Network Analysis By Ganesh Rao Pdf Free 'LINK' 45
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Abstract: Network telemetry is essential for administrators to monitor massive data traffic in a network-wide manner. Existing telemetry solutions often face the dilemma between resource efficiency (i.e., low CPU, memory, and bandwidth overhead) and full accuracy (i.e., error-free and holistic measurement). We break this dilemma via a network-wide architectural design OmniMon, which simultaneously achieves resource efficiency and full accuracy in flow-level telemetry for large-scale data centers. OmniMon carefully coordinates the collaboration among different types of entities in the whole network to execute telemetry operations, such that the resource constraints of each entity are satisfied without compromising full accuracy. It further addresses consistency in network-wide epoch synchronization and accountability in error-free packet loss inference. We prototype OmniMon in DPDK and P4. Testbed experiments on commodity servers and Tofino switches demonstrate the effectiveness of OmniMon over state-of-the-art telemetry designs.
Abstract: Recently, traffic engineering mechanisms have been developed that guarantee that a network (cloud provider WAN, or ISP) does not experience congestion under failures. In this paper, we show that existing congestion-free mechanisms, notably FFC, achieve performance far short of the network's intrinsic capability. We propose PCF, a set of novel congestion-free mechanisms to bridge this gap. PCF achieves these goals by better modeling network structure, and by carefully enhancing the flexibility of network response while ensuring that the performance under failures can be tractably modeled. All of PCF's schemes involve relatively light-weight operations on failures, and many of them can be realized using a local proportional routing scheme similar to FFC. We show PCF's effectiveness through formal theoretical results, and empirical experiments over 21 Internet topologies. PCF's schemes provably out-perform FFC, and in practice, can sustain higher throughput than FFC by a factor of 1.11X to 1.5X on average across the topologies, while providing a benefit of 2.6X in some cases.
Abstract: Recent verification work has made advances in finding bugs in P4 programs before deployment, but it requires that the programmer specifies table rules that are possible at runtime[32, 24, 27]. This imposes a specification burden on the programmer, while at the same time failing to guarantee that bugs will not be inserted at runtime by faulty controllers.We present bf4, a novel verification approach for P4 programs that uses a mix of static verification, code changes and runtime checks to ensure that the deployed P4 program is bug free. To achieve this, bf4 uses static analysis to find all possible bugs in the P4 program; for each possible bug, bf4 attempts to find predicates that, when applied to table rules inserted by the controller, make that bug unreachable. If such predicates do not exist, bf4 can change the P4 code and re-run the procedure above.We applied bf4 to a wide range of P4 programs; for all these, bf4 is able to generate controller assertions and propose fixes that guarantee no controller-induced bug is reachable. At runtime, bf4 checks that the controller does not insert faulty rules; when it does, it throws an exception which helps troubleshoot the bug.
Abstract: The Domain Name System (DNS) plays a vital role in today's Internet but relies on complex distributed management of records. DNS misconfiguration related outages have rendered popular services like GitHub, HBO, LinkedIn, and Azure inaccessible for extended periods. This paper introduces GRoot, the first verifier that performs static analysis of DNS configuration files, enabling proactive and exhaustive checking for common DNS bugs; by contrast, existing solutions are reactive and incomplete. GRoot uses a new, fast verification algorithm based on generating and enumerating DNS query equivalence classes. GRoot symbolically executes the set of queries in each equivalence class to efficiently find (or prove the absence of) any bugs such as rewrite loops. To prove the correctness of our approach, we develop a formal semantic model of DNS resolution. Applied to the configuration files from a campus network with over a hundred thousand records, GRoot revealed 109 bugs within seconds. When applied to internal zone files consisting of over 3.5 million records from a large infrastructure service provider, GRoot revealed around 160k issues of blackholing, initiating a cleanup. Finally, on a synthetic dataset with over 65 million real records, we find GRoot can scale to networks with tens of millions of records.
Abstract: Persistent packet loss in the cloud-scale overlay network severely compromises tenant experiences. Cloud providers are keen to automatically and quickly determine the root cause of such problems. However, existing work is either designed for the physical network or insufficient to present the concrete reason of packet loss. In this paper, we propose to record and analyze the on-site forwarding condition of packets during packet-level tracing. The cloud-scale overlay network presents great challenges to achieve this goal with its high network complexity, multi-tenant nature, and diversity of root causes. To address these challenges, we present VTrace, an automatic diagnostic system for persistent packet loss over the cloud-scale overlay network. Utilizing the "fast path-slow path" structure of virtual forwarding devices (VFDs), e.g., vSwitches, VTrace installs several "coloring, matching and logging" rules in VFDs to selectively track the packets of interest and inspect them in depth. The detailed forwarding situation at each hop is logged and then assembled to perform analysis with an efficient path reconstruction scheme. Experiments are conducted to demonstrate VTrace's low overhead and quick responsiveness. We share experiences of how VTrace efficiently resolves persistent packet loss issues after deploying it in Alibaba Cloud for over 20 months.
Abstract: WiFi backscatter communication has the potential to enable battery-free sensors which can transmit data using a WiFi network. In order for WiFi backscatter systems to be practical they should be compatible with existing WiFi networks without any hardware or software modifications. Moreover, they should work with networks that use encryption. In this paper, we present WiTAG which achieves these requirements, making the implementation and deployment of WiFi backscatter communication more practical. In contrast with existing systems which utilize the physical layer for backscatter communication, we take a different approach by leveraging features of the MAC layer to communicate. WiTAG is designed to send data by selectively interfering with subframes (MPDUs) in an aggregated frame (A-MPDU). This enables standard compliant communication using modern, open or encrypted 802.11n and 802.11ac networks without requiring hardware or software modifications to any devices. We implement WiTAG using off-the-shelf components and evaluate its performance in line-of-sight and non-line-of-sight scenarios. We show that WiTAG achieves a throughput of up to 4 Kbps without impacting other devices in the network.
Abstract: The difficulty of building large data centers in dense metro areas is pushing big cloud providers towards a different approach to scaling: multiple smaller data centers within tens of kilometers of each other, comprising a "region". We show that networking this small number of nearby sites with each other is a surprisingly challenging and multi-faceted problem. We draw out the operational goals and constraints of such networks, and highlight the design trade-offs involved using data from Microsoft Azure's regions.Our analysis of the design space shows that network topologies that achieve lower latency and allow greater flexibility in data center placement are, unfortunately, encumbered by their much greater cost and complexity. We thus present and demonstrate a novel optical-circuit-switched architecture, Iris, that lowers these cost and complexity barriers, making a richer topology design space more accessible to operators of regional networks. With Iris, topologies which, in comparison to a simple hub-and-spoke topology can increase the area in which a new DC can be placed by 2-5x, can be implemented at a cost within 1.1x of the simple hub-and-spoke topology, and 7x cheaper than a natural packet-switched network.
Abstract: 5G, as a monumental shift in cellular communication technology, holds tremendous potential for spurring innovations across many vertical industries, with its promised multi-Gbps speed, sub-10 ms low latency, and massive connectivity. On the other hand, as 5G has been deployed for only a few months, it is unclear how well and whether 5G can eventually meet its prospects. In this paper, we demystify operational 5G networks through a first-of-its-kind cross-layer measurement study. Our measurement focuses on four major perspectives: (i) Physical layer signal quality, coverage and hand-off performance; (ii) End-to-end throughput and latency; (iii) Quality of experience of 5G's niche applications (e.g., 4K/5.7K panoramic video telephony); (iv) Energy consumption on smartphones. The results reveal that the 5G link itself can approach Gbps throughput, but legacy TCP leads to surprisingly low capacity utilization (< 32%), latency remains too high to support tactile applications and power consumption escalates to 2 - 3x over 4G. Our analysis suggests that the wireline paths, upper-layer protocols, computing and radio hardware architecture need to co-evolve with 5G to form an ecosystem, in order to fully unleash its potential.
Abstract: While many deep learning (DL)-based networking systems have demonstrated superior performance, the underlying Deep Neural Networks (DNNs) remain blackboxes and stay uninterpretable for network operators. The lack of interpretability makes DL-based networking systems prohibitive to deploy in practice. In this paper, we propose Metis, a framework that provides interpretability for two general categories of networking problems spanning local and global control. Accordingly, Metis introduces two different interpretation methods based on decision tree and hypergraph, where it converts DNN policies to interpretable rule-based controllers and highlight critical components based on analysis over hypergraph. We evaluate Metis over two categories of state-of-the-art DL-based networking systems and show that Metis provides human-readable interpretations while preserving nearly no degradation in performance. We further present four concrete use cases of Metis, showcasing how Metis helps network operators to design, debug, deploy, and ad-hoc adjust DL-based networking systems. 2b1af7f3a8