A load balancing multi-path routing scheme based on effective voids for optical burst switching networks

Multi-path routing in the optical burst switching(OBS) networks can reduce the burst loss probability(BLP) by distributing the data burst traffic to multiple paths, compared with single path routing. Unlike the other multi-path routing schemes without considering the carrying capability of the routes, a new multi-path routing scheme based on effective voids(MPEV) is proposed to balance the load of multi-path and reduce the BLP in the paper. MPEV scheme first obtains the information on effective voids of the bottleneck link of multipath by sending a probe packet periodically. The effective voids can accommodate data bursts and accurately represent the available channel resource that is the main determinant of the BLP for OBS networks without optical random access memory. Then MPEV scheme distributes the burst traffic between an ingress node and an egress node to multiple link-disjoint paths by the ratio of the effective voids. More traffic is distributed to the path that has more effective voids, and vice versa. And the distributed amount is proportional to the effective voids of the bottleneck link. So MPEV scheme can balance the load of multi-path routes and can effectively reduce the BLP by avoiding the high load of a single path. And it is easy to implement and agilely adapt to dynamic network traffic. The performance of MPEV scheme is analyzed by queuing theory and is evaluated by simulation. The numerical results show that the proposed scheme can effectively reduce the BLP and balance the traffic load over multiple paths at the same time.     

MBA:A market-based approach to data allocation and dynamic migration for cloud database

With the coming shift to cloud computing,cloud database is emerging to provide database service over the Internet.In the cloud-based environment,data are distributed at Internet scale and the system needs to handle a huge number of user queries simultaneously without delay.How data are distributed among the servers has a crucial impact on the query load distribution and the system response time.In this paper,we propose a market-based control method,called MBA,to achieve query load balance via reasonable data distribution.In MBA,database nodes are treated as traders in a market,and certain market rules are used to intelligently decide data allocation and migration.We built a prototype system and conducted extensive experiments.Experimental results show that the MBA method significantly improves system performance in terms of average query response time and fairness.     

Achieve load balancing with a dynamic re-routing CICQ switching scheme

Multi-path based routing and switching can achieve network-wide load balancing and reduce the port conflicts of switching devices.Motivated by this novel idea,in this paper,through analyzing the feasibility of implementing multi-next-hops in core switching networks comprehensively,we advance a switching scheme called MHRS(multi-next-hop re-routing switch)and a forwarding table management scheme called HMFT(hierarchical multi-stage forwarding table)to support multi-next-hop dynamical re-routing.MHRS implements dynamical re-routing in the switches according its congestion status to achieve real-time load balancing,while HMFT can provide traffic with different forwarding paths based on their QoS requirements.Theoretical analysis and simulation results show that switches equipped with HMFT and MHRS can provide good delay and throughput performance.Besides,they can reduce port conflicts significantly.     

Achieving fair service with a hybrid scheduling scheme for CICQ switches

Providing performance guarantees for arriving traffic flows has become an important measure for today’s routing and switching systems. However, none of current scheduling algorithms built on CICQ (combined input and cross-point buffered) switches can provide flow level performance guarantees. Aiming at meeting this requirement, the feasibility of implementing flow level scheduling is discussed thoroughly. Then, based on the discussion, it comes up with a hybrid and stratified fair scheduling (HSFS) scheme, which is hierarchical and hybrid, for CICQ switches. With HSFS, each input port and output port can schedule variable length packets independently with a complexity of O(1). Theoretical analysis show that HSFS can provide delay bound, service rate and fair performance guarantees without speedup. Finally, we implement HSFS in SPES (switch performance evaluation system) to verify the analytical results.     

A unified algorithm for mobility load balancing in 3GPP LTE multi-cell networks

3GPP long term evolution (LTE) is a promising candidate for the next-generation wireless network, which is expected to achieve high spectrum efficiency by using advanced physical layer techniques and flat network structures. However, the LTE network still faces the problem of load imbalance as in GSM/WCDMA networks, and this may cause significant deterioration of system performance. To deal with this problem, mobility load balancing (MLB) has been proposed as an important use case in 3GPP self-organizing network (SON), in which the serving cell of a user can be selected to achieve load balancing rather than act as the cell with the maximum received power. Furthermore, the LTE network aims to serve users with different quality-of-service (QoS) requirements, and the network-wide objective function for load balancing is distinct for different kinds of users. Thus, in this paper, a unified algorithm is proposed for MLB in the LTE network. The load balancing problem is first formulated as an optimization problem with the optimizing variables being cell-user connections. Then the complexity and overhead of the optimal solution is analyzed and a practical and distributed algorithm is given. After that, the proposed algorithm is evaluated for users with different kinds of QoS requirements, i.e., guaranteed bit rate (GBR) users with the objective function of load balance index and non-GBR (nGBR) users with the objective function of total utility, respectively. Simulation results show that the proposed algorithm leads to significantly balanced load distribution for GBR users to decrease the new call blocking rate, and for nGBR users to improve the cell-edge throughput at the cost of only slight deterioration of total throughput.     

Performance evaluation of mesh-based NoCs: Implementation of a new architecture and routing algorithm

This paper presents the result of experiments conducted in mesh networks on different routing algorithms, traffic generation schemes and switching schemes. A new network on chip (NoC) topology based on partial interconnection of mesh network is proposed and a routing algorithm supporting the proposed architecture is developed. The proposed architecture is similar to standard mesh networks, where four extra bidirectional channels are added which remove the congestion and hotspots compared to standard mesh networks with fewer channels. Significant improvement in delay (60% reduction) and throughput (60% increase) was observed using the proposed network and routing when compared with the ideal mesh networks. An increase in number of channels makes the switches expensive and could increase the area and power consumption. However, the proposed network can be useful in high speed applications with some compromise on area and power.     

A Parallel Interval Computation Model for Global Optimization with Automatic Load Balancing

In this paper,we propose a decentralized parallel computation model for global optimization using interval analysis.The model is adaptive to any number of processors and the workload is automatically and evenly distributed among all processors by alternative message passing.The problems received by each processor are processed based on their local dominance properties,which avoids unnecessary interval evaluations.Further,the problem is treated as a whole at the beginning of computation so that no initial decomposition scheme is required.Numerical experiments indicate that the model works well and is stable with different number of parallel processors,distributes the load evenly among the processors,and provides an impressive speedup,especially when the problem is time-consuming to solve.     

加密网络流量类型识别研究

针对传统的检测方法无法识别加密网络流量类型的问题,对加密网络流量类型的识别进行了研究。从加密后保持不变的网络流量特征着手,提出了通过统计数据包长度、数据包到达时间间隔以及流的方向等方法可以正确地识别加密网络流量类型,最后设计出加密网络流量类型识别的模型和相应的加密网络流量实时识别方案,通过对该方案的验证表明采用该方案能够获得较好的效果。     

On the designing principles and optimization approaches of bio-inspired self-organized network: a survey

A plethora of studies on self-organization has been carried out in broad areas including chemistry, biology, astronomy, medical science, telecommunications, etc., in both academia and industry. Following the studies on swarm intelligence observed in social species, the artificial self-organized systems are expected to exhibit some intelligent features (e.g., flexibility, robustness, decentralized control, self-evolution, etc.) that may have made social species so successful in the biosphere. In this paper, the application of swarm intelligence in communications networks will be studied, and we survey different aspects of bio-inspired mechanisms and examine various algorithms that have been proposed to improve the performance of artificial systems. Some fundamental self-organized networking (SON) mechanisms, designing principles and optimization approaches for artificial systems will then be investigated, followed by some well-known bio-inspired algorithms (e.g., cooperation, division of labor, distributed network synchronization, load balancing, etc.) as well as their applications to the maintenance/operation/optimization of artificial systems being analyzed. Besides, some new emerging technologies, such as the Self-X capabilities and cognitive machine-to-machine (M2M) optimization for the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE)/LTE-Advanced systems, are also surveyed. Finally, the remaining challenges to be faced in designing the future heterogeneous systems will be discussed.     

Resource management in radio access and IP-based core networks for IMT Advanced and Beyond

The increased capacity needs, primarily driven by content distribution, and the vision of Internet-of-Things with billions of connected devices pose radically new demands on future wireless and mobile systems. In general the increased diversity and scale result in complex resource management and optimization problems in both radio access networks and the wired core network infrastructure. We summarize results in this area from a collaborative Sino-Swedish project within IMT Advanced and Beyond, covering adaptive radio resource management, energy-aware routing, OpenFlow-based network virtualization, data center networking, and access network caching for TV on demand.     

基于逐跳计算的分布式负载均衡算法

网络中流量的不断增长容易导致流量不均衡、网络拥塞,进而影响用户的体验。因特网服务提供商（ISP）通常采用优化开放最短路径优先（OSPF）权值（OPW）算法应对网络拥塞,然而该算法存在三个方面的问题：1）需要实际流量矩阵;2）容易导致网络震荡;3）OPW已经被证实为NP难题,并且需要采用集中式方法求解。针对OPW算法存在的问题,提出了一种基于逐跳计算的分布式负载均衡算法（DLBH）。首先,为所有节点设置虚拟流量;然后,根据虚拟流量计算所有链路的代价;最后,采用分布式算法计算最优路由。DLBH采用分布式方法解决网络拥塞问题,而OPW只能采用集中式方法解决网络拥塞问题,因此DLBH的扩展性优于OPW的扩展性。理论分析表明,DLBH的时间复杂度远远小于OPW的时间复杂度。实验结果表明,DLBH的最大链路利用率明显低于OPW算法的最大链路利用率,大幅降低了网络拥塞。     

MF-DLB: Multimetric forwarding and directed acyclic graph-based load balancing for geographic routing in FANETs

Flying ad hoc network (FANET) comprising unmanned aerial vehicles (UAVs) emerges as a promising solution for numerous military and civil applications. Transferring data collected from the environment to the ground station (GS) is a primary concern for meeting the communication demands of most of these applications. However, the highly mobile UAVs with limited communication range, resulting in frequent topology change and intermittent connectivity, make data routing challenging. In such scenarios, geographic routing is a viable solution due to its scalability and robustness. However, the basic forwarding mechanism of geographic routing favors the neighboring UAV nearest to the destination, impacted substantially by link failures and routing holes in a dynamic environment. Additionally, routing decisions ignoring the current load over UAVs contribute to performance degradation due to the high concentration of data traffic near the GS. Thus, to address these issues, a geographic routing protocol named MF-DLB comprising multimetric forwarding (MF) and a directed acyclic graph-based load balancing (DLB) scheme is proposed to enhance packet forwarding in FANETs. MF takes account of multiple metrics related to connectivity, geographic progress, link lifetime, and residual energy to select the next hop with a stable communication link while effectively bypassing the routing holes. The second scheme, DLB, focuses on proactively maintaining routing paths near GS for load distribution among underutilized nodes to address the congestion problem. Simulations performed in network simulator ns-3 confirm the outperformance of MF-DLB over other related routing schemes in terms of different performance metrics.     

基于POMDP的负载均衡贪婪转发策略

针对贪婪地理路由协议的贪婪转发策略在业务量比较大时系统吞吐量急剧下降、网络节点能量消耗严重不平衡,缩短了系统的使用寿命,提出一种基于部分状态可观测的马尔可夫决策理论的负载均衡贪婪转发策略,设定队列长度剔除门限值,有效地控制传输路径上节点的队列长度,通过避开负载较重的节点来实现网络负载均衡。仿真结果表明,该算法能降低端到端时延、减少数据分组的丢失、提高网络数据传输的实时性和可靠性。     

一种区分服务域内的IP流量规划方法

IP流量规划与区分服务结合是增强网络服务质量保证的新方法.在分析区分服务对流量规划需求的基础上,设计了区分服务与流量规划结合的功能框架,提出了适合流量规划要求的队列调度方法和流量分割与映射的原理与方法.流分割方法基于表对数据流进行分割.该方法既能体现区分服务数据包的转发优先级的差异,又能保证数据流的延迟与同步要求.     

基于负载感知的数据流动态负载均衡策略

针对大数据流式计算平台中存在节点间负载不均衡、节点性能评估不全面的问题,提出基于负载感知算法的动态负载均衡策略,并将算法应用于Flink数据流计算平台中。首先通过有向无环图的深度优先搜索算法获取节点的计算延迟时间作为评估节点性能的依据,并制定负载均衡策略;然后基于数据分块管理策略实现流式数据的节点间负载迁移技术,通过反馈实现全局和局部的负载调优;最后通过实验评估时空代价论证算法的可行性,并讨论重要参数对算法执行效果的影响。经实验验证算法通过优化流式计算任务的负载分配提高了任务的执行效率,与采用Flink平台现有的负载均衡策略相比,任务执行时间平均缩短6.51%。     

基于MPLS流量工程的多路径负载均衡方法

对多协议标签交换（MPLS）流量工程负载均衡问题，提出了两种多路径基于约束的负载均衡方法，在LSP建立初期就融入负载均衡思想。在通常的CSPF算法中，对于一个大带宽约束很可能无法找到可行路径，文中所提方法在没有单一路径满足带宽约束时，能将带宽约束划分为两个或多个子约束，并为每一子约束找到约束路径。实验结果表明，所提方法能增加路径建立的成功率，提高网络资源利用率，达到流量均衡。     

多检测引擎监测的动态负载均衡算法

为解决多引擎入侵检测系统的负载均衡问题,提出一种检测引擎的动态负载调节算法。首先,监测各引擎节点计算负载;然后,以过载或空载节点出现为调度时机,以会话为单位调度重负载节点的流量到低负载节点,并遍历节点进行负载均衡的调节。由于以会话为调度单位,算法并不以负载的绝对平均为目的,只需保障各引擎节点不出现过载或空载即达到基本目标。采用KDD cup99数据集进行模拟实验,实验结果表明,与平均分配流量算法和基于较大流调整的安全分流算法相比,所提算法对检测引擎基于会话的负载均衡效果显著,运行开销较低且降低了重负载状态下的丢包率,有利于提高入侵检测系统的检测率。     

MPLS的基于最小干涉的负载均衡算法研究

当MPLS网络中的业务流请求存在时间上的先后顺序时,选择一个高效的路由算法使得已存在的业务流的LSP对后续业务流的LSP路由影响最小变得很重要.在分析了常用的几种QoS保障的算法基础上,提出了一种基于最小干涉的负载均衡算法.该算法解决了MPLS网络中所有"入口/出口对"之间的业务流相互干扰的问题,为后续业务流路由预留了必要的"关键链路".     

基于时间偏差协议的动态负载平衡技术*

对并行VHDL模拟的特殊性进行分析后,建立了一个并行VHDL模拟的动态负载平衡模型。在此模型中,提出动态调节最佳并行规模的动态负载平衡方法来解决系统资源紧张的问题,采用一种新的模拟中负载的度量方法——模拟推进度。此模型还包括基于标准偏差和最小通信变化量的动态负载平衡算法和一个运行中的负载迁移机制。最后对该模型进行可行性分析。     

一种基于负载反馈的分布式数字集群动态负载均衡算法

针对传统负载均衡算法不能满足公网数字集群系统高并发用户请求和快速呼叫建立等需求,提出一种基于负载反馈的分布式数字集群动态负载均衡算法,实现公网数字集群系统负载均衡,提高用户容量。首先建立参与MCPTT服务器的静态负载和动态负载监控机制和指标;然后利用加权轮询算法为用户分配参与MCPTT服务器,并通过用户请求的处理获得复合负载参数;根据负载指标的反馈更新参与MCPTT服务器权值以动态调整服务器负载。仿真结果表明,该算法的负载均衡效果优于传统算法和其他动态反馈算法,负载均衡度更小、用户请求响应延迟更低。