Three-Dimensional Position-Based Adaptive Real-Time Routing Protocol for wireless sensor networks
© Entezami and Politis. 2015
Received: 4 March 2015
Accepted: 4 June 2015
Published: 31 July 2015
Devices for wireless sensor networks (WSN) are limited by power, and thus, routing protocols should be designed with this constraint in mind. WSNs are used in three-dimensional (3D) scenarios such as the surface of sea or lands with different levels of height. This paper presents and evaluates the Three-Dimensional Position-Based Adaptive Real-Time Routing Protocol (3DPBARP) as a novel, real-time, position-based and energy-efficient routing protocol for WSNs. 3DPBARP is a lightweight protocol that reduces the number of nodes which receive the radio frequency (RF) signal using a novel parent forwarding region (PFR) algorithm. 3DPBARP as a Geographical Routing Protocol (GRP) reduces the number of forwarding nodes and thus the traffic and packet collision in the network. A series of performance evaluations through MATLAB and Omnet++ simulations show significant improvements in network performance parameters and total energy consumption over the 3D Position-Based Routing Protocol (3DPBRP) and Directed Flooding Routing Protocol (DFRP).
The main duty of a wireless sensor network (WSN) as a distributed computing network is collecting data from a large number of nodes that have the capacity to sense the environment and process data and also communicate over a short range. WSN applications collect data from wireless sensors, and an appropriate routing protocol could help them achieve scalability and improve performance. In real-life WSN applications, wireless sensor nodes are deployed in three-dimensional coordinate system (3D) environments such as mountains or sea surfaces. Most of the position-based routing protocols consider the topology as a two-dimensional scenario. In this paper, deploying wireless sensors in 3D environments has been considered. Data collection protocols can form a planner or tree topology that could be in cluster or mixed data collection form. The Three-Dimensional Position-Based Adaptive Real-Time Routing Protocol (3DPBARP) is one of the many-to-one routing protocols which is based on the spanning tree method [1, 2]. 3DPBARP establishes at least one data collection tree with a sink as the root node in the topology. All data which are produced by sensors are forwarded to the root node. Each node is responsible not only for sending its own data but also for relaying other’s data, so that they cover more distance to the root node [3, 4]. The Trickle algorithm  optimizes the overhead cost and makes the routing protocols more flexible. The control protocol packets are sent based on changes in topology, and if there is no change in topology, the interval times (duration) between when updates are sent is increased with a resulting decrease in the number of control packets. It also makes routing protocols react quickly and be adaptable to any changes in topology, and if any change in topology is sensed, then the interval time is reset to minimum in order to update the topology very quickly [6, 7]. 3DPBARP enhances greedy forwarding by considering congestion and packet delivery information when looking for the best path to the destination. 3DPBARP uses a mechanism for choosing a parent that it is based on the spherical distance (SD) value of each neighbour that chooses the best possible parent between existing qualified neighbours. 3DPBARP avoids occurring a loop in topology by using some mechanism. It also uses the Rainbow mechanism that makes 3DPBARP be able to avoid dead end routes . 3DPBARP uses a new mechanism to make it more energy efficient than other existing algorithms. The proposed protocol uses unique restricted parent forwarding regions (PFRs) based on the algorithm that limits the number of nodes that receive the packets. It decreases the radio frequency (RF) range to the minimum to cover the nodes’ parent only, and for this reason, other nodes do not consume energy to receive the signal and retransmit them. Geographical Routing Protocols (GRPs) make all nodes be able to learn more about their location and also the position of neighbours and the sink. GRPs could make decisions with better performance in real-time and dynamic scenarios. GRPs decrease the overhead of the protocols significantly and make them more efficient. The disadvantages of GRPs are the cost of additional hardware and also the accuracy of location determination which depends on the mechanism and techniques whether the location of each node is calculated. Some techniques such as radio ranging have less accuracy, and some techniques such as the Global Positioning System (GPS) have more accuracy [9–11].
In this paper, 3DPBARP as a 3D, real-time and geographical routing protocol has been proposed that provides a soft real-time capability for an effective heuristic solution for void node problem or hole problem. The void node problem (VNP) or hole problem is called to a situation when a packet arrives at a node that does not have any neighbour to forward the packet toward the sink. The Rainbow mechanism is used to avoid dead end routes. The proposed protocol also uses a unique restricted PFR-based algorithm that limits the number of nodes that receive the packet.
This paper is organized as follows: Section 2 describes previous works, and Section 3 shows the 3DPBARP design details and system model. Evaluation and results from simulations come in Section 5, and finally, the conclusion is provided in Section 6.
2 Related works
O-CTP  is based on investigation of WSN routing protocol behaviour in networks that are affected by interference. O-CTP is a hybrid routing protocol that uses the high packet delivery ratio of opportunistic routing in error-prone networks, and it is also an energy-efficient routing protocol .
ICTP  uses both long path with good link quality and also short path with bad link quality. It may decrease the reliability, but it improves efficiency to avoid congestion. Li et al. have shown that the energy consumption in ICTP is less than that in the Collection Tree Protocol (CTP) in the same scenarios based on reducing the possibility of congestion.
BCTP  is a balanced version of CTP that enables the network to avoid the heavy traffic nodes. It uses average transmission rate as a metric. BCTP has been evaluated by a testbed, and the results show that the load in hot spot drops by 61.9 %. RAP  is a real-time GRP which uses the velocity of each packet as a gradient to deliver the packets. Each velocity is calculated based on the distance to the destination and its delivery deadline. The packets with higher velocities can be sent earlier than the packets with lower velocities. However, this protocol does not provide any guarantee in end-to-end real-time delivery. EDF  provides a real-time decentralized scheduling that guarantees end-to-end delivery, but it needs a priori defined schedule that is not feasible in most of WSN applications. SPEED  is a real-time GRP that uses neighbour information to estimate distance in a routing protocol. SPEED lets each node decide which neighbour would be the next hop forwarding node, and in case there is no suitable node existing in neighbours, the node with the lowest miss ratio is used for forwarding the packets. MMSPEED  is an enhanced version of SPEED that focused on reliability levels and multiple timelines. It uses resources with better performance than SPEED. RTLD  is a real-time routing protocol with load balancing based on link quality, packet delay and remaining power in the next-hop neighbours. All the abovementioned protocols are based on 2D coordinate systems and need neighbour information to decide about the next hop to forward the packets. ALBA-R  is a 3D GRP that deals with VNP, and it restricts the packet forwarding to a cubical region only 3D greedy routing  is a 3D GRP that is based on density population of wireless nodes, and it also has an issue regarding VNP in low-density population nodes’ scenarios. 3DPBARP  is a 3D GRP that controls the number of forwarding nodes and delivers packets within a specific deadline. In this protocol, the forwarding decisions depend on the expected number of nodes toward the sink and also the queuing delay in the forwarding nodes .
A WSN consists of small devices, and energy consumption is a vital key. Any protocols that are used have to be energy aware. The Three-Dimensional Position-Based Routing Protocol (3DPBRP) is a 3D and position-based version of the CTP as a lightweight, simple reliable, efficient, best-effort, many-to-one routing protocol. Using the CTP concept in a 3D routing protocol is one of the motivations of this paper. Adding energy consumption efficiency in current routing protocols is another motivation for this paper. Decreasing the number of nodes that receive unrelated signals decreases the number of retransmissions and could save more energy. Energy consumption in a transponder is based on the range of coverage by RF, the energy consumed in the transponder being proportional to the square of the RF range radius. Any reduction in RF transmission range could save significant energy in wireless nodes.
The location management phase is one of the key factors in 3DPBARP. The PFR is calculated in location management phase to ideally contain minimum forwarding nodes to limit the number of retransmitting nodes in a group of one-hop neighbours. In PFR, the parent location is denoted as (X p, Y p, Z p), and the node location is denoted as (X n, Y n, Z n).
where (X p,Y p,Z p) denotes the position of the parent and (X n,Y n,Z n) denotes the position of the node. Each node selects its parent from a group of qualified neighbours that have already advertised their minimum root distance (MRD) values. The neighbour that is selected as the node’s parent is the neighbour with the least MRD value. The second goal of the proposed protocols is to use the Rainbow mechanism to solve VNP to enhance the reliability of the protocol and increase the packet delivery ratio. The proposed protocol has three main functionalities: parent selection that selects the best parent from the qualified neighbours of the node, location management that calculates the position of each node and the minimum radius of RF range, and the VNP handling that avoids forwarding the packets toward the hole or dead end.
3.3 Parent selection in 3DPBARP
where Link(SD) denotes the surface distance of the node, (X p,Y p,Z p) denotes the position of the parent and (X,Y,Z) denotes the position of the node. Each node selects its parent from a group of qualified neighbours that have already advertised their MRD values. The neighbour that is selected as the node’s parent is the neighbour with the least MRD value.
3.3.1 3.3.1 Rainbow mechanism in 3DPBARP
In this section, the Rainbow mechanism has been considered, and how it is used in 3DPBARP to avoid dead end routes is demonstrated.
The colour code in each node is calculated based on a counter. The rainbow counter is the number of received packets from the sink. Any node with higher value of this counter shows that it is closer to the sink than other nodes with lower value.
3.4 Loop avoidance in 3DPBARP
3DPBARP uses a detection mechanism during the data packet transmission to validate the routing path and topology. This mechanism makes 3DPBARP avoid loops by checking the previous N(l) nodes where a packet comes through. If the current node is in the list of N(l) last nodes, a network loop will occur and reconsidering the topology will be needed to put it in order. N(l) sets in the initiate stage.
4 Evaluation system model
System evaluation has been performed through massive simulations. Omnet++ has been used as a WSN simulator, and MATLAB has been used for simulating the energy model. Each scenario runs more than 20 times to collect the reliable results with confidence intervals of 0.95.
4.1 System channel model
The simulations run on a field area of 200×200×100 m, and the radio feature CC2420 has been used as radio module that is working on IEEE 802.15.4 standard . Simulations have been run from 18 up to 3000 s. The variety of radio channel has been set up by ‘Wireless Channel Sigma’ that is 0, 1, 3, and 5. Wireless Channel Sigma shows the standard deviation of the communication channel diversity . The received signal strength at a wireless node in real scenarios depends not only on distance from the transmitter but also on shadowing effects. The sigma parameters represent the random shadowing effects in the wireless channel parameters.
The Radio Collision Model has been selected as the one that puts more collision than normal.
4.2 Energy consumption model
where E Tx is the energy consumption in the transmitter node, E amp is the energy required to transmit 1 bit in the RF module, k is the length of the message (bit) and d denotes the distance between the transmitter and receiver measured in metres. Figure 3 is a graphical vision of energy model system and shows the elements of this model.
5 Performance evaluation
Omnet ++ simulation parameters
Number of nodes
100 pJ/bit/m 2
Wireless Channel Sigma
0, 1, 3, 5
CtoNoe, 3DPBARP, DFRP
App packet rate
Constant 150 bytes
Max frame size
Radio Tx power
Radio Collision Model
This paper proposed 3DPBARP as an Energy Efficient Rainbow Collection Routing Protocol. 3DPBARP has shown a performance improvement in packet delivery parameters. 3DPBARP performs with more accuracy by using a new parent selection and Rainbow mechanisms to choose the parents with more accuracy. It also employs techniques to avoid loops in the topology. 3DPBARP as a GRP decreases the RF range in each node by reducing the number of nodes which receive the signal, using a new PFR technique. Nodes reduce the RF range to cover their parents only and not any nodes with further distance in the location management phase and PFR. A massive simulation on 3DPBARP shows a significant improvement in performance regarding energy consumption compared to 3DPBRP and DFRP in different scenarios. 3DPBARP shows that it could save more than 80 % of the total energy consumption in the network by using the special technique in PFR. It also provides better performance in busy and noisy environments in terms of packet delivery time and the ratio of successful packet delivery.
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