A Novel Multi-ACK Based Data Forwarding Scheme in Wireless Sensor Networks

Transcription

1 A Novel Multi-ACK Based Data Forwarding Scheme in Wireless Sensor Networks Dang Tu Nguyen 1, Wook Choi 2, Minh Thiep Ha 1, and Hyunseung Choo 1 1 School of Information and Communication Engineering, Sungkyunkwan Univ., S. Korea {dangtu,thiepha,choo}@skku.edu 2 Department of Computer Science and Engineering, Hankuk Univ. of Foreign Studies, S. Korea twchoi@hufs.ac.kr Abstract Data forwarding schemes that use a single ACKbased retransmission mechanism are widely used to increase the packet delivery ratio in wireless sensor networks. However, these schemes may waste a considerable amount of energy for data transmissions, especially when the link quality is low for ACK transmissions. In this paper, we propose a novel multi- ACK-based data forwarding scheme to minimize the energy consumption for unnecessary data retransmissions. The next hop forwarder selection significantly affects the energy efficiency of communications. Hence, we also develop a new next hop forwarder selection metric, called effective energy consumption (EEC), which makes the proposed data forwarding scheme suitable for geographic routing protocols. Mathematical analysis and simulation results demonstrate that the proposed multi-ack data forwarding scheme can save much energy and reduce the total amount of traffic load in the network. More specifically, the combination use of multi-ack data forwarding and EEC metric increases the energy efficiency by 47.8% when node density is low, and 75.0% when node density is high, compared to the geographic forwarding protocols which use a well-known metric, P RR Distance. I. INTRODUCTION Wireless sensor networks (WSN) are composed of a large number of sensor nodes and in general, they are deployed in inaccessible and hostile environments, e.g., dense jungles, battlefields, and inside phenomenon [1], [3], [4]. Sensor nodes in such networks operate under stringently-constrained resources including low-power energy, the replenishment of which may not often be feasible. This characteristic and other factors such as multipath routing, stochastic interference, data diffusion and scattering make the wireless link between sensor nodes irregular and unreliable [9], [11], [12]. Therefore, the design of communication stacks must take into account the radio layer reality. In order to cope with the wireless link unreliability in the network layer, several efforts have been made to define metrics that characterize the energy efficiency of communications [2], [10]. Communication over the unreliable links could be optimized based on those metrics. Moreover, the most common mechanism to increase the packet delivery ratio used in previous work is to retransmit data packets using the acknowledgment (ACK) message. Because of the asymmetric characteristic of unreliable links, the link quality for the ACK message transmission is sometimes low, while that of the data packet is relatively high. Therefore, there may be situations that the data packets actually arrive at the destination node but the ACK messages fail to arrive at the source node. This leads to unnecessary data retransmissions, thus eventually wasting a considerable amount of energy. In this paper, we propose a novel energy-efficient multi- ACK data forwarding scheme to minimize the unnecessary energy consumption as mentioned above. In the proposed scheme, when the destination node receives a data packet, it responds to the source node with a suitable number of ACK messages to ensure that the source node can successfully receive one. The next hop forwarder selection also significantly affects the energy efficiency of communications. Hence, we develop a new local metric per a unit distance, called effective energy consumption (EEC). This metric is based on a unit distance called expected progress (described in Section V) and reflects how much energy consumed to transmit the data packet towards the destination node and how successfully the data packet can be delivered by forwarding it to a selected neighbor. The key contributions of our work are threefold: Helping sensor nodes conserve a large amount of energy that is otherwise used for unnecessary data transmissions, by using multiple ACK messages. Significantly reducing the traffic load in the network, thereby minimizes the risk of traffic collisions among sensors and the routing overhead. Introducing a local optimal metric, EEC, for a next hop forwarder selection that is suitably used for geographic routing protocols in realistic environments. The combination use of multi-ack forwarding and EEC metric can considerably increase the energy efficiency. The remainder of this paper is organized as follows. In Section II, we discuss related work. Section III presents assumptions, notations, and system models while Section IV and V describe the proposed multi-ack data forwarding scheme and EEC metric, respectively. Section VI provides the performance evaluation results. Finally, we conclude the paper in Section VII. II. RELATED WORK Research on radio properties indicates that the wireless links between low power sensor devices are extremely unreliable [9], [11], [12]. Specifically, the authors in [11] provided a comprehensive analysis of the root causes of link unreliability

2 and asymmetry. In particular, they defined the packet reception rate as a function of distance. Zamalloa et al. studied the distance-hop trade-off for geographic routing in wireless sensor networks [10]. They showed that the product of the packet reception rate (PRR) and the distance to the destination (P RR Distance) is an optimal metric to select a next hop forwarder. In [2], the authors introduced the concept of expected transmission count metric (ETX) that finds high-throughput paths on multi-hop wireless networks. Previous work frequently used a data packet retransmission mechanism to increase the packet delivery ratio. In the retransmission mechanism, a node sends a data packet to a next hop forwarder and waits for an ACK message. If the next hop forwarder receives the data packet, it responds with an ACK message to the source node. After a timeout duration, if the source node does not receive the ACK message, it retransmits the same data packet. These steps are repeated until the source node receives an ACK message or the number of retransmissions exceeds the threshold. This leads to unnecessary data retransmissions, thus wasting energy. This motivates our work. A. Assumptions III. PRELIMINARIES In this paper, mathematical analysis and simulations are done based on the following assumptions: Wireless links between nodes are bidirectional and the link qualities of both directions are not equal. Nodes know their location, one-hop neighbor location, and the position of the final destination and also they know the link qualities of their neighbors, which are characterized by the packet reception rate (PRR). B. Notations d cur dst : Distance between the current node and the destination node. d nbr dst : Distance between the neighboring node and the destination node. P RR out : PRR of outgoing link for sending out a data packet. P RR in : PRR of incoming link for receiving an ACK message. ARQ: Maximum number of data retransmissions. K out : Number of data packet retransmissions up to the first success. K in : Number of ACK message retransmissions up to the first success. P ARQ : Probability of successfully sending a data packet after ARQ attempts. e data : Amount of energy consumed for transmitting a data packet. e ACK : Amount of energy consumed for transmitting an ACK message. e total : Total amount of energy consumed during one hop data transmission session. C. Link Layer Model We use a realistic link layer model introduced in [11], which is based on the log-normal path loss model [7]. When Manchester encoding and NCFSK modulation schemes are used, the PRR for a distance d between a transmitter and a receiver becomes a random variable that is given by: P RR(d) (1 1 2 exp 10 γ d ) ρ 8f where γ is the signal to noise ratio in db; ρ is the encoding ratio (ρ 2 for Manchester encoding); f is the frame length in bytes. D. Energy Consumption Model We consider only the energy consumption for data transmissions. More specifically, we do not consider other kinds of energy consumption, e.g., energy spent in state (active/idle/sleep) transitions. For a node in the transmitting/receiving state, the power consumption, P, can be obtained by: P I V where I denotes the current consumption; V is the supply voltage. Given P, the energy consumption, e, in one state can be obtained by: e P T where T is the time duration spent on that state. Simulations in this study use the power model used in the Mica2 hardware platform to measure the energy consumption. Table 1 shows the Mica2 power model [8]. E. Transmission Delay Model We use IEEE standard for the physical and medium access layers. Although Mica2 platform does not support IEEE , it can operate at the frequency of 915MHz. Hence, our wireless model is still valid for the Mica2 platform [5]. As in [6], the transmission delay each frame experiences is formulated as: delay(x) T BO + T frame (x) + T T A + T ACK + T IF S where T BO denotes the back off period in seconds; T frame (x) is the transmission time for a frame with a payload of x bytes; T T A denotes the turnaround time; T ACK is the transmission time for an ACK; T IF S is the IFS time as shown in Fig. 1. The duration of a frame is given by: T frame (x) 8 L P HY +L MAC HDR +L address +x+l MAC F T R R data TABLE I POWER MODEL FOR THE MICA2. THE MOTE WAS MEASURED WITH THE MICASB SENSOR BOARD AND A 3V POWER SUPPLY. Mode Current Mode Current Rx 7.0 ma Tx (-5 dbm) 7.1 ma Tx (-20 dbm) 3.7 ma Tx (0 dbm) 8.5 ma Tx (-19 dbm) 5.2 ma Tx (+4 dbm) 11.6 ma Tx (-15 dbm) 5.4 ma Tx (+8 dbm) 17.4 ma Tx (-8 dbm) 6.5 ma Tx (+10 dbm) 21.5 ma

3 Back Off Period Fig. 1. Frame ACK Turnaround Time 1 Frame Duration IFS Frame sequence in IEEE standard. where L P HY denotes the length of the PHY header in bytes (6 bytes); L MAC HDR is the length of the MAC header in bytes (3 bytes); L address is the length of the MAC address info field; L MAC F T R is the length of the MAC footer in bytes (2 bytes); and R data denotes the raw data rate. The duration of an ACK is calculated as follows: T ACK 8 L P HY + L MAC HDR + L MAC F T R R data A. Basic Idea IV. MULTI-ACK DATA FORWARDING The goal of our proposed multi-ack data forwarding scheme is to minimize the number of unnecessary data retransmissions and thus save energy. When the next hop forwarder receives a data packet, it replies to the source node with multiple ACK messages, so that the source node can successfully receive at least one ACK. Before retransmitting a data packet, the source node waits for a certain amount of time, called timeout, which is long enough for the next hop forwarder to reply with one ACK message successfully. To achieve the goal, there are two problems to be solved: i) how many ACK messages the next hop forwarder should reply with to the source node and ii) how long the source node should wait for the ACK messages. In the following, we probabilistically analyze the suitable values for the number of ACK messages and the timeout for waiting the multiple ACK. B. Preliminaries for Probabilistic Analysis We assume the value of K out as a random variable which follows Geometric random distribution, i.e., depending on the link quality between two sensor nodes, K out varies. Therefore, given a PRR, the probability that K out equals k is measured by: P [K out k] (1 P RR out ) k 1 P RR out Since we consider the maximum number of ARQ retransmissions, K out can range from 1 to ARQ. So, the probability, P ARQ, is derived as follows: P ARQ P [K out ARQ] ARQ k1 ARQ k1 (1 P RR out ) k 1 P RR out P [K out k] 1 (1 P RR out ) ARQ (1) For the random variable K out, we use the expected value of K out which is given by: E[K out ] kp [K out k] k0 k(1 P RR out ) k 1 P RR out k0 1 P RR out Similarly, the expected value of K in is given by: 1 E[K in ] P RR in C. Analysis of Energy Consumption 1) Traditional Data Forwarding: Probabilistically, for E[K out ] data retransmissions, one packet successfully arrives at the next hop forwarder. For each of successfully-transmitted packets, the next hop forwarder responds with one ACK message. Eventually, E[K in ] ACK messages should be sent to make sure that the source node can receive at least one message successfully. Given this probabilistic behavior, the total energy consumption is given by: e total E[K in ] (E[K out ] e data + e ACK ) 2) Multi-ACK Data Forwarding: Similarly to the case of the traditional data forwarding, for E[K in ] ACK messages sent by the next hop forwarder, one message successfully arrives at the source node. So, when the next hop forwarder receives a data packet, it replies to the source node with E[K in ] ACK messages. As a result, the total energy consumption can be measured as follows: e total E[K out ] e data + E[K in ] e ACK (2) Finally, the amount of energy savings from the use of the proposed multi-ack data forwarding scheme against the traditional data forwarding scheme is measured as follows: e save E[K out ] (E[K in ] 1) e data Using multiple ACK messages, nodes can save a lot of energy that is otherwise consumed for unnecessary data transmissions. However, on the downside, the source node has to wait for a longer timeout after sending one data packet, thereby increases the transmission delay. In the following, we analyze this trade-off between energy saving and transmission delay. D. Analysis of Transmission Delay We analyze the additional transmission delay resulted from the use of multiple ACK messages against the traditional forwarding. Fig. 2 illustrates the use of multiple ACK. First, we measure the expected one-hop transmission delay and timeout duration of the traditional data forwarding and multi-ack data forwarding, respectively.

4 Fig. 2. Back Off Period Frame ACK Turnaround Time 1 Frame Duration ACK Frame sequence in IEEE standard using multi-ack. 1) Traditional data forwarding: delay E[K out ] (T BO + T frame (x) + T T A +T ACK + T IF S ) T single ACK timeout 2) Multi-ACK data forwarding: T T A + T ACK + T IF S delay E[K out ] (T BO + T frame (x) + T T A +E[K in ] T ACK + T IF S ) T multi ACK timeout IFS T T A + E[K in ] T ACK + T IF S The expected additionally one-hop transmission delay of multi-ack forwarding against the traditional forwarding is given by: ExtraDelay E[K out ] (E[K in ] 1) T ACK for T multi ACK timeout > T single ACK timeout. V. DESCRIPTION OF EEC METRIC In order to effectively use the proposed multi-ack data forwarding scheme in existing geographic routing protocols, we introduce a novel local metric, effective energy consumption (EEC), per a unit expected progress for the next hop forwarder selection. Before deriving the EEC metric, we first define the average energy consumption per a unit expected progress as: e total AEC ExpectedP rogress e total d cur dst d nbr dst where e total is calculated by using equation (2); the ExpectedProgress is measured as shown in Fig. 3. This definition reflects how much energy is consumed to transmit a data packet one unit expected progress toward the destination node by forwarding it to a selected neighbor. Now, let us merge Current node S Fig Expected progress 3 D Destination node Expected progress measurement for EEC metric the average energy consumption per a unit expected progress with the probability, P ARQ, that the current node sends a data packet successfully after the maximum number of ARQ retransmissions. Recall that P ARQ 1 (1 P RR out ) ARQ (refer to Eq. (1)). Then, the EEC metric is derived as follows: EEC e total P ARQ (d cur dst d nbr dst ) e total (1 (1 P RR out ) ARQ ) (d cur dst d nbr dst ) A. Use of EEC Metric in Forwarding Process When a node has a packet to send to a destination, it calculates the EEC values of its one-hop neighbors that are closer to the destination node and selects a neighbor with the smallest EEC value as its forwarder. It then uses the multi- ACK data forwarding scheme to transmit the data packet to the selected forwarder. For example, as shown in Fig. 3, when the current node S wants to send a data packet to the destination node D, S calculates the EEC metrics of its one-hop neighbors (i.e., 1, 2, 3, 4, and 5 neighbors) using the above equation, selects node 2 with the smallest EEC value as its forwarder (Table 2. shows an example of such calculations), and finally uses the multi-ack scheme to transmit the data packet to it. TABLE II EXAMPLE FOR THE COMBINATION USE OF MULTI-ACK AND EEC. Neighbor Node P RR out P RR in Expected Progress EEC VI. PERFORMANCE EVALUATION Using multi-ack is motivated by the unnecessary data retransmissions due to the ACK failures of the single-ack based data forwarding scheme. This happens more frequently when the link quality for ACK transmission is low. We use the one-hop data forwarding to evaluate the performance of multi- ACK scheme, compared to the traditional approach. To have a better view on the performance of multi-ack and EEC, we use the multi-hop data forwarding in networks having a realistic link layer as in [10], [11]. A. Methodology We use the IEEE standard for the physical and medium access layers. The data packet size is 100 bytes and ACK message size is 11 bytes [6], [10]. The maximum number of data retransmissions is 10. In one-hop data forwarding, the value of P RR out is a random value between 0.01 and 1. The value of P RR in varies from 0.1 to 1 with 0.1 increment. For each value of the P RR in, 100 data packets are sent and the average results are obtained. In multi-hop data forwarding, we compare the combination use of multi-ack and EEC (multi-ack EEC) with that of

5 (a) The energy efficiency. (b) The delivery ratio. (c) The traffic load. (d) The transmission delay. Fig. 4. Evaluating multi-ack in one-hop data forwarding. (a) The energy efficiency. (b) The delivery ratio. (c) The traffic load. (d) The transmission delay. Fig. 5. Evaluating the combination of multi-ack and EEC in multi-hop data forwarding with varying network sizes. (a) The energy efficiency. (b) The delivery ratio. (c) The traffic load. (d) The transmission delay. Fig. 6. Evaluating the combination of multi-ack and EEC in multi-hop data forwarding with varying node densities. PRRxDistance and global ETX. For ETX, we use the Dijkstra algorithm to compute the shortest path from the source to the destination, where the weight of each link is equal to the reciprocal of P RR out P RR in. In this simulation, nodes are deployed uniformly at random [10], and for each pair of the nodes, we use the same link model as in [10] and [11] to generate the one-hop packet reception rate. We run 100 experiments in two different scenarios: i) varying densities in networks of 1000 nodes and ii) varying network sizes with a fixed density (50 neighbors/range). In each simulation run, 100 pairs of random sources and random destinations are chosen to send one data packet and the results are computed as the average of the 100 runs. 1) Evaluation Metrics: We use the following four metrics to evaluate the performance of schemes: Energy efficiency: Number of bits successfully delivered to the destination node for each unit of energy spent by the network in communication events. Packet delivery ratio: Percentage of packets sent by the source node that reach the destination node. Traffic load: Average amount of transmitted data per each successful communication. Transmission delay: Average transmission time per each successful communication. B. Energy Efficiency 1) One-hop data forwarding: As shown in Fig. 4(a), the energy efficiency of the multi-ack scheme is much greater than that of the traditional approach, especially when P RR in is low, since multi-ack can save much energy for unnecessary data retransmissions. 2) Multi-hop data forwarding: From Fig. 5(a), we can see that the energy efficiency of multi-ack EEC is about 1.5 times greater than that of PRRxDistance. For example, when the number of nodes is 600, the energy efficiencies of multi- ACK EEC, PRRxDistance, and ETX are 0.34, 0.23, and 0.43,

6 respectively. That is, multi-ack EEC can improve the energy efficiency of PRRxDistance 47.8% ( ). This advantage becomes much better when node density increases, as shown is Fig. 6(a). For example, when node density is 140, the energy efficiencies of multi-ack EEC, PRRxDistance, and ETX are 0.63, 0.36, and 0.71, respectively. This figure demonstrates that the performance of multi-ack EEC is 75% ( ) greater than that of PRRxDistance and equals 89% ( ) that of global ETX when node density is high. C. Packet Delivery Ratio 1) One-hop data forwarding: Fig. 4(b) shows the delivery ratio of the multi-ack scheme is the same as the value of the traditional approach, since the P RR out is the same for two schemes. 2) Multi-hop data forwarding: It can be seen in Fig. 5(b) the delivery ratio of multi-ack EEC and PRRxDistance are close together and decrease for larger networks, since paths become longer and the probability of path disconnections increases. In contrast, the value of global ETX is always close to 100%, because ETX is almost guaranteed to find a path to the destination, if one exists. The delivery ratio of multi-ack EEC and PRRxDistance are very low when node density is low, as shown in Fig. 6(b). D. Traffic Load 1) One-hop data forwarding: As shown in Fig. 4(c), the traffic load created by the multi-ack scheme is much smaller than that of the traditional approach, especially when P RR in is low. 2) Multi-hop data forwarding: From Fig. 5(c), we can see that the multi-ack EEC considerably reduce the traffic load compared to PRRxDistance. When node density is high, the traffic load created by multi-ack EEC becomes much smaller than that of PRRxDistance and close to the value of ETX, as shown in Fig. 6(c). E. Transmission Delay 1) One-hop data forwarding: Fig. 4(d) shows the transmission delay of the multi-ack scheme is much greater than that of the traditional approach, especially when P RR in is low, since node has to wait for a longer timeout after sending a data packet. 2) Multi-hop data forwarding: As shown in Fig. 5(d) and Fig. 6(d), the transmission delay of multi-ack EEC is slightly higher than that of PRRxDistance and ETX, since EEC can select good forwarders that have high value of P RR out and P RR in. When node density is very low, the transmission delay of ETX is much greater than that of multi-ack EEC and PRRxDistance, since ETX can deliver 56% of data packets while multi-ack EEC and PRRxDistance can only deliver 7% of data packets, as shown in Fig. 6(b). VII. CONCLUSION In this paper, we introduced a novel multi-ack-based data forwarding scheme with an ultimate goal of minimizing the unnecessary energy consumption while transmitting data over unreliable wireless links in wireless sensor networks. In order to effectively use the proposed multi-ack data forwarding scheme in geographic routing protocols, we also developed a novel local metric, called effective energy consumption (EEC), which reflects how much energy consumed to transmit the data packet towards the destination node and how successfully the data packet can be delivered by forwarding it to a selected neighbor. Mathematical analysis and simulation results demonstrated that our proposed scheme reduces the transmission energy and the traffic load by using multiple ACK messages, and thus increases the energy efficiency and the network lifetime. ACKNOWLEDGMENT This research was supported by MKE, Korea under ITRC NIPA (C ). Dr. Choo is the corresponding author. REFERENCES [1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, vol. 40, pp , [2] D. Couto, D. Aguayo, D. Bicket J. and Morris R., A high-throughput Path Metric for Multi-hop Wireless Routing, Wireless Network 11, 4, , [3] C. Gui and P. Mohapatra, Power conservation and quality of surveillance in target tracking sensor networks, Proc. MobiCom 04, pp , [4] M. T. Ha, T. D. Le, and H. Choo, Employing a Novel Two Tiered Network Structure to Extend the Lifetime of WSNs, Proc. WCNC, pp. 1 6, [5] M. Harthikote-Matha, T. Banka, and A. P. Jayasumana, Performance Degradation of IEEE Slotted CSMA/CA due to Hidden Nodes, Proc. IEEE LCN 07, pp , [6] B. Latr, P. D. Mil, I. Moerman, B. Dhoedt, and P. Demeester, Throughput and Delay Analysis of Unslotted IEEE , Journal of Networks, Vol. 1, No. 1, May [7] T. Rappaport, Wireless Communications, Prentice Hall, PTR Upper Saddle River, NJ, [8] V. Shnayder, M. Hempstead, B. Chen, G. W. Allen, and M. Welsh, Simulating the Power Consumption of Large-Scale Sensor Network Applications, Proc. SenSys 04, pp , [9] A. Woo et al., Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks, Proc. SenSys, pp , [10] M. Z. Zamalloa, K. Seada, B. Krishnamchari, and A. Helmy, Efficient Geographic Routing over Lossy Links in Wireless Sensor Networks, ACM Transactions on Sensor Networks, [11] M. Z. Zamalloa and B. Krishnamachari, An Analysis of Unreliability and Asymmetry in Low-Power Wireless Links, ACM Transactions on Sensor Networks, [12] J. Zhao and R. Govindan, Understanding packet delivery performance in dense wireless sensor networks, Proc. Sensys, pp. 1 13, 2003.