MultiEdge: An Edge-based Communication Subsystem for Scalable Commodity Servers
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At the core of contemporary high performance computer systems is the communication infrastructure. For this reason, there has been a lot of work on providing low-latency, high-bandwidth communication subsystems for clusters. In this paper, we introduce MultiEdge, a connection oriented communication system designed for high-speed commodity hardware. MultiEdge provides support for end-to-end flow -control, ordering, and reliable transmission. It transparently supports multiple physical links within a single connection. We use MultiEdge to examine the behavior of edge-based protocols using both micro-benchmarks and real-life shared memory applications. Our results show that MultiEdge is able to deliver about 88% of the nominal link throughput with a single 10-GBit/s link and more than 95% with multiple 1-GBit/s links. Our application results show that performing all of the communication protocol at the edge does not seem to cause any degradation in performance.Internet of Things is a widespread technology that comprises several networking solutions for connecting things to the rest of the Internet. Understanding the characteristics of such solutions is fundamental in order to satisfy the diverse requirements of all the possible applications. The goal of this paper is to empirically evaluate and compare the performance of the most spread technologies for IoT low-power long-range communications. The parameters considered are the energy efficiency, the message losses, and the latency of a message. Obtained results show that up to 2% of messages can be lost when using LoRaWAN, but the latency is always smaller than 7 seconds. NB-IoT shows slightly larger latency values and more delivered messages than LoRaWAN. The messages sent using Sigfox are always correctly delivered, but the communication introduces delays up to 100 seconds. These results are of great importance for all the players in the IoT scenario interested in LPWAN technologies. The results of this study show how different communication technologies provide significantly different performance.
LPWAN
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High latency internet connection can impair the perception of live broadcasts, create problems in case working in video chats, trading on the exchange and streaming because of the standard way of data packet processing. The ways to reduce latency using new methods of forming and processing data packets had been considered. Comparison of latency between video chats and broadcasts with/without latency reduction technologies was made. Solutions were analyzed for implementing low latency in Internet TV. Existing low latency solutions were researched and analyzed. A streaming session was performed using some of the popular low latency solutions. The claimed delay time was compared with the actual. It was concluded that modern technologies that provide a low level of delay reduce it to a low level when streaming video over the Internet TV.
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Internet video
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With the rapid development of streaming media applications, clustered streaming media proxy servers have become the mainstream of high-end streaming media proxy. To increase the IO throughput capacity of streaming media proxy servers, the most effective method is middle-ware technology in which several servers are bridged together to form a proxy cache server cluster, and the key is the coordination of individual proxy servers. The decision problem of the user request dispatch actually belongs to NP-complete. This article proposes an online coordination algorithm for the load sharing streaming media proxy servers, and discusses the relative deviation of the online algorithm from the optimal solution, to serve as a reference to the specific applications of clustered streaming media proxy servers.
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Load sharing
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Content Delivery Networks (CDNs) are increasingly being used to deliver live streaming on today's Internet. The new application type of live streaming exposes unique characteristics and challenges that require more advanced design of CDN infrastructure. Unlike traditional web-object delivering, which allows CDN content servers to cache contents and thus typically only involves certain CDN servers (e.g. edge content servers) for delivering contents, live streaming requires a real-time full CDN streaming path that spans across the streaming source, the CDN ingest server, the CDN content server, and end-viewers. Though the ingest server is typically fixed for a particular live stream, appropriate content servers need to be selected for delivering the stream to end viewers. Though today's CDNs typically employ layered infrastructure for delivering live streaming, in this work, we propose a flat-layered design which is referred to as Constrained Server Chaining (CSC) for selecting optimal content servers to deliver live streams. Rather than employing a strictly layered infrastructure, CSC allows CDN streaming servers to dynamically choose upstream servers, thus saves transit cost for CDN providers.
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Content Delivery
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Live streaming remains a challenge in the adaptive streaming space due to the stringent requirements for not just quality and rebuffering, but also latency. Many solutions have been proposed to tackle streaming in general, but only few have looked into better catering to the more challenging low-latency live streaming scenarios. In this paper, we re-visit and extend several important components (collectively called Low-on-Latency, LoL) in adaptive streaming systems to enhance the low-latency performance. LoL includes bitrate adaptation (both heuristic and learning-based), playback control and throughput measurement modules.
Live Streaming
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In machine type communication (MTC), diverse applications requiring high reliability and low latency lead to the consideration of ultra-reliable and low-latency MTC (uMTC) communication scenarios. Consequently, two-step random access procedure (RAP), as an alternative to the four-step RAP, is introduced into the 5th generation (5G) communication systems to reduce the unnecessary latency caused by the multi-round transmissions in the wireless medium. In this paper, we first analyze the delay performance of the two-step RAP based on which we further propose an algorithm to control the number of preambles allocated for the two-step RAP to meet a given average delay requirement. In particular, our proposed algorithm estimates the number of active devices in an online manner and controls the number of preambles to be allocated. Through extensive simulations, we show the effectiveness of our proposed algorithm in satisfying the delay requirement as well as minimizing the preamble resource usage.
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In the present paper, an attempt is made to combine Mask-CTC and the triggered attention mechanism to construct a streaming end-to-end automatic speech recognition (ASR) system that provides high performance with low latency. The triggered attention mechanism, which performs autoregressive decoding triggered by the CTC spike, has shown to be effective in streaming ASR. However, in order to maintain high accuracy of alignment estimation based on CTC outputs, which is the key to its performance, it is inevitable that decoding should be performed with some future information input (i.e., with higher latency). It should be noted that in streaming ASR, it is desirable to be able to achieve high recognition accuracy while keeping the latency low. Therefore, the present study aims to achieve highly accurate streaming ASR with low latency by introducing Mask-CTC, which is capable of learning feature representations that anticipate future information (i.e., that can consider long-term contexts), to the encoder pre-training. Experimental comparisons conducted using WSJ data demonstrate that the proposed method achieves higher accuracy with lower latency than the conventional triggered attention-based streaming ASR system.
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In this paper, we present very recent results regarding the latency characterization of a novel bidirectional visible light communication (VLC) system for vehicular applications, which could be relevant in intelligent transportation system (ITS) safety applications, such as the assisted and automated braking of cars and motorbikes in critical situations. The VLC system has been implemented using real motorbike head- and tail-lights with distances up to 27 m in a realistic outdoor scenario. We performed a detailed statistical analysis of the observed error distribution in the communication process, assessing the most probable statistical values of expected latency depending on the observed packet error rate (PER). A minimum attainable observed round-trip latency of 2.5 ms was measured. Using our dataset, we have also estimated the probability to receive correctly a message with a specific average latency for a target PER, and we compare it to the ultra-reliable low-latency (URLL) 5G communications service. In addition, a mobility model is implemented to compare the VLC and radio frequency (RF) technologies (IEEE802.11p, LTE, 5G) to support an automated braking systems for vehicles in urban platooning.
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Simulations based on real-time data continuously gathered from sensor networks all over the world have received growing attention due to the increasing availability of measured data. Furthermore, predictive techniques have been employed in the realm of such networks to reduce communication for energy-efficiency. However, research has focused on the high amounts of data transferred rather than latency requirements posed by the applications. We propose using predictors to supply data with low latency as required for accurate simulations. This paper investigates requirements for a successful combination of these concepts and discusses challenges that arise.
Realm
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