Azure Data Lake Store (ADLS) is a fully-managed, elastic, scalable, and secure file system that supports Hadoop distributed file system (HDFS) and Cosmos semantics. It is specifically designed and optimized for a broad spectrum of Big Data analytics that depend on a very high degree of parallel reads and writes, as well as collocation of compute and data for high bandwidth and low-latency access. It brings together key components and features of Microsoft?s Cosmos file system-long used by internal customers at Microsoft and HDFS, and is a unified file storage solution for analytics on Azure. Internal and external workloads run on this unified platform. Distinguishing aspects of ADLS include its design for handling multiple storage tiers, exabyte scale, and comprehensive security and data sharing features. We present an overview of ADLS architecture, design points, and performance.

We present a new metric for routing in multi-radio, multi-hop wireless networks. We focus on wireless networks with stationary nodes, such as community wireless networks.The goal of the metric is to choose a high-throughput path between a source and a destination. Our metric assigns weights to individual links based on the Expected Transmission Time (ETT) of a packet over the link. The ETT is a function of the loss rate and the bandwidth of the link. The individual link weights are combined into a path metric called Weighted Cumulative ETT (WCETT) that explicitly accounts for the interference among links that use the same channel. The WCETT metric is incorporated into a routing protocol that we call Multi-Radio Link-Quality Source Routing.We studied the performance of our metric by implementing it in a wireless testbed consisting of 23 nodes, each equipped with two 802.11 wireless cards. We find that in a multi-radio environment, our metric significantly outperforms previously-proposed routing metrics by making judicious use of the second radio.

Routing protocols for wireless ad hoc networks have traditionally focused on finding paths with minimum hop count. However, such paths can include slow or lossy links, leading to poor throughput. A routing algorithm can select better paths by explicitly taking the quality of the wireless links into account. In this paper, we conduct a detailed, empirical evaluation of the performance of three link-quality metrics---ETX, per-hop RTT, and per-hop packet pair---and compare them against minimum hop count. We study these metrics using a DSR-based routing protocol running in a wireless testbed. We find that the ETX metric has the best performance when all nodes are stationary. We also find that the per-hop RTT and per-hop packet-pair metrics perform poorly due to self-interference. Interestingly, the hop-count metric outperforms all of the link-quality metrics in a scenario where the sender is mobile.

The Border Gateway Protocol (BGP) populates Internet backbone routers with routes or prefixes. We present an algorithm to locally compute (without any modification to BGP) equivalent forwarding tables that provably contain the minimal number of prefixes. For large backbone routers, the Optimal Routing Table Constructor (ORTC) algorithm that we present produces routing tables with roughly 60% of the original number of prefixes. The publicly available MaeEast database with 41315 prefixes reduces to 23007 prefixes when ORTC is applied. We present performance measurements on four publicly available databases and a formal proof that ORTC does produce the optimal set of routes.

This paper describes ongoing investigations into algorithms for modular distributed real-time resource management. These investigations are being conducted in the context of the Rialto operating system-an object-based real-time kernel and programming environment currently being developed within Microsoft Research. Some of the goals of this research include developing appropriate real-time programming abstractions to allow multiple independent real-time programs to dynamically coexist and share resources on the same hardware platforms. Use of these abstractions is intended both to allow individual applications to reason about their own resource requirements and for per-machine system resource planner applications to reason about and control resource allocations between potentially competing applications. The set of resources being managed is dynamically extensible, and may include remote resources in distributed environments. The local planner conducts resource negotiations with individual applications on behalf of the user, with the goal of maximizing the user's perceived utility of the set of running applications with respect to resource allocations for those applications.

We have improved the performance of the Mach 3.0 operating system by redesigning its internal thread and interprocess communication facilities to use continuations as the basis for control transfer. Compared to previous versions of Mach 3.0, our new system consumes 85% less space per thread. Cross-address space remote procedure calls execute 14% faster. Exception handling runs over 60% faster.In addition to improving system performance, we have used continuations to generalize many control transfer optimizations that are common to operating systems, and have recast those optimizations in terms of a single implementation methodology. This paper describes our experiences with using continuations in the Mach operating system.