Energy Saving Optimization Technique-Based Routing Protocol in Mobile Ad-Hoc Network with IoT Environment

K, Vinoth Kumar; Izonin, Ivan; Subramanian, Sugumaran; Shandilya, Shishir Kumar; Velayutham, Sivasankaran; Munichamy, Thillai Rani; Havryliuk, Myroslav

doi:10.3390/en16031385

Cited by 21 publications

(9 citation statements)

References 29 publications

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“…The question arises: at what size of RU will we obtain the maximum gain from using OFDMA? Generally speaking, OFDMA shows better results with small RUs [5,8]. Now let us comment on the previously mentioned Multi-User Multiple-Input, Multiple-Output (MU-MIMO) system [6,7,[9][10][11].…”

Section: Introductionmentioning

confidence: 91%

“…Let us examine the functions (7) and (8). The first of them is a monotonic function of the argument → s .…”

Section: The Markov Concept Of the Energy Efficiency Assessment Of Th...mentioning

confidence: 99%

“…The first of them is a monotonic function of the argument → s . Let us focus on function (8). The classical signal transmission theory [25] says: if the function of the signal-to-noise ratio is ρ c ≥ ρ c ∀c ∈ U, then the inequality π c ≥ π c ∀c ∈ U is satisfied for the corresponding power characteristics.…”

Section: The Markov Concept Of the Energy Efficiency Assessment Of Th...mentioning

confidence: 99%

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Information Technology for Maximizing Energy Consumption for Useful Information Traffic in a Dense Wi-Fi 6/6E Ecosystem

Kovtun,

Altameem,

Al-Maitah

et al. 2023

Electronics

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In Wi-Fi standards, a relatively narrow range of frequency spectrums is declared as working, on the operation of which additional restrictions are imposed in different countries. When creating dense wireless network ecosystems focused on massive information traffic, this circumstance causes significant interference even in the case of using Wi-Fi 6/6E-compatible equipment. An effective solution to this problem is the implementation of a centralized management mechanism for the relevant parameters of the target network ecosystem. The growing attention to ecology and rational use of electricity makes the problem of maximizing energy consumption for useful information traffic in a dense Wi-Fi 6/6E ecosystem an urgent task. Only the addressed information traffic between the transmitter and the target subscriber, which are subjects of the OFDMA technology and the MU-MIMO multiple access system (with an emphasis on the latter), is considered useful. To solve the problem, the authors formalized the Wi-Fi 6/6E ecosystem’s energy consumption model, which takes into account the specifics of OFDMA and MU-MIMO, the influence of the communication channel characteristics on the speed of target information transfer, and detailed energy consumption for maintaining the network infrastructure in a functional state. Based on the created model, the research problem is represented by the difference between two monotonic functions, relative to which the problem of optimization with restrictions is set. The process of solving this problem is presented in the form of information technology with a branch-and-bound hierarchy and a nested unconditional optimization problem. The results of simulated modelling in the MATLAB-NS3 environment showed a significant advantage of the authors’ approach. The energy power consumption by the Wi-Fi 6/6E ecosystem, the parameters of which were adjusted with the help of the authors’ information technology, decreased by more than four times.

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Section: Introductionmentioning

confidence: 91%

“…Let us examine the functions (7) and (8). The first of them is a monotonic function of the argument → s .…”

Section: The Markov Concept Of the Energy Efficiency Assessment Of Th...mentioning

confidence: 99%

Section: The Markov Concept Of the Energy Efficiency Assessment Of Th...mentioning

confidence: 99%

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Information Technology for Maximizing Energy Consumption for Useful Information Traffic in a Dense Wi-Fi 6/6E Ecosystem

Kovtun,

Altameem,

Al-Maitah

et al. 2023

Electronics

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“…Krishnamoorthy et al 21 proposed a fantastic heterogeneous network in IT. The Internet of Things (IoT), WSN, and MANET all work together to foster innovation in technology, but their heterogeneity introduces new challenges.…”

Section: Related Workmentioning

confidence: 99%

IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

Sanshi,

Vatambeti

2024

Int J Communication

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SummaryMany protocols, services, and electrical devices with built‐in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre‐existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large‐scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On‐Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results.

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“…A significant challenge within MANETs is the identification of an optimal cluster head node. This node is tasked with managing communication within a group of nodes, representing the cluster, in a manner that bolsters network performance and sustains energy longevity, thereby extending the network's lifespan [3,4]. As the size of the MANET expands, the selection of the cluster head node becomes crucial to ensure efficient communication, optimal resource utilization, and secure communication routes [5,6].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Cluster Head Selection in Mobile Ad Hoc Networks: A Connectivity Probability Approach Using Poisson Distribution and Residual Energy

Tawfeeq

2023

ISI

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The selection of an optimal cluster head (CH) node, acting as an intermediary between the base station and ancillary nodes, is a pivotal challenge in mobile Ad Hoc networks, significantly impacting network performance and efficiency. This study introduces a novel approach for CH node selection in Mobile Ad Hoc Networks (MANETs), aiming to bolster network efficiency. This approach selects the head of a nodes cluster based on the Connectivity Probability (CP), derived from the Poisson probability and each node's residual energy. The Poisson distribution, governed by a key parameter, lambda, serves to determine the likelihood of a specific outcome. In the context of this study, lambda signifies the average distance between any given node and the base station, measured relative to their communication range. Considering the direct influence of a node's residual energy on connection probability, the product of these two parameters is computed to ascertain CP. Nodes demonstrating the highest CP values are considered prime candidates for CH selection. The efficacy of the proposed algorithm was evaluated against established protocols, namely the LEACH and R-LEACH. Simulation results suggest that the proposed algorithm significantly improves network performance, extending the network lifetime by over 6 times and 3 times that of LEACH and R-LEACH, respectively. It also enhances network stability by approximately 7 times compared to LEACH and over 2 times that of R-LEACH. Furthermore, the algorithm notably improves throughput, exhibiting an increase by approximately 7 times relative to both protocols. In conclusion, the proposed algorithm offers a promising strategy for CH node selection in MANETs, potentially benefitting a wide gamut of applications.

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Energy Saving Optimization Technique-Based Routing Protocol in Mobile Ad-Hoc Network with IoT Environment

Cited by 21 publications

References 29 publications

Information Technology for Maximizing Energy Consumption for Useful Information Traffic in a Dense Wi-Fi 6/6E Ecosystem

Information Technology for Maximizing Energy Consumption for Useful Information Traffic in a Dense Wi-Fi 6/6E Ecosystem

IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

Optimizing Cluster Head Selection in Mobile Ad Hoc Networks: A Connectivity Probability Approach Using Poisson Distribution and Residual Energy

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