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The same problem exists when using simulation as the principal performance evaluation tool. Traf c Control Traf c control for self-similar traf c has been explored on two fronts: (1) as an extension of performance analysis in the resource provisioning context, and (2) from the multiple time scale traf c control perspective where correlation structure at large time scales is actively exploited to improve network performance. The resource provisioning aspect advocates a small buffer=large bandwidth resource dimensioning policy, which when coupled with the central limit theorem yields predictable multiplexing gains when a large number of independent ows are aggregated. Whereas resource provisioning is open-loop in nature, multiple time scale traf c control seeks to achieve performance gains by exploiting correlation structure in self-similar traf c at time scales exceeding the time horizon of the feedback loop to impart proactivity to reactive controls (e.g., TCP). This is relevant in broadband wide area networks where the delay bandwidth product problem is especially severe, and mitigating the performance degradation due to outdated feedback is critical to facilitating scalable, adaptive traf c control. The initial success of this approach [62, 67 69] (see 18 for an application to rate-based congestion control) leads to a generalization to workload-sensitive traf c control, where facilitation of workload sensitivity is expanded along several traf c control dimensions including the two core features for harnessing predictability at large time scales: long-range correlation in network traf c and heavy-tailedness of connection durations. Workload-sensitive traf c control is a broad area that can bene t from concerted efforts at several fronts, spanning novel mechanisms for detecting and exploiting large time scale predictability structure, short-duration connection management, packet scheduling, end system support, and dynamic admission control with self-similar call arrivals and=or heavy-tailed connection durations.



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and has its own complete view of the network, IP addresses, memory, CPU, scheduling, and all other functions controlled by the OS One of the advantages of domains is that you can shuffle resources between them, in many cases while the system is running Have a large workload that needs another four processors Borrow them from the QA domain, run the job to completion, then put the processors back into the degraded QA domain for normal operation Dynamic reconfiguration of hardware involves draining CPU and memory boards of data, then detaching and reattaching them to appropriate domains This hardware-level VM capability is frequently controlled by a console or command-line function available to a privileged user only VMs can be created, destroyed, and reallocated very quickly and easily under software control One of the most common uses for software VMs (such as VMware, wwwvmware.

21.2 21.2.1





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The meaning coded into words can t be measured in bytes. It s deeply compressed. Twelve words from Voltaire can hold a lifetime of experience. Mark Horowitz, Visualizing Big Data. Wired, June 23, 2008. www.wired.com/science/discoveries/magazine/ 16-07/pb visualizing It s great that your name is being mentioned by friends and fans but it s also being mentioned by those who are neither. It s your job to note if those people are saying sad things, mad things, or bad things. It s your job to listen and respond and hopefully change their mind and change their tune. It would be better if they repeat and reinforce those characteristics you want them to associate with your brand and your products. It would be nice if they propagate the notion that your company stands for luxury, value, quality, excitement, status, or fun. You pray that you can change their dissatisfaction to support.

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com) is to allow a user to run more than one operating system on a PC or workstation Once the host software has been installed on the physical system, it can be used to create new virtual machines, each one of which could run a different operating system A sophisticated user or administrator could choose to run Windows XP, Windows 2000, Windows NT, Solaris for Intel, Red Hat Linux, and SuSe Linux at the same time on six virtual machines on the same Intel-based computer As with any technology that touches system resources, there are good and bad aspects of partitions and domains in the reliability engineering world: Good Running multiple environments on the same box Separate environments for each stage of the deployment lifecycle were highlighted in 5, 20 Key High Availability Design Principles (Rule #9).

Unlike many systems of study including economic, social, and certain physical sciences (e.g., astronomy, earth and atmospheric science), network systems admit to design, implementation, and controlled experimentation of the underlying physical system at nontrivial scales for example, protocol deployment in autonomous systems belonging to a single service provider which facilitates an intimate, mechanistic understanding of the system at hand. Model selection is not bound by ``black box'' evaluations, and physical models that can explicate traf c characteristics in terms of elementary, veri able system properties and network mechanics, in addition to data tting, provide an opportunity to be exploited. The challenge lies in combining relevant features from workload modeling, network architecture protocols and transmission technology user behavior, and analytical modeling into a

consistent, effective description of network systems, in particular, the Internet. As such, physical modeling is a research program that transcends workload modeling, encompassing both performance analysis and traf c control. 21.2.2 Multifractal Traf c Characterization

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