On Goodput and Energy Measurements of Network Coding Schemes in the Raspberry Pi

Marcano, Néstor J. Hernández; Sorensen, Chres W.; Cabrera, Juan A.; Wunderlich, Simon; Lucani, Daniel E.; Fitzek, Frank H. P.

doi:10.3390/electronics5040066

Cited by 8 publications

(7 citation statements)

References 36 publications

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“…The computational cost is highly reduced if we use a binary field, as it only requires exclusive-or operations which are natively supported by most central processing units (CPUs). If we measure the actual time used to transmit and decode, it is suggested in Reference [ 62 ] that the overall time is shorter if we use a binary field for all the field operations.…”

Section: Bats Codesmentioning

confidence: 99%

A Protocol Design Paradigm for Batched Sparse Codes

Yin

Yeung

Yang

2020

Entropy

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Internet of Things (IoT) connects billions of everyday objects to the Internet. The mobility of devices can be facilitated by means of employing multiple wireless links. However, packet loss is a common phenomenon in wireless communications, where the traditional forwarding strategy undergoes severe performance issues in a multi-hop wireless network. One solution is to apply batched sparse (BATS) codes. A fundamental difference from the traditional strategy is that BATS codes require the intermediate network nodes to perform recoding, which generates recoded packets by network coding operations. Literature showed that advanced recoding schemes and burst packet loss can enhance and diminish the performance of BATS codes respectively. However, the existing protocols for BATS codes cannot handle both of them at the same time. In this paper, we propose a paradigm of protocol design for BATS codes. Our design can be applied in different layers of the network stack and it is compatible to the existing network infrastructures. The modular nature of the protocol can support different recoding techniques and different ways to handle burst packet loss. We also give some examples to demonstrate how to use the protocol.

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Section: Bats Codesmentioning

confidence: 99%

A Protocol Design Paradigm for Batched Sparse Codes

Yin

Yeung

Yang

2020

Entropy

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“…The delay for a transmission with acknowledgement during connection also depends on buffer queueing and internal device processing. However, we did not include these two processes as they are negligible compared to the delays stemming from propagation and transmission processes for small embedded devices (Paramanathan et al, 2014;Hernandez Marcano et al, 2016).…”

Section: Communication Time Delay In Data Transmissionmentioning

confidence: 99%

A General Overview for Localizing Short Gamma-Ray Bursts with a CubeSat Mega-Constellation

Inceoglu¹,

Marcano²,

Jacobsen³

et al. 2020

Front. Astron. Space Sci.

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The Gamma-Ray Burst Monitor (GBM) on the Fermi Gamma-Ray Space Telescope, for the first time, detected a short gamma ray burst (SGRB) signal that accompanies a gravitational wave signal GW170817 in 2017. The detection and localization of the gravitational wave and gamma-ray source led all other space-and ground-based observatories to measure its kilonova and afterglow across the electromagnetic spectrum, which started a new era in astronomy, the so-called multi-messenger astronomy. Therefore, localizations of short gamma-ray bursts, as counterparts of verified gravitational waves, is of crucial importance since this will allow observatories to measure the kilonovae and afterglows associated with these explosions. Our results show that, an automated network of observatories, such as the Stellar Observations Network Group (SONG), can be coupled with an interconnected multi-hop array of CubeSats for transients (IMPACT) to localize SGRBs. IMPACT is a mega-constellation of ∼80 CubeSats, each of which is equipped with gamma-ray detectors with ultra-high temporal resolution to conduct full sky surveys in an energy range of 50-300 keV and downlink the required data promptly for high accuracy localization of the detected SGRB to a ground station. Additionally, we analyze propagation and transmission delays from receipt of a SGRB signal to ground station offload to consider the effects of constellation design, link, and network parameters such as satellites per plane, data rate, and coding gain from erasure correcting codes among others. IMPACT will provide near-real-time localization of SGRBs with a total delay of ∼5 s, and will enable SONG telescopes to join the efforts to pursue multi-messenger astronomy and help decipher the underlying physics of these events.

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“…RLNC computation on a fixed instruction-set Raspberry PI (Raspberry Pi Foundation, Cambridge, United Kingdom) testbed was studied in Refs. [77,78]. Related energy saving strategies were studied in Refs.…”

Section: Computation Of Rlncmentioning

confidence: 99%

Hardware Acceleration for RLNC: A Case Study Based on the Xtensa Processor with the Tensilica Instruction-Set Extension

et al. 2018

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Random linear network coding (RLNC) can greatly aid data transmission in lossy wireless networks. However, RLNC requires computationally complex matrix multiplications and inversions in finite fields (Galois fields). These computations are highly demanding for energy-constrained mobile devices. The presented case study evaluates hardware acceleration strategies for RLNC in the context of the Tensilica Xtensa LX5 processor with the tensilica instruction set extension (TIE). More specifically, we develop TIEs for multiply-accumulate (MAC) operations for accelerating matrix multiplications in Galois fields, single instruction multiple data (SIMD) instructions operating on consecutive memory locations, as well as the flexible-length instruction extension (FLIX). We evaluate the number of clock cycles required for RLNC encoding and decoding without and with the MAC, SIMD, and FLIX acceleration strategies. We also evaluate the RLNC encoding and decoding throughput and energy consumption for a range of RLNC generation and code word sizes. We find that for GF ( 2 8 ) and GF ( 2 16 ) RLNC encoding, the SIMD and FLIX acceleration strategies achieve speedups of approximately four hundred fold compared to a benchmark C code implementation without TIE. We also find that the unicore Xtensa LX5 with SIMD has seven to thirty times higher RLNC encoding and decoding throughput than the state-of-the-art ODROID XU3 system-on-a-chip (SoC) operating with a single core; the Xtensa LX5 with FLIX, in turn, increases the throughput by roughly 25% compared to utilizing only SIMD. Furthermore, the Xtensa LX5 with FLIX consumes roughly four orders of magnitude less energy than the ODROID XU3 SoC.

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On Goodput and Energy Measurements of Network Coding Schemes in the Raspberry Pi

Cited by 8 publications

References 36 publications

A Protocol Design Paradigm for Batched Sparse Codes

A Protocol Design Paradigm for Batched Sparse Codes

A General Overview for Localizing Short Gamma-Ray Bursts with a CubeSat Mega-Constellation

Hardware Acceleration for RLNC: A Case Study Based on the Xtensa Processor with the Tensilica Instruction-Set Extension

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