RepFlow: Minimizing Flow Completion Times with Replicated Flows in Data Centers

Short TCP flows that are critical for many interactive applications in data centers are plagued by large flows and head-of-line blocking in switches. Hash-based load balancing schemes such as ECMP aggravate the matter and result in long-tailed flow completion times (FCT). Previous work on reducing FCT usually requires custom switch hardware and/or protocol changes. We propose RepFlow, a simple yet practically effective approach that replicates each short flow to reduce the completion times, without any change to switches or host kernels. With ECMP the original and replicated flows traverse distinct paths with different congestion levels, thereby reducing the probability of having long queueing delay. We develop a simple analytical model to demonstrate the potential improvement of RepFlow. Extensive NS-3 simulations and Mininet implementation show that RepFlow provides 50%--70% speedup in both mean and 99-th percentile FCT for all loads, and offers near-optimal FCT when used with DCTCP.Comment: To appear in IEEE INFOCOM 201

Synthesis and Characterization of Au:Ag Core-Shell Nanoparticles with 4-Aminothiophenol Surface Enhance Raman Spectroscopy (SERS) Tag

At the Linfield Symposium the research on silver coated gold nanoparticles tagged SERS will be presented. Gold core nanoparticles were synthesized and coated with a silver shell. These core-shell nanoparticles were tagged with a Surface Enhanced Raman Signal (SERS) tag, 4-aminothiophenol. These tagged particles were monitored for stability and signal enhancement over time. When stability was proven, the tagged particles were coated with a polymer (PAH) and then a lipid bilayer (POPS:LPC). These particles were again monitored for stability and signal strength on the Raman. The overall goal was to synthesize silver coated gold nanoparticles, tag and enhance their Raman signal, and coat them with lipids while keeping the particles at a reasonable small size

Measuring Burstiness in Data Center Applications

Buffer sizing is a tricky task --- it depends on a large number of variables, ranging from congestion control to traffic engineering. Still, the most unpredictable contributors are the workloads running in the network. The link utilization and burstiness of these workloads dictate the buffer depth needed by a switch. But what is a burst? Do traditional definitions still apply in the age in which switches transfer terabits of data and billions of packets every second? Unless we assess bursts correctly, we are unlikely to size buffers appropriately. In this work, we present a measurement-led evaluation of the burstiness of different data center applications. We address the question of ``what is a burst?'' and assert that common techniques cannot answer this question in modern data centers. We quantify the change in burstiness of the studied applications across multiple vectors, including latency and network perspective, and generalize our results to the common case. Our observations can inform future buffer sizing efforts and guide switch configurations. Our dataset is openly available for the benefit of the community.Leverhulme Trust Isaac Newton Trus

Resource Management Algorithms for Computing Hardware Design and Operations: From Circuits to Systems

The complexity of computation hardware has increased at an unprecedented rate for the last few decades. On the computer chip level, we have entered the era of multi/many-core processors made of billions of transistors. With transistor budget of this scale, many functions are integrated into a single chip. As such, chips today consist of many heterogeneous cores with intensive interaction among these cores. On the circuit level, with the end of Dennard scaling, continuously shrinking process technology has imposed a grand challenge on power density. The variation of circuit further exacerbated the problem by consuming a substantial time margin. On the system level, the rise of Warehouse Scale Computers and Data Centers have put resource management into new perspective. The ability of dynamically provision computation resource in these gigantic systems is crucial to their performance. In this thesis, three different resource management algorithms are discussed. The first algorithm assigns adaptivity resource to circuit blocks with a constraint on the overhead. The adaptivity improves resilience of the circuit to variation in a cost-effective way. The second algorithm manages the link bandwidth resource in application specific Networks-on-Chip. Quality-of-Service is guaranteed for time-critical traffic in the algorithm with an emphasis on power. The third algorithm manages the computation resource of the data center with precaution on the ill states of the system. Q-learning is employed to meet the dynamic nature of the system and Linear Temporal Logic is leveraged as a tool to describe temporal constraints. All three algorithms are evaluated by various experiments. The experimental results are compared to several previous work and show the advantage of our methods

FastPay: High-Performance Byzantine Fault Tolerant Settlement

FastPay allows a set of distributed authorities, some of which are Byzantine, to maintain a high-integrity and availability settlement system for pre-funded payments. It can be used to settle payments in a native unit of value (crypto-currency), or as a financial side-infrastructure to support retail payments in fiat currencies. FastPay is based on Byzantine Consistent Broadcast as its core primitive, foregoing the expenses of full atomic commit channels (consensus). The resulting system has low-latency for both confirmation and payment finality. Remarkably, each authority can be sharded across many machines to allow unbounded horizontal scalability. Our experiments demonstrate intra-continental confirmation latency of less than 100ms, making FastPay applicable to point of sale payments. In laboratory environments, we achieve over 80,000 transactions per second with 20 authorities---surpassing the requirements of current retail card payment networks, while significantly increasing their robustness