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Traditionally, the idea of overlapping generations in network coding research has focused on reducing the complexity of decoding large data files while maintaining the delay performance expected of a system that combines all data packets. However, the effort for encoding and decoding individual generations can still be quite high compared to other sparse coding approaches. This paper focuses on an inherently different approach that combines (i) sparsely coded generations configured on-the-fly based on (ii) controllable and infrequent feedback that allows the system to remove some original packets from the pool of packets to be mixed in the linear combinations. The latter is key to maintain a high impact of the coded packets received during the entire process while maintaining very sparsely coded generations. Interestingly, our proposed approach naturally bridges the idea of overlapping generations with that of tunable sparse network coding, thus providing the system with a seamless and adaptive strategy to balance complexity and delay performance. We analyze two families of strategies focused on these ideas. We also compare them to other standard approaches both in terms of delay performance and complexity as well as providing measurements in commercial devices to support our conclusions. Our results show that a judicious choice of the overlapping of the generations provides close-to-optimal delay performance, while reducing the decoding complexity by up to an order of magnitude with respect to other schemes.

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Abstract:Given that next generation networks are expected to be populated by a large number of devices, there is a need for quick deployment and evaluation of alternative mechanisms to cope with the possible generated traffic in large-scale distributed data networks. In this sense, the Raspberry Pi has been a popular network node choice due to its reduced size, processing capabilities, low cost and its support by widely-used operating systems. For information transport, network coding is a new paradigm for fast and reliable data processing in networking and storage systems, which overcomes various limitations of state-of-the-art routing techniques. Therefore, in this work, we provide an in-depth performance evaluation of Random Linear Network Coding (RLNC)-based schemes for the Raspberry Pi Models 1 and 2, by showing the processing speed of the encoding and decoding operations and the corresponding energy consumption. Our results show that, in several scenarios, processing speeds of more than 80 Mbps in the Raspberry Pi Model 1 and 800 Mbps in the Raspberry Pi Model 2 are attainable. Moreover, we show that the processing energy per bit for network coding is below 1 nJ or even an order of magnitude less in these scenarios.

Abstract:In the near future, upcoming communications and storage networks are expected to tolerate major difficulties produced by huge amounts of data being generated from the Internet of Things (IoT). For these types of networks, strategies and mechanisms based on network coding have appeared as an alternative to overcome these difficulties in a holistic manner, e.g., without sacrificing the benefit of a given network metric when improving another. There has been recurrent issues on: (i) making large-scale deployments akin to the Internet of Things; (ii) assessing and (iii) replicating the obtained results in preliminary studies. Therefore, finding testbeds that can deal with large-scale deployments and not lose historic data in order to evaluate these mechanisms are greatly needed and desirable from a research perspective. However, this can be hard to manage, not only due to the inherent costs of the hardware, but also due to maintenance challenges. In this paper, we present the required key steps to design, setup and maintain an inexpensive testbed using Raspberry Pi devices for communications and storage networks with network coding capabilities. This testbed can be utilized for any applications requiring results replicability.

Although network coding has shown the potential to revolutionize networking and storage, its deployment has faced a number of challenges. Usual proposals involve two approaches. First, deploying a new protocol (e.g., Multipath Coded TCP), or retrofitting another one (e.g., TCP/NC) to deliver benefits to any application in a computer. However, incorporating new protocols to the Internet is a challenging and slow process. Second, deploying coding at the application layer, which forces each application to implement network coding. This paper proposes an alternative approach through the use of a network coded filesystem shim (NCFSS), where coded data is generated at the filesystem level supporting any application and any network protocol. Our design allows multiple sources of a content to serve data without coordination to a receiver over multiple data paths. Another interesting feature of our approach is that it allows caches in the network to store only a fraction of a specific content in coded form, but sharing the same object identification, i.e., it simplifies the signaling and search of coded content. We describe the NCFSS design and implementation using FUSE and carry out measurements using servers in six countries to demonstrate gains of two to five fold in download speed.