Inspired from Ants Colony: Smart Routing Algorithm of Wireless Sensor Network

Bouarafa, Saleh; Saadane, Rachid; Rahmani, Moulay Driss

doi:10.3390/info9010023

Cited by 7 publications

(8 citation statements)

References 13 publications

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“…Bouarafa et al 33 proposed an ant colony‐based smart routing algorithm (SRA) to lengthen the lifespan in WSN. The nodes are randomly distributed within the networks.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient optimal parent selection based routing protocol for Internet of Things using firefly optimization algorithm

Sankar¹,

Ramasubbareddy

Luhach

et al. 2020

Trans Emerging Tel Tech

103

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Energy conservation is a major challenge in the Internet of Things (IoT) as the number of resource‐constrained devices is connected to the network. Routing plays a vital role in IoT to extend the lifespan of the network. Routing protocol for low‐power and lossy networks (RPL) is a standard routing protocol in IoT. The parent selection is a crucial role in the routing process to exchange the data. In RPL, the researchers have introduced a single metric, composite metric, and multiobjective optimization algorithm for parent selection. However, the improper parent selection causes the packet losses, congestion among the network nodes, depletes more energy, and increases the convergence time. To overcome these issues, this article proposes energy efficient optimal parent selection in RPL (EEOPS‐RPL) using firefly optimization algorithm to extend the lifespan of the IoT network. In EEOPS‐RPL, each node in the network is considered to be firefly and also calculates the current location of firefly, attraction of the fireflies, random function, velocity, and the global best values in the network. Residual energy and expected transmission count are attractiveness parameters and distance is a movement parameter to choose the optimum parent in the destination‐oriented directed acyclic graph for data transmission. The simulation is conducted using COOJA. The EEOPS‐RPL provides better performance in comparison to the efficient parent selection for RPL (EPC‐RPL) and the E‐RPL. The EEOPS‐RPL improves the packet transmission ratio and lifespan of the network by 2% to 5%, and 5% to 10%, respectively, compared with EPC‐RPL and E‐RPL. In EEOPS‐RPL, each participant node applies the firefly algorithm over the parent node information such as distance, residual energy, and expected transmission count through DODAG information object control message to pick the best parent node in the DODAG. The firefly algorithm provides the fast convergence that able to choose the optimal parent quickly. Thus, it avoids the packet loss during the route establishment in network. Thus, EEOPS‐RPL extends the lifespan of the network and reduces the convergence time.

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“…Bouarafa et al 33 proposed an ant colony‐based smart routing algorithm (SRA) to lengthen the lifespan in WSN. The nodes are randomly distributed within the networks.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient optimal parent selection based routing protocol for Internet of Things using firefly optimization algorithm

Sankar¹,

Ramasubbareddy

Luhach

et al. 2020

Trans Emerging Tel Tech

103

View full text Add to dashboard Cite

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“…As a outcome, in the massive quantity of applications of the IoT, 19 energy-efficient communication and stable energy supply have become the priority objectives in the division of resources. 20 In the network node traffic balancing, node hold-ups are needed to be considered for increasing reliability. 21 Congestion has an important influence on Quality of Service (QoS) authorizations such as throughput, delay, and energy ingestion in wireless nodes.…”

Section: Literature Surveymentioning

confidence: 99%

“…The essential concerns correlated to the uses of IoT are extending the battery life of machine‐to‐machine (M2M) mobile devices to create the IoT system work for an extensive era. As a outcome, in the massive quantity of applications of the IoT, 19 energy‐efficient communication and stable energy supply have become the priority objectives in the division of resources 20 . In the network node traffic balancing, node hold‐ups are needed to be considered for increasing reliability 21 .…”

Section: Literature Surveymentioning

confidence: 99%

DACASN: Dynamic ant routing‐based channel accessing cognitive sensor network in Internet of Things

Arulanantham¹,

Palanisamy

2020

Int J Communication

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SummaryThe Internet of Things (IoT) is a structure with sensors, base station, gateway, and network servers. Users can access the information contained in it and use it as they need. These sensors are embedded in several data collection locations in a uniform or random manner to collect data. The users in many parts of the world obtain such data that fit their requirements. For example, sensors are used in remote areas to monitor various areas such as forests, wildlife sanctuaries, fields, industrial needs, human condition, and changes in the ocean. The changes like these that take place in the open spaces require the selection of the best routing method and seamless delay reduction in data collection helps to immediately reach those involved in it. In the proposed protocol, dynamic ant routing‐based channel accessing cognitive sensor network (DACASN) in the IoT, cognitive sensors are used. It is made with the knowledge of choosing a channel for communication as well as selecting the parameters for path selection and setting the most accurate path with the channel knowledge and communicating with the internet server. The sensors set the paths for this route selection using the centrifugal method and the anticolonial method. As a result, it can be seen in the results and discussion section that the quality of the routing information is high because it is delivered to the destination in the shortest possible time.

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“…The Smart Routing Algorithm (SRA) proposed by Bouarafa, Saadane, and Rahmani (2018) aims to improve the routing performance in the WSN and prolong the network lifetime of the system. The predecessor node will broadcast the request message to all successors, which are neighbor nodes, during the searching process to the destination node.…”

Section: Aco Work In Wireless Sensor Networkmentioning

confidence: 99%