447 research outputs found

    Talk More Listen Less: Energy-Efficient Neighbor Discovery in Wireless Sensor Networks

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    Neighbor discovery is a fundamental service for initialization and managing network dynamics in wireless sensor networks and mobile sensing applications. In this paper, we present a novel design principle named Talk More Listen Less (TMLL) to reduce idle-listening in neighbor discovery protocols by learning the fact that more beacons lead to fewer wakeups. We propose an extended neighbor discovery model for analyzing wakeup schedules in which beacons are not necessarily placed in the wakeup slots. Furthermore, we are the first to consider channel occupancy rate in discovery protocols by introducing a new metric to trade off among duty-cycle, latency and channel occupancy rate. Guided by the TMLL principle, we have designed Nihao, a family of energy-efficient asynchronous neighbor discovery protocols for symmetric and asymmetric cases. We compared Nihao with existing state of the art protocols via analysis and real-world testbed experiments. The result shows that Nihao significantly outperforms the others both in theory and practice.Comment: 9 pages, 14 figures, published in IEEE INFOCOM 201

    Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

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    Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

    Channel Access Management in Data Intensive Sensor Networks

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    There are considerable challenges for channel access in Data Intensive Sensor Networks - DISN, supporting Data Intensive Applications like Structural Health Monitoring. As the data load increases, considerable degradation of the key performance parameters of such sensor networks is observed. Successful packet delivery ratio drops due to frequent collisions and retransmissions. The data glut results in increased latency and energy consumption overall. With the considerable limitations on sensor node resources like battery power, this implies that excessive transmissions in response to sensor queries can lead to premature network death. After a certain load threshold the performance characteristics of traditional WSNs become unacceptable. Research work indicates that successful packet delivery ratio in 802.15.4 networks can drop from 95% to 55% as the offered network load increases from 1 packet/sec to 10 packets/sec. This result in conjunction with the fact that it is common for sensors in an SHM system to generate 6-8 packets/sec of vibration data makes it important to design appropriate channel access schemes for such data intensive applications.In this work, we address the problem of significant performance degradation in a special-purpose DISN. Our specific focus is on the medium access control layer since it gives a fine-grained control on managing channel access and reducing energy waste. The goal of this dissertation is to design and evaluate a suite of channel access schemes that ensure graceful performance degradation in special-purpose DISNs as the network traffic load increases.First, we present a case study that investigates two distinct MAC proposals based on random access and scheduling access. The results of the case study provide the motivation to develop hybrid access schemes. Next, we introduce novel hybrid channel access protocols for DISNs ranging from a simple randomized transmission scheme that is robust under channel and topology dynamics to one that utilizes limited topological information about neighboring sensors to minimize collisions and energy waste. The protocols combine randomized transmission with heuristic scheduling to alleviate network performance degradation due to excessive collisions and retransmissions. We then propose a grid-based access scheduling protocol for a mobile DISN that is scalable and decentralized. The grid-based protocol efficiently handles sensor mobility with acceptable data loss and limited overhead. Finally, we extend the randomized transmission protocol from the hybrid approaches to develop an adaptable probability-based data transmission method. This work combines probabilistic transmission with heuristics, i.e., Latin Squares and a grid network, to tune transmission probabilities of sensors, thus meeting specific performance objectives in DISNs. We perform analytical evaluations and run simulation-based examinations to test all of the proposed protocols

    Energy-efficient wireless sensor networks via scheduling algorithm and radio Wake-up technology

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    One of the most important requirements for wireless sensor networks (WSNs) is the energy efficiency, since sensors are usually fed by a battery that cannot be replaced or recharged. Radio wake-up - the technology that lets a sensor completely turn off and be reactivated by converting the electromagnetic field of radio waves into energy - is now one of the most emergent strategies in the design of wireless sensor networks. This work presents Scheduled on Demand Radio WakeUp (SORW), a flexible scheduler designed for a wireless sensor network where duty cycling strategy and radio wake-up technology are combined in order to optimize the network lifetime. In particular, it tries to keep sensors sleeping as much as possible, still guaranteeing a minimum number of detections per unit of time. Performances of SORW are provided through the use of OMNet++ simulator and compared to results obtained by other basic approaches. Results show that with SORW it is possible to reach a theoretical lifetime of several years, compared to simpler schedulers that only reach days of activity of the network

    Technical Report: Energy Evaluation of preamble Sampling MAC Protocols for Wireless Sensor Networks

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    The paper presents a simple probabilistic analysis of the energy consumption in preamble sampling MAC protocols. We validate the analytical results with simulations. We compare the classical MAC protocols (B-MAC and X-MAC) with LAMAC, a method proposed in a companion paper. Our analysis highlights the energy savings achievable with LA-MAC with respect to B-MAC and X-MAC. It also shows that LA-MAC provides the best performance in the considered case of high density networks under traffic congestion

    Medium Access Control in Energy Harvesting - Wireless Sensor Networks

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    Sub-GHz LPWAN network coexistence, management and virtualization : an overview and open research challenges

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    The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. Low power wide area networks (LPWANs) fulfill these requirements by using sub-GHz radio frequencies (typically 433 or 868 MHz) with typical transmission ranges in the order of 1 up to 50 km. As a result, a single base station can cover large areas and can support high numbers of connected devices (> 1000 per base station). Notorious initiatives in this domain are LoRa, Sigfox and the upcoming IEEE 802.11ah (or "HaLow") standard. Although these new technologies have the potential to significantly impact many IoT deployments, the current market is very fragmented and many challenges exists related to deployment, scalability, management and coexistence aspects, making adoption of these technologies difficult for many companies. To remedy this, this paper proposes a conceptual framework to improve the performance of LPWAN networks through in-network optimization, cross-technology coexistence and cooperation and virtualization of management functions. In addition, the paper gives an overview of state of the art solutions and identifies open challenges for each of these aspects

    Polling-Based Downlink Communication Protocol for LoRaWAN using Traffic Indication

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2019. 2. ๊น€์ข…๊ถŒ.LPWAN (Low Power Wide Area Network) technologies such as LoRa and SigFox are emerging as a technology of choice for the Internet of Things (IoT) applications where tens of thousands of untethered devices are deployed over a wide area. In such operating environments, energy conservation is one of the most crucial concerns and network protocols adopt various power saving schemes to lengthen device lifetimes. For example, to avoid idle listening, LoRaWAN restricts downlink communications. However, the confined design philosophy impedes the deployment of IoT applications that require asynchronous downlink communications. In this thesis, we design and implement an energy efficient downlink communication mechanism, named TRILO, for LoRaWAN. We aim to make TRILO be energy efficient while obeying an unavoidable trade-off that balances between latency and energy consumption. TRILO adopts a beacon mechanism that periodically alerts end-devices which have pending downlink frames. We implement the proposed protocol on top of commercially available LoRaWAN components and confirm that the protocol operates properly in real-world experiments. Experimental results show that TRILO successfully transmits downlink frames without losses while uplink traffic suffers from a slight increase in latency because uplink transmissions should halt during beacons and downlink transmissions. Computer simulation results also show that the proposed scheme is more energy efficient than the legacy LoRaWAN downlink protocol.์ „๋ ฅ ๊ณต๊ธ‰์ด ์ œํ•œ์ ์ธ ์ˆ˜ ๋งŒ๊ฐœ์˜ ๋””๋ฐ”์ด์Šค๋“ค์„ ์ด์šฉํ•˜์—ฌ ๋„“์€ ์ง€์—ญ์„ ๋ฐ”ํƒ•์œผ๋กœ ์šด์˜๋˜๋Š” ์‚ฌ๋ฌผ์ธํ„ฐ๋„ท ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•˜๋Š” ๋ฐ์— ์žˆ์–ด์„œ LoRa, SigFox์™€ ๊ฐ™์€ ์ €์ „๋ ฅ ๊ด‘์—ญ ๋„คํŠธ์›Œํฌ ๊ธฐ์ˆ (LPWA)์ด ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ ํ™˜๊ฒฝ์—์„œ ์—๋„ˆ์ง€ ์ ˆ์•ฝ์€ ์ค‘์š”ํ•œ ๊ด€์‹ฌ์‚ฌ ์ค‘ ํ•˜๋‚˜์ด๋ฉฐ ๋„คํŠธ์›Œํฌ ํ”„๋กœํ† ์ฝœ๋“ค์€ ๋‹ค์–‘ํ•œ ์ ˆ์ „ ๋ฐฉ์‹์„ ์ฑ„ํƒํ•˜์—ฌ ๋””๋ฐ”์ด์Šค์˜ ์ˆ˜๋ช…์„ ๋ณด์žฅํ•˜๋ ค ํ•˜๊ณ  ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๋ถˆํ•„์š”ํ•œ ๋Œ€๊ธฐ ์ฒญ์ทจ๋กœ ์ธํ•œ ์—๋„ˆ์ง€ ์†์‹ค์„ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•ด์„œ LoRaWAN์€ ๋‹ค์šด๋งํฌ ํ†ต์‹ ์„ ์ œํ•œํ•˜๊ณ  ์žˆ๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ์„ค๊ณ„ ์ฒ ํ•™์€ ๋น„๋™๊ธฐ์ ์ธ ๋‹ค์šด๋งํฌ ํ†ต์‹ ์„ ํ•„์š”๋กœ ํ•˜๋Š” IoT ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ์š”๊ตฌ ์‚ฌํ•ญ์„ ์ถฉ์กฑ์‹œํ‚ค์ง€ ๋ชปํ•˜๋Š” ๋ฌธ์ œ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” LoRaWAN์—์„œ ๋‹ค์šด๋งํฌ๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ์ปจํŠธ๋กคํ•  ์ˆ˜ ์žˆ๋„๋ก TRILO๋ผ๋Š” ์—๋„ˆ์ง€ ํšจ์œจ์ ์ธ ๋‹ค์šด๋งํฌ ํ†ต์‹  ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์„ค๊ณ„ํ•˜๊ณ  ๊ตฌํ˜„ํ•˜์˜€๋‹ค. TRILO๋Š” ๋‹ค์šด๋งํฌ ํ”„๋ ˆ์ž„์ด ํŒฌ๋”ฉ๋˜์–ด ์žˆ๋Š” ์—”๋“œ ๋””๋ฐ”์ด์Šค๋“ค์˜ ๋ฆฌ์ŠคํŠธ ์ •๋ณด๋ฅผ ์ฃผ๊ธฐ์ ์œผ๋กœ ๋„คํŠธ์›Œํฌ์— ์•Œ๋ฆฌ๋Š” ๋น„์ฝ˜ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ฑ„ํƒํ•˜์˜€๊ณ , ์„œ๋ฒ„์™€ ๋””๋ฐ”์ด์Šค๋“ค์ด ๊ฐ๊ฐ ์ •ํ•ด์ง„ ์ˆœ์„œ์— ๋”ฐ๋ผ ๋‹ค์šด๋งํฌ ์ „์†ก ๋ฐ ์ˆ˜์‹ ์„ ์Šค์ผ€์ค„๋งํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์„ค๊ณ„ํ•œ ํ”„๋กœํ† ์ฝœ์ด ์ œ๋Œ€๋กœ ๋™์ž‘ํ•˜๋Š”์ง€ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด์„œ ๊ธฐ์กด LoRaWAN์˜ ๊ตฌ์„ฑ ์š”์†Œ ์œ„์— ์ œ์•ˆ๋œ ํ”„๋กœํ† ์ฝœ์„ ๊ตฌํ˜„ํ•œ ํ›„ ์‹ค์ œ ํ…Œ์ŠคํŠธ ๋ฒ ๋“œ๋ฅผ ๊ตฌ์ถ•ํ•˜์—ฌ์„œ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด TRILO๋Š” ๊ธฐ์กด ํ”„๋กœํ† ์ฝœ์˜ ์—…๋งํฌ ํ†ต์‹  ์„ฑ๋Šฅ์„ ์ €ํ•ดํ•˜์ง€ ์•Š์œผ๋ฉด์„œ๋„ ์ถ”๊ฐ€์ ์ธ ๋‹ค์šด๋งํฌ ํ”„๋ ˆ์ž„์„ ์†์‹ค ์—†์ด ์„ฑ๊ณต์ ์œผ๋กœ ์ „์†ก ๋ฐ ์ˆ˜์‹ ํ•˜์˜€๊ณ , ์ปดํ“จํ„ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ ๋˜ํ•œ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ๊ธฐ์กด์˜ LoRaWAN ๋‹ค์šด๋งํฌ ํ”„๋กœํ† ์ฝœ๋ณด๋‹ค ๋” ์—๋„ˆ์ง€ ํšจ์œจ์ ์œผ๋กœ ๋™์ž‘ํ•˜๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค.ABSTRACT ........................................................................................................... โ…ฐ CONTENTS ........................................................................................................... โ…ฒ LIST OF FIGURES ............................................................................................ โ…ณ LIST OF TABLES .............................................................................................. โ…ต CHAPTER โ… : Introduction ................................................................................ 1 CHAPTER โ…ก: Related Work ............................................................................. 8 CHAPTER โ…ข: A Primer on LoRa and LoRaWAN .................................. 11 CHAPTER โ…ฃ: Downlink Communications Scheme .................................. 17 4.1 Comparison of Two Polling Schemes ..................................... 19 4.2 Proposed Downlink Communications Scheme ....................... 26 CHAPTER โ…ค: Implementation ........................................................................ 28 CHAPTER โ…ฅ: Evaluation ................................................................................. 31 6.1 Experimental Results .................................................................... 32 6.2 Simulation Results ......................................................................... 37 CHAPTER โ…ฆ: Discussion ................................................................................. 42 CHAPTER โ…ง: Conclusion ................................................................................. 45 BIBLIOGRAPHY ................................................................................................... 47 ์ดˆ๋ก ........................................................................................................................... 51Maste

    Neighbor discovery for industrial wireless sensor networks with mobile nodes

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    Industrial wireless sensor networks can facilitate the deployment of a wide range of novel industrial applications, including mobile applications that connect mobile robots, vehicles, goods and workers to industrial networks. Current industrial wireless sensor standards have been mainly designed for static deployments, and their performance significantly degrades when introducing mobile devices. One of the major reasons for such degradation is the neighbor discovery process. This paper presents and evaluates two novel neighbor discovery protocols that improve the capability of mobile devices to remain connected to the industrial wireless sensor networks as they move. The proposed protocols exploit topology information and the nature of devices (static or mobile) to reliably and rapidly discover neighbor devices. This is achieved in some cases at the expense of increasing the number of radio resources utilized and the energy consumed in the discovery process. The proposed solutions have been designed and evaluated considering the WirelessHART standard given its widespread industrial adoption. However, they can also be adapted for the ISA100.11a and IEEE 802.15.4e standards.This work was supported in part by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the project TEC2014-57146-Rby the Local Government of Valencia with reference ACIF/2013/060 and by the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 723909 (AUTOWARE project)
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