Infrastructureless smart cities. Use cases and performance

Paradells, Josep; Gómez, Carles; Demirkol, Ilker; Oller, Joaquim; Catalán, Miguel

doi:10.1109/saconet.2014.6867772

Cited by 16 publications

(16 citation statements)

References 15 publications

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“…The sensing nodes will only be activated when the mobile data collector sends the WuS querying these nodes for data (on-demand) [17]. The feasibility of utilizing WuRs for data aggregation and for opportunistic networking in a smart city scenario has been demonstrated in [166].…”

Section: B Smart Citymentioning

confidence: 99%

Ultra Low Power Wake-Up Radios: A Hardware and Networking Survey

Piyare

Murphy

Király

et al. 2017

IEEE Commun. Surv. Tutorials

221

160

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In wireless environments, transmission and 1 reception costs dominate system power consumption, motivating 2 research effort on new technologies capable of reducing the 3 footprint of the radio, paving the way for the Internet of 4 Things. The most important challenge is to reduce power 5 consumption when receivers are idle, the so called idle-listening 6 cost. One approach proposes switching off the main receiver, 7 then introduces new wake-up circuitry capable of detecting 8 an incoming transmission, optionally discriminating the packet 9 destination using addressing, then switching on the main radio 10 only when required. This wake-up receiver technology represents 11 the ultimate frontier in low power radio communication. In 12 this paper, we present a comprehensive literature review of 13 the research progress in wake-up radio (WuR) hardware and 14 relevant networking software. First, we present an overview of 15 the WuR system architecture, including challenges to hardware 16 design and a comparison of solutions presented throughout the 17 last decade. Next, we present various medium access control and 18 routing protocols as well as diverse ways to exploit WuRs, both 19 as an extension of pre-existing systems and as a new concept to 20 manage low-power networking.

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Section: B Smart Citymentioning

confidence: 99%

Ultra Low Power Wake-Up Radios: A Hardware and Networking Survey

Piyare

Murphy

Király

et al. 2017

IEEE Commun. Surv. Tutorials

221

160

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“…In [4], the authors discussed the networking and communications challenges encountered in smart cities. Paradells et al [7] state that deploying wireless sensor networks along with the aggregation network in different locations in the smart city is very costly and consequently propose an infrastructure-less approach in which vehicles equipped with sensors is used to collect data.…”

Section: Related Workmentioning

confidence: 99%

Opportunistic Data Ferrying in Areas with Limited Information and Communications Infrastructure

Mohammed

Tabatabai

Al-Fuqaha

et al. 2019

2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)

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Interest in smart cities is rapidly rising due to the global rise in urbanization and the wide-scale instrumentation of modern cities. Due to the considerable infrastructural cost of setting up smart cities and smart communities, researchers are exploring the use of existing vehicles on the roads as "message ferries" for the transport data for smart community applications to avoid the cost of installing new communication infrastructure. In this paper, we propose an opportunistic data ferry selection algorithm that strives to select vehicles that can minimize the overall delay for data delivery from a source to a given destination. Our proposed opportunistic algorithm utilizes an ensemble of online hiring algorithms, which are run together in passive mode, to select the online hiring algorithm that has performed the best in recent history. The proposed ensemblebased algorithm is evaluated empirically using real-world traces from taxies plying routes in Shanghai, China, and its performance is compared against a baseline of four state-of-the-art online hiring algorithms. A number of experiments are conducted and our results indicate that the proposed algorithm can reduce the overall delay compared to the baseline by an impressive 13% to 258%.Index Terms-Data ferrying, opportunistic online algorithm, smart communities, limited information and communications infrastructure, hiring algorithms.

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“…The next column shows the error detection latency (EDL), which is given by the workload size S required for the online signal probabilities to converge. Following is the number of monitored cones C = [1,5,10,15]. The next columns present the EC of errors induced by 1, 2, or 3 input bit-flips in the selected cones, which are calculated as shown in (3).…”

Section: A Error Coverage Simulationmentioning

confidence: 99%

“…The maintenance of electronic devices used in low-power Internet-of-Things (IoT) applications often requires physical access which might be impractical and has to be planned in advance [1]. Devices that exhibit systematic erroneous behaviour (SEB) must be identified and replaced.…”

Section: Introductionmentioning

confidence: 99%

Low cost error monitoring for improved maintainability of IoT applications

Gutierrez

Tenentes

Kázmierski

et al. 2017

2017 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)

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Abstract-Electronic systems with power-constrained embedded devices are used for a variety of IoT applications, such as geomonitoring, parking sensors and surveillance. Such applications may tolerate few errors. However, with the increasing occurrence of faults in-the-field, devices that exhibit systematic erroneous behaviour must be eventually identified and replaced. In this paper, we propose a novel low cost error monitoring technique to assist the maintainability planning of low power IoT applications by ranking devices based on the systematic erroneous behaviour they exhibit. Small on-chip monitors are used to collect the signal probability information at the outputs of each device which is then transmitted to the system software via the communications channel of the system to rank them accordingly. To evaluate the error monitoring capabilities of the proposed technique, we injected multiple bit-flips and stuck-at faults on a set of the EPFL and the ISCAS benchmarks. Results demonstrate an average error coverage of 84.4% and 73.1% of errors induced by bit-flips and stuck-at faults, respectively, with an average area cost of 1.52%. A maintainability planning simulation shows that the proposed technique achieves a reduction of 26x to 263x in area cost and static power, and consumes over 625x less power for communications when compared against duplication and comparison.

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Infrastructureless smart cities. Use cases and performance

Cited by 16 publications

References 15 publications

Ultra Low Power Wake-Up Radios: A Hardware and Networking Survey

Ultra Low Power Wake-Up Radios: A Hardware and Networking Survey

Opportunistic Data Ferrying in Areas with Limited Information and Communications Infrastructure

Low cost error monitoring for improved maintainability of IoT applications

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