Recent literature including our past work provide analysis and solutions for using (i) erasure coding, (ii) parallelism, or (iii) variable slicing chunking (i.e., dividing an object of a specific size into a variable number of smaller chunks) in speeding the I O performance of storage clouds. However, a comprehensive approach that considers all three dimensions together to achieve the best throughput-delay trade-off curve had been lacking. This paper presents the first set of solutions that can pick the best combination of coding rate and object chunking slicing options as the load dynamically changes. Our specific contributions are as follows: (1) We establish via measurement that combining variable coding rate and chunking is mostly feasible over a popular public cloud. (2) We relate the delay optimal values for chunking level and code rate to the queue backlogs via an approximate queueing analysis. (3) Based on this analysis, we propose TOFEC that adapts the chunking level and coding rate against the queue backlogs. Our trace-driven simulation results show that TOFEC's adaptation mechanism converges to an appropriate code that provides the optimal throughput-delay trade-off without reducing system capacity. Compared to a non-adaptive strategy optimized for throughput, TOFEC delivers @math lower latency under light workloads; compared to a non-adaptive strategy optimized for latency, TOFEC can scale to support over @math as many requests. (4) We propose a simpler greedy solution that performs on a par with TOFEC in average delay performance, but exhibits significantly more performance variations.
FEC in connection with multiple paths and or multiple servers is a well investigated topic in the literature @cite_14 @cite_2 @cite_12 @cite_3 . However, there is very little attention devoted to the queueing delays. FEC in the context of network coding or coded scheduling has also been a popular topic from the perspectives of throughput (or network utility) maximization and throughput vs. service delay trade-offs @cite_1 @cite_18 @cite_13 @cite_5 . Although some incorporate queuing delay analysis, the treatment is largely for broadcast wireless channels with quite different system characteristics and constraints. FEC has also been extensively studied in the context of distributed storage from the points of high durability and availability while attaining high storage efficiency @cite_19 @cite_0 @cite_9 .
@cite_18 @cite_14 @cite_9 @cite_1 @cite_3 @cite_0 @cite_19 @cite_2 @cite_5 @cite_13 @cite_12
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We consider use of FEC to reduce in-order delivery delay over packet erasure channels. We propose a class of streaming codes that is capacity achieving and provides a superior throughput-delay trade-off compared to block codes by introducing flexibility in where and when redundancy is placed. This flexibility results in significantly lower in-order delay for a given throughput for a wide range of network scenarios. Furthermore, a major contribution of this paper is the combination of queuing and coding theory to analyze the code's performance. Finally, we present simulation and experimental results illustrating the code's benefits. High-performance real-time applications, expected to be of importance in the upcoming 5G era, such as virtual and augmented reality or tele-presence, have stringent requirements on throughput and per-packet in-order delivery delay . Use of multipath transport is gaining momentum for supporting these applications. However, building an efficient, low latency multipath transfer mechanism remains highly challenging. The primary reason for this is that the delivery delay along each path is typically uncertain and time-varying. When the transmitter ignores the stochastic nature of the path delays, then packets sent along different paths frequently arrive out of order and need to be buffered at the receiver to allow in-order delivery to the application. In this paper, we propose Stochastic Earliest Delivery Path First (S-EDPF), a generalization of EDPF which takes into account uncertainty and time-variation in path delays yet has low-complexity suited to practical implementation. Moreover, we integrate a novel low-delay Forward Error Correction (FEC) scheme into S-EDPF in a principled manner by deriving the optimal schedule for coded packets across multiple paths. Finally, we demonstrate, both analytically and empirically, that S-EDPF is effective at mitigating the delay impact of reordering and loss in multipath transport protocols, offering substantial performance gains over the state of the art. In this paper, we study the problem of reducing the delay of downloading data from cloud storage systems by leveraging multiple parallel threads, assuming that the data has been encoded and stored in the clouds using fixed rate forward error correction (FEC) codes with parameters (n, k). That is, each file is divided into k equal-sized chunks, which are then expanded into n chunks such that any k chunks out of the n are sufficient to successfully restore the original file. The model can be depicted as a multiple-server queue with arrivals of data retrieving requests and a server corresponding to a thread. However, this is not a typical queueing model because a server can terminate its operation, depending on when other servers complete their service (due to the redundancy that is spread across the threads). Hence, to the best of our knowledge, the analysis of this queueing model remains quite uncharted. Recent traces from Amazon S3 show that the time to retrieve a fixed size chunk is random and can be approximated as a constant delay plus an i.i.d. exponentially distributed random variable. For the tractability of the theoretical analysis, we assume that the chunk downloading time is i.i.d. exponentially distributed. Under this assumption, we show that any work-conserving scheme is delay-optimal among all on-line scheduling schemes when k = 1. When k > 1, we find that a simple greedy scheme, which allocates all available threads to the head of line request, is delay optimal among all on-line scheduling schemes. We also provide some numerical results that point to the limitations of the exponential assumption, and suggest further research directions. This paper proposes a Random Early Detection Forward Error Correction (RED-FEC) mechanism to improve the quality of video delivered over Wireless Local Area Networks (WLANs). In contrast to previous FEC schemes, in which the rate determination information is fed back from the receiver side, in our proposed method, the redundancy rate is calculated directly at the wireless Access Point (AP) in accordance with the network traffic load, as indicated by the AP queue length. An analytical model is developed to predict the effective packet loss rate of a video stream delivered over a WLAN with RED-FEC protection. The numerical results show that the proposed RED-FEC mechanism consistently achieves higher recovery efficiency than a conventional FEC scheme under high and low network loading conditions.