Adaptive dynamic network slicing in LoRa networks

Dawaliby, Samir; Bradai, Abbas; Pousset, Yannis

doi:10.1016/j.future.2019.01.042

Cited by 51 publications

(29 citation statements)

References 16 publications

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“…In this paper, we performed a comprehensive analysis of solutions that have been developed to optimize ADR algorithms. The proposed optimization techniques address specific challenges such as scalability [ 28 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ], throughput [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] and energy efficiency [ 20 , 46 , 47 , 48 , 49 , 50 , 51 ]. Our analysis distinguished the approaches used and highlighted the challenges and performance in the studies considered.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…ADR schemes that maximize throughput maximizing solutions for the ADR scheme were discussed in [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. The ordered waterfalling technique used in [ 37 ] for even distribution of channel load between the end nodes in the system by equally distributing SFs and then channel utilization.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…A concept of network slicing was introduced in [ 43 ]. The LoRaWAN network is partitioned into several virtual networks, termed network slices, to efficiently assign network resources to support specific QoS requirements for every slice.…”

Section: Review Of Adaptive Data Rate Algorithmsmentioning

confidence: 99%

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A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Kufakunesu

Hancke

Abu‐Mahfouz

2020

Sensors

113

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Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions.

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Section: Comparison and Discussionmentioning

confidence: 99%

Section: Comparison and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Kufakunesu

Hancke

Abu‐Mahfouz

2020

Sensors

113

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“…In a similar way to the previous study, Dawaliby et al [48] formulated network slicing optimization as a threefold problem that includes: (i) the network slice admission model and its links to LoRaWAN devices, (ii) a strategy for determining the optimal inter-slicing resource reservation, and (iii) an approach to intra-slice resource allocation. They proposed a slicing optimization algorithm consisting of three stages.…”

Section: Network Slicingmentioning

confidence: 99%

A Survey on Long-Range Wide-Area Network Technology Optimizations

et al. 2021

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Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN's performance. We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future.

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“…and are respectively the load rate and the reliability rate. The algorithm summarized in Pseudo-Code 3 based on the Analytical and Hierarchy Process (AHP), searches for the efficient and reliable link that gives the highest utility metric and allocate resources accordingly [19]. Formula (37) represent the trade-off between reliability and load which explains the less critical latency and priority of HCLE slice and the massive number of connected IoT devices.…”

Section:    mentioning

confidence: 99%