A Novel Energy-Conscious Access Point (<i>e</i>AP) System With Cross-Layer Design in Wi-Fi Networks for Reliable IoT Services

Lee, Seungjin; Choi, Hyung-Woo; Kim, Tae-Hwa; Park, Hong-Shik; Choi, Jun Kyun

doi:10.1109/access.2022.3181304

Cited by 8 publications

(14 citation statements)

References 31 publications

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“…As a result, the energy efficiency of transmitting devices can deteriorate rapidly in grant-free transmission. In this experiment, we calculated the energy consumption for UL IoT devices in the simulated environment, considering three operational modes for IoT devices: transmission (Tx), receiving (Rx), and sleep, with energy usage rates of 0.45, 0.15, and 0.00012 W , respectively [75]. The energy computation also included transmission (ReTx) and receiving (ReRx) energy resulting from retransmissions.…”

Section: F Performance Comparison For Energy Consumptionmentioning

confidence: 99%

Deep Reinforcement Learning Driven Joint Dynamic TDD and RRC Connection Management Scheme in Massive IoT Networks

Park,

Lee,

Kim

et al. 2024

IEEE Access

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To support dramatically increasing services from internet of thing (IoT) devices with the sporadic and fluctuated generation of short packet traffic, this paper investigates joint dynamic time division duplexing (TDD) and radio resource control (RRC) connection management in a single-cell massive IoT network. Specifically, under the grant-free transmission incurring packet collision, this study models the factors affecting the time resource utilization (TRU) and energy consumption of IoT devices as a comprehensive system utility and further formulates the problem as a decision-making process aiming for balancing the long-term average TRU and energy consumption. To address the formulated problem, based on the deep reinforcement learning framework, this paper designs an experience-driven joint dynamic TDD and RRC connection management scheme that intelligently i) determines the TDD configuration based on the most recent downlink (DL)/uplink (UL) traffic demands and ii) adjusts the RRC state of each IoT device to control the maximum number of transmitting IoT devices. Finally, trace-driven simulation results demonstrate that the proposed scheme outperforms existing benchmarks, such as Static TDD and Dynamic TDD, in terms of transmission success ratio difference (TSRD) (up to 89% reduction), time resource utilization (TRU) (up to 17× increase), and energy consumption (up to 70% reduction) of IoT devices. INDEX TERMSInternet of things, Time division duplexing, Grant-free transmission, Radio resource control, Deep reinforcement learning

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Section: F Performance Comparison For Energy Consumptionmentioning

confidence: 99%

Deep Reinforcement Learning Driven Joint Dynamic TDD and RRC Connection Management Scheme in Massive IoT Networks

Park,

Lee,

Kim

et al. 2024

IEEE Access

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“…IoT mewajibkan sebuah perangkat terhubung ke jaringan internet supaya dapat melakukan pertuakaran data dengan perangkat lainnya [12]. Supaya dapat melakukan komunikasi dua arah antar perangkat, dibutuhkan komputer yang berperan sebagai pihak perantara bernama web service yang memiliki wujud berupa Application Programming Interface (API) [13].…”

Section: Tinjauan Pustakaunclassified

Efisiensi Pertukaran Data Client-Server menggunakan Web Socket pada Perangkat Berbasis Internet of Things

Nugraha

2024

JEPIN

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Internet of Things (IoT) banyak digunakan dengan tujuan membantu mempermudah hidup masyarakat dalam wujud perangkat-perangkat yang dapat bekerja secara otomatis. Perangkat IoT secara umum dapat dipantau atau dikendalikan menggunakan perangkat lain seperti komputer atau telepon seluler melalui perantara server yang dikenal sebagai Application Programming Interface (API). Umumnya, protokol yang digunakan untuk pertukaran data antara client dan server adalah Message Queuing Telemetry Transport (MQTT). Namun MQTT memiliki beberapa kelemahan di sisi kehandalan dan keamanan data, sehingga tidak dapat digunakan pada segala jenis kondisi dan situasi. Sebagai alternatif, terdapat protokol Hypertext Transfer Protocol (HTTP) yang dapat mengakomodasi kekurangan tersebut. Namun HTTP memiliki kelemahan di mana server tidak dapat mengirimkan data kepada client apabila client tidak mengirimkan request terlebih dahulu. Sementara pada perangkat IoT, data seharusnya bisa dikirimkan oleh kedua belah pihak. Terdapat satu buah protokol lain yang dapat menjadi solusi dari kedua kebutuhan tersebut, yaitu Web Socket. Penelitian ini bertujuan untuk mengimplementasikan arsitekur client-server berbasis Web Socket untuk melakukan pertukaran data antara perangkat IoT dengan server. Hasil pengujian menunjukkan bahwa protokol Web Socket memiliki nilai latency yang paling rendah di antara protokol yang lain, yaitu dengan nilai rata-rata antara 10,75 sampai dengan 23,29 milidetik. Rentang tersebut termasuk kategori yang baik, sehingga dapat disimpulkan bahwa Web Socket dapat digunakan sebagai alternatif pengganti MQTT.

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“…Both problems will lead to software access problems, thereby affecting the security of user privacy data. 25…”

Section: • Iotivitymentioning

confidence: 99%

“…36 To solve the access control problem, Lee et al proposed a functionality-centric scheme involving nothing about cryptographic knowledge, namely FACT. 25 However, as the number of devices increased, the ACL gradually showed its drawbacks, because the time complexity of the query accessing the ACL is at least (logn). [37][38][39] Then, Giffin et al put forward a new access control solution which restricts the app's permissions through MAC.…”

Section: Security In Iotmentioning

confidence: 99%

Toward data privacy preservation with ciphertext update and key rotation for IoT

Shen

Yang

Liu

2021

Concurrency and Computation

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Fine‐grained access control become a research spotlight in the scenario of the smart home with Internet‐of‐Things (IoTs). However, most of the existing works could only realize ciphertext outsourcing with an unchangeable encryption key in the cloud. That is because the trivial solution needs great communication overhead. To overcome this challenge, we propose an updatable encryption based on SM9 (SM9‐UE) scheme for the IoT smart home scenario, where SM9 is an identity and cryptographic standard adopted by GM/T0044. SM9‐UE realizes secure and lightweight ciphertext updating through using the token generated by the data owner, which is information independent with the plaintext. We give the formal security definition and prove it to be adaptive update indistinguishability (IND‐UPD) secure. Theoretical comparison and analysis show that our scheme is efficient in computation and storage overhead. Experimental results also indicate that SM9‐UE can be practically applied to IoT smart home.

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A Novel Energy-Conscious Access Point (eAP) System With Cross-Layer Design in Wi-Fi Networks for Reliable IoT Services

Cited by 8 publications

References 31 publications

Deep Reinforcement Learning Driven Joint Dynamic TDD and RRC Connection Management Scheme in Massive IoT Networks

Deep Reinforcement Learning Driven Joint Dynamic TDD and RRC Connection Management Scheme in Massive IoT Networks

Efisiensi Pertukaran Data Client-Server menggunakan Web Socket pada Perangkat Berbasis Internet of Things

Toward data privacy preservation with ciphertext update and key rotation for IoT

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