Design of wireless sensor network based on random linear network coding

Wei Ou Information science and engineering school of Hunan University

Changsha, 41000 ,China

Zhixin Yang Information science and engineering school of Hunan University

Changsha, 41000 ,China

Liang Tang Detection and analysis of electronic products in Hunan Province Research Institute

Changsha, 41000 ,China

Guanzhong Yang Information science and engineering school of Hunan University

Changsha, 41000 ,China

Abstract—he usage of random linear network coding in wireless sensor network is consistent with sociality, for this feature, proposed a network coding scheme for sociality for wireless sensor networks. Analyzed the process of coding and decoding of random linear network coding and summarized the advantages and disadvantages of the scheme in practical application, at last through NS2 to compare the scheme of using random linear network coding and traditional coding , the random linear network is better at network performance.

Keywords-wireless sensor network; random linear network coding; sociality; network performance

I. INTRODUCTION As one kind of ad-hoc, WSN (wireless sensor

network)[1] is composed of a large number of sensor nodes and has new information acquisition and processing technology, between nodes in center-free wireless multi-hop connected and the nodes can perceive gathering and process information collaboratively, the network Is widely used in military, civilian and industrial production and other fields. WSN is a data-centric networks, data exchange and processing is its main task, efficiency of network information exchange means that the overall performance improvement. In wireless sensor networks via adding other technologies to improve the efficiency of the WSN information exchange has become one of the hot. [2] and [3] is added to ant colony algorithm in WSN to improve or optimize the WSN routing protocols.[4] In

combination with the features of artificial immune systems, presents an optimized neighborhood node selection algorithm in WSN. In order to improve overall network performance though improving information exchange Efficiency, the introduction of network coding [5] in WSN, proposed social network coding scheme.

II. SOCIAL NETWORK CODING SCHEME In WSN, general nodes’ computer ability are weak,

and energy and storage space are limited, as source node or relay node the general sensor node’ task is sending or forwarding data to the cluster head node, because its computing power, energy and storage space is relatively better, cluster head node will send collected data to the base station, station is the end of returning data of all source sensor nodes. Sensor nodes are randomly deployed in a region, nodes quickly and automatically network according to a method of becoming clusters, only sensor nodes from the same cluster can exchange information, between cluster head and cluster head can exchange information. Figure 1 is a cluster-based WSN topology.

Figure 1 cluster-based WSN's topology

Each sensor node in the program is not only as the source node to generate data, and can be a relay node to store and encode, cluster head node cannot encode and

2012 International Conference on Computer Science and Service System

978-0-7695-4719-0/12 $26.00 © 2012 IEEE

DOI 10.1109/CSSS.2012.250

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decode data, only station can decode data, sensor node has two triggers: one is Two-way trigger which can start and shut down encoding function, the another one is encoding trigger. When network begin to initialize, the nodes do not have encoding function, to one sensor node, only the encoding function is touched off that the node has encoding function, however the one already has be triggered can shut down encoding function by triggering again. Once the conditions are met for the coding node, the node will touch off the encoding trigger to encode the data received and produced. In the traditional network coding scheme, all sensor nodes begin to encode as long as meet the conditions, node encoding has a certain blindness, cannot fully play the advantages of network coding, there are some limitations especially in small handling business or a small busy part of network. A good social [6] program proposed to solve the above problem of the traditional network coding.

A. Social of the nodes Human society has two important features: the

centrality and the community. Human society can be divided into several groups based on various characteristics; the relationship is closely in the same community, otherwise the contact between communities is very little, the function and labor division of individuals in the same community are different, the movement patterns are quite different, some of them are very active and very exposed, they are strong individual centers. In the community only a few individuals are strong center [7], such as a manager of neighborhood community, compared to the average people, he can contact with many people frequently, so he is a strong central, and this is very similar to WSN, there are only rarely nodes are strong central in the WSN. Some of the network environment can be seen as composed of multiple communities, the vast majority of nodes only exposure to the nodes in same community, a very small number of nodes in the community can contact with the nodes outside, such as members of the community with frequency communication between each other. In figure 2, n1, n2, n3 can contact between each other, the equivalent of the cluster head node in WSN, c1, c2, c3 are the equivalent of the manager of neighborhood communities, and in the community he is a strong central.

Figure 2 community of network topology

Freeman [8] made a lot of ways to measure central node, over a period of time T, where each node uses times of communicating with each other nodes to indicate the

size of node central. Definition 1: Ci refers to number of nodes that communicate with node i, and the times of contacting with node i should more than 1:

( )1

,N

i Tji j

C E i j=≠

=

(1)

Here N is the number of nodes in the network, T refers to the pre-defined fixed time length, if in the period T node i and node j linked, then the ET (i, j) = 1, or ET (i, j) = 0. Ci used to describe the central of node, large Ci has a strong central of node, where T can be set according to the actual situation of the network.

B. program description The programs according to how much energy

consumption in a period as conditions of whether to trigger a node as the encoding node, a node consumes more energy in a period of time, that means it can deal with more information, and suitable for efficient coding, for each node to set two threshold of the energy consumption, one is the start threshold, one is off threshold, in a fixed period of time, coding function started after node’s energy consumption exceeds the start threshold, After that, set a time for the node periodically checks, confirm whether the node encoding should be closed, If you find that the energy consumption is lower than off threshold, encoding will be closed. check time’s setting is based on the strength of the centrality of the node, A node with a strong centrality that means it has a lot of neighbor nodes to communicate, then the node has more opportunities to continue to work, satisfy the conditions of efficient coding in the long duration, do not need too frequently check, you can set a longer period of checking time, Similarly, for weak centrality neighbor nodes, may be shorter duration can satisfy the conditions of efficient coding, Need to be checked frequently ready to close the encoding function, the nodes need to be checked frequently and ready to close the encoding function, so this kinds of nodes need to set a shorter cycle time check. Program is divided into two stages of start coding and periodic inspection, suppose threshold for the start node isα in period T, off threshold is β ,which β is much smaller than α , each sensor node has a central value of C, updates the value every time T. Start coding phase: 1) Initialization process of time T in the network. 2) In T, if a node's energy consumption greater than or equalα , start encoding function, or else, as an ordinary sensor node and wait, as long as they meet the conditions they can be encoded nodes. 3) As a coding node, when the trigger encoder meet certain conditions, information can be Received or stored on the encoded processing. Cycle inspection stages:

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1 using periodic inspection to encoding nodes, according to the centrality of node, set different inspection cycle time, such as the central value is C, the corresponding time period is t, than C1 corresponding cycle time is t1, ( )1 1 /t C C t= ∗ .

2 By checking, if you find continuous n times that node encoded data is less than half of buffer queue length, enters the soft-coded state, soft-coded status is that double the timeout of trigger-encoder, the value of n according to the actual situation. 3) When a node in a soft encoding state, detected encoded data is less than half of buffer queue length, than energy consumption test is beginning, If that energy consumption is less than β that get the trigger to close encoding function of the node , or to maintain soft encoding state.

When a node in a soft-coded status detected encoded data more than half of the cache queue, also begun to test energy, and if energy more than β , turn nodes from soft-coded state into the normal coding state, or maintain the soft coding. The program compared to the traditional coding scheme its biggest advantage is: Node can be on and off encoding function automatically according to the differences of the volume of business handled, A good solution to the traditional network coding scheme that some nodes’ blind coding problem, get busy node to be a coding node, And when coding is most needed that the busy nodes will be encoding ones, when encoding is not needed the coding is closed. Truly powerful network coding is implemented, greatly improved the proficiency of information exchange between nodes, and ultimately to maximize network performance. The disadvantage is a little complicated to implement specific program, and node requires some hardware support, and the cost of the network is increased.

III. RANDOM LINEAR NETWORK CODING The program is used in a random linear network

coding [9,10], Assumed that the source data packet information X1, X2, X3 ... ... Xn, then after data packets are processed by encoding nodes, they can be expressed as:

1

n

i ii

Z g X=

=

(2)

Which gi is randomly selected from finite field Fq, and gi is the corresponding encoded factor. In general case, if a node is stored encoded data packet information X1, X2, X3 … Xn, new received information packet Y1, Y2, Y3 … Ym, the encoded data can be expressed as:

1 1

n m

i i i ii i

Z g X f Y= =

= +

(3)

gi and fi which are randomly selected from the finite field Fq, and gi and fi is the corresponding coding factor, and X

and Y can be a source packets information , and can also be encoded packet information.

A. Encoding Packets transmitted between nodes in the network

include two parts that are vector and information coding vector, the source packets can be considered to be corresponding unit vector of code vector. The main purpose for packet including the encoding vector is decoding of receiver. Encoding process using iterative methods [11], Suppose a node has received and stored data packet information (g1, Y1), (g2, Y2) … (gn, Yn), when encoding to meet the conditions, the node randomly selected k1, k2 ... ... kn and expression from the finite field Fq.

1

n

i ii

Z k Y=

=

(4)

And expression:

( )1

21 2

0 0......0 0......

.............0 0 0

n

n

gg

g k k k

g

=

(5)

Getting new data packet information (g, Z), this

process is repeated in the coding node. When encoding node receives a data packet information, temporarily stored in the buffer queue, Each packet of information stored at the same time start a timer, the timeout is set p_time, while each packet stored, start a timer, Timeout is p_time, If this information packet is encoded, the corresponding timer is cleared, buffer queue length up to q_len. In order to ensure the timeliness of the data and decode success rate, we use the following two mechanisms to trigger code triggers: �one of the packets’ timer expires; �Information packets length is equal to q_len in the queue. Information packets broadcast after the encoding node encoded, in a cluster, only the hops of reaching the cluster head node smaller than the hops of the encoding node that the nodes will accept the packet of information, and placed in the queue.

B. decoding After base station collect data packet information

from Cluster head node, and extracted encoding vector and information vector from the node, put them into the decoding matrix in the form of row vector, only packets information from the same cluster was placed in the same decoding matrix. Using Gaussian elimination method [11], if a packet is received, decoded information can increase the rank of the matrix which is called the update packet information, otherwise ignored. when the decoding matrix’s rank equal to the number of the source code

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packets, the decoding is successfully finished. For example, a cluster from a base station receives the data packet information (g1, Z1), (g2, Z2), ... ... (gm, Zm), the information vector of packet contains the source data packets whose number maximum is n, for the decoding source data, need to solve the n unknowns of m equations, and requires m n, so that the number of information packets received at least equal to the number of source data packets, Since we are using a random linear network coding, coding vector is randomly selected from a finite field, they are linearly independent probability close to 1

[12], so in the case m = n, the probability of all the decoding source data close to 1.

IV. SIMULATIONS AND PERFORMANCE ANALYSIS NS2-based simulation platform, simulation

environment as follows: 60 sensor nodes, 3 cluster head node, 1 base station, the sensor nodes are randomly distributed in 1000m * 1000m area, Form 3 clusters, and the cluster head node does not have the codec functions, sensor node communication distance 100m, use random linear network coding vectors encoding based on the finite field GF (28).

Under different business volume in the network of this program and the traditional program, compare the total number of contracting, energy consumption and transmission time, CBR sending interval is used here to indicate the volume of business. Set the node's cache queue length is 6, timer timeout is 0.6s, the fixed time period T of the program is 10s, the initial energy of sensor nodes is 4J, α = 6 × 10-3J, β =1.6 × 10-3J, C=5 the corresponding t=5s, n=3, the simulation results shown in Figure 3,4,5:

Figure 3 The total number of sending packets of different

interval

Figure 4 The energy consumption of different interval

Figure 5 Average transfer time of different interval

As can be seen from Figure 4, 5, the program compared to traditional solutions, the total number of contracting is very close, in energy consumption and average transmission time this program is better than traditional programs, The program both in the case of the smaller business volume or in the case of large business volume, have shown a good performance, in the case of moderate business volume, the program is showing its superiority.

V. CONCLUSION In the WSN, Proposes a novel network coding

schemes Based on the social, and describe the program design process in detail, the program according to different network traffic dynamically select the encoding node, And each node according to their volume of business to automatic startup and shutdown code function, make coding has target timeliness intelligence and other characteristics, truly achieve an efficient network coding. Through simulation experiments, the program and the traditional program were compared, the program demonstrated that the overall performance is better than the traditional program. Wireless network environment is more complex, simulation is carried out under ideal conditions, Lack of general, In addition in the concrete realization of the program will be a bit complicated, and requires some hardware support, and the cost of the network will be increased. Next, will be combined with other aspects of technical, design a simple cost savings superior performance of the network coding scheme, network coding to further improve the performance in WSN.

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