一种新颖的P2P文件共享系统的动力学模型

提出一种新颖的P2P文件共享系统的动力性学模型.在模型中定义了描述节点之间相互作用关系的状态量.同时,分析了P2P文件共享系统中最重要的算法,如节点选择算法及带宽分配算法等等,最终给出了模型的具体形式.最后,网络实验和仿真证明了此模型能够反映P2P文件共享系统的本质特征,从而为设计高性能P2P网络,改进现有的P2P算法,以及研究P2P系统的稳定性提供一种新颖的方法.     

针对负载均衡的P2P动态副本策略

对等网络系统面临的最大的问题就是负载均衡.针对P2P网络中负载均衡的问题,提出了两种基于动态副本策略的负载均衡技术:周期性副本策略和基于需求的副本策略.在周期性副本策略里,每个超级节点周期性地把文件的副本发送给请求该文件频率最高的远程超级节点.在基于需求的副本策略里,当一个超级节点发现其对某个文件的访问频率过高时,就向拥有该文件的超级节点发送文件请求,以获得该文件副本.本文分析了这两种技术的平均访问代价和副本负载代价.一系列的模拟实验证实了这两种技术的可行性及其带来的好处.     

Histogram-Based Global Load Balancing in Structured Peer-to-Peer Systems

Over the pass few years, peer-to-peer (P2P) systems have rapidly grown in popularity and become a dominant means for sharing resources. In these systems, load balancing is a key challenge because nodes are often heterogeneous. While several load balancing schemes have been proposed in the literature, these solutions are typically ad-hoc, heuristic-based and localized. In this paper, we present a general framework, HiGLOB, for global load balancing in structured P2P systems. Each node in HiGLOB has two key components: (1) A histogram manager maintains a histogram that reflects a global view of the distribution of the load in the system, and (2) A load-balancing manager that redistributes the load whenever the node becomes over or under loaded. We exploit the routing metadata to partition the P2P network into non-overlapping regions corresponding to the histogram buckets. We propose mechanisms to keep the cost of constructing and maintaining the histograms low. We further show that our scheme can control and bound the amount of load imbalance across the system. Finally, we demonstrate the effectiveness of HiGLOB by instantiating it over three existing structured P2P systems: Chord, Skip Graph and BATON. Our experimental results indicate that our approach works well in practice.     

MMOG中的一种动态负载共享算法*

针对MMOG中的服务器超载问题,提出一种动态负载共享算法,使得一个超载的服务器能够方便地将它的一部分负载迁移到没有超载的服务器上.同时在基于预订区域概念的基础上,通过扩大邻居服务器的范围,提出一种客户端迁移方案来减少该算法的开销,从而提高系统的响应速度和性能.     

Free-Riding on BitTorrent-Like Peer-to-Peer File Sharing Systems: Modeling Analysis and Improvement

BitTorrent has emerged as a very popular peer-to-peer file sharing system, which uses an embedded set of incentive mechanisms to encourage contribution and prevent free-riding. However, the capability BitTorrent has of preventing free-riding needs further study. In this paper, we present a fluid model with two different classes of peers to capture the effect of free-riding on BitTorrent-like systems. With the model, we find that BitTorrent's incentive mechanism is successful in preventing free-riding in a system without seeds, but may not succeed in producing a disincentive for free-riding in a system with a high number of seeds. The reason for this is that BitTorrent does not employ any effective mechanisms for seeds to effectively guard against freeriding. Therefore, we propose a seed bandwidth allocation strategy for the BitTorrent system to reduce the effect of seeds on free-riding. Finally, simulation results are given, which validate what we have found in our analysis and demonstrate the effectiveness of the proposed strategy.     

Inferring Cross-Sections: When Internal Visualizations Are More Important Than Properties of External Visualizations

Three experiments examined how cognitive abilities and qualities of external visualizations affected performance of a mental visualization task; inferring the cross-section of a complex three-dimensional object. Experiment 1 investigated the effect of animations designed to provide different task-relevant views of the external object. Experiment 2 examined the effects of both stereoscopic and motion-based depth cues. Experiment 3 examined the effects of interactive animations, with and without stereoscopic viewing conditions. In all experiments, spatial and general reasoning abilities were measured. Effects of animation, stereopsis, and interactivity were relatively small and did not reach statistical significance. In contrast, spatial ability was significantly associated with superior performance in all experiments, and this remained true after controlling for general intelligence. The results indicate that difficulties in this task stem more from the cognitive ability to perform the relevant internal spatial transformations, than limited visual information about the three-dimensional structure of the object.     

More than bin packing: Dynamic resource allocation strategies in cloud data centers

Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need to be allocated and deallocated to servers over time. Simple bin packing heuristics have been analyzed and used to place virtual machines upon arrival. However, these placement heuristics can lead to suboptimal server utilization, because they cannot consider virtual machines, which arrive in the future. We ran extensive lab experiments and simulations with different controllers and different workloads to understand which control strategies achieve high levels of energy efficiency in different workload environments. We found that combinations of placement controllers and periodic reallocations achieve the highest energy efficiency subject to predefined service levels. While the type of placement heuristic had little impact on the average server demand, the type of virtual machine resource demand estimator used for the placement decisions had a significant impact on the overall energy efficiency.     

分布式实时系统中动态负载共享新策略

提出了一个在实时分布式系统中有失败结点情况下容错的，动态的，带区域状态变化信息广播的负载共享算法。如果结点n自从最后一次收到结点的广播信息以及Tout^(i)还没有收到结点i的广播信息，然后调整各正常的结点的优先列表，以保证每个结点被一个也只能是一个站点选作自己的第k个优先结点，以减少任务的失败率，该文主要确定最佳的超时值及时检测一个结点的失败，调整 结点的优先列表以处理结点的失败。     

基于动态配置等价多路径技术的无线传感器网络负载均衡算法研究

随着物联网应用的推广,作为底层核心构件的传感器网络所承载传输业务成激增趋势,使得窄带宽无线信道成为了制约物联网应用的首要因素。合理分流流量,实现负载均衡是提升网络承载能力的有效方法。本文将ECMP ( Equal-Cost Mul-tipaths)技术与传感器网络自组织特性相融合,传感器网络多跳自组织特性为业务传输提供多条等价最短路径,ECMP将业务均衡分担到这些等价最短路径上,实现负载均衡。理论证明传统ECMP 配置方法全网节点开通ECMP 功能不仅会增加网络控制信息开销,而且在某些情况下反而会增大区域负载,形成网络拥塞。因此,本文提出动态选择开通 ECMP 算法( DC-ECMP )。算法以流入节点流量等于流出节点流量作为业务守恒约束,链路带宽上限作为链路容量约束,以最大链路利用率最小化为目标函数,建立多约束优化模型。并依据最大链路使用率和节点度判定开通ECMP 优先级,动态选择需开通节点,以获取最优网络传输性能。仿真结果表明DC-ECMP算法比已有PPV算法有效降低最大链路使用率,消除网络局部拥塞隐患,并且最大减少传输延时9.9 ms,节省网络资源消耗4.06%。     

一种基于P2P系统的动态负载平衡算法

在P2P系统中，负载平衡算法的好坏将直接影响到系统的使用效率。在这篇文章中提出了一种负载平衡算法，从地址空间平衡与动态负载等几个方面提出对现有算法的改进策略，目的是提高负载平衡效率并使其适应于更广的DHT应用。     

GSM:一种多服务器系统的动态负载均衡调度模型

设多服务器系统由 n个服务器结点和 1个中心任务调度结点组成 ,所有服务器具有同样的处理能力 ,任务的到达是一速率参数为 nλ的泊松流 ,任务的服务器处理时间服从参数为 1/μ的指数分布 (λ<μ) ,一次负载信息收集时间和任务调度时间在理想情况下可忽略不计 .基于这些假设 ,提出了多服务器系统的广义超级市场调度模型 (GeneralizedSuperm arket Model,GSM) ,详细分析并证明了该调度模型的解特性 .结论表明 :对于大规模多服务器系统 ,广义超级市场调度模型与随机选择服务调度策略相比 ,可指数级地提高平均任务消耗时间性能 ;与文献 [1,2 ,3]的结果相比 ,达到其极小化平均任务消耗时间     

Library eBooks: Some Can't Find Them,Others Find Them and Don't Know What They Are

When discussing eBooks, people generally fall into two camps: they either don't know what eBooks are or know what they are but cannot find them at their local library. Libraries are beginning to successfully address the gap between patron awareness of electronic books in general and a library's holdings and circulation options. EBooks are a relatively new format, and many rights and business model issues between authors, publishers and distributors remain unresolved. EBook readers to a large degree receive more media attention than eBooks themselves. More and more people are looking to libraries to fill their eBook needs. OverDrive (http://overdrive.com) offers libraries eBooks with true to expectations portability. Libraries are beginning to successfully market their eBook collections and make discovery easier.     

A Case Study of Load Sharing Based on Popularity in Distributed VoD Systems

In our research, we consider a distributed video-on-demand (VoD) system in which only the most popular videos are replicated in all the servers, whereas the rest of them are distributed through the system following some allocation scheme. In this paper, we present an algorithm to efficiently share the load in such a system and an analytical model that captures the performance of this algorithm, which we validate through simulations. One novelty in our work is that our analytical model lets us relate popularity and partial replication of some of the videos and to predict the user waiting time. We exploit such relationships to assist the system designer to select the size of the servers and network, the optimal number of servers to maintain short waiting time and to predict when the network encounters bottleneck     

Cyber-Physical Systems of Systems and Complexity Science: The Whole is More than the Sum of Individual and Autonomous Cyber-Physical Systems

Abstract

Cyber-physical systems-of-systems (CPSoS) are networks that interconnect cyber-physical systems and people. Intercommunications and interaction between a wide range of separate and autonomous components make a cyber-physical system-of-systems a highly complex entity. This complex entity works based on self-organization that is made possible by the exchange and sharing of information among the separate components. Information produces a temporary form of entanglement between the separate components of the new entity. Entanglement enables the new entity to develop emergent properties that are responsible for the functioning of this new entity. New scientific knowledge is required to be able to analyze and design this entity.     

Dynamic Load Balancing in Distributed Systems in the Presence of Delays: A Regeneration-Theory Approach

A regeneration-theory approach is undertaken to analytically characterize the average overall completion time in a distributed system. The approach considers the heterogeneity in the processing rates of the nodes as well as the randomness in the delays imposed by the communication medium. The optimal one-shot load balancing policy is developed and subsequently extended to develop an autonomous and distributed load-balancing policy that can dynamically reallocate incoming external loads at each node. This adaptive and dynamic load balancing policy is implemented and evaluated in a two-node distributed system. The performance of the proposed dynamic load-balancing policy is compared to that of static policies as well as existing dynamic load-balancing policies by considering the average completion time per task and the system processing rate in the presence of random arrivals of the external loads.     

A Dynamic Load Balancing Framework for Real-time Applications in Message Passing Systems

Load balancing algorithms are designed essentially to equally distribute the load on processors and maximize their utilities while minimizing the total task execution time. In order to achieve these goals, the load-balancing mechanism should be “fair” in distributing the load across the different processors. This implies that the difference between the heaviest-loaded and the lightest-loaded processors should be minimized. Therefore, the load information on each processor must be updated such that the load-balancing mechanism can be more effective. In this work, we present an application independent dynamic algorithm for scheduling tasks and load- balancing in message passing systems. We propose a DAG-based Dynamic Load Balancing algorithm for Real time applications (DAG-DLBR) that is designed to work dynamically to cope with possible changes in the load that might occur during runtime. This algorithm addresses the challenge of devising a load balancing scheme which judicially deals with the hybrid execution of existing real-time application (represented by a Direct Acyclic Graph (DAG)) together with newly arriving jobs. The main objective of this algorithm is to reduce response times of the newly arriving jobs while maintaining the time constrains of the existing DAG. To evaluate the performance of the DAG-DLBR algorithm, a comparison with the performance of two common dynamic load balancing algorithms is presented. This comparison is performed by evaluating, experimentally, the execution time of different load balancing algorithms on a homogenous real parallel machine. In addition, the values of load imbalance, the execution time, and the communication overhead time are evaluated analytically using different benchmarks as test-bed workloads. These workloads cover a wide range of dynamic applications with different task types. Experimental results illustrate the improved performance of the DAG-DLBR algorithm compared to both distributed and hierarchal based algorithms by at least 12 and 19%, respectively. This improvement is true for all workloads, even with highly dependent workload. The DAG-DLBR algorithm achieves lower computation time than its corresponding values of both the distributed and the hierarchical-based algorithms for 4, 8, 12 and 16 processors.     

A Uniform Framework for Dynamic Load Balancing Strategies in Distributed Processing Systems

Load balancing plays a central role in processor utilizations in distributed systems. Several strategies have been proposed in the literature to achieve load balancing. Usually, these strategies attempt to achieve a tradeoff between reducing the execution time of an application and minimizing the synchronization and the communication overhead. In this paper, we present a general model in which load balancing decisions are reached by enforcing performance metrics which may be adapted to reflect the specific requirements of different environments. Many of the load balancing schemes that have been suggested in the literature can be viewed as specific instances of the general framework presented in this paper. The basic scheme in this framework uses a load contention number that accounts for the load of the processors, the communication cost and the distance among processors. It is meant to be adaptable to the overall load on the system, the load on the communication devices, the run time characteristics of the tasks, and the configuration of the system. Furthermore, its implementation is not computationally complex. Thus, the gains made by load balancing are not overshadowed by the load balancing cost.     

Beyond Music Sharing: An Evaluation of Peer-to-Peer Data Dissemination Techniques in Large Scientific Collaborations

The avalanche of data from scientific instruments and the ensuing interest from geographically distributed users to analyze and interpret it accentuates the need for efficient data dissemination. A suitable data distribution scheme will find the delicate balance between conflicting requirements of minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We identify several data distribution techniques, some successfully employed by today’s peer-to-peer networks: staging, data partitioning, orthogonal bandwidth exploitation, and combinations of the above. We use simulations to explore the performance of these techniques in contexts similar to those used by today’s data-centric scientific collaborations and derive several recommendations for efficient data dissemination. Our experimental results show that the peer-to-peer solutions that offer load balancing and good fault tolerance properties and have embedded participation incentives lead to unjustified costs in today’s scientific data collaborations deployed on over-provisioned network cores. However, as user communities grow and these deployments scale, peer-to-peer data delivery mechanisms will likely outperform other techniques.     

Some Open Problems in Dynamic Analysis of Flexible Multibody Systems

Some open questions arising in the dynamical formulation ofsystems of hinge-connected flexible bodies are discussed. The first one deals with the choice of the floating reference frame associated to abody undergoing large rigid body motions but small elastic deformations.The second one concerns the so-called geometric stiffening (orcentrifugal stiffening) effects. The last problem is concerned with theeventual appearance of higher-order terms in the kinetic energy of thesystem for large rates and large accelerations.