users in the same channel. The most suitable user lay in the OCS of the interference space was scheduled to avoid suffering interference from neighboring cells based on the criterion of system capacity maximizing and proportional fairness. The simulation results show that the average system capacity can be improved by 2%-4% compared with the DS-OCS algorithm with the Max C/I algorithm,by 6%-10% compared with the DPFS-OCS algorithm with the PF algorithm.

DYNAMIC BANDWIDTH ALLOCATION ALGORITHM UTILIZING FULL BAND

A kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm is introduced. This algorithm allows a single link to use bandwidth far beyond its fair share bandwidth in a multi-service packet transporting system. Three important parameters as the bound on maximum and minimum bandwidth, the maximum packet delay and the minimum band width utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system to use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.

DISTRIBUTED PROPORTIONAL FAIR FREQUENCY ALLOCATION ACROSS MULTIPLE BASE STATIONS

The problem of distributed proportional fair inter-cell frequency allocation for flat-structured cellular systems is studied in this paper. We firstly propose a framework of the frequency allocation in which the whole frequency allocation process is decomposed into many consecutive stages, then identify that for each stage the key is to find the Maximum Weight Independent Set (MWIS) in a given weighted conflict graph in the distributed manner. A new distributed algorithm for MWIS is described in which each node iteratively exchanges messages with neighbors. With this distributed MWIS algorithm, a new distributed proportional fair frequency allocation scheme is presented. The performance of the proposed algorithm is tested in computer experiments simulating the Long Term Evolution (LTE) cellular systems. Simulation results show the performance of the proposed distributed proportional fair frequency allocation scheme is comparable with the centralized ones.

Utility-optimization dynamic subcarrier allocation algorithm for SC-FDMA systems

Two utility-optimization dynamic subcarrier allocation(DSA) algorithms are designed for single carrier frequency division multiple access system(SC-FDMA).The two proposed algorithms aim to support diverse transmission capacity requirements in wireless networks,which consider both the channel state information(CSI) and the capacity requirements of each user by setting appropriate utility functions.Simulation results show that with considerable lower computational complexity,the first utility-optimization algorithm can meet the system capacity requirements of each user effectively.However,the rate-sum capacity performance is poor.Furthermore,the second proposed utility-optimization algorithm can contribute a better trade-off between system rate-sum capacity requirement and the capacity requirements of each user by introducing the signal to noise ratio(SNR) information to the utility function based on the first utility-optimization algorithm,which can improve the user requirements processing capability as well as achieve a better sum-rate capacity.

可信学习分析构建:风险桎梏、理论纾解与实践解蔽

可信学习分析技术的发展已成为全球研究者共同关注的焦点。国内外学者已就其内涵意蕴、价值逻辑等开展广泛探讨,但也存在关键问题不明、理论边界不清和实践路径模糊等问题。为此,研究以关键问题提炼和理论框架构建为先导,以实践路径的探索和实施为主线,对可信学习分析技术的教育应用进行分析。在实践问题方面,研究分析了阻碍可信学习分析实现的关键因素,包括数据漂移现象所导致的算法失准、样本分布失衡现象导致的算法偏见以及算法黑盒现象导致的决策结果失信等一系列问题。在理论研究方面,研究结合理论与实践问题分析,建立起面向学习环境、数据治理、建模分析和干预反馈四要素的可信学习分析理论框架。随后,研究依托该理论框架,结合相关研究方法和技术,构建了可信学习分析的实践路径,如结合价值敏感设计的伦理调适等。研究为可信学习分析研究从理论到实践提供系统化的解决思路。

多核处理器公平共享并行总线的方法

针对综合化电子系统中多个功能运行于同一多核处理器的不同核同时访问同一并行总线的冲突避免以及实时性问题,提出一种基于最小访问颗粒度的多核处理器公平共享并行总线的方法,并详细介绍了该方法的设计实现及验证。该方法不仅通过为每核分配一个总线操作缓冲队列保障了同一核的总线操作先到先服务,而且通过单个读写操作周期的公平队列算法保障了每核总线操作的实时性。工程实践表明,该方法是一种多核处理器公平共享并行总线的有效方法。

蜂窝网络下同时同频全双工设备到设备组网的干扰协调算法

蜂窝网络下的同时同频全双工(CCFD)设备到设备(D2D)组网可以进一步提升网络频谱效率,然而由此引入的残余自干扰(RSI)及蜂窝用户(CU)与D2D用户(DU)之间共享频谱的干扰会严重影响到蜂窝用户的体验。因此,该文为蜂窝网络下同时同频全双工组网设计了两种干扰协调算法,即CU和速率最大化算法(MaxSumCU)与CU最小速率最大化算法(MaxMinCU),在小区频谱效率得到提升的同时尽可能地保证CU的体验。对于MaxSumCU算法,该文以CU和速率为优化目标建立混合整数非线性规划问题(MINLP),其在数学上为非确定性多项式(NP-hard)问题。算法将其分解为功率控制与频谱资源分配两个子问题,并用图形规划找到最优功率解后,使用二向图最大权值匹配算法决定频谱共享的CU与DU。为了保证每一个蜂窝用户体验的公平性,该文设计了Max Min CU算法用以最大化所有CU速率中的最小值,该算法基于二分查找与二向图最小权值匹配算法来完成用户的资源分配。数值结果表明,与小区和速率最大化(MaxSumCell)设计相比,该文所提的两种算法在提升小区和速率的同时均有效地提升了蜂窝用户的体验。

有向传感器网络中基于公平的目标覆盖最大化问题研究

以视频传感器和图像传感器为代表的有向传感器可以为安全防卫提供有效信息,已经被广泛应用于各种场景。首次提出了有向传感器网络中基于公平的目标覆盖最大化问题:在有向传感器网络中,采用具有P个确定工作方向的有向传感模型,研究基于公平的目标覆盖最大化问题,目的是激活最少的传感器,通过调度有向传感器的工作方向使目标被覆盖的最小累积覆盖时间达到最大,从而保证目标被覆盖的时间尽量均衡。首先选择最少的传感器,保证所有目标位于所选传感器的传感圆之内(该问题是NP-困难问题),为解决该问题设计了近似比为(1+lnγ)的最少传感器选择算法,其中γ=max 1≤i≤N{|s_(i)||s_(i)∈S};其次,基于最大需求优先覆盖的原则,提出了最大的无冲突目标集合选择算法。实验结果表明,该算法能有效解决有向传感器网络中基于公平的目标覆盖最大化问题。

数字平台算法决策歧视的认定与规制

基于算法决策的数字歧视是算法社会化应用中一项亟待解决的问题。算法对于个体的重塑效应是歧视产生的直接原因,而算法之社会化应用过程中的价值冲突则是产生算法歧视的根本原因。由此也导致了算法分析过程呈现出忽略意义的关系分析,以概率性陈述为基础的算法评价所导致的受保护特征的不确定。算法社会化应用中的歧视认定,应当冲破传统反歧视理论,从受保护场景、是否存在算法支配关系、基于受保护特征的差别待遇、对个体或者群体的不利影响以及是否符合比例原则几个角度综合评估。有鉴于此,《个人信息保护法》第24条的相关表述需要进行重新解释和厘定,其中包括决策“公平、公正”、算法解释的内容等;另外,基于算法的数字歧视行为,需同现行侵权制度接榫,并适时进行制度赓续,完善算法歧视的规范治理体系。

RG-BFT:基于随机分组的拜占庭容错算法

随着网络环境的复杂性和网络用户数量的不断增长,区块链的发展逐渐受到共识算法的效率、安全性和可靠性的制约。针对此类问题,提出一种基于随机分组的拜占庭容错算法(random grouping-based Byzantine fault tolerant algorithm, RG-BFT),提高共识算法的效率和可靠性。使用随机选择算法与投票机制相配合,减少共识过程中的节点数量和消息数。此方案具有随机性和公正性,在保证系统活性的前提下,提高了达成共识的效率。实验结果表明,RG-BFT算法能实现较低的共识时延和通信开销及高交易吞吐量。

Maximizing Submodular+Supermodular Functions Subject to a Fairness Constraint

We investigate the problem of maximizing the sum of submodular and supermodular functions under a fairness constraint.This sum function is non-submodular in general.For an offline model,we introduce two approximation algorithms:A greedy algorithm and a threshold greedy algorithm.For a streaming model,we propose a one-pass streaming algorithm.We also analyze the approximation ratios of these algorithms,which all depend on the total curvature of the supermodular function.The total curvature is computable in polynomial time and widely utilized in the literature.

面向船联网的NOMA系统用户公平性研究

非正交多址技术(Non-orthogonal Multiple Access,NOMA)有助于提升船联网的连接数量和频谱效率。通过研究公平性约束下船联网NOMA系统的能量效率优化问题,设计基于速率方差的用户公平性因子,并提出了一种公平性约束下NOMA系统的能量效率优化策略。首先,假设基站到各个簇的发射功率相同且簇内用户数固定,以最大化能量效率作为用户分簇的目标,利用遗传算法对用户分簇方案进行优化;其次,在满足最小公平因子的条件下对簇内用户间的功率分配进行优化。仿真结果表明该优化策略能提高能量效率且用户公平性得到了保证。

High Performance Fairness Algorithm for Resilient Packet Ring

Resilient Packet Ring (RPR) is MAN technology with two counter-rotating rings that multiple stations share the bandwidth. The stations on ring must negotiate the allowed rate that they can transmit fairness eligible traffic based on the total amount of uncommitted bandwidth. RPR draft employs distributed bandwidth control algorithm in order to assure global fairness. In this paper, we suggest a new fairness control algorithm termed Congestion Distributed Fairness Algorithm (CDFA) that exhibits better pe...

多重约束下的受灾点应急物资智能优化调度策略

制定公平有效的应急物资分配策略是降低突发灾害损失的重要保障.在物资缺乏的情况下综合考虑紧急程度、最大化满足率和公平性,提出了一种带多重约束的应急物资调度模型,并提出了一种混合麻雀搜索算法用于模型求解.针对所提模型多重约束条件,设计了平衡解码策略提高所提算法的解码能力,同时设计了局部变换搜索算子提高所提算法的局部寻优能力.实验结果表明,所提模型能够在多重约束条件下能最大限度提高应急物资利用效能,为应急物资分配提供有力支撑;所提算法具有较好的寻优能力,能够得到公平有效的应急物资调度方案,满足应急物资智能优化调度的需要.