IRPL: An energy efficient routing protocol for wireless sensor networks

Zhang, Wenbo; Han, Guangjie; Feng, Yongxin; Lloret, Jaime

doi:10.1016/j.sysarc.2017.03.006

Cited by 45 publications

(23 citation statements)

References 17 publications

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“…The amount of energy required for transmitting “ s ” bits of data from node “ x ” to node “ y ” with respect to the distance dis ( x , y ) and its calculation is given in Equation (1) [ 55 ].The total transmission energy

calculation is given in Equation (1).

where

energy dissipated in the amplifier while dis ≤

and

is the energy dissipated in the amplifier while dis ≥

is the consumed energy in the transmission unit,

is a constant, and s is number of data bits.…”

Section: Cluster Tree-based Routing Protocolmentioning

confidence: 99%

CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things

Sankar¹,

Ramasubbareddy

Luhach

et al. 2020

Sensors

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Energy conservation is one of the most critical challenges in the Internet of Things (IoT). IoT devices are incredibly resource-constrained and possess miniature power sources, small memory, and limited processing ability. Clustering is a popular method to avoid duplicate data transfer from the participant node to the destination. The selection of the cluster head (CH) plays a crucial role in gathering and aggregating the data from the cluster members and forwarding the data to the sink node. The inefficient CH selection causes packet failures during the data transfer and early battery depletion nearer to the sink. This paper proposes a cluster tree-based routing protocol (CT-RPL) to increase the life span of the network and avoid the data traffic among the network nodes. The CT-RPL involves three processes, namely cluster formation, cluster head selection, and route establishment. The cluster is formed based on the Euclidean distance. The CH selection is accomplished using a game theoretic approach. Finally, the route is established using the metrics residual energy ratio (RER), queue utilization (QU), and expected transmission count (ETX). The simulation is carried out by using a COOJA simulator. The efficiency of a CT-RPL is compared with the Routing Protocol for Low Power and Lossy Networks (RPL) and energy-efficient heterogeneous ring clustering routing (E2HRC-RPL), which reduces the traffic load and decreases the packet loss ratio. Thus, the CT-RPL enhances the lifetime of the network by 30–40% and the packet delivery ratio by 5–10%.

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calculation is given in Equation (1).

where

energy dissipated in the amplifier while dis ≤

and

is the energy dissipated in the amplifier while dis ≥

is the consumed energy in the transmission unit,

is a constant, and s is number of data bits.…”

Section: Cluster Tree-based Routing Protocolmentioning

confidence: 99%

CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things

Sankar¹,

Ramasubbareddy

Luhach

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…For any node, its n i -round serves as cluster head once, so the energy accumulation period is n i . According to formula (14), formula (15) and formula (16), ETh i is:…”

Section: Design Of Multi-hop Energy Neutral Clustering Routing Promentioning

confidence: 99%

“…path to implement searching from the data source node to the target node [11]. There are two main methods of implementation [12]- [15]: one is to establish a suitable data transmission link, and the other is to correctly transmit datagram along the established data link. In the traditional Ad hoc network, the primary purpose of routing protocol design is to utilize the limited bandwidth resources of the network [16].…”

Section: Introductionmentioning

confidence: 99%

Energy-Saving Algorithm and Simulation of Wireless Sensor Networks Based on Clustering Routing Protocol

2019

IEEE Access

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An efficient and energy-saving algorithm, K-means and FAH (KAF), has been proposed to solve the problems of node energy constraints, short network cycle and low throughput in current wireless sensor networks. Network clustering is obtained by optimizing K-means clustering. Based on FAHP (Fuzzy Analytic Hierarchy Process) method, the cluster head selection is optimized considering the factors of node energy, distance from base station and energy efficiency of nodes. Based on the factors of transmission distance, energy and hop number, multi-hop routing is constructed to effectively reduce the energy consumption of nodes in data transmission. The simulation results show that compared with other protocols, KAF algorithm has obvious advantages in reducing node energy consumption, prolonging network life cycle and increasing network throughput. And under different routing protocol, the performances of the algorithm are verified. By adjusting the size of the candidate node set selection area, the reliability of data transmission of the long-distance node is increased, and the energy consumption load of the near-distance node is reduced. At the same time, the use of opportunistic transmission strategies increases the reliability of data transmission. The simulation results show that the proposed protocol can effectively reduce the energy consumption of nodes and prolong the network life cycle. INDEX TERMS Wireless sensor networks, K-means clustering, multi-hop routing, energy-saving.

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“…Kim et al [10] proposed a queue utilisation based on the objective function to select the Preferred Parent Node (PPN) of the neighbour nodes as their hop distances to the sink node. Zhang et al [11] proposed an enhanced protocol to balance energy consumption across the WSN. This protocol was based on partitioning the network into a group of clusters by using the clustering algorithm and the topology control model for establishing the best route based on the optimal direction angle in the ring domains of the cluster.…”

Section: Introductionmentioning

confidence: 99%