MIXIM framework simulation of WSN with QoS

2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT)

MIXIM Framework Simulation of WSN with QoS Ravi Kishore Kodali

Vijay Kumar Malothu

Dept. of Electronics and Communication Engineering National Institute of Technology, Warangal WARANGAL, INDIA [email protected]

Dept. of Electronics and Communication Engineering National Institute of Technology, Warangal WARANGAL, INDIA

Abstract— The Wireless sensor network (WSN) deployment areas in real time environment are often inaccessible and unreliable communication resulting in degradation of network performance. The critical issues in any WSN are QoS and energy. Post deployment, it may not always be feasible to replace the batteries in a WSN. Long hops of transmission maintaining the QoS with more energy consumption results in reduction of network lifetime. This paper concentrates on adjustment of power, range and bit rates to attain adaptive topology control (ATC) at physical layer to maintain optimum QoS. The simulation has been carried out using Omnet++ 4.6 along with MIXIM 2.3 framework. A comparison of a conventional WSN or non-ATC and ATC based WSN has been made involving range, throughput and packet delivery ratio and an improvement of 29% has been observed in ATC. Index Terms—WSN, MIXIM, OmNet++, QoS

I.

INTRODUCTION

There are many advanced applications provided by wireless sensor networks like industry, medical, security, military and weather monitoring etc. Sensing, computing and communication are the three basic activities in any wireless sensor networks. Basic benefits of using WSN are low cost, reliable, small size and scalability. To provide effective communication and sensing WSN needs to improve Quality of Services (QoS). Quality of Service requirements of MAC layer comprise of communication range, throughput, transmission reliability and energy efficiency. MAC transmission reliability determines whether the WSN’s mission (like monitoring) is successful or not. MAC layer is capable of performing these functions: according to deadlines of packets it observes the average delay of packet and loss rate of individual neighbor node so that it can give best transmission reliability to the network. These parameters of transmission, number of retransmissions and redundancy influence the QoS. Adaptive topology control (ATC) impacts the communication nodes which is capable of selecting or modifying their neighbor nodes or active links. It can provide good connectivity, energy efficiency and lower interference. It is implemented in different stack layers. This work presents an implementation of ATC at MAC layer with adjustment of power and range. The impact of ATC on network performance is also presented. By controlling the power changes the number of active

ISBN No.978-1-4673-9545-8

links of the network and connections with the neighbor nodes. Such changes influence performance of network, such as throughput, packet end-to-end communication ratio and delay. The primary objective of this work to maintain the QoS by adjusting power, range and bit rates at physical layer. The rest of paper is organized as follows: section II gives the related work. Section III explains the proposed model, MIXIM framework and model architecture. Results are discussed in section IV. Conclusion and future work are provided in section V. II.

RELATED WORK

Different techniques have been proposed for improvement of Quality of Service (QoS) of sensor networks. The authors in [1] discussed about behavior of (m,k) gur game approach. They mainly concentrated on monitoring field autonomic nodes performing wake up and sleep dynamically to increase the network life time. The practical scenario in adhoc network with a new algorithm which elevate three advantages in the network has been presented in [2]. The algorithm XTC is discussed by considering different types of grapes like general weighted Elucedian graphs and unit disk graphs. The results are compared with the previously proposed algorithm and objective was concluded. The performance of network through power and rate adaption has been discussed in [3] for optimization of wireless networks. The degree of impact of ATC in the network performance at physical layer is presented and explored by the authors. The inheritance of physical constraints in wireless networks by adapting modeling communication in networks has been discussed in [4]. The real time problem i.e., connectivity by using unit disk graph was also discussed and model proposed to overcome the problem. The authors used the hybrid model (combination of two) to provide better quality of service in sensor networks. The prediction of path loss of on network environment by considering radio frequency propagation model is explained in [5]. Two different path loss models are used in predicting the path loss between the sensor node in sand terrain environment. The MAC protocol modeling for the mobile sensor network to regulate the access of shared wireless

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2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT) medium. In [7] aware of sensor mobility MAC protocol and challenges in underlying have been presented. III.

PROPOSED OMNET++ MODEL

A simulation model using the OMNET++ simulator has been created. It consists of libraries to design various models and analyze the characteristics of these models. MIXIM is an upgraded version of mobility framework which is used for WSN using OMNET++. A. System Model A 500 m x 500 m area has been considered for deployment of sensor nodes of 30 and 100 nodes with unit disc graph and simple path loss models. It is executed with improved QoS in MIXIM 2.3 network simulator. It comprises of the features of high performance when compared with other WSNs. It has high packet end-to-end delivery ratio and throughput.

Fig. 1. Simulation scenario in OMNET++

B. OmNet++ (MIXIM) Project Design For WSN and mobility WSN simulation with OMNET++, a MIXIM 2.3 has been used. Advantage of OMNET++ and MIXIM is that it reduces the complexity of a model and provides hierarchy modeling and obtain accurate analysis. OMNET++ model consists of NED, Installation file, msg file, result analysis file, C++ development and building application. MIXIM provides the libraries on OMNET++ for mobility and wireless communication models. To build a new model in OMNET++ (MIXIM) the following steps are needed: x Import MIXIM and create a project x Add project preference of MIXIM x Design the model(NED, C++ x Configure the project(Installation file) x Build project x Run and analyze the result. MIXIM is divided in two types: analogue module and basic module. Analogue module has the ability to add user’s simulation parameters. One of the analogue modules used in the simulation is simple path loss model and another module is unit disc model. Both of these modules have been simulated individually. C. Node architecture The architecture of a node in WSN has different layers i.e.: application, presentation, session, transmission, network and NIC layer. Application layer is responsible for sending the request for transmission. Mac layer is a part of transceiver and it consumes more energy in WSN. CSMA is used for Mac layer in this paper. Network layer performs reconfiguration and code reusability in a quick manner by using routing protocols. Each layer has a connection with upper layer and lower layer.

Fig. 2. Node architecture IV.

RESULTS AND DISCUSSION

Before you begin to format your paper, first write and save the content as a separate text file. Keep your text and graphic files separate until after the text has been form In this paper, the performance of Medium access control (MAC) Layer protocol is computed in distinct power steps. In this study, simple pathloss and unit disc model are employed. The simple pathloss model provides fixed attenuation of the signal. The exponent of path loss is taken as 3. The Unit disc model implies the node to transmit the signal without attenuation in specified transmission range. It shows trying to receive the signal” when the distance exceeds the range. Figure 1 shows a scenario used in this study. We considered 100 and 30 nodes over an area of 500x500

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2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT) sq.m. The source is placed in (0, 0) and destination placed in (500,500). It is conducted in MIXIM2.3 framework. The performance of CSMA is measured in different ways in terms of packet end-to-end delivery ratio and throughput. Throughput is defined as the successful receiving packet at destination per unit time. It has two ways of investigation; they are control of power and controlling bit rate with power. A. Control of power on CSMA Here we have taken transmitted power in six different values as shown in Table 2. For every round, all the nodes and hosts are in same range or power. Nodes and hosts are unable to change their respective parameters like communication frequency, transmission power or range and bit rate.

power, the ratio of packet delivery will drop after certain value and it’s called cut-off. This happens due to the degree of nodal. For 30 nodes, power and range are about 100mW and 450m, for 100 nodes 75mW and 400m respectively.Throughput of network comprising of nodes 100 and 30 and with control of power is shown in Figure 4.

TABLE I NETWORK PARAMETERS USED FOR SIMULATION

Fig. 4. Throughput of simple pathloss and unit disc versus controlling power and range

The aim of this is to measure ATC network performance i.e. control of power over Medium access control layer protocol. Throughput and packet delivery ratio are plotted against transmitted power in simple pathloss model, whereas in the case of unit disk model bit rate is also included. Figure 3 shows that for a 30 node network control of power (PC) provides maximum of packet delivery ratio of 97.2 percentage at 100mW for 100 nodes its about 92.1 percentage at 75mW. In simulation analysis we got that 30 and 100 nodes has shown similar result for low power transmission.

From Figures 3 and 4, it can be observed that with increasing of power and range up to 100mW and 400m, the result is better. After that cut-off point the control of power did not maintain a good throughput and packet delivery ratio. Due to extended power and range, channel gets congested which results in high overhead and low throughput. On an average, the overhead of 30 nodes simulation is 54 and 100 nodes is 112.5. This shows that result of performance is better in 30 nodes than in 100 nodes. The overhead at high power (150mW) in 100 nodes is 2.5 times higher than 30 node network. It also shows that 29 percentage better performance in 100 node network with power control on comparison with non-power control network. B. Bit rate and Power control In this paper, above part has investigation on power control on Medium access control Layer protocol CSMA. In this section, we control the bit rate and power. Here, changing bit rate is calculated as per below formula for scheme -2 NewBitrate = log2(1 + SNRx)R SNRx = SNR × (D/d) where R is radius of transmission range. D is old bit rate. Scheme -1 is as per normal bit rate and power control. Change in bit rate with respect to power or range is provided in Table II. TABLE II SCHEME-1 POWER, RANGE AND BIT RATE

Fig. 3. Packet delivery ratio versus controlling power and range For low power and range, transmission graph shows likeineffective communication. As increasing the

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2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT) Figure 5 shows that packet delivery changes are very high about 97.2 % at low range communication (less than 100 m). Figure 6 illustrates that throughput is dropped at 400m in schme-1 but in scheme 2 it is dropped at 500m. Scheme-2 is approximately 41 % better than scheme-1.

FIG. 5. PACKET DELIVERY RATIO FOR SCHEME1 AND SCHEME 2

Fig.6. Throughput for scheme1 and scheme2 V.

CONCLUSIONS

Based on the simulation study it can be concluded that adaptive topology control improves the network packet delivery ratio and throughput. An improvement of 29 % in network performance has been observed with range variation and power adaptation. It can be concluded that QoS of WSN in terms of packet error rate, energy efficiency and throughput are improved in adaptive topology control.

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