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2015 IEEE Conference on Computer Communications (INFOCOM)最新文献

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Mitigating macro-cell outage in LTE-Advanced deployments 减少LTE-Advanced部署中的宏蜂窝中断
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218504
R. Sivaraj, Ioannis Broustis, N. K. Shankaranarayanan, V. Aggarwal, P. Mohapatra
LTE network service reliability is highly dependent on the wireless coverage that is provided by cell towers (eNB). Therefore, the network operator's response to outage scenarios needs to be fast and efficient, in order to minimize any degradation in the Quality of Service (QoS). In this paper, we propose an outage mitigation framework for LTE-Advanced (LTE-A) wireless networks. Our framework exploits the inherent design features of LTE-A; it performs a dual optimization of the transmission power and beamforming weight parameters at each neighbor cell sector of the outage eNBs, while taking into account both the channel characteristics and residual eNB resources, after serving its current traffic load. Assuming statistical Channel State Information about the users at the eNBs, we show that this problem is theoretically NP-hard; thus we relax it as a convex optimization problem and solve for the optimal points using an iterative algorithm. Contrary to previously-proposed power control studies, our framework is specifically designed to alleviate the effects of sudden LTE-A eNB outages, where a large number of mobile users need to be efficiently offloaded to nearby towers. We present the detailed analytical design of our framework, and we assess its efficacy via extensive NS-3 simulations on an LTE-A topology. Our simulations demonstrate that our framework provides adequate coverage and QoS across all examined outage scenarios.
LTE网络服务的可靠性高度依赖于蜂窝塔(eNB)提供的无线覆盖。因此,网络运营商对中断场景的响应需要快速有效,以尽量减少服务质量(QoS)的下降。在本文中,我们提出了一个LTE-Advanced (LTE-A)无线网络的中断缓解框架。我们的框架利用了LTE-A固有的设计特点;它在服务于当前流量负载后,对中断eNB的每个相邻小区扇区的传输功率和波束形成权重参数进行双重优化,同时考虑信道特性和剩余eNB资源。假设关于enb用户的统计信道状态信息,我们表明这个问题在理论上是np困难的;因此,我们将其松弛为一个凸优化问题,并使用迭代算法求解最优点。与之前提出的功率控制研究相反,我们的框架专门设计用于减轻LTE-A eNB突然中断的影响,在这种情况下,大量移动用户需要有效地转移到附近的塔上。我们介绍了我们框架的详细分析设计,并通过在LTE-A拓扑上进行广泛的NS-3模拟来评估其有效性。我们的模拟表明,我们的框架在所有检查的停机场景中提供了足够的覆盖和QoS。
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引用次数: 3
Need for speed: CORA scheduler for optimizing completion-times in the cloud 速度需求:用于优化云中的完成时间的CORA调度器
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218460
Zhe Huang, Bharath Balasubramanian, Michael Wang, Tian Lan, M. Chiang, D. Tsang
There is an increasing need for cloud service performance that can be tailored to customer requirements. In the context of jobs submitted to cloud computing clusters, a crucial requirement is the specification of job completion-times. A natural way to model this specification, is through client/job utility functions that are dependent on job completion-times. We present a method to allocate and schedule heterogeneous resources to jointly optimize the utilities of jobs in a cloud. Specifically: (i) we formulate a completion-time optimal resource allocation (CORA) problem to apportion cluster resources across the jobs that enforces max-min fairness among job utilities, and (ii) starting with an integer programming problem, we perform a series of steps to transform it into an equivalent linear programming problem, and (iii) we implement the proposed framework as a utility-aware resource scheduler in the widely used Hadoop data processing framework, and finally (iv) through extensive experiments with real-world datasets, we show that our prototype achieves significant performance improvement over existing resource-allocation policies.
对可根据客户需求定制的云服务性能的需求越来越大。在提交到云计算集群的作业上下文中,一个关键的需求是作业完成时间的规范。对该规范建模的一种自然方法是通过依赖于作业完成时间的客户机/作业实用程序函数。提出了一种分配和调度异构资源的方法,以共同优化云计算中作业的效用。具体地说:(i)我们制定了一个完成时间最优资源分配(CORA)问题,以便在作业之间分配集群资源,从而在作业实用程序之间实现最大最小公平性;(ii)从整数规划问题开始,我们执行一系列步骤将其转换为等效的线性规划问题;(iii)我们在广泛使用的Hadoop数据处理框架中实现了提议的框架,作为实用程序感知的资源调度程序。最后(iv)通过对真实世界数据集的广泛实验,我们表明我们的原型比现有的资源分配策略实现了显着的性能改进。
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引用次数: 49
Performance analysis for overflow loss systems of processor-sharing queues 处理器共享队列溢出丢失系统的性能分析
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218518
Yin-Chi Chan, Jun Guo, E. Wong, M. Zukerman
Overflow loss systems have wide applications in telecommunications and multimedia systems. In this paper, we consider an overflow loss system consisting of a set of finite-buffer processor-sharing (PS) queues, and develop effective methods for evaluation of its blocking probability. For such a problem, an existing approximation of the blocking probability is based on decomposition of the system into independent PS queues. We provide a new approximation which instead performs decomposition on a surrogate model of the original system, and demonstrate via extensive numerical results that our new approximation is more accurate and robust than the existing approach. We also examine the sensitivity of the blocking probability to the service time distribution, and demonstrate that an exponential distribution is a good approximation for a wide range of service time distributions.
溢流损耗系统在电信和多媒体系统中有着广泛的应用。本文考虑了由一组有限缓冲处理器共享(PS)队列组成的溢出损失系统,并开发了评估其阻塞概率的有效方法。对于此类问题,现有的阻塞概率近似是基于将系统分解为独立的PS队列。我们提供了一个新的近似,而不是对原始系统的代理模型进行分解,并通过广泛的数值结果证明,我们的新近似比现有的方法更准确和鲁棒。我们还研究了阻塞概率对服务时间分布的敏感性,并证明指数分布是一个很好的近似,适用于广泛的服务时间分布。
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引用次数: 8
Optimal scheduling of a large-scale multiclass parallel server system with ergodic cost 具有遍历成本的大型多类并行服务器系统的最优调度
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218467
A. Arapostathis, A. Biswas, G. Pang
We consider the optimal scheduling problem for a large-scale parallel server system with one large pool of statistically identical servers and multiple classes of jobs under the expected long-run average (ergodic) cost criterion. Jobs of each class arrive as a Poisson process, are served in the FCFS discipline within each class and may elect to abandon while waiting in their queue. The service and abandonment rates are both class-dependent. Assume that the system is operating in the Halfin-Whitt regime, where the arrival rates and the number of servers grow appropriately so that the system gets critically loaded while the service and abandonment rates are fixed. The optimal solution is obtained via the ergodic diffusion control problem in the limit, which forms a new class of problems in the literature of ergodic controls. A new theoretical framework is provided to solve this class of ergodic control problems. The proof of the convergence of the values of the multiclass parallel server system to that of the diffusion control problem relies on a new approximation method, spatial truncation, where the Markov policies follow a fixed priority policy outside a fixed compact set.
在预期的长期平均(遍历)成本准则下,我们考虑了一个大规模并行服务器系统的最优调度问题,该系统具有一个统计上相同的大型服务器池和多个作业类别。每个类的作业作为泊松过程到达,在每个类的FCFS纪律中服务,并且可以在等待队列时选择放弃。服役率和放弃率都与类别有关。假设系统在Halfin-Whitt模式下运行,其中到达率和服务器数量适当增长,以便系统在服务和放弃率固定的情况下获得临界负载。通过在极限下的遍历扩散控制问题得到最优解,形成了遍历控制文献中一类新的问题。为解决这类遍历控制问题提供了一个新的理论框架。多类并行服务器系统的值收敛于扩散控制问题的值的证明依赖于一种新的逼近方法——空间截断,其中马尔可夫策略遵循固定紧集外的固定优先级策略。
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引用次数: 0
RUSH: Routing and scheduling for hybrid data center networks RUSH:混合数据中心网络的路由和调度
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218407
K. Han, Zhiming Hu, Jun Luo, Liu Xiang
The recent development of 60GHz technology has made hybrid Data Center Networks (hybrid DCNs) possible, i.e., augmenting wired DCNs with highly directional 60GHz wireless links to provide flexible network connectivity. Although a few recent proposals have demonstrated the feasibility of this hybrid design, it still remains an open problem how to route DCN traffics with guaranteed performance under a hybrid DCN environment. In this paper, we make the first attempt to tackle this challenge, and propose the RUSH framework to minimize the network congestion in hybrid DCNs, by jointly routing flows and scheduling wireless (directional) antennas. Though the problem is shown to be NP-hard, the RUSH algorithms offer guaranteed performance bounds. Our algorithms are able to handle both batched arrivals and sequential arrivals of flow demands, and the theoretical analysis shows that they achieve competitive ratios of O(log n), where n is the number of switches in the network. We also conduct extensive simulations using ns-3 to verify the effectiveness of RUSH. The results demonstrate that RUSH produces nearly optimal performance and significantly outperforms the current practice and a simple greedy heuristics.
60GHz技术的最新发展使混合数据中心网络(hybrid dcn)成为可能,即通过高度定向的60GHz无线链路增强有线dcn,以提供灵活的网络连接。虽然最近的一些建议已经证明了这种混合设计的可行性,但如何在混合DCN环境下保证性能的DCN流量路由仍然是一个悬而未决的问题。在本文中,我们首次尝试解决这一挑战,并提出了RUSH框架,通过联合路由流和调度无线(定向)天线来最小化混合dcn中的网络拥塞。虽然这个问题被证明是np困难的,但RUSH算法提供了有保证的性能界限。我们的算法能够处理批量到达和顺序到达的流需求,理论分析表明,它们实现了O(log n)的竞争比,其中n是网络中的交换机数量。我们还使用ns-3进行了大量模拟,以验证RUSH的有效性。结果表明,RUSH产生了近乎最优的性能,并且显著优于当前的实践和简单的贪婪启发式。
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引用次数: 48
PeerClean: Unveiling peer-to-peer botnets through dynamic group behavior analysis PeerClean:通过动态群体行为分析揭示点对点僵尸网络
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218396
Qiben Yan, Yao Zheng, Tingting Jiang, W. Lou, Y. T. Hou
Advanced botnets adopt a peer-to-peer (P2P) infrastructure for more resilient command and control (C&C). Traditional detection techniques become less effective in identifying bots that communicate via a P2P structure. In this paper, we present PeerClean, a novel system that detects P2P botnets in real time using only high-level features extracted from C&C network flow traffic. PeerClean reliably distinguishes P2P bot-infected hosts from legitimate P2P hosts by jointly considering flow-level traffic statistics and network connection patterns. Instead of working on individual connections or hosts, PeerClean clusters hosts with similar flow traffic statistics into groups. It then extracts the collective and dynamic connection patterns of each group by leveraging a novel dynamic group behavior analysis. Comparing with the individual host-level connection patterns, the collective group patterns are more robust and differentiable. Multi-class classification models are then used to identify different types of bots based on the established patterns. To increase the detection probability, we further propose to train the model with average group behavior, but to explore the extreme group behavior for the detection. We evaluate PeerClean on real-world flow records from a campus network. Our evaluation shows that PeerClean is able to achieve high detection rates with few false positives.
高级僵尸网络采用点对点(P2P)基础设施,以实现更有弹性的命令和控制(C&C)。传统的检测技术在识别通过P2P结构进行通信的机器人时变得不那么有效。在本文中,我们提出了PeerClean,这是一个仅使用从C&C网络流量中提取的高级特征来实时检测P2P僵尸网络的新系统。PeerClean通过综合考虑流量级流量统计和网络连接模式,可靠地区分受P2P僵尸感染的主机和合法的P2P主机。PeerClean不是处理单个连接或主机,而是将具有相似流量统计数据的主机集群到组中。然后,通过利用一种新的动态群体行为分析,提取每个群体的集体和动态连接模式。与单个主机级连接模式相比,集体组模式具有更强的鲁棒性和可微性。然后使用多类分类模型根据已建立的模式识别不同类型的机器人。为了提高检测概率,我们进一步提出用平均群体行为训练模型,而探索极端群体行为进行检测。我们根据校园网的真实流量记录来评估PeerClean。我们的评估表明,PeerClean能够实现高的检测率和很少的假阳性。
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引用次数: 33
Energy-aware video streaming on smartphones 智能手机上的节能视频流
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218493
Wenjie Hu, G. Cao
Video streaming on smartphone consumes lots of energy. One common solution is to download and buffer future video data for playback so that the wireless interface can be turned off most of time and then save energy. However, this may waste energy and bandwidth if the user skips or quits before the end of the video. Using a small buffer can reduce the bandwidth wastage, but may consume more energy and introduce rebuffering delay. In this paper, we analyze the power consumption during video streaming considering user skip and early quit scenarios. We first propose an offline method to compute the minimum power consumption, and then introduce an online solution to save energy based on whether the user tends to watch video for a long time or tends to skip. We have implemented the online solution on Android based smartphones. Experimental results and trace-driven simulation results show that that our method can save energy while achieving a better tradeoff between delay and bandwidth compared to existing methods.
智能手机上的视频流会消耗大量能源。一种常见的解决方案是下载并缓冲未来的视频数据以供回放,这样无线接口就可以在大多数时候关闭,从而节省能源。然而,如果用户在视频结束前跳过或退出,这可能会浪费能量和带宽。使用较小的缓冲区可以减少带宽浪费,但可能会消耗更多的能量并引入重缓冲延迟。在本文中,我们分析了视频流的功耗,考虑用户跳过和提前退出场景。我们首先提出了一种离线方法来计算最小功耗,然后根据用户是否倾向于长时间观看视频或倾向于跳过视频引入在线解决方案来节省能源。我们已经在基于Android的智能手机上实现了在线解决方案。实验结果和跟踪驱动仿真结果表明,与现有方法相比,该方法在节省能量的同时,更好地平衡了延迟和带宽。
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引用次数: 72
Incentivize crowd labeling under budget constraint 预算约束下的人群标签激励
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218674
Qi Zhang, Yutian Wen, Xiaohua Tian, Xiaoying Gan, Xinbing Wang
Crowdsourcing systems allocate tasks to a group of workers over the Internet, which have become an effective paradigm for human-powered problem solving such as image classification, optical character recognition and proofreading. In this paper, we focus on incentivizing crowd workers to label a set of binary tasks under strict budget constraint. We properly profile the tasks' difficulty levels and workers' quality in crowdsourcing systems, where the collected labels are aggregated with sequential Bayesian approach. To stimulate workers to undertake crowd labeling tasks, the interaction between workers and the platform is modeled as a reverse auction. We reveal that the platform utility maximization could be intractable, for which an incentive mechanism that determines the winning bid and payments with polynomial-time computation complexity is developed. Moreover, we theoretically prove that our mechanism is truthful, individually rational and budget feasible. Through extensive simulations, we demonstrate that our mechanism utilizes budget efficiently to achieve high platform utility with polynomial computation complexity.
众包系统通过互联网将任务分配给一组工作人员,这已经成为人工解决图像分类、光学字符识别和校对等问题的有效范例。在本文中,我们关注的是在严格的预算约束下,激励群体工作者标记一组二元任务。我们在众包系统中适当地描述任务的难度等级和工人的素质,其中收集的标签使用顺序贝叶斯方法进行汇总。为了刺激工人承担人群标签任务,工人与平台之间的互动被建模为反向拍卖。我们发现平台效用最大化是一个棘手的问题,为此我们建立了一个具有多项式时间计算复杂度的激励机制来决定中标和支付。并从理论上证明了该机制是真实的、个体理性的和预算可行的。通过大量的仿真,我们证明了我们的机制有效地利用了预算,以多项式的计算复杂度实现了高的平台效用。
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引用次数: 99
Distributed algorithms for content allocation in interconnected content distribution networks 互联内容分发网络中内容分配的分布式算法
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218624
Valentino Pacifici, G. Dán
Internet service providers increasingly deploy internal CDNs with the objective of reducing the traffic on their transit links and to improve their customers' quality of experience. Once ISP managed CDNs (nCDNs) become commonplace, ISPs would likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper we consider the problem of using distributed algorithms for computing a content allocation for nCDNs. We show that if every ISP aims to minimize its cost and bilateral payments are not allowed then it may be impossible to compute a content allocation. For the case of bilateral payments we propose two distributed algorithms, the aggregate value compensation (AC) and the object value compensation (OC) algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real AS-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs' density and the nCDN capacity.
互联网服务提供商越来越多地部署内部cdn,目的是减少传输链路上的流量,并改善客户的体验质量。一旦ISP管理的cdn (ncdn)变得普遍,ISP可能会提供公共接口来互连他们的ncdn,以实现互利,就像他们今天对对等网络所做的那样。在本文中,我们考虑使用分布式算法计算ncdn的内容分配问题。我们表明,如果每个ISP的目标是使其成本最小化,并且不允许双边支付,那么计算内容分配可能是不可能的。对于双边支付的情况,我们提出了两种分布式算法,总价值补偿(AC)和对象价值补偿(OC)算法,它们在允许的并行性水平和ncdn之间交换的信息量方面有所不同。证明了算法的收敛性,并提出了一种保证事后个体合理性的方案。在真实的as级网络拓扑和合成拓扑上进行的仿真表明,该算法具有几何收敛速度,并能很好地适应图的密度和nCDN容量。
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引用次数: 14
Redundancy control through traffic deduplication 通过流量重复数据删除实现冗余控制
Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218362
K. Hua, Ning Jiang, J. Kuhns, V. Sundaram, C. Zou
Statistics show that 79% of the Internet traffic is video and mostly “redundant”. Video-On-Demand in particular follows a 90/10 access pattern, where 90% of the users access the same 10% of all video content. As a result, redundant data are repeatedly transmitted over the Internet. In this paper, we propose a novel traffic deduplication technique to achieve more efficient network communication between video sources (video servers or proxy servers in a CDN) and clients. The proposed SMART (Small packet Merge-Able RouTers) overlay network employs an opportunistic traffic deduplication approach and allows each SMART router to dynamically merge independent streams of the same video content, forming a video streaming tree (VST). The merged streams are tunneled through the overlay together with TCP sessions information before eventually being de-multiplexed and delivered to the clients fully compatible with the TCP protocol. We present theoretical analysis findings on the merging strategy between the video source and clients, the efficiency of the SMART router to save traffic during a merge process, and the overall performance of implementing a SMART overlay topology between a video source and clients. Finally, we prototyped SMART in the PlanetLab environment. We illustrate that performance evaluation results are consistent with our theoretical analysis and significant bandwidth saving is achieved.
统计数据显示,79%的互联网流量是视频,而且大部分是“冗余”的。视频点播尤其遵循90/10访问模式,其中90%的用户访问所有视频内容的相同10%。因此,冗余数据在因特网上重复传输。在本文中,我们提出了一种新的流量重复数据删除技术,以实现视频源(CDN中的视频服务器或代理服务器)和客户端之间更有效的网络通信。提出的SMART (Small packet merge - able RouTers)覆盖网络采用机会性的流量重复数据删除方法,允许每个SMART路由器动态合并相同视频内容的独立流,形成视频流树(video streaming tree, VST)。合并后的流与TCP会话信息一起在覆盖层中隧道化,最终被解复用并交付给完全兼容TCP协议的客户端。我们对视频源和客户端之间的合并策略、SMART路由器在合并过程中节省流量的效率以及在视频源和客户端之间实现SMART覆盖拓扑的整体性能进行了理论分析。最后,我们在PlanetLab环境中创建了SMART原型。我们证明了性能评估结果与我们的理论分析一致,并且实现了显著的带宽节省。
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引用次数: 5
期刊
2015 IEEE Conference on Computer Communications (INFOCOM)
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