Score Based Reliable Routing in Wireless Sensor Networks

Score Based Reliable Routing in Wireless Sensor Networks Hamed Yousefi#l, Ali Dabirmoghaddam*2, Kambiz Mizanian#3, Amir Hossein Jahangir#4 #Department ofComputer Engineering, Shari/University ofTechnology, Tehran, Iran *Department ofComputer Science, University ofCalgary, Alberta, Canada [email protected], 2 adab [email protected], 3 [email protected], [email protected] Abstract- The main purpose of a sensor network is information gathering and delivery. Therefore, the quantity and quality of the data delivered to the end-user is very important. In this paper, we focus on designing a general energy efficient, fault tolerant, and highly reliable routing protocol that prolongs the network lifetime; we caD it SBRR (Score Based Reliable Routing). As the main objectives of this protocol are the reduction of packet loss and packet error, we select the best quality path of the network for highly reliable data transfer. The routing decision is based on a heuristic parameter named 'Path Score', which is a combination of four factors. These factors are relevant to hop count, energy level of sensors, error rate of links, and free buffer size of sensors for each path. Also our algorithm utilizes a disjoint backup path for every source; as a result, this reduces the risk of data loss and delivery delay. Simulation results reveal that the proposed algorithm yields a longer network lifetime, less packet latency, and higher delivery ratio than other existing schemes. I. INTRODUCTION Recent advancement in wireless communications, electronics, low power design and also tendency to use high performance low cost products have led to emergence of Wireless Sensor Networks (WSNs) [1]. As the main purpose of a WSN is information gathering and transmission of it to the sink node, the main problem is to deliver information correctly with minimum energy consumption. Besides, whereas the majority of developed applications for WSNs are event-critical applications, achieving reliable data transfer as the main factor of dependability and quality of service seems vital. An important issue in WSN is routing protocol; since it deals with energy consumption, delay, delivery ratio, and network lifetime. Several attempts have been recently made to propose reliable routing protocols. SWR [2] (Single path With Repair routing scheme) is a scheme in which data is forwarded along a pre-established single path. SWR consists of four phases: optimal path setup, data forwarding along the selected path, broken link detection, and path repairing. High delivery ratio is achieved by path repair whenever a break is detected. LQER [3] (Link Quality Estimation Routing) creates a connectivity graph based on minimum hop count field and it uses a concept to estimate link quality before route selection. However, this greedy algorithm does not consider quality of subsequent links when it selects the best link for data transmission in each hop. So, the selected path is not optimal.

In [4], authors have proposed a multi-path based transmission method which finds all the possible paths for any arbitrary given node to base station and picks up the best path considering energy levels. In [5], authors have proposed a novel algorithm to find a set of minimum energy disjoint reliable paths (SMEDRP). The proposed polynomial time algorithm is based on Dijkstra's shortest path algorithm. RM-IDLF [6] (Reliable Multi-path Information Dissemination via Label Forwarding) is a resource-aware and data centric routing protocol which takes advantage of the shortest path in network. In case of isolated node failures, existence of an alternate path helps divert the information packets through the active nodes. However, RM-IDLF only improves fault tolerance of the sensor networks. In [7], authors have proposed a hybrid FEC-feedback multi-path mechanism. The feedback scheme is used to send ACK packets from the sink to the source node when the information bit stream is actually recovered. REAR [8] (Reliable Energy Aware Routing) introduces local node selection, path reservation and path request broadcasting delay. It combines the broadcasting speed with the available energy on intermediate nodes. Also, it provides a robust transmission environment based on the energy-aware routing and energy-reservation mechanism at the network layer and provides reliable transmission at the transport layer. In this paper, we focus on building a general routing protocol called SBRR which takes into consideration of four factors that affect the routing policy. These factors are relevant to hop count, energy level of sensors, error rate of links, and free buffer size of sensors for each path. All these factors are mixed and integrated into the notion of Path Score in this protocol. As the main objectives of this protocol are the reduction of packet loss and packet error, we are interested in choosing the best quality path of the network for highly reliable data transfer in order to reduce number of retransmissions caused by poor paths. If a poor path is chosen to deliver the data, loss rate will be high and retransmissions will cause extra energy consumption and consequently less network lifetime. Also more traffic yields a higher collision probability and higher delivery delay. Also, SBRR attempts to provide a backup path for every source. Sensor nodes can not store large amounts of data due to their limited memory. With a backup path, transmission will not be paused for a new path discovery, and the data will

not overflow the memory of sensor nodes. Also, it improves fault tolerance of the network. Actually, this energy efficient protocol guarantees a longer network lifetime, higher reliability, less packet latency, and higher delivery ratio. The remainder of the paper is organized as follows. Section II explains the proposed scheme and presents the specifications of SBRR. Simulation results are presented and discussed in section III. Finally, Section IV concludes our work, and discusses some future directions. II. PROTOCOL OVERVIEW AND PROPERTIES SBRR is a fault tolerant, energy-aware and highly reliable routing protocol that crosses the network layer. The algorithm comprises: Path Discovery stage for main path discovery and backup path discovery, Path Reservation stage and Data Transmission stage. However, the main idea of SBRR protocol is the combination of four factors to make a general routing protocol for optimal path selection. In the proposed protocol, each label (route request packet) carries the information of target source ID, 'Path info' (onto which the intermediate nodes piggyback their IDs), and Path Score parameters. These parameters include: 'Hop Count', 'Min Energy', 'Path Reliability', and 'Min Free Buffer Size'. The routing decision is made based on these parameters. As the routing decision is a function of these parameters, in the next section we will explain them and will formally define how to calculate the value of the Path Score. Fig. 1 shows the label format. target source ID

Path info

Path Score parameters

Fig. 1 Label fonnat

A. PATH SCORE DEFINITION AND CALCULATION As described earlier, Path Score is a key parameter to make a decision during routing. Path Score is formally defined as PathScore =axW L +pxW E +yxW Q +AXW H (1)

U, p, 'Y, and A are coefficients denoting the significance of each factor. All coefficients take their value in the interval [0,1]. Also, the sum of the coefficients must be equal to 1. If we set any of them to be zero, the corresponding component is no longer considered. So, SBRR can have variant configurations depending on application and one can choose a suitable configuration set to satisfy his/her specific requirements. Next, we will give a formal definition for each factor separately. 1. Each link of the path has an error rate indicator. In order to calculate this measure, we use a sliding window which gets the average success ratio on each link [3]. It is necessary to select a path which consists of links that have higher quality and lower bit error rate to increase the data transfer reliability. Therefore, among several paths arriving in one node, we are interested in the path 'Path Reliability' parameter is more than other paths. The factor W L is calculated by:

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WL = Path ReliabiliW= TI(l-LERi )

(2)

i=1

where, LERi is the error rate on the i-th link of the path. 'Hop Count' and 'Path Reliability' parameters denote the number of hops and reliability of the path navigated by a label. The initial values for these parameters are 0 and 1, respectively. As 'Path Reliability' decreases, the Score value will also decrease. The advantage of using this factor is to select a higher quality path which causes reduction of retransmissions, reduction of energy consumption and thereby prolongation of network lifetime. 2. In order to increase the network lifetime and to reduce the retransmissions due to the frequent path breakdowns, it is necessary to select a path which consists of the sensor nodes with more residual energy. Therefore, among several paths arriving in one node, we are interested in the path where 'Min Energy' parameter is more than other paths. The factor WE is calculated by: WE = Min Energy (3) Eo where, 'Min Energy' parameter denotes the mInImum residual node energy in the path nodes. The initial value for this parameter is initial energy (Eo). As this parameter deceases, the factor WE and the Score value will decrease. By providing a more stable transmission environment, SBRR can reduce packet loss due to the energy depletion of intermediate nodes. Consequently, route request packets will be reduced. Thus, more energy can be saved for relaying data packets, instead of being wasted on excessive path discoveries. 3. In order to balance the network traffic load and to prevent buffer overflow in intermediate nodes, it is crucial that the candidate path consists of the sensor nodes with less traffic load. Therefore, among several paths arriving in one node, we are interested in the path where 'Min Free Buffer Size' parameter is more than other paths. This parameter yields a path with minimum number of nodes joined to other paths. The factor W Q is calculated by: W = Min Free Buffer Size (4) Q

Bo

where, buffer size (B o) is identical for all nodes in the network and 'Min Free Buffer Size' parameter denotes the minimum free buffer size in the path nodes. The initial value for this parameter is Bo. As this parameter decreases, the factor W Q and the Score value will decrease as well. Other main advantages of using this factor are reduction of packet loss due to buffer overflow and reduction of the end to end packet transmission delay. 4. Among several paths arriving in one node, we are interested in the path for which the total hop count is less than other paths. It leads to employing the shortest path and reducing the end to end packet transmission delay. The factor W H is calculated by: W = (1 + Max Hop Count - Hop Count) (5) H

Max Hop Count

where, Max Hop Count is the network diameter. As 'Hop Count' parameter increases, the factor W H and the Score value will decrease. Another advantage of using this factor is to reduce the number of intermediate nodes and wireless links on the path, and consequently an improved reliability. Finally, all these factors are mixed and integrated into the notion of Path Score in SBRR protocol. Path Score takes a value in the interval [0,1] and a higher value indicates a better path. B. PATHDISCOVERYSTAGE

Unlike other routing protocols [6, 8] which attempt to find the main path and the backup path in two steps, our proposed protocol discovers them in a single path discovery stage. The process starts at the sink by broadcasting a route request packet (label) to its neighbors. We suppose that there are two Path Score levels and one Path info parameter in each intermediate node. Initially, the values of these Path Score levels are set to be zero. Also, Path info parameter is initially set to be Null. Whenever an intermediate sensor node receives a label through a path, it frrst checks its own available energy. If the residual energy is less than the operation energy (e.g. twice the packet transmission energy), it indicates that the node does not have enough energy to take more transmissions. Thus the node simply discards the received label. Therefore, SBRR provides an energy sufficient path instead. Thereafter, the node decides to transmit or discard the label according to shown algorithm in Fig. 2. These labels are flooded throughout the network until they reach the Source node. The target source waits a defmite time for the labels that have not yet been discarded in the network. This time is equal to label transmission delay on network diameter. Thereafter, the path discovery stage finishes. It should be noted that there may be many potential paths from sink to source. However, we are interested in two optimal paths towards the source. Target source selects two labels with maximum Path Score which have been received from two disjoint paths (the path with the highest score value is main path (optimal path) and the other with the second most score is chosen as the backup path). The reason for using two Path Score levels in each intermediate node is presented below. Using only one Path Score level could result in discarding the labels by the nodes in vicinity of the optimal path (see Fig. 3). Suppose that node '4' has only one Path Score level and it has received two labels from node '1' and node '2', respectively. In this case, the label received from node '2' will be discarded if the label received from node' l' has a greater Score value. It will result in that the path (Sink - 2 - 4 - ... - Source) cannot be selected as a backup path for the main path (Sink - 1- 3 -... - Source). C. PATHREsERVATIONSTAGE After the target source retrieves the route information from the received labels, two corresponding route reply messages will be generated. These massages will be unicast along the

retrieved paths towards the sink. Therefore, two completely disjoint paths will be established. The procedure of path reservation ends once the sink receives the route reply messages. 1: An intermediate node receives a label 2: If (residual energy < operation energy) 3:

discard the received label.

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Fig. 2 The routing decision algorithm in each intermediate node

•

Fig. 3 Using one Path Score level in each node can cause problem.

D. DATA TRANSMISSION STAGE

For every source node, two disjoint paths are established but only one of these paths is used for data delivery at any point in time. At first, all the data transmissions between this target source and the sink can be unicast on the main path until it is broken. In the event of a path failure, an error report will be generated and broadcast to both terminals of the broken main path. The old path will be removed from the route table of the sink and the source, and all the transmissions between that source and the sink (remaining and lost packets) will be switched to the completely disjoint backup path. Also, the sink will simultaneously start a new path discovery once it receives this error report packet. Once a new main path is

established, the traffic will be switched back to the new main path. This switching is seamless, because the source indicates the route for every packet at its generation time. We use ACK affirm mechanism to check whether a packet gets lost or not; thus we can judge the reliable transmission easier. III. PERFORMANCE ANALYSIS In this section, we evaluate the performance of our algorithm via simulation. We implemented a simulation framework using OMNeT++, an object-oriented discrete event network simulator [9]. The goal of the simulation is to show that SBRR can provide a high quality transmission environment in an error-prone network. The results are compared with three latest reliable routing protocols for WSNs named LQER [3], RM-IDLF [6] and REAR [8]. A. SIMULATION MODEL The same network setup is used to compare the four routing protocols. Table I summarizes the network characteristics. Each intermediate node is equipped with a total amount of energy ranging from 2J to 3J at the beginning of the simulation. Specifically, energy dissipation for transceiver E e1ec and amplifier Eamp are 50nJibit and 10pJlbit/m2 • Also, we assumed that the size of data packets is 10 times greater than the size of the label. We simulated the scenarios where a noisy wireless medium is compounded by node failure. We have divided up all the links into two categories: one with a normal error rate of 2%, and the other with a high value of 30%. The percentage of network links with high error rate varies over simulations (10-50%). A fault model is used in which each intermediate node in the network may fail with probability lE-5 at every second of simulation time. We used a traffic scenario, where four source nodes at the left side of the terrain send periodic data to the sink at the right side. Each source node generates data units according to a Poisson process with mean value 20 packets/s and a total of 5000 packets. The four coefficients (1, ~, y, and A are respectively set to be 0.5, 0.2, 0.1 and 0.2 for Path Score calculation. These values are chosen based on our several experiences run with different coefficient settings during the test. If a packet loss occurs for any reason during the transmission, it will be retransmitted until it is successfully delivered to the sink. TABLE I. NETWORK CHARACTERISTICS

Simulation Area (Terrain) Radio Range Number of Nodes Node Deployment Bandwidth Data Packet Size Buffer Size

600 X 800 meters 200 meters 60 nodes Uniform 200 kb/sec 50 Bytes 10 packets

B. PERFORMANCE METRICS AND SIMULATION RESULTS We use the following metrics to evaluate the performance of SBRR and compare the results with the traditional schemes. III.B.l

ENERGY EFFICIENCY

The average energy consumption of network nodes can provide a clear view of the network energy efficiency feature. The efficient energy consumption can lead to prolong the whole network lifetime that is one of the most important goals of a routing protocol. III.B.2

DELIVERY RATIO

The Delivery Ratio parameter represents the network ability for transporting an offered packet load. It is the ratio of the number of successfully received data packets at the sink to the total number of data packets sent by a source including retransmissions. This factor is one of the most important parameters ofQoS. Total Packets received (6) Delivery Ratio

=- - - - - - - - - Total Packets Sent By Source

The equation 6 shows that delivery ratio will increase by decreasing packet retransmissions. Inasmuch as delivery ratio strongly depends on the number of packet retransmissions, we have considered this parameter as an alternative factor for performance analysis. III.B.3

PACKET LATENCY

Packet latency is the average time that takes for a packet from its generation in the source until the sink successfully receives it. Thus, if a packet loss occurs, the source will retransmit the lost packet and this results in an increase in packet delivery latency.

c.

SIMULATION RESULTS

We ran the simulation with several parameters, including percentage of network links with high error rate and time. Simulation results are obtained from multiple runs and results are averaged over the runs (with a 90% confidence level and 10% confidence intervals). Fig. 4, Fig. 5, and Fig. 6 show the relation of the total energy consumption, number of retransmissions, and average packet latency with the percentage of network links with high error rate using the four routing protocols, respectively. From Fig. 4, we can find that as the percentage of network links with high error rate increases, number of retransmissions increases as well and therefore more energy wastes in the network. However, SBRR has better energy consumption and network lifetime. As it can be seen from Fig. 5, by increasing the percentage of network links with high error rate, number of retransmissions increases in all cases. SBRR, however, gives the minimum number of retransmissions. Fig. 6 shows the comparison of average packet latency under various percentages of network links with high error rates. However, our proposed scheme yields less average packet latency due to the selection of the high quality paths preventing excessive

retransmissions. Also with a fixed percentage of network links with high error rate (50%), total number of retransmissions vs. simulation time has been illustrated in Fig. 7. This figure compares the number of retransmissions in four schemes over the time. Simulation results reveal that the proposed algorithm can achieve a longer network lifetime, less packet latency, and higher delivery ratio than the other protocols. These improvements result mainly from selecting high quality paths which provide maximum energy level, minimum traffic, minimum hop count, links with minimum error rate and the fewest retransmissions. •

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In this paper, we focused on designing a general energyefficient, fault tolerant, and highly reliable routing protocol named SBRR. The routing decision is based on a heuristic parameter named "Path Score". We evaluated the performance of SBRR protocol through simulation under different scenarios. The performance of SBRR was compared with LQER, RM-IDLF, and REAR protocols by investigating the effects of error rates. We demonstrated that SBRR protocol exhibits a better performance when operating in a noisy wireless environment along with node failure. The algorithm could be modified to take into account some aspects that have not been addressed in this work, and that can be interesting subject of future research. For instance, studying a deadline-aware and reliable algorithm can be considered as a future work. V. REFERENCES

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