In this article, a routing protocol EARP (Energy Aware Routing Protocol) with the terminal node is proposed, to deal with the impact of the limited energy resources of Cognitive Radio Networks on the whole network routing. The protocol allows choosing the route from the neighbor nodes in different transmission paths, according to energy consumption of a single node and the full path. If the path breaks, the protocol will increase local routing maintenance strategy. It effectively reduces the retransmission caused by the situation, and improves the routing efficiency. It also can prevent the link transmission process selecting the fault route due to the energy depletion. Through simulation experiments compared with the LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, the results showed that in the same experimental environment, the proposed EARP could obviously balance the load, protect low energy nodes, prolong the network survival time and reduce packet loss rate and packet delay of data delivery. So it can improve the energy consumption of sensing node and provide routing capabilities.
Haykin [
Nowadays, the energy saving algorithm based on node energy consumption has attracted much attention of researchers. Huang et al. summed up the characteristics of different routing protocols in following: a sensor network of clusters with a hierarchical routing protocol to increase network lifetime was reported [
Based on the above analysis, this paper proposes a new energy aware routing protocol (EARP) for the CRNs. According to the routing strategy, this protocol can achieve the goal of improving network performance at different energy stages (the normal stage, the warning stage, the danger stage) [
The rest of this paper is organized as follows. The energy-consuming model of CRNs is reviewed in Section 2. Section 3 describes the routing protocol based on residual energy aware. Then Section 4 provides the result of simulation experiment. Finally, Section 5 concludes this paper and outlines the future work of node energy consumption.
In the cognitive radio networks, nodes may need to communication with the other nodes which are beyond their ranges. As shown in
According to the network model of W. B. Heinzelman [
Assuming that the distance between a pair of transmitting and receiving node is d, in the free space propagation, the receiving node needed energy to receive the signal is
In Equation (1), n value generally equals 2 or 4, and k is a constant. It indicates that the receiving signal energy is weakened with the increase of the node distance. In this paper, n equals 2 and k equals 1. So it can be simplified as Equation (2).
Supposing that
For a single node i,
In a complete path of data transmission, the link includes the source node, the destination node and all the intermediate nodes,
In
Due to the network lifetime of the routing protocol as the function standard in this paper, if the residual energy of each node is the same as link routing cost influence degree, then they have the same weight, the singular point will affect the optimal routing of the link effect.
Presuming that the data transmission network is reversible, so it does not cause a one-way link. Thus only node i sending data can cause the node j energy consumption.
If
If the overall residual energy value
In this paper, two threshold
So according to the route strategy analysis, when the residual energy is in the normal stage, the relative residual energy value of the node
When the residual energy is in the warning stage, the value of
When the residual energy is in danger stage, the node is protected and not forwarded. Then the value of
If the node wants to send data, it first finds out whether there is a valid route available in the routing table [
When the neighbor nodes and intermediate nodes receive the RREQ message from the source node, they first check whether their route in the routing table is effective according to the requirements, then avoid the loop generating sequence [
If
then
else
the new residual energy
When the route request reaches the destination node, the destination node will start the timer T to set the delay for receiving the valid routing request. If the intermediate node contains the destination node, the RREQ can be sent directly to the source node for completing the route discovery process. The destination node receives the RREQ, comparing the energy information
In the working process of CRNs, if the current node residual energy has been run out, then the sensing node needs to choose the next-hop routing sensing node. As specific selection is shown in
Step 1: The node of the largest residual energy is selected from neighbor sensing node.
Step 2: If the residual energy of selected neighbor sensing node is greater than predetermined threshold (
Step 3: If the residual energy of selected neighbor sensing node is less than predetermined threshold (
When the residual energy of the node is reduced to the trigger that power saving protection mechanism, the link will be broken, and lead to the reselecting alternative way of data transmission. According to the EARP, the residual energy of the node can be predicted in advance [
In
According to local route maintenance strategy, it can design the algorithm of EARP.
In order to test the effectiveness and superiority of energy aware routing protocol for Cognitive Radio Networks, simulation experiment is achieved using Matlab 2015b simulation software in the computer of AMD dual-core 2.20 GHz, 4G RAM, Windows 7 operating system. The simulation results of the protocol EARP in this paper are comparable and convincing. Comparing with the LEACH protocol, it makes a comprehensive analysis of their average energy consumption, the network lifetime, packet loss rate, etc. The simulation parameters are shown in
1) Comparison of average energy consumption of nodes
Generally along with increased production cycle of time sequence, the energy consumption of all routing protocols for CRNs has been declining. It can be clearly seen from
Parameter name | Value | Parameter name | Value |
---|---|---|---|
Area size | 200 m × 200 m | Request packet | 50 bit |
The total number of nodes | 100 | Transmission packet | 40 bit |
Packet size l | 4000 bit | d | 50 m |
Sensing node | (0,0) | Eamp | 0.0013 pJ/bit/m2 |
Cluster radius | 20 m | Eelec | 50 nJ/bit |
4 × 10−3 J/s | Emin | 2 × 10−3 J/s | |
4.5 × 10−5 J/s | T1 | 1 ms | |
9 × 10−4 J/s | 0.1 J |
the energy consumption of continuous transmission. It has chosen the neighbor sensing node with the maximum residual energy as the next node hop, establishing the data forward routing with the minimum energy consumption, thus ensuring the energy balance of the entire CRNs. Because of the energy consumption balance, the two protocols become close to each other at the time sequence between 8 and 12 from the
2) Comparison of network lifetime
Network lifetime is usually described using survival of network of sensing nodes. The survival curve of sensing nodes for protocol is shown in
3) Comparison of packet loss rate
Packet loss rate is a meaningful indicator of measuring routing protocol per-
formance for CRNs. The packet loss rate curve of CRNs for this protocol is shown in
In this paper, it has been proposed an energy aware routing protocol for CRNs, named EARP. The proposed protocol balances the traffic load among different CRNs nodes according to their nodal residual energy and prolongs the lifetime of individual CRNs node as well as the overall networks. Extensive simulation results have shown that the proposed protocol can decrease the message delay and the consumed energy. In addition, it increases the system throughput, the routing success rate, the ratio of survival nodes and the network lifetime. Accordingly, the routing path formed by EARP is more reliable and stable. Future works should focus on the theoretical performance analysis of the algorithm. In summary, the proposed energy aware routing scheme provides an efficient and practical solution for data routing in cognitive radio networks.
This work was supported in part by: National Natural Science Foundation of China, No. 61379005; 2016 Key Base of Tourism and Scientific Research of Sichuan Provincial Tourism Administration, No. ZHZ16-02;2014 Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things, No. 2014WYY03; 2014 Artificial Intelligence Key Laboratory of Sichuan Province, No. 2014RYY02; 2015 Key Base of Tourism and Scientific Research of Sichuan Provincial Tourism Administration, No. ZHY15-04; 2014 Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things, No. 2014WYY02.
Song, Y., He, X.L. and Binsack, R.V. (2017) Energy Aware Routing Protocol for Cognitive Radio Net- works. Wireless Sensor Network, 9, 103- 115. https://doi.org/10.4236/wsn.2017.93006