Lifetime-Improvement Routing Protocol for Wireless Sensor Networks

Ai-Zubi, Raed T.; Abedsalam, Noor; Atieh, Ahmad; Darabkh, Khalid A.

doi:10.1109/ssd.2018.8570628

Cited by 17 publications

(6 citation statements)

References 20 publications

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“…The main steps of our proposed fuzzy based LEACH approach are discussed in this section. In proposed algorithm, optimum number of head nodes are chosen using Kopt from (1).…”

Section: Methodsmentioning

confidence: 99%

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Ameliorate the performance using soft computing approaches in wireless networks

Dadhirao¹,

Sangam²

2023

IJECE

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<span lang="EN-US">Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.</span>

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“…The main steps of our proposed fuzzy based LEACH approach are discussed in this section. In proposed algorithm, optimum number of head nodes are chosen using Kopt from (1).…”

Section: Methodsmentioning

confidence: 99%

“…In terms of productivity in WSNs, routing protocols [1], [2] play a vital role. Routing is one of the most challenging techniques on WSN.…”

mentioning

confidence: 99%

Ameliorate the performance using soft computing approaches in wireless networks

Dadhirao¹,

Sangam²

2023

IJECE

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“…There are three modules in the controller, topology discovery, period monitor, and an ANN model, which are used to explore In recent years, several routing mechanisms [32][33][34][35][36][37][38] combined with AI technology have been proposed to enhance learning ability from past experiences and smart route-decision capability, thereby improving overall network performance. First of all, the works in [33][34][35] introduced AI technology to routing protocols for wireless sensor networks in order to improve the energy consumption of each node. On the other hand, the authors of [36] implemented an intelligent routing protocol in a particular, simple SDN topology.…”

Section: System Architecturementioning

confidence: 99%

Artificial Intelligence Enabled Routing in Software Defined Networking

Hwang²,

Hwang³

et al. 2020

Applied Sciences

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Software defined networking (SDN) is an emerging networking architecture that separates the control plane from the data plane and moves network management to a central point, called the controller. The controller is responsible for preparing the flow tables of each switch in the data plane. Although dynamic routing can perform rerouting in case of congestion by periodically monitoring the status of each data flow, problems concerning a suitable monitoring period duration and lack of learning ability from past experiences to avoid similar but ineffective route decisions remain unsolved. This paper presents an artificial intelligence enabled routing (AIER) mechanism with congestion avoidance in SDN, which can not only alleviate the impact of monitoring periods with dynamic routing, but also provide learning ability and superior route decisions by introducing artificial intelligence (AI) technology. We evaluate the performance of the proposed AIER mechanism on the Mininet simulator by installing three additional modules, namely, topology discovery, monitoring period, and an artificial neural network, in the control plane. The effectiveness and superiority of our proposed AIER mechanism are demonstrated by performance metrics, including average throughput, packet loss ratio, and packet delay versus data rate for different monitoring periods in the system.

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“…According to this type of protocols, the nodes in the network are classified into two types: Cluster Head (CH) nodes and normal nodes. Some protocols (as in [5]) have another type of nodes called Relay Nodes (RNs) that receive data from CHs and then send it to BS. The nodes are grouped into many clusters.…”

Section: Introductionmentioning

confidence: 99%

ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

Al‐Zubi¹,

Alawad²,

Kreishan³

et al. 2021

ITC

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Wireless Sensor Networks (WSNs) have a wide range of applications in human life. Accordingly, WSNs have beenthoroughly considered in research community to improve their performance and address their challenges. Eventreporting in WSNs has always been a major challenge in terms of energy consumption. Event reporting requiressensing the event and sending a reporting packet from the sensor to the centralized base station (BS). However,sensor’s energy is limited and stored in a non-rechargeable battery. Therefore, several event-reporting (or datacollection) protocols have been proposed to improve energy consumption in WSNs, and consequently, to extendtheir lifetime. In this paper, we propose an efficient event reporting protocol for WSNs called Event ReportingProtocol Based on Distributed Data Aggregation (ERP-DDA). This protocol mainly aims at reporting any event byno more than one sensor node such that energy saving is satisfied in the whole network. To achieve this goal, ERPDDAis mainly based on the following features: it is a cluster-based protocol, it is a multi-hop routing protocol, itapplies distributed data aggregation, and it employs variable clustering and cluster head selection. Simulationsshow that ERP-DDA significantly extends the lifetime of WSNs compared with other related protocols.

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Lifetime-Improvement Routing Protocol for Wireless Sensor Networks

Cited by 17 publications

References 20 publications

Ameliorate the performance using soft computing approaches in wireless networks

Ameliorate the performance using soft computing approaches in wireless networks

Artificial Intelligence Enabled Routing in Software Defined Networking

ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

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