Easy as Pi: A Network Coding Raspberry Pi Testbed

Sorensen, Chres W.; Marcano, Néstor J. Hernández; Guerrero, Josep M.; Wunderlich, Simon; Lucani, Daniel E.; Fitzek, Frank H. P.

doi:10.3390/electronics5040067

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…It then passes the acquired data to the client application, which is running on a Linux Debian operating system. It is equipped with a powerful application processor [ 25 , 26 , 27 ]. The client-end sends 4 × 4 keypad’s user-data and the GPS sensor’s location data serially to the General Purpose Input/Output (GPIO) pins of the Raspberry Pi.…”

Section: System Design and Implementationmentioning

confidence: 99%

An Emergency Response System: Construction, Validation, and Experiments for Disaster Management in a Vehicular Environment

Khaliq

Chughtai

Shahwani

et al. 2019

Sensors

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Natural disasters and catastrophes not only cost the loss of human lives, but adversely affect the progress toward sustainable development of the country. As soon as disaster strikes, the first and foremost challenge for the concerned authorities is to make an expeditious response. Consequently, they need to be highly-organized, properly-trained, and sufficiently-equipped to effectively respond and limit the destructive effects of a disaster. In such circumstances, communication plays a vital role, whereby the consequences of tasks assigned to the workers for rescue and relief services may be streamlined by relaying necessary information among themselves. Moreover, most of the infrastructure is either severely damaged or completely destroyed in post-disaster scenarios; therefore, a Vehicular Ad Hoc Network (VANET) is used to carry out the rescue operation, as it does not require any pre-existing infrastructure. In this context, the current work proposes and validates an effective way to relay the crucial information through the development of an application and the deployment of an experimental TestBed in a vehicular environment. The TestBed may able to provide a way to design and validate the algorithms. It provides a number of vehicles with onboard units embedded with a credit-card-size microcomputer called Raspberry Pi and a Global Positioning System (GPS) module. Additionally, it dispatches one of the pre-defined codes of emergency messages based on the level of urgency through multiple hops to a central control room. Depending on the message code received from a client, the server takes appropriate action. Furthermore, the solution also provides a graphical interface that is easy to interpret and to understand at the control room to visualize the rescue operation on the fly.

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Section: System Design and Implementationmentioning

confidence: 99%

An Emergency Response System: Construction, Validation, and Experiments for Disaster Management in a Vehicular Environment

Khaliq

Chughtai

Shahwani

et al. 2019

Sensors

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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

Self Cite

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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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“…Ad hoc nodes implemented by using Raspberry Pi with USB wireless network card model of TP-Link WN722N. In the paper [6], the authors present the required steps to implement and configure an inexpensive testbed. This testbed built using Raspberry Pi nodes for communications and storage.…”

Section: Related Workmentioning

confidence: 99%

MANET Testbed using Raspberry PIs

Sati¹,

El-bareg²

2018

IJWMT

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Mobile ad-hoc networks (MANETs) are without any infrastructure and consists only of equal peers. This paper presents an empirical tests for MANET routing protocols. The testbed based on Linux platform installed in mobile computers. Some parameters are analyzed such as movement speed and the number of hops which impact on routing performance. The testbed consists of several Raspberry Pis (RPis) without the need for any central master device. For making the RPis mobile and independent of any fixed power sockets, each of them is powered by a battery. On the other hand, for the evaluation of the testbed, two routing protocols are chosen. The first protocol is called BABEL, which considered as a distance vector routing algorithm. The other one, the Optimized Link State Routing Protocol (OLSR) which considered as proactive routing protocol. The use case was a multi-hop download of files with different size. The aim is to evaluate how multiple hops influence the bandwidth and delay. The results show that OLSR performs better regarding the throughput. But Babel has less delay and faster regarding convergence.

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Easy as Pi: A Network Coding Raspberry Pi Testbed

Cited by 5 publications

References 10 publications

An Emergency Response System: Construction, Validation, and Experiments for Disaster Management in a Vehicular Environment

An Emergency Response System: Construction, Validation, and Experiments for Disaster Management in a Vehicular Environment

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

MANET Testbed using Raspberry PIs

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