Computer Networks, an undergraduate computer science course, is taught through a variety of new technological tools but more attention on assessment strategies using those technological tools is desirable. Research studies have shown that assessment methods also influence students' learning. Current assessment techniques, even those which include technology, focus more on summative assessment rather than formative. Formative assessment is necessary for teaching and assessment of complex skills like troubleshooting or network design. Therefore, there exists a need for assessments to capture students' problem solving process and chosen approaches during the assessment. By tracking a student's behaviors in an immersive assessment environment, the path that the student takes towards the solution can be studied. Virtual Worlds are naturally immersive environments and can be effectively used to record interactions that students made in the worlds. We have developed NetWorld in Open Wonderland, an open source software for creating 3D virtual worlds. NetWorld is a 3D virtual world built for detailed assessment of computer network concepts for computer science undergraduate students. This detailed assessment happens at 3 levels -- conceptual understanding, diagnostic abilities and the ability to design a network. This paper describes the design principles and implementation of NetWorld and a plan to evaluate its usability.

Data center power is a scarce resource that often goes underutilized due to conservative planning. This is because the penalty for overloading the data center power delivery hierarchy and tripping a circuit breaker is very high, potentially causing long service outages. Recently, dynamic server power capping, which limits the amount of power consumed by a server, has been proposed and studied as a way to reduce this penalty, enabling more aggressive utilization of provisioned data center power. However, no real at-scale solution for data center-wide power monitoring and control has been presented in the literature. In this paper, we describe Dynamo -- a data center-wide power management system that monitors the entire power hierarchy and makes coordinated control decisions to safely and efficiently use provisioned data center power. Dynamo has been developed and deployed across all of Facebook's data centers for the past three years. Our key insight is that in real-world data centers, different power and performance constraints at different levels in the power hierarchy necessitate coordinated data center-wide power management. We make three main contributions. First, to understand the design space of Dynamo, we provide a characterization of power variation in data centers running a diverse set of modern workloads. This characterization uses fine-grained power samples from tens of thousands of servers and spanning a period of over six months. Second, we present the detailed design of Dynamo. Our design addresses several key issues not addressed by previous simulation-based studies. Third, the proposed techniques and design have been deployed and evaluated in large scale data centers serving billions of users. We present production results showing that Dynamo has prevented 18 potential power outages in the past 6 months due to unexpected power surges, that Dynamo enables optimizations leading to a 13% performance boost for a production Hadoop cluster and a nearly 40% performance increase for a search cluster, and that Dynamo has already enabled an 8% increase in the power capacity utilization of one of our data centers with more aggressive power subscription measures underway.

Erasure coding schemes provide higher durability at lower storage cost, and thus constitute an attractive alternative to replication in distributed storage systems, in particular for storing rarely accessed "cold" data. These schemes, however, require an order of magnitude higher recovery bandwidth for maintaining a constant level of durability in the face of node failures. In this paper we propose lazy recovery, a technique to reduce recovery bandwidth demands down to the level of replicated storage. The key insight is that a careful adjustment of recovery rate substantially reduces recovery bandwidth, while keeping the impact on read performance and data durability low. We demonstrate the benefits of lazy recovery via extensive simulation using a realistic distributed storage configuration and published component failure parameters. For example, when applied to the commonly used RS(14, 10) code, lazy recovery reduces repair bandwidth by up to 76% even below replication, while increasing the amount of degraded stripes by 0.1 percentage points. Lazy recovery works well with a variety of erasure coding schemes, including the recently introduced bandwidth efficient codes, achieving up to a factor of 2 additional bandwidth savings.

Energy accounts for a significant fraction of the operational costs of a data center, and data center operators are increasingly interested in moving toward low-power designs. Two distinct approaches have emerged toward achieving this end: the power-proportional approach focuses on reducing disk and server power consumption, while the green data center approach focuses on reducing power consumed by support-infrastructure like cooling equipment, power distribution units, and power backup equipment. We propose an integrated approach, which combines the benefits of both. Our solution enforces power-proportionality at the granularity of a rack or even an entire containerized data center; thus, we power down not only idle IT equipment, but also their associated support-infrastructure. We show that it is practical today to design data centers to power down idle racks or containers-and in fact, current online service trends strongly enable this model. Finally, we show that our approach combines the energy savings of power-proportional and green data center approaches, while performance remains unaffected.

We present a power-lean storage system, where racks of servers, or even entire data center shipping containers, can be powered down to save energy. We show that racks and containers are more than the sum of their servers, and demonstrate the feasibility of designing a storage system that powers them up and down on demand further, we show that such a system would save an order of magnitude more energy than current disk-based power-proportional storage systems. Our simulation results using file system traces from the Internet Archive show over 44% energy savings, a 5x improvement over disk-based power management systems, without performance impact. We explore the tradeoffs in choosing the right unit to power off/on, and present an automated framework to compute the optimal power management unit for different scenarios.

The global network of data centers is emerging as an important distributed systems paradigm-commodity clusters running high-performance applications, connected by high-speed “lambda” networks across hundreds of milliseconds of network latency. Packet loss on long-haul networks can cripple applications and protocols: A loss rate as low as 0.1% is sufficient to reduce TCP/IP throughput by an order of magnitude on a 1-Gb/s link with 50-ms one-way latency. Maelstrom is an edge appliance that masks packet loss transparently and quickly from intercluster protocols, aggregating traffic for high-speed encoding and using a new forward error correction scheme to handle bursty loss.