Multi-Objective Optimization Modeling of Clustering-Based Agricultural Internet of Things

Effah, Emmanuel; Thiaré, Ousmane; Wyglinski, Alexander M.

doi:10.1109/vtc2020-fall49728.2020.9348460

Cited by 4 publications

(34 citation statements)

References 10 publications

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“…The power-and resource-constrained SNs that form the WSN-based Agri-IoT network in the aforementioned context require limited data transmission rates, computational capabilities, memory capacities, communication distance, and operational stability. Consequently, the associated routing protocol [9,12,17,21], communication technology, and routing architecture [22][23][24] must support mechanisms that ensure packet size and communication distance moderation [16], efficient channel access management (CAM), and SN's tasks management. It is not a mere application of conventional IoT to a farm, as many authors attempted [1, [10][11][12][17][18][19][20]23,25,26], which lacked application-specific requirements such as dense network inter-connectivity, higher information perceptibility, compre-hensive intelligence services, remote monitoring, smart decision making, and the execution of precise control/actuation actions on the farm.…”

Section: Agri-iot Technology Lacks Comprehensive Context-based Synthe...mentioning

confidence: 99%

“…To date, Agri-IoT-related surveys and tutorials focused on high-power-demanding communication technologies (Wi-Fi and cellular-based technologies), the centralized architecture-constrained ZigBee standard, and the operation principles of conventional IoT as authored in [1, 10,11,14,18,19] without an in-depth consideration of the unique case of Agri-IoT. It is well established that the cluster-based architecture is the best candidate for Agri-IoT application [12,16,17,24]; however, there are no systematic evaluations to cement this fact.…”

Section: Superficial Consideration Of Desired Communication Technolog...mentioning

confidence: 99%

“…Like BS in WSNs, IoT devices can connect to the Internet/IoT cloud via fixed-line (thus, for a factory), 5G/4G/LTE cellular/mobile networks, or Wi-Fi for further processing, storage, and decisions/actions. As presented in Figure 4, WSN-based Agri-IoT is an information-and knowledgeintensive intelligent feedback control system for farm monitoring, data sampling/computing, resource optimization, automation of farm operation (e.g., precision irrigation, chemical application, livestock monitoring, and disease management [16]), and actionable decision making via a variety of battery-powered and wirelessly connected SNs with sensing, processing, and communication capacities [2,29,30]. Unlike the WSN, Agri-IoT and IoT sample data to an Internet-based cloud.…”

Section: Comparative Overview Of Wsn Iot and Agri-iot Technologiesmentioning

confidence: 99%

“…In designing an efficient Agri-IoT system of global significance, it is imperative to propose suitable architectural layers and evaluate how the various components interact in these layers. With the emerging advances in low-power, freely available, and boundless communication standards (e.g., BLE) and unfulfilled potentials of CA-IoT network [12,16], a new framework of cluster-based architectural layers for the WSN-based Agri-IoT ecosystem is proposed in the left side of Figure 5. The center portion of Figure 5 presents the key components/technologies required in each layer, while the Things taxonomies of hardware components from the related literature [4,8,29] are depicted on the right portion of Figure 5.…”

Section: Proposed Architectural Layers For Wsn-based Agri-iotmentioning

confidence: 99%

“…Consequently, Agri-IoT users in Africa expect a contextrelevant solution that is affordable, simple to deploy and operate by non-experts, location-unrestricted, supportive of large-scale farm management, and based on freely available technologies that do not require licensing. Thus, they are unlike popular IoT use cases such as medical, vehicular, and industrial IoT, whose designs are mainly affected by critical factors including security, stable connectivity, and interference, respectively, Agri-IoT is compelled to drive on affordable battery-powered SNs, which make architecture, low-power communication technology, power optimization, cost, fault tolerance, multihop routing, scalability, and environmental impact critical design factors in order to address its resource or deployment-induced challenges [12,16,17]. 2.…”

Section: Introduction and Tutorial Contributionsmentioning

confidence: 99%

See 4 more Smart Citations

A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

Effah

Thiaré

Wyglinski

2023

IoT

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This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via a systematic survey and synthesis of the related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on the specific performance and user expectations as well as technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault-tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a three-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

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Section: Agri-iot Technology Lacks Comprehensive Context-based Synthe...mentioning

confidence: 99%

Section: Superficial Consideration Of Desired Communication Technolog...mentioning

confidence: 99%

Section: Comparative Overview Of Wsn Iot and Agri-iot Technologiesmentioning

confidence: 99%

Section: Proposed Architectural Layers For Wsn-based Agri-iotmentioning

confidence: 99%

Section: Introduction and Tutorial Contributionsmentioning

confidence: 99%

See 3 more Smart Citations

A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

Effah

Thiaré

Wyglinski

2023

IoT

Self Cite

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Hardware Evaluation of Cluster-Based Agricultural IoT Network

Effah,

Thiare,

Wyglinski

2024

IEEE Access

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In this paper, we present a real-world hardware evaluation of a robust, affordable, locationindependent, simple, and infrastructure-less cluster-based agricultural Internet of Things (CA-IoT) network based on a commercial off-the-shelf (COTS) Bluetooth Low-Energy (BLE) communication technique and Raspberry Pi module 3 B + (RPI 3 B +) to address global food insecurity caused by climate change and increasing global population via precision farming and greenhouses. Using an engineering design approach, an initial centralized agricultural IoT hardware test-bed was implemented with the aid of BLE, RPi 3 B +, DHT22, STEMMA soil moisture sensors, UM25 meters, and LoPy /low-power Wi-Fi modules, among other devices. This test-bed was adapted and modified after the proposed cluster-based architecture to evaluate the performance of CA-IoT networks. This study provides holistic account of our location-independent CA-IoT solution covering the design and deployment experiences that can serve as a reference document to the agricultural Internet of Things (Agri-IoT) community. Additionally, the proposed solution performed satisfactorily when tested under indoor and outdoor (on-farm) environmental conditions in the USA and Senegal. Unlike existing Agri-IoT test-beds, a sample performance evaluation showed that our contextrelevant CA-IoT technology is simple to deploy and manage by inexperienced users and is energy-efficient, location-independent, robust, and task-and size-scalable to provide a rich set of measurements for both educational and commercial purposes.

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Multi-Objective Cluster Head-Based Energy-Aware Routing Protocol using Hybrid Woodpecker and Flamingo Search Optimization Algorithm for Internet of Things Environment

Arivubrakan

Ramasubramanian

2023

Int. J. Info. Tech. Dec. Mak.

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Internet of Things (IoT) plays a vital role in the world of Internet and integrates computing devices. The digital machines provide unique identifiers. The capacity to send data through the network using a better path is one of the capabilities of digital machines. IoT generates huge data based on fast aggregation data and processes these data efficiently. In this paper, a multi-objective hybrid woodpecker and flamingo search optimization algorithm is proposed for finding optimum Cluster Head (CH)-based energy-aware routing protocol in IoTs environment (Hyb-WFSOA-CHS-IoT). Here, the proposed Hyb-WFSOA-CHS-IoT model executes routing method through CH. The woodpecker and flamingo search optimization algorithm is used as the intelligent CH selection that consumes same energy as sensors. Hybrid woodpecker and flamingo search optimization algorithm (Hyb-WFSOA) is examined by using fitness functions, like distance, delay, energy consumption, throughput. The proposed Hyb-WFSOA-CHS-IoT method is activated in MATLAB software. Then, the performance of the proposed system is examined with different metrics, like delay, packet delivery ratio, throughput, network lifetime, energy consumption. Therefore, the proposed method attains lower delay 28.38%, 32.34% and 47.45%, higher delivery ratio 19.34%, 23.12% and 18.96% and lower energy consumption 11.25%, 7.90% and 12.88% compared with existing methods, like multi-objective fractional gravitational search algorithm for energy-efficient routing on IoT (FGSA-CHS-IoT), multi-objective sunflower-based gray wolf optimization algorithm for multiple path routing on IoT network (SFG-CHS-IoT) and energy-aware routing in the IoT with improved grasshopper metaheuristic algorithm with chaos theory and fuzzy Logic (FLGOA-CHS-IoT).

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Multi-Objective Optimization Modeling of Clustering-Based Agricultural Internet of Things

Cited by 4 publications

References 10 publications

A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

Hardware Evaluation of Cluster-Based Agricultural IoT Network

Multi-Objective Cluster Head-Based Energy-Aware Routing Protocol using Hybrid Woodpecker and Flamingo Search Optimization Algorithm for Internet of Things Environment

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