Enabling Reliable, Asynchronous, and Bidirectional Communication in Sensor Networks over White Spaces

Saifullah, Abusayeed; Rahman, M.; Ismail, Dali; Lu, Chenyang; Liu, Jie; Chandra, Ranveer

doi:10.1145/3131672.3131676

Cited by 30 publications

(25 citation statements)

References 20 publications

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“…Since each node (non BS) has just a single half-duplex radio, it can be either receiving or transmitting, but not doing both at the same time. Both experiments and large-scale simulations show high efficiency of SNOW in latency and energy with a linear increase in throughput with the number of nodes, demonstrating its superiority over existing designs [3], [4]. We consider many coexisting SNOWs that are under the same management/control and need to coordinate among themselves for extended coverage in a wide area or to host different applications.…”

Section: B Snow Mac Layermentioning

confidence: 99%

“…In regard to the white space networking, the closest work to ours is [36] which considers multiple WiFi-like networks in white spaces, where all users have access to white space database, and every access point (AP) chooses a single channel, the problem thus is different from our integration. Here we provide a brief overview of the design and architecture of a single SNOW that we developed in [2]- [4]. SNOW is an asynchronous, long range, low power WSN platform to operate over TV white spaces.…”

Section: Related Workmentioning

confidence: 99%

“…Thanks to their lower frequencies (54-862MHz in the US), white spaces have excellent propagation characteristics over long distance and obstacles. While their potentials have been explored mostly for broadband access (see survey [5]), our design and experimentation demonstrated the potential of SNOW to enable asynchronous, low power, bidirectional, and massively concurrent communications between numerous sensors and a base station (BS) directly over long distances [2]- [4].…”

Section: Introductionmentioning

confidence: 99%

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Integrating Low-Power Wide-Area Networks for Enhanced Scalability and Extended Coverage

Rahman

Saifullah

2020

IEEE/ACM Trans. Networking

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Low-Power Wide-Area Networks (LPWANs) are evolving as an enabling technology for Internet-of-Things (IoT) due to their capability of communicating over long distances at very low transmission power. Existing LPWAN technologies, however, face limitations in meeting scalability and covering very wide areas which make their adoption challenging for future IoT applications, especially in infrastructure-limited rural areas. To address this limitation, in this paper, we consider achieving scalability and extended coverage by integrating multiple LPWANs. SNOW (Sensor Network Over White Spaces), a recently proposed LPWAN architecture over the TV white spaces, has demonstrated its advantages over existing LPWANs in performance and energyefficiency. In this paper, we propose to scale up LPWANs through a seamless integration of multiple SNOWs which enables concurrent inter-SNOW and intra-SNOW communications. We then formulate the tradeoff between scalability and inter-SNOW interference as a constrained optimization problem whose objective is to maximize scalability by managing white space spectrum sharing across multiple SNOWs. We also prove the NPhardness of this problem. To this extent, We propose an intuitive polynomial-time heuristic algorithm for solving the scalability optimization problem which is highly efficient in practice. For the sake of theoretical bound, we also propose a simple polynomialtime 1 2 -approximation algorithm for the scalability optimization problem. Hardware experiments through deployment in an area of (25x15)km 2 as well as large scale simulations demonstrate the effectiveness of our algorithms and feasibility of achieving scalability through seamless integration of SNOWs with high reliability, low latency, and energy efficiency.Index Terms-Low-power wide-area network, white spaces, sensor network.

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Section: B Snow Mac Layermentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integrating Low-Power Wide-Area Networks for Enhanced Scalability and Extended Coverage

Rahman

Saifullah

2020

IEEE/ACM Trans. Networking

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“…SNOW is a highly scalable LPWAN technology operating in the TVWS [12,53,[66][67][68][69]. It supports asynchronous, reliable, bi-directional, and concurrent communication between a BS and numerous nodes.…”

Section: Snow (Sensor Network Over White Spaces)mentioning

confidence: 99%

A comprehensive survey on networking over TV white spaces

Rahman

Saifullah

2019

Pervasive and Mobile Computing

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TV white spaces refer to the allocated but locally unused TV spectrum and can be used by unlicensed devices as secondary users. Thanks to their lower frequencies (e.g., 54 -698 MHz in the US), communication over the TV spectrum has excellent propagation characteristics over long distances and through obstacles. These characteristics along with their wide availability make the TV white spaces a great choice and alternative to many existing wireless technologies, especially the ones that need long range and high bandwidth communication. In the last decade, there have been numerous efforts from academia, industries, and standards bodies for exploiting the potentials of the TV white spaces for several applications including wireless broadband Internet access.Their characteristics and features also hold potentials for many new applications including sensing and monitoring, Internet of Things, wireless control, smart utility, location-based services, and transportation and logistics. In this paper, we perform a retrospective review and comparative study of existing work on networking in the TV white spaces. Additionally, we discuss the associated research challenges such as dealing with the interference between primary and secondary TV spectrum users, TV white space temporal and spatial variations and fragmentation, antenna design, mobility, and security. We also describe the future research directions to handle the above challenges. To the best of our knowledge, this is the first comprehensive survey on the literature of TV white space networking research.

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“…They provide a vast amount of online information in the deployment field. However, due to constraints on the signal processing and communication capabilities [1][2][3][4][5] of WSNs, some unusual data (called outliers) may result from sensor malfunction, process disturbances, human-related errors, and/or a sudden change in the state of the environment [6][7][8][9][10]. The outliers might seriously affect the accuracy of data analysis, which leads to model misspecification.…”

Section: Introductionmentioning

confidence: 99%

Temporal and spatial outlier detection in wireless sensor networks

Nguyen

Thai

2019

ETRI Journal

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Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph‐based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state‐of‐the‐art methods in terms of accuracy and work well with various data types.

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Enabling Reliable, Asynchronous, and Bidirectional Communication in Sensor Networks over White Spaces

Cited by 30 publications

References 20 publications

Integrating Low-Power Wide-Area Networks for Enhanced Scalability and Extended Coverage

Integrating Low-Power Wide-Area Networks for Enhanced Scalability and Extended Coverage

A comprehensive survey on networking over TV white spaces

Temporal and spatial outlier detection in wireless sensor networks

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