Proposed Network Coding for WirelessMultimedia Sensor Network (WMSN)

A. A. Shahidan, N. Fisal, Nor-Syahidatul N. Ismailand Farizah Yunus

Abstract Wireless sensor network has caused a lot of interest in many applica-tions especially in real-time multimedia data transfer over wireless network whichis known as wireless multimedia sensor network (WMSN). Even though suchapplication is quite complex and very challenging to be realized, the availability ofCMOS camera and microphones with low cost, low power and small size hasreduce the complexity of developing the WMSN. Apart from this, there are severalsubjects that may also contribute toward the realization of WMSN such as routingprotocol, source coding and channel coding. This research is focusing on networkcoding which is one of the most important research interests since a few years agodue to its ability to increase the throughput and reduce energy consumption of thewireless network system. Many ideas have been proposed involving several net-work coding schemes based on applications in certain wireless network standard.This project is aimed for multimedia application in IEEE 802.15.4 wireless sensornetwork. Therefore, the constraint of this standard must be taken into considerationin the propose network coding scheme.

Keywords Network coding �Wireless multimedia sensor network � Transmissiondelay

A. A. Shahidan (&) � N. Fisal � N.-S. N. Ismail � F. YunusUTM-MIMOS Center of Excellent, Faculty of Electrical Engineering,Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysiae-mail: ashahidan@fke.utm.my

J. J. Park et al. (eds.), IT Convergence and Services,Lecture Notes in Electrical Engineering 108, DOI: 10.1007/978-94-007-2598-0_41,� Springer Science+Business Media B.V. 2012

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1 Introduction

The research on wireless sensor network (WSN) technology has begun since a fewyears ago. Research communities are developing the technology for many appli-cations such as environmental monitoring, hazardous environment exploration,and military tracking [1]. Wireless sensor network consists of many self-organizedsensing nodes [2] where every single node has the capability of data monitoringand collecting, data processing and data sharing among the adjacent nodes.

The usage of WSN technology has evolved rapidly from simple applicationwhich involves small information size such as water level and temperature to themore complex one which is involving multimedia data such as video and sound.As for multimedia data application, real time response is one of the demandingissues in the research of WSN technologies. Therefore, one of the aims in theresearch on WSN is to find the possible ways to ensure reliability during datatransmission so that higher volume of information can be transferred through thenetwork and the responses of the system is approaching real-time characteristic.

This is to compromise with WSN constraint such as miniature, low cost and lowpower consumption. Due to such constraint, IEEE 802.15.4 compliant radio ischosen to be widely used in WSN [3]. The maximum achievable rate is up to only250 kbps [4]. Therefore, only small size of data is usually transmitted. The WSNdata rate is considered too slow for multimedia and hence the data should becompressed or coded in such a way that the transmission speed can be compro-mised. Even though the transmission delay is one of the main issues for multi-media in WSN, the processing delay is a more significant issue.

In WSN, the network layer and transport layer play an important role inachieving data transmission reliability. The network layer offers a best effortservice and the transport layer is responsible for achieving reliable, provide con-gestion control and flow control [5]. At transport layer, both of reliability andcongestion control algorithm should be taken into consideration to ensure that thedata reach at the destination successfully and achieving high reliability datadelivery as proposed in [6]. At network layer, reliability also needs to be con-sidered as an important requirement for data transfer.

Thus, we consider the problem of reducing the energy consumption andincreasing the throughput of the network. This can be handled by a coding methodknown as network coding which has become interesting in the research of WSN inthe last few years [7]. In this paper, we investigate the benefit of the networkcoding in reducing the number of transmissions over the network that operated inerasure channel model. Performance of the network coding used for the purpose ofmultimedia data transfer is analyzed using simulation experiment.

The remainder of this paper is organized as follows. Related works in wirelessmultimedia network are reviewed and summarized in Sect. 2. Network codingconcept is described in Sect. 3. The details of system model, result and discussionare described in Sects. 4 and 5 respectively. Lastly, Sect. 6 presents the conclusionand recommendation for future works.

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2 Related Works

There are several works that apply network coding for various applications inwireless sensor networks. In [8], the authors used raptor codes like network codingfor multimedia streaming. The throughput of the networks is increased usingmulticast routing algorithm with network coding as introduced in [9].

Meanwhile, network coding is also realized using fountain approach in order tohave low-complexity characteristic networks as described in [10]. The work ismeant for data collection in wireless sensor networks which is done throughsimulation experimented. In [11], the authors used hexagonal lattice topology inwireless sensor network to achieve the maximum possible energy benefit usingnetwork coding. This scheme is applied for multiple unicast networks.

In this project, network coding will be applied in multimedia application. Thereare several research that focus on this application in wireless network such as in[12–14]. In Yakubu Suleiman Baguda et al. [12], introduce cross layer design totransmit H.264 video standard over IEEE 802.11e wireless local area network(WLAN). They take the advantages of EDCA mechanism in IEEE 802.11e toprioritize the frame.

In WSN, the feasibility to transmit multimedia application at low rate and lowpower using IEEE 802.15.4 has already been proven in [13]. The author usedCOTS CMOS Camera together with TelG mote platform to transmit JPEG image.Thus, this work has inspiring the author in [14] to propose the transmission ofMPEG-4 in the same medium. The priority frames are applied at application layerto improve the quality of video transmission. However, all of this research does notapplied network coding for their multimedia transmission.

3 Network Coding Concept

Network coding has become a new research area in the field of information theorywhich is used in practical networking system [7]. The main assumption of thenetwork coding is; instead of just forwarding the data, the node can combineseveral received packet to form a new packet or several new packets throughcertain mechanism [7].

The following is the example of a simple network coding scenario. Let X andY be two nodes that are located separately and cannot make a direct connectionbetween each other. Let S be an intermediate node between X and Y where the datawill be passing through. The connection of these three nodes is illustrated inFig. 1. Assume that X and Y want to exchange data a and data b respectivelythrough node S. Based on traditional method, four transmissions are required inorder to exchange both data. The process is illustrated in Fig. 2. Transmission T1is for sending data a from node X to node S followed by the transmission T2 fortransmitting data b from node Y to node S. The transmission T3 is to send data

Proposed Network Coding for Wireless Multimedia Sensor Network 389

a from node S to node Y and follow by transmission T4 which is for passing datab from node S to node X.

By using network coding on the other hand, both data a and b will be combinedin node S through X-or operation to form a XOR b. Then the combined data willbe broadcasted and both node X and Y will receive the combined data as shown inFig. 3. The received data will be processed and the particular data will be collectedby each node for further processing while the unused data will be dropped. Thecombined data is transmitted during the third transmission. Here, only threetransmissions are required.

Besides, we also know that the nodes in WSN are ubiquitous [1]. Therefore, wecan exploit this characteristic to enhance the reliability of the system through co-operative data processing. In short, the sensed information data will be encodedand distributed to the selected adjacent nodes in the sensor field through certainmechanism. The node which received the data will do a simple processing beforeredistributing the received data to the selected nodes. The process will be repeateduntil the data reach the destination node. Due to the distribution of the data in thesensor field, it is expected that the data passes through several paths in the sensorfield before reaching the destination. As a result, the system becomes more reliablein reducing the number of packet loss.

S YXFig. 1 Node S as anintermediate node for nodeX and Y

aS YXT1

bS YXT2

aS YXT3

S YXT4b

Fig. 2 Four transmissionsare required for exchangingdata between X and Y

S YXT1a

S YXT2b

S YXT3a XOR ba XOR b

Fig. 3 Three transmissionsare sufficient for exchangingdata between X and Y

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4 System Model

We use network model as shown in Fig. 4 which consists of three parts which aresource, relay and destination. The source part consists of a source node thatprovides the information data through the sensor attached to it. The data fromsource node will be passed to the relay part. Relay part consists of several relaynodes forming a certain number of hops. Users can vary the number of nodes toensure that the distance between two adjacent nodes are in the transmission range.The ubiquity of the system is increased as the number of node increases and wecan exploit this characteristic to increase the data transmission reliability. In ourcase however, we consider various number of relay nodes. Up to fifteen nodes withmaximum six-hops have been deployed to simplify the simulation. The destinationpart consists of a sink node.

The algorithm is aimed to be implemented for image sequence data transfer inmultimedia data transmission. The following are the description of the datatransmission process in our simulation. The information data will be fragmentedinto a few small packets. The size of the fragmented packets is obtained from themaximum size of packet that can be handled by the physical layer of the sensornode. For example, the users of TelG mote [15] need to ensure that the packet sizemust not be greater than 128 bytes since the sensor node use Xbee wireless modulethat can only handle the packet up to 128 bytes of size.

In every transmission, the source node will broadcast a packet to all relay nodes inthe first hop. After receiving a packet, the relay node will buffer the packet andfollowed by network coding process which is done with probability PNC. The processis done by combining the received packet with the packet that is previously stored inthe buffer. The same activities occur in every relay nodes until the packet reach thedestination node intact. Network coding must not be done in every transmission inorder to ensure that the degree-one packets reach the destination. The reason is thatthe decoder used is based on LT-Codes decoder where a certain number of degree-one packets are required in order to reduce the ripple size or the degree of the receivedpackets so that the original packets can be recovered [16].

5 Result and Discussion

In our simulation, we operate the system in erasure channel where the packet witherror will be dropped. For performance evaluation, we have also introduced a fewparameters such as the maximum hop, H and the number of nodes per hop, L.The maximum degree of the packet, D is obtained from the equation (1).

D ¼ 1þ Bð ÞðH�1Þ ð1Þ

The number of packets after fragmentation is K. The probability of networkcoding being done at a node is PNC, while the probability of packet loss is PE.

Proposed Network Coding for Wireless Multimedia Sensor Network 391

Every node has a buffer of size B. The simulation is conducted using the networkmodel in Fig. 4. We set the value of H = 4; B = 1 and hence the value of D will be8. Since this algorithm is still immature, we will not compare it with otherestablished algorithm. The data used for the simulation is computer generated data.We repeat the simulation with value of K from 1 to 100 in three differentconditions.

In the first condition, we want to find out the effect of network coding on thenumber of packets required for data recovery. The receiver is allowed to collect thepackets larger than K so that all data can be recovered without any losses. Sec-ondly, we would like to observe the effect of network coding on the number ofpackets loss limited number of collected packets. In this condition, the receiver isallowed to collect the packets up to the value of K.

For the first and second condition, we are comparing the result between thenetwork using network coding and the network without network coding. Figure 5shows the result obtained from the simulation using PNC = 0.5 and PE = 0.2. Wecan see from Fig. 5a that the network with network coding has lower number ofcollected packets in order to recover overall data compare to the one without

Source Part

Relay Part Destination Part

L

Fig. 4 System model for simulation

0 10 20 30 40 50 60 70 80 90 1000

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LT-Codes without NCLT-Codes with NC

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0 10 20 30 40 50 60 70 80 90 1000

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Fig. 5 a Number of packets collected to recover all data without any packet loss b Number ofpackets loss for equivalent number of collected packets and transmitted packets

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network coding. Meanwhile in Fig. 5b, the number of packet loss for the networkwith network coding is always lower that the one without network coding. It iscorresponded to the benefit of network coding itself which is to reduce the numberof transmissions in the network and hence will reduce the transmission delay. Inaddition, the reducing of transmission delay is important for multimedia datatransfer because of sensor nodes are battery powered. Based on traditional method,only one packet is transmitted at an instance of time. The transmitter will con-tinuously transmit the packet without knowing whether the packet sent is receiveby the receiver or it is being dropped. Due to the merging of several packets intoone packet in network coding, a lesser number of transmissions are sufficient toovercome packet loss.

In the last condition, the value of L is varied from one to three in order to studythe effect of different number of node per hop on transmission reliability. We limitthe number of the collected packets up to the value of K. The number of packetsloss for every single value of L is obtained and illustrated in Fig. 6. As the numberof nodes per hop increases, the number of packets loss decreases. We know thatthe increasing number of nodes will result in the improvement of the networkubiquity. Hence, we have exploited this characteristic to enhance the reliability ofdata transmission and reduce the number of packets loss.

6 Conclusion and Future Work

In recent years, network coding has received considerable attention due to itsability to increase the throughput and reduce energy consumption in wirelessnetwork system. In this paper, we proposed a network model that applied networkcoding in wireless multimedia sensor network. Through packet combinationmethod, the system become more reliable and reduces the number of packet loss.The assumptions made for the simulation are described while the result obtainedshows that the network coding is functioning according to the theory.

In order to improve this network model, there are lots of works to be done.Adaptive routing protocol can be implemented as a future work to enhance themultimedia transmission in this works. The adaptive routing protocol such as in [18]

0 10 20 30 40 50 60 70 80 90 1000

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L=1L=2L=3

Fig. 6 Number of packet loss network with NC with various numbers of nodes per hop

Proposed Network Coding for Wireless Multimedia Sensor Network 393

that used biological inspired to find a route and in [19] that take care of parameters inphysical layer to choose optimal forwarding decision suitable to be implementing inthis work.

Acknowledgments The Author would like to thank to the Ministry of Science, Technology andInnovation (MOSTI) Malaysia for sponsorship, UTM-MIMOS Center of Excellent for their fullsupport and good advice and for Research Management Center (RMC) Universiti TeknologiMalaysia. Thanks also to all anonymous reviewers for their invaluable comments ant the guesteditors who handle the review of this paper.

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