The efficient use of energy is an important performance metric to extend the lifetime of wireless sensor networks. Since major energy consumption of node is due to its transceiver, the design of MAC protocol plays a vital role in sensor network design. In cluster based sensor networks, due to the different functions of member node and cluster head node, the usage of common MAC protocol results increased energy consumption. To overcome this problem, a novel energy efficient hybrid MAC protocol (EEHMAC) for cluster based wireless sensor networks is proposed in this paper. The proposed EEHMAC protocol uses E-TDMA (Energy efficient TDMA) for intra-cluster communication and FDMA (Frequency Division Multiple Access) for inter-cluster communication. IDS (Iterative Deepening Search) based Scheduling algorithm is used for assigning time slot and frequency slot to nodes. Nodes in EEHMAC follow the periodic duty cycle, which reduces the idle listening, and overhearing problems. Simulation results reveal that an average of 18% energy saving is achieved compared to LEACH (Low Energy Adaptive Clustered Hierarchy) protocol and 10% energy is saved in comparison with GH-MAC (Graph theory based Hybrid MAC) protocol. It is evident that delay of EEHMAC is reduced by 17% and throughput is increased by 15% under all traffic conditions. These results demonstrate that EEHMAC performs better than existing MAC protocols in terms of energy efficiency, delay and throughput.
A wireless sensor network (WSN) is a collection of a large number of low cost distributed sensor nodes to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and cooperatively pass their data through the network to a main location i.e., base station. These nodes are usually equipped with limited energy source. In majority of application scenarios, recharging or replacement of batteries are not possible because of its deployment in harsh and remote environment. This makes energy efficiency an important issue to extend the lifetime of sensor nodes. Because of these reasons, nowadays researchers are focusing on the development of energy aware protocols for wireless sensor networks [
There are four major sources of energy waste in MAC protocol: collision, idle listening, overhearing and protocol overhead [
The rest of the paper is structured as follows: Section 3 emphasizes on the design of proposed EEHMAC protocol and the heuristic method to select the number of clusters. The results are presented in Section 4 following with the conclusion in Section 5.
Energy management is an important research area in the sensor networks. S-MAC [
One palpable approach is to use either TDMA or FDMA for interference free scheduling. Nevertheless, TDMA has many other disadvantages [
In energy efficient hybrid MAC protocol for cluster based network [
To solve this issue, an energy efficient hybrid MAC protocol (EEHMAC) that considers the characteristics of sensor node is proposed in this paper. The proposed EEHMAC uses TDMA for intra-cluster communication since the member nodes required to transmit minimum data for short duration. Since CH nodes are required to transmit maximum data for long duration, FDMA is used for inter-cluster communication. To avoid inter channel interference, the number of frequencies is limited to number of clusters and frequency reuse concept is utilized in the proposed protocol. A heuristic method is used to select the optimum number of clusters for varying network density. With the help of simultaneous data transmission, delay of sensor node is reduced to greater extend and energy efficiency is improved. The performance of proposed EEHMAC protocol is estimated in terms of energy efficiency, delay and throughput.
The main goal of EEHMAC protocol is to reduce energy consumption and delay, while increasing throughput. By combining the advantages of TDMA and FDMA, the proposed protocol achieves better energy efficiency compared to LEACH and GH-MAC. This protocol is suitable for applications in which data gathered by sensor nodes are delivered to destination in a timely manner.
In a cluster based wireless sensor network two types of communication involves namely inter-cluster and intra- cluster communication. Nodes sense the environment and transmit data to the Cluster Head (CH) during intra- cluster communication and CH communicates to the base station and other CH during inter-cluster communication. In intra-cluster communication, the amount of data transmitted is limited but the contention is more. Therefore, the active period is divided into “S” number of slots and is assigned to all users using TDMA approach. In inter-cluster communication, cluster head transmits more data, which is collected from its member nodes. Therefore, the entire active period is given to the CH nodes with “N” different frequencies using FDMA concept. The system model of proposed protocol is shown in
The hybrid MAC protocol is organized into rounds and each round is subdivided into setup phase and steady state phase. During the setup phase, CH is selected based on the energy level and the selected CH will broadcast the advertisement message. The nodes that can reach the cluster head with minimum energy will join in that cluster. After forming the cluster, CH will assign the TDMA slot and forward it to the member nodes. Then the system enters into the steady state phase. During the assigned time slot, the node will be in the active state and goes to sleep state otherwise.
Based on the advertisement message broadcasted by the CH, sink will assign the frequency slot to the CH and broadcast during the cluster setup phase. The frame structure of hybrid MAC is shown in
The network is using ISM band. The entire bandwidth (2.4 GHz) is divided into two parts in the ratio of 1:3. Lower part of the bandwidth is 0.8 GHz and is used for intra-cluster communication. Upper part of the bandwidth is 1.6 GHz and is used for inter-cluster communication. The network is modeled as a graph G = (V, E), in which V is the set of nodes and E represents the link between the nodes. If the nodes i and j are in the communication range then there exists (i, j) ϵ E and (j, i) ϵ E. Based on the relationship between scheduling algorithm and graph theory, NP-hard coloring problem can be used to assign the time slots to the nodes [
Here the IDS (Iterative Deepening Search) algorithm is used for slot assignment. It combines the space efficiency of Depth First Search (DFS) with the optimality of Breath First Search (BFS) algorithm. For node time slot assignment the scheduling algorithm performs the IDS constructing a tree having cluster head as its root. As each node, i is traversed by IDS, it is assigned a default time slot. For frequency slot assignment the scheduling algorithm performs IDS constructing sink node as its root.
slots, one CH is assigned with one frequency. Therefore, the optimum number of clusters in the network will decide the number of frequencies required.
A simple model, in which the transmitter dissipates energy to run radio electronics and the power amplifier and the receiver dissipates energy to run radio electronics is considered [
In the data collection process, first the node will send data to the cluster head and from there the data is forwarded to sink node. Therefore, the total energy spent for data transmission is calculated by combining the energy consumed by member node and by head node.
Energy spent by the member node to transmit a packet of m bits to its head node of distance d is given by
where Eelec is the energy depleted per bit to operate the transceiver circuit, Era is the radio amplifier energy. Apparently, the distance between the member node and its c luster head is less than the crossover distance, so the energy dissipation follows the Friss free space model (i.e.) d2 power loss. The network consists of N nodes distributed uniformly in an M ´ M region. Network is divided into k number of circle clusters and the distance from head node to member node is given by
The total energy spent by the member node is given by
Each cluster head will dissipates energy by receiving data from member nodes, by data aggregation and by transmitting the aggregated data to sink node. Thus, the energy spent by the head node during single frame is given by,
In this case, the distance from cluster head node to base station is greater than the cross over distance. Therefore, energy dissipation follows the two-ray ground model (i.e.) d4 power loss.
where Eda is the data aggregation energy and ETRA is the transmitter amplifier energy. The total energy spent by the cluster is given by
By substituting the Equation (6) and Equation (4) in Equation (7), we get
The total energy consumed by the network is given by
We can find the optimum number of frequencies by calculating optimum number of clusters. This can be done by setting the derivative of total energy with respect to k to zero.
By using the Equation (10), the number of frequencies (clusters) required is calculated. If the optimum number of clusters is increased then the energy consumed by the network will be reduced and thereby increasing lifetime of network.
Equation (9) defines the energy consumed by the network in a single frame and the total energy consumption is given by Equation (11).
where Nf represents the number of frames. In sensor networks, data collection is a time-sensitive function. Therefore, it is important to receive the data in a timely manner. Here, delay is defined as the time taken to transmit the data successfully. In intra-cluster communication, the member node has to wait for node status information and then only it can transmit the data. Therefore, the delay for intra-cluster communication is given by,
During inter-cluster communication, the CH will transmit the data after collecting it from the member nodes. So, the delay for inter-cluster communication is given by,
where ts, tr and tag represents time taken for node status information, data reception and data aggregation respectively. Distance from member node to CH node is smaller than the distance between CH node and base station. Therefore, different timings are used like tdCH and tdBS.
This section evaluates the energy consumption, end-to-end delay and throughput for various schemes using MATLAB simulation tool. Since LEACH is the basic protocol developed for cluster based networks, the performance of EEHMAC is compared with it. GH-MAC is cluster based MAC protocol that uses adaptive MAC scheme for inter and intra-cluster communication. Therefore, the results of EEHMAC are compared with GH-MAC also. The parameters used for simulation are given in
Parameters | Values |
---|---|
No. of nodes (N) | 100 - 1000 |
Topology | Uniform, Random |
Size | 100 × 100 |
Distance to base station | 100m - 250 m |
Number of frequencies | 1 - 14 |
Eda | 5 nJ/bit |
Packet size (m) | 500 bytes |
Eelec | 50 nJ/bit |
Efs | 10 pJ/bit |
ETRA | 0.0013 pJ/bit |
Since the number of frequencies used in the proposed system depends on the number of clusters in the network, the optimum number of clusters required is calculated and compared with conventional cluster based protocol LEACH. Simulation is run by varying network density from 100 to 1000 and the results are shown in
An average energy spent by the nodes for different number of clusters is calculated for EEHMAC and
of clusters and increased if the number of clusters exceeded the optimum value. If numbers of clusters are less than the optimum size then more number of member nodes has to transmit data for long distance to reach CH node. This results in depletion of node’s energy. When the numbers of clusters are more than optimum value, then the number of transmissions done by the CH to the base station is greater than data aggregation process and leads to increased energy consumption. The result shown in
For the network having 1000 nodes, total energy consumed by the EEHMAC protocol is calculated by varying the number of frequency slots, and the result is shown in
the protocol overhead and results in reduced energy consumption. The proposed EEHMAC protocol reduced the frame energy for k clusters by 23.6% and 12.5% in comparison with LEACH and GHMAC. For CH nodes, the energy consumption is reduced by 20% than GHMAC. Thus, these results demonstrate that EEHMAC performs better than LEACH and GHMAC in terms of energy efficiency under various load conditions.
In this section, we first study the end-to-end (E2E) delay for both GHMAC and EEHMAC while the traffic load is varied from 0.1 to one erlangs. As clearly seen from
protocols for various traffic load when the distance is constant and topology is the same. Compared to LEACH, EEHMAC improved the throughput of network by 56% and 14% improvement with GH-MAC. This is due to the collision free characteristics of hybrid EEHMAC protocol. However, the probability of collision is increased in GHMAC if numbers of nodes are increased. This results in reduced throughput of GHMAC. Thus, from the figure it is evident that the best MAC protocol in terms of throughput is EEHMAC than LEACH and GHMAC.
In this paper, we introduced EEHMAC, an energy efficient hybrid MAC protocol for cluster based wireless sensor networks. EEHMAC allows member nodes of cluster to use TDMA and FDMA for CH nodes. Scheduling mechanism embedded in the MAC protocol helps to achieve this. This scheduling mechanism not only assigns the channel, but also reduces collision problem and thereby achieved the lifetime extension of sensor nodes. The number of frequency slots is limited to number of clusters. By selecting optimum number of clusters for energy efficient operation and by combining TDMA and FDMA techniques for channel accessing, EEHMAC becomes more energy efficient, more robust to topological changes and fairer in resource allocation. It gracefully adapts to network density and improves energy efficiency as well as throughput.
The performances of overall MAC scheme evaluated through simulation have shown a significant improvement in energy efficiency by 56.3% and 45.23% compared to LEACH and GHMAC respectively. In comparison with GHMAC, 67.8% throughput is improved in EEHMAC due to its collision free nature. EEHMAC achieved 19% reduction in end-to-end delay in comparison with GHMAC.
In future, we aim to achieve further enhancement over EEHMAC through the proposal of a more dynamic and efficient mechanism for transmission power control. We also look forward to implement it over test bed to validate the simulation results provided here.
B. Priya,S. Solai Manohar, (2016) Lifetime Enhancement of Cluster Based Wireless Sensor Network through Energy Efficient MAC Protocol. Circuits and Systems,07,2296-2308. doi: 10.4236/cs.2016.79200