An energy-aware service placement strategy using hybrid meta-heuristic algorithm in iot environments

Hu, Yongbin; Huang, T.; Yu, Yang; An, Yunzhu; Cheng, Meng Tzu; Zhou, Wen; XIAN, Wentao

doi:10.1007/s10586-022-03751-8

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…The depletion of energy from a single IoT node can have a significant impact on the overall monitoring operation. Therefore, the key challenge in this context is to ensure energy-efficient and fault-tolerant communication, given the difficulty of managing and restoring defective IoT devices scattered across the extensive pipeline, either through recharging or replacing batteries, as needed ( Hu et al, 2023 ). Furthermore, the data collected by these IoT devices can be categorized as normal or critical.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient routing protocol for reliable low-latency Internet of Things in oil and gas pipeline monitoring

Karam,

Bilal,

Khan

et al. 2024

PeerJ Computer Science

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The oil and gas industries (OGI) are the primary global energy source, with pipelines as vital components for OGI transportation. However, pipeline leaks pose significant risks, including fires, injuries, environmental harm, and property damage. Therefore, maintaining an effective pipeline maintenance system is critical for ensuring a safe and sustainable energy supply. The Internet of Things (IoT) has emerged as a cutting-edge technology for efficient OGI pipeline leak detection. However, deploying IoT in OGI monitoring faces significant challenges due to hazardous environments and limited communication infrastructure. Energy efficiency and fault tolerance, typical IoT concerns, gain heightened importance in the OGI context. In OGI monitoring, IoT devices are linearly deployed with no alternative communication mechanism available along OGI pipelines. Thus, the absence of both communication routes can disrupt crucial data transmission. Therefore, ensuring energy-efficient and fault-tolerant communication for OGI data is paramount. Critical data needs to reach the control center on time for faster actions to avoid loss. Low latency communication for critical data is another challenge of the OGI monitoring environment. Moreover, IoT devices gather a plethora of OGI parameter data including redundant values that hold no relevance for transmission to the control center. Thus, optimizing data transmission is essential to conserve energy in OGI monitoring. This article presents the Priority-Based, Energy-Efficient, and Optimal Data Routing Protocol (PO-IMRP) to tackle these challenges. The energy model and congestion control mechanism optimize data packets for an energy-efficient and congestion-free network. In PO-IMRP, nodes are aware of their energy status and communicate node’s depletion status timely for network robustness. Priority-based routing selects low-latency routes for critical data to avoid OGI losses. Comparative analysis against linear LEACH highlights PO-IMRP’s superior performance in terms of total packet transmission by completing fewer rounds with more packet’s transmissions, attributed to the packet optimization technique implemented at each hop, which helps mitigate network congestion. MATLAB simulations affirm the effectiveness of the protocol in terms of energy efficiency, fault-tolerance, and low latency communication.

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Section: Introductionmentioning

confidence: 99%

Energy-efficient routing protocol for reliable low-latency Internet of Things in oil and gas pipeline monitoring

Karam,

Bilal,

Khan

et al. 2024

PeerJ Computer Science

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“…Addressing energy consumption, delay, throughput, network performance, packet loss, and attack detection rate are additional requirements of the applications beyond security. Issues including transmission delay, detection ratio, and energy consumption may be handled by current algorithms [9][10]. By integrating EBOA with LBO optimization techniques, this hybrid approach aims to enhance the authentication process's efficiency and scalability while minimizing energy consumption overhead.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Metaheuristic Algorithm based energy efficient Authentication method for IoT enable edge computing

Mishra,

Kumar,

Awasthi

2024

Preprint

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With the proliferation of Internet of Things (IoT) devices and the increasing demand for low-latency data processing, edge computing has emerged as a critical paradigm. However, challenges related to energy efficiency and security in this dynamic and distributed environment persist. This paper proposes a novel Hybrid Election-based Ladybug Beetle Optimization (ELBO-H) method tailored to address these challenges concurrently. By synergizing the principles of Election-based Optimization Algorithm (EBOA) and the Ladybug Beetle Optimization (LBO), our approach aims to enhance energy efficiency and bolster authentication protocols in IoT-enabled edge computing environments. We begin by elucidating the exigencies of energy-efficient operations and trust-based authentication within the burgeoning landscape of IoT and edge computing. The proposed ELBO-H method involves integrating this algorithm into the edge computing architecture, optimizing energy usage while ensuring robust security measures between IoT devices, edge nodes. To evaluate the proposed method, we conducted simulations in a controlled environment, considering various scenarios and workload conditions. Results indicate a significant improvement in energy efficiency without compromising security. Our proposed ELBO-H method demonstrates an average Attack detection rate of 94.28% compared to the IB-SEC, G-BHO, DEEC-KSA, and CPSO methods, which have average Attack detection rates of 78.23%, 72.45%, 74.89%, and 52.67%, respectively.

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“…Especially, these algorithms can be compartmentalized different categories using different descriptions. Common names are evolutionary algorithm (EA) [1], nature-inspired algorithm (NIA) [2], meta-heuristic algorithm (MA) [3], and swarm intelligence (SI) algorithm [4], however, some of the algorithms included are the same. Thus, a challenge of the algorithm is that searching for the optima in the search space with higher convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Duck swarm algorithm: theory, numerical optimization, and applications

Zhang,

Wen

2024

Cluster Comput

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A swarm intelligence-based optimization algorithm, named Duck Swarm Algorithm (DSA), is proposed in this study. This algorithm is inspired by the searching for food sources and foraging behaviors of the duck swarm. The performance of the DSA is verified by using eighteen benchmark functions, where its statistical (best, mean, standard deviation, and average runningtime) results are compared with seven well-known algorithms like Particle swarm optimization (PSO), Firefly algorithm (FA), Chicken swarm optimization (CSO), Grey wolf optimizer (GWO), Sine cosine algorithm (SCA), and Marine-predators algorithm (MPA), and Archimedes optimization algorithm (AOA). Moreover, the Wilcoxon rank-sum test, Friedman test, and convergence curves of the comparison results are used to prove the superiority of the DSA against other algorithms. The results demonstrate that DSA is a high-performance optimization method in terms of convergence speed and exploration-exploitation balance for solving high-dimension optimization functions. Also, DSA is applied for the optimal design of six engineering constraint problems and the node optimization deployment task of the Wireless Sensor Network (WSN). Overall, the comparison results revealed that the DSA is a promising and very competitive algorithm for solving different optimization problems.

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An energy-aware service placement strategy using hybrid meta-heuristic algorithm in iot environments

Cited by 8 publications

References 37 publications

Energy-efficient routing protocol for reliable low-latency Internet of Things in oil and gas pipeline monitoring

Energy-efficient routing protocol for reliable low-latency Internet of Things in oil and gas pipeline monitoring

Hybrid Metaheuristic Algorithm based energy efficient Authentication method for IoT enable edge computing

Duck swarm algorithm: theory, numerical optimization, and applications

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