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Cross-Layer Optimized MAC to Support Multihop QoS Routing for Wireless Sensor Networks Heping Wang, Xiaobo Zhang, Farid Naït-Abdesselam, Member, IEEE, and Ashfaq Khokhar, Fellow, IEEE
Abstract—This paper presents an efficient hybrid mediumaccess control (HMAC) protocol with an embedded cross-layer optimization solution to provide routing-layer coarse-grained endto-end quality-of-service (QoS) support for latency-sensitive traffic flows. A novel channel-reservation technique is proposed to significantly reduce the end-to-end delay for delay-sensitive traffic flows by allowing packets to go through multiple hops within a single medium-access control (MAC) frame and by also giving them higher priority channel access to reduce possible queuing delay. Our proposed protocol (HMAC) combines energy-efficient features of the existing contention-based and time-division multipleaccess (TDMA)-based MAC protocols and adopts a short frame structure to expedite packet delivery. Simulation results in ns-2 show that HMAC achieves significant performance improvements in energy consumption, latency, and throughput over existing MAC protocols. Index Terms—End-to-end latency, energy efficiency, hybrid medium-access control (HMAC), latency-sensitive traffic, quality of service (QoS).
I. I NTRODUCTION
N
ETWORKING low-cost smart sensors through a wireless medium to form wireless sensor networks (WSNs) has broad applications, such as surveillance, event detection, etc. However, due to battery-constrained computationally and communication-wise less powerful nodes in WSNs, traditional protocols are not suitable for WSNs in terms of energy efficiency, scalability, and design complexity. Current research efforts for WSNs mainly focus on exploring energy-efficient network operations in WSNs. At the network layer, a multihop routing paradigm based on short-range communication is popularly adopted by existing network layer protocols to improve energy efficiency [20]. However, multihop routing in wireless environments incurs increased end-to-end delivery latency and exacerbates potential hidden/exposed terminal problems [16].
Manuscript received January 26, 2009; revised May 27, 2009 and September 23, 2009; accepted November 9, 2009. Date of publication February 17, 2010; date of current version June 16, 2010. This work was supported in part by the U.S. National Science Foundation under Grant CNS0910988. The review of this paper was coordinated by Prof. H. Hassanein. H. Wang is with Lemko Corporation, Schaumburg, IL 60173 USA (e-mail:
[email protected]). X. Zhang is with CISCO Systems, San Jose, CA 95134 USA (e-mail:
[email protected]). F. Naït-Abdesselam is with the University of Sciences and Technologies of Lille, 59655 Villeneuve d’Ascq, France (e-mail:
[email protected]). A. Khokhar is with the Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL 60607 USA (e-mail:
[email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TVT.2010.2042185
Existing medium access control (MAC) layer solutions [1]– [6] for WSNs generally aim at reducing energy waste due to channel idle listening and overhearing. In most of these solutions, per-hop latency is compromised in favor of energy efficiency, thus deteriorating end-to-end communication delay. Without considering the performance requirements at upper layers, an energy-efficient MAC solution for WSN may not be optimal from the holistic networking and applications perspective, where end-to-end latency is sometimes an important consideration [7]. In this paper, we present a new MAC protocol, which is referred to as hybrid MAC (HMAC), which is suitable for WSNs in terms of energy efficiency, latency, and design complexity. HMAC combines channel-allocation schemes from existing contention-based and time-division multiple-access (TDMA)based MAC protocols to allow the realization of tradeoffs between different performance metrics. It uses a short slotted frame structure and a novel wakeup scheme to achieve highenergy performance, low delivery latency, and improved channel utilization. Compared with existing TDMA-based MAC protocols [5], [6], HMAC is simple and scalable since each node does not have to maintain neighborhood information. In addition, HMAC provides routing layer coarse-grained quality-of-service (QoS) support at the MAC layer. To the best of our knowledge, very few existing MAC layer works handle such QoS issues in WSNs. Quality of service-aware medium access control [17] assigns each flow a channel-access priority to reduce the queuing delay for high-priority flows, but it still suffers from a long end-to-end delay. The MAC protocols presented in [12]–[15] reduce the end-to-end delivery latency while increasing control overhead without considering different performance demands between flows. The HMAC design presents an extremely low-cost solution compared with the designs proposed in [12]–[15]. Our simulation results on ns-2 [9] show that HMAC outperforms sensor-MAC (S-MAC) and routing-enhanced MAC (RMAC) in terms of per-hop latency and delivery ratio while still maintaining superior energy performance. II. R ELATED W ORK Different WSN applications have their own performance demands for the underlying MAC protocols. A significant body of the existing research in WSNs have mainly explored energyefficient MAC techniques, such as channel duty cycling [1], [2], low power listening [4], and distributed TDMA-based MAC solutions [5], [6].
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WANG et al.: CROSS-LAYER OPTIMIZED MAC TO SUPPORT MULTIHOP QOS ROUTING FOR WIRELESS SENSOR NETWORKS
A. Contention-Based MAC Protocols Contention-based MAC protocols [1]–[3] basically access the radio channel based on a duty cycling scheme (also called periodical listen and sleep) to reduce the energy waste in idle listening in low traffic networks. S-MAC [2] introduces adaptive listening into its original design [1] to cut its end-to-end latency by half. Timeout-MAC (T-MAC) [3] extends S-MAC by adapting the channel duty cycle based on the traffic load to improve the MAC performance. T-MAC also proposed a technique to partially reduce the early sleep-problem in S-MAC. To further solve the sleep-delay issue in S-MAC and T-MAC, data gathering MAC [12] and the work in [14] have proposed pipelined forwarding to reduce the end-to-end latency. RMAC [13] is the most recent work based on S-MAC and optimizes the end-to-end delay. RMAC extends the listen period in S-MAC so that multiple Pioneer frame packets can be accommodated to reserve the channel and set up the corresponding data transmission schedules in the sleep period within a single MAC frame time. Different from S-MAC, Berkeley MAC (B-MAC) [4] is an asynchronous contention-based MAC protocol based on preamble sampling. Senders put a preamble in front of each outgoing packet; a nonsender node periodically wakes up for a short duration to detect such a preamble for possible packet transmission. Both the energy efficiency and the latency performance of B-MAC depend on the preamble length. B. Contention-Free MAC Protocols In contention-free MAC protocols [5], [6], nodes maintain TDMA-based contention-free schedules for channel access. These MAC protocols are naturally energy efficient since each node is only active within a dedicated portion of time for contention-free channel access. TRAMA [5] is a trafficadaptive TDMA-based MAC protocol. Each node must collect consistent two-hop neighbor information to determine contention-free schedules. TRAMA exhibits higher energy efficiency and channel utilization than S-MAC. In TDMA-W [6], each node is assigned two slots: 1) a wake-up slot and 2) a unique send slot within its two-hop neighborhood. A wakeup mechanism is proposed to reduce the energy waste due to idle listening. TDMA-W is highly energy efficient and guarantees deterministic upper bounded end-to-end delays. TDMA-based MAC solutions are suitable for high-traffic conditions under which all nodes share a similar traffic pattern. However, they will incur high design complexity to maintain a contention-free schedule, long latency in a large-scale network, and low channel utilization in low-traffic situations. C. Hybrid MAC Protocols Hybrid MAC protocols [8], [15] combine different mediumaccess techniques to improve network performance. Zebra MAC (Z-MAC) [8] is built on B-MAC [4] and aims to improve channel utilization and latency under different network situations to overcome the shortcomings of both carrier sense multiple access (CSMA) and TDMA schemes. Based on the traffic load in the network, Z-MAC can act as CSMA in a low-traffic situation or like TDMA in a high-traffic situation.
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Funneling-MAC [15] specifically handles the funnel effect issue in areas with more intensive traffic load and eliminates collisions that frequently happen in such areas. FunnelingMAC adopts a TDMA scheduling on nodes in the trafficintensive region while allowing nodes far away from the sink to compete channel access in a CSMA fashion. Similar to TDMAbased MAC protocols, Hybrid MAC solutions incur high design complexity. In conclusion, existing body of research work on MAC protocols for WSNs is generally focused on energy-efficient designs at the cost of compromising other network performance metrics, such as delivery latency. Contention-based solutions [1]–[3] have lower design complexity and are preferred for light-traffic applications compared with TDMA-based solutions [5], [6] and hybrid designs [8], [15]. Some optimization techniques have been introduced to improve the latency performance of existing MAC protocols [12]–[14], but these techniques have introduced significant control overhead. Furthermore, providing QoS support at the MAC layer for multihop routings has also been neglected in most of the existing works. III. H YBRID M EDIUM -ACCESS C ONTROL P ROTOCOL D ESIGN The fact that sensor networks generally exhibit low traffic loads most of the time motivates us to develop an HMAC protocol that exploits the energy-efficient characteristics of lowduty-cycled contention-based protocols and efficient channelutilization characteristics of TDMA-based protocols. HMAC introduces the concept of a short slotted frame structure in which slots are dynamically shared. A slotted frame structure helps to improve energy efficiency; a short frame length can intuitively decrease the queuing delays of packets and thus reduce the latency and collision when the traffic load increases. Another motivation comes from the observation that there may exist some flows that have lower end-to-end delay requirement than others in some WSN applications. Providing end-to-end QoS support in an energy-efficient way at the MAC layer is desirable in such applications. A. Assumptions We assume that the nodes are randomly distributed over a given area, and each node has a unique identifier. Each node uses a short-range radio to communicate with neighbors to save energy. Thus, nodes separated by long distances induce a multihop network. In HMAC, the slotted frame structure requires time synchronization within each node’s two-hop neighborhood. We can provide some guard time at both ends of each slot to deal with the short-term CPU clock drift. The provided guard time, together with the existing synchronization mechanisms [10], [18] or a cheap GPS-based solution, can meet the synchronization requirement in HMAC. We can also adopt the lightweight and energy-efficient time synchronization technique in [19] or the global schedule algorithm in [14] to synchronize nodes in HMAC by using the first wakeup slot in each HMAC frame to exchange SYNC messages between nodes. In this paper, we assume that the nodes in HMAC are synchronized.
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Fig. 1. HMAC frame structure: wake-up and data slots.
B. Details of Implementation Time is organized into nonoverlapping frames, and each frame contains multiple very short wakeup slots (W_SLOT) and multiple data slots (D_SLOT), as shown in Fig. 1. The number of W_SLOTs can be set according to the density of the network, and the number of D_SLOTs can be set based on the potential traffic load in the network and end-to-end delay requirements. Each W_SLOT contains a carrier sensing (CS) and wakeup message (WAKEUP) period, and each D_SLOT includes CS and periods for RTS/CTS/DATA/ACK messages. The reason why we provide the CS periods at the beginning of both wakeup slots and data slots is that possible concurrent transmissions could be initiated by multiple senders within a neighborhood. Under such a scenario, channel access conflicts can happen during both receivers’ wakeup stage and datatransmission stage when some receivers share the same wakeup slot or some senders happen to choose the same data slot. To reduce such channel access conflicts, all senders should perform CS to check the channel availability after backing off by some duration. The backoff time is randomly distributed within a predetermined contention window. In Section III-C, we further discuss how to provide QoS support at the MAC layer by properly dividing the CS period of each data slot into two sections, which provide two classes of channel-access priorities for two different types of traffic flows. Each node has its own wakeup slot to listen to the channel for the possible incoming “WAKEUP” message. It sleeps in all the other wakeup slots. Since WSNs generally have light traffic most of the time, we do not assign each node a data slot a priori. Whenever a node has data to transmit, it just randomly picks up a data slot and notifies the receiver(s) of the corresponding slot number in the receiver’s wakeup slot via a “WAKEUP” message. The receiver only wakes up in the corresponding data slot to receive data. One exception is that when a node receives more than one “WAKEUP” message during its wakeup slot (we call it wakeup collision), the receiver wakes up in all the data slots for possible data transmission because the receiver cannot determine the data slot the sender will use or how many senders will send data. This will mostly likely happen in bottleneck areas. The well-known RTS/CTS mechanism is used to reserve channel and avoid the hidden terminal problem if more than one sender exists within a receiver’s one-hop neighborhood and all of them happen to choose the same D_SLOT. Before initiating an RTS message, each sender needs to perform carrier sense to avoid potential collision of channel contention with other senders. The RTS/CTS/DATA/ACK message sequence is followed only for unicast data packet. For a broadcast packet, once a clear channel is determined during CS period at the beginning of a D_SLOT, a sender sends out its packet immediately. Each node simply determines its W_SLOT number (i.e., the position index of the W_SLOT within an HMAC frame)
as n mod M , where n is the node identifier, and M is the total number of W_SLOTs in a MAC frame. This way, each node does not need to collect the W_SLOT information of its one-hop neighbors and, hence, reduces the corresponding communication overhead, which can be very high in a dense or dynamic network. The regular unicast data exchange between nodes can be performed as follows: 1) Each node turns on its radio during its own wakeup slot and sleeps during all the other wakeup slots. 2) Each sender randomly picks up a data slot and announces the data slot number along with the receiver’s node identifier via a “WAKEUP” message in the receiver’s wakeup slot. 3) Upon reception of a “WAKEUP” message, a node checks the embedded node identifier in the “WAKEUP” message. If it is the intended receiver, then the node turns on its radio for the incoming data packet in the specified data slot; otherwise, it just sleeps. If a broadcast address is included in the “WAKEUP” message, then all nodes receiving this message should wake up in the specified data slot simultaneously. 4) If any collision occurs in a node’s wakeup slot, then the node turns on its radio for a duration long enough to receive an RTS packet at the beginning of each data slot for a possible incoming data packet. If the node learns that it is the intended receiver from the received RTS message, then it keeps the radio on to receive the data packet; otherwise, it returns to sleep in the remaining period of the data slot. This way, a node can minimize the extra energy cost under such a situation. 5) In each data slot, unicast data transmission must follow the well-known RTS/CTS/DATA/ACK scheme in IEEE802.11 [11] to avoid the “hidden terminal problem,” since two senders may choose the same data slot to send data to their receivers at the same time, and the transmissions happen to be in a common interference range. HMAC also provides support for one-hop broadcast operation. When a node has data to broadcast, it sends out a “WAKEUP” message containing a broadcast address and a data slot in each wakeup slot. After receiving such “WAKEUP” messages, all neighbors will wake up in the same data slot to receive the broadcast message. In addition, different from unicast operation, when the sender finds an idle channel during the CS period in the chosen data slot, it will immediately send out the broadcast message without following the aforementioned RTS/CTS/DATA/ACK scheme. C. QoS Support at MAC Layer As previously mentioned, there may exist traffic flows with different performance requirements in some sensor applications. Some of them are more latency sensitive (referred to as TYPE I flows in this paper) than others (referred to as TYPE II flows in this paper). Through cross-layer optimization, a MAC layer design can provide coarse-grained QoS support to routing layer by minimizing the end-to-end latency for TYPE I
WANG et al.: CROSS-LAYER OPTIMIZED MAC TO SUPPORT MULTIHOP QOS ROUTING FOR WIRELESS SENSOR NETWORKS
Fig. 2.
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Channel reservation mechanism across multiple hops. Fig. 3. Prioritized channel access.
flows at the MAC layer. In this section, we propose a channel reservation scheme combined with a prioritized channel-access technique to support “expedited” transmission of TYPE I flows. In the following, N represents the total number of data slots within an HMAC frame. 1) Channel Reservation: Let us start with an example to see how our channel reservation scheme works. Considering a TYPE I flow path shown in Fig. 2, node S is the source, and node D is the destination. Within a specific HMAC frame, for any data packet p, if we can deliver it from source S to destination D in a pipelined fashion as follows: S sends p to A in D_SLOT 1, A forwards p to B in D_SLOT 2, and then B sends p to node D in D_SLOT 3; then, the event packet p can be delivered from S to D within a single HMAC frame. However, without channel reservation, HMAC will take three frames’ time to deliver p. The channel reservation is performed on a per-flow basis between any source–destination pair. To support flow-based channel reservation, the source node either issues a special reservation request before sending its time-critical packets or piggybacks the reservation request in its first event packet. This can easily be done at the upper layer in the source node by setting a special bit (we refer to it as REV-bit) in each outgoing packet, which indicates whether the subsequent packets from the specific sources should be transmitted in a “expedited” or “regular” way. By “regular” way, we mean that each packet will be delivered only one hop closer to the destination within each HMAC frame. The REV-bit helps to reserve the wireless channel along paths for any duration needed by the “expedited” flows. During the transmission of the first packet with a REV-bit set to “1,” the channel is reserved along the path from the source toward the destination as follows: If a node receives a packet with a set REV-bit in the ith D_SLOT, then it will reserve the ((i + 1) mod N )th D_SLOT and forward the subsequent data packets from the same source node to its next hop in the ((i + 1) mod N )th D_SLOT, provided the receiving node itself is not the destination. This process continues until the packets arrive at the destination. Therefore, for each “expedited” flow, all related intermediate nodes locally reserve two adjacent D_SLOTs during the transmission of “fast” flows: one for receiving data (we call it R_D_SLOT) from its previous hop and the other for sending data (we call it S_D_SLOT) to its immediate next hop. The reserved channel will be released when a node receives a packet with a clear REV-bit or a predetermined timer expires, and then, all related nodes release the reserved slots. During the reservation period, for each packet belonging to a particular TYPE I traffic flow, receivers at each hop will not be woken up by WAKEUP messages issued by their previous hop for the same flow; each participating node will listen to the channel in its reserved receiving data slot (R_D_SLOT) for a duration approximately equal to the lengths of CS and RTS periods; if no RTS is received, then the node will sleep in the
remaining time of R_D_SLOT and S_D_SLOT, provided it is not woken up for data transmission by any other node. For a TYPE II packet with a REV-bit set to “0,” nodes forward the packet at each hop using the “regular” HMAC channel-reservation procedure described in Section III-B. 2) Prioritized Channel Access: To give TYPE I flows higher channel access priority over TYPE II flows, the random backoff time for each type of flows is differently determined during the CS period at the beginning of each D_SLOT. We divide the CS period into two periods: 1) TI and 2) TII . TYPE I flows compete channel access only within the period TI , whereas TYPE II flows compete channel access only within the period TII (refer to Fig. 3). This way, TYPE I flows can be assigned higher priority for channel access. If a node finds a free channel within a reserved D_SLOT during TI and it happens to have data to send, then it can compete with other potential senders for reusing this D_SLOT for TYPE II flows; otherwise, this D_SLOT is occupied by TYPE I flows. IV. AVERAGE E ND - TO -E ND L ATENCY A NALYSIS In this section, we analyze the average per-hop latency and multihop end-to-end latency of HMAC for different traffic flows. We first consider the scenario without channel reservation, which is for TYPE II flows or the reservation packets for the TYPE I flows. To simplify the analysis of the average delivery delay a message may experience at each hop, we assume that no collision occurs. We also assume that the traffic load of the network is light, and there is no buffering of packets at the intermediate nodes. For the purpose of analysis, we define the following notations: N number of data slots in an HMAC frame; M number of wakeup slots in an HMAC frame; i index of data slot in which the sender chooses to send data packet; j index of wakeup slot of the receiver (next hop); t event/packet arrival instance in an HMAC frame; length of an HMAC frame; Tf length of a data slot; Td length of a wakeup slot; Tw p(x) probability density function (pdf) of random variable x; E[x] expectation of random variable x. Therefore, we have relations 0 ≤ i ≤ N − 1, 0 ≤ j ≤ M − 1, 0 ≤ t ≤ Tf , and Tw = (Tf − N ∗ Td )/M (see Fig. 4). We also define tws = j ∗ Tw . We assume uniform distributions for random variables i, j, and t, and the corresponding pdf’s are 1/N , 1/M , 1/Tf , respectively. Case 1) If t < tws , or the packet arrives at the sender before the left end of the wakeup slot j of the next-hop node, then it is obvious that the sender can send the
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Fig. 4. Average delivery latency analysis.
packet to the receiver in the current frame; therefore, after the sender chooses a data slot i, the packet can be delivered in the current frame (not including time for CS/RTS/CTS) with the following delay: ti,j delay = (Tf − N Td − t) + iTd .
(1)
Case 2) If t > tws , or the packet arrives at a sender node after the right end of the wakeup slot j of the nexthop node (in fact the time in wakeup slot j when the sender could not wake up the receiver), then the sender will have to send the packet in the next frame; therefore, after a sender chooses a data slot i, the packet can be delivered in the following frame with the following delay: ti,j delay = (Tf − N Td + iTd ) + (Tf − t).
(2)
Combining the foregoing two cases for the given slots i and j, the delivery latency of a packet can be calculated as follows: ti,j delay
tws = [(Tf − N Td − t) + iTd ] p(t)dt 0
Tf +
[(Tf − N Td + iTd ) + (Tf − t)] p(t)dt
tws
= 1.5Tf − N Td + iTd − jTw .
(3)
Since i and j are randomly selected, the average delivery delay of a packet can finally be determined as i,j ti,j = E t delay delay = 1.5Tf − N Td + E[i]Td − E[j]Tw N −1 M −1 Td − Tw = 1.5Tf − N Td + 2 2 = Tf − 0.5Td + 0.5Tw .
t1q =
M ∗ Tw . 2
(6)
However, if the packet is generated after the reserved data slot of S, then the average waiting time is t2q = M ∗ Tw +
N ∗ Td . 2
(7)
If we assume a uniform distribution for the random variable t, then combining (6) and (7), we have the expectation for tq as tq = t1q
M ∗ Tw N ∗ Td Tf . + t2q = Tf Tf 2
(8)
2) Propagation time tp a packet travels from source node S to destination node D: We also assume that source node S reserves the first data slot for its TYPE I packets each time; therefore, it will take at most n/N full HMAC frames and n mod N data slot time for a TYPE I packet to travel from node S to node D. The propagation time tp is n tp = (n mod M ) ∗ Td + N ∗ Td ∗ N n−1 + M ∗ Tw ∗ . (9) N Therefore, under channel reservation, the average end-to-end latency for TYPE I packet flows can approximately be determined as
(4)
Note that (4) only formulates the average per hop latency that a packet experiences. Therefore, for an n-hop path between a pair of source S and destination D, the average end-to-end latency can be determined as Dn (S, D) = n ∗ ti,j delay = n(Tf − 0.5Td + 0.5Tw ).
fashion. It is obvious that a packet can be N hops closer toward the destination within a single HMAC frame, where N is the number of data slots in an HMAC frame. The average end-toend latency can simply be divided into two parts: 1) Waiting delay or queuing delay tq at the source node S: At source S, a TYPE I data packet may be generated at any instance t within an HMAC frame and can only be delivered to the next hop in the reserved data slot of S determined by the channel-reservation operation. Therefore, some queuing delay will be incurred on each data packet at source S. If t is before the left end of the reserved data slot of S, and we further assume it to be the first data slot, then the average waiting delay is
(5)
Based on the foregoing notations, we now determine the average end-to-end latency for TYPE I traffic flows. For any n-hop TYPE I flow between a specific pair of source S and destination D, flow packets will be delivered in the reserved slots of all nodes along the path from S to D in a pipelined
Dn (S, D)−R = tp + tq
n = (n mod M ) ∗ Td + N ∗ Td ∗ N n−1 Tf . (10) + M ∗ Tw ∗ + N 2
V. P ERFORMANCE E VALUATION We have implemented HMAC in ns-2 network simulator with Carnegie Mellon University’s wireless model extension. In our simulations, each node is assumed to have one omnidirectional antenna and uses two ray ground reflection radio propagation models. The transmission and sensing ranges are set to 250 and 550 m, respectively.
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TABLE I M AJOR I MPLEMENTATION PARAMETERS
Fig. 6. Multiple-hop cross topology.
Fig. 5.
Multiple-hop chain topology.
We mainly choose the following three metrics to investigate the performance of HMAC and compare it with S-MAC [1] and RMAC [13]: 1) average energy consumption: total energy consumed during the simulation divided by the total number of nodes in the network; 2) average end-to-end delay: time difference between the arrival times of a packet at each pair of source and destination averaged over all packets successfully received by destinations; 3) delivery ratio: total number of packets successfully arrived at receivers divided by the total number of packets sent by all sources In our experiments, the data packet length is fixed as 50 B for all three MAC protocols under evaluation. The average power consumption in transmission, receiving, idle listening, and sleeping states are modeled as 1.83 : 1 : 1 : 0.001. The other key simulation parameters are summarized in Table I. In our simulation, we assume that each data packet is forwarded along the shortest paths toward the destination. In the following sections, we describe the network topologies used in our simulations and present the corresponding results.
Fig. 7. Energy consumption in a ten-hop chain topology.
Fig. 8. Energy consumption in a ten-hop cross topology.
A. Simulation Topologies In our simulation, we use two types of popular topologies adopted in both S-MAC [1], [2] and RMAC [13] to study the performance: 1) multihop chain network (see Fig. 5) and 2) a multihop cross network (see Fig. 6). B. Energy Consumption Comparison Each source generates constant bitrate (CBR) traffic flows to its corresponding destination. The traffic arrival interval λ of CBR flows is varied from 5 to 50 s with 5-s steps. From Figs. 7–9, we can see that HMAC outperforms S-MAC and RMAC in terms of energy consumption, since HMAC is scheduling based and uses a novel wake up scheme. Note that the energy consumed in the synchronization operation in HMAC is included in the results reported here. Figs. 7 and 8 show that the nodes in HMAC consume less energy than both S-MAC and RMAC on average. While Fig. 9 demonstrates
Fig. 9. Standard deviation of energy consumption in a ten-hop cross topology.
that the nodes’ remaining energies in HMAC are more evenly distributed than in both S-MAC and RMAC, and hence, HMAC will have a longer lifetime on average. In Figs. 7 and 8, we should mention that the nodes in S-MAC consume less energy in the scenario of λ = 5 than that of λ = 10. This is because more packets get dropped at nodes due to collision under the increased traffic loads, and we assume that the MAC layer does not cache more than one packet. C. End-to-End Latency Comparison We vary the length of paths between each pair of source and destination nodes. The experimental results are shown in Figs. 10 and 11 for the two network topologies used in our
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Fig. 10. End-to-end latency in a ten-hop chain topology.
Fig. 12. HMAC latency. Simulation versus analytical results in a ten-hop cross topology.
Fig. 11. End-to-end latency in a ten-hop cross topology.
experiments. To evaluate how the MAC layer can enhance coarse-grained QoS support for a particular class of traffic, first, only TYPE I flows are considered and generated in source nodes. The simulation results demonstrate that for TYPE I flows, HMAC outperforms both RMAC and S-MAC. This is partly due to the fact that HMAC adopts a shorter frame structure; at each hop, packets can be transmitted and forwarded faster in HMAC than in S-MAC and RMAC. In addition, our proposed channel reservation scheme significantly reduces the end-to-end delivery latency for TYPE I flows. In the mean time, HMAC allows multiple data transmission within a single MAC frame duration, which can further expedite the data delivery when more than one sender exists in a small area. This can be justified from the point view of queuing theory, since a short frame length means a short service time, which reduces collision and queuing delay. Next, we discuss the latency performance of HMAC when different classes of traffic flows coexist in the network and validate our performance analysis conducted in Section IV. To do this, we only use cross topology and perform the experiment as follows: We let one source generate TYPE I flows and the other source generate TYPE II flows. Similar to the experiments reported for RMAC [13], we force the two sources to simultaneously generate their CBR traffic to intentionally create channel congestion in the intersection area of the two chains. The experiment and analysis results are shown in Fig. 12. From the figure, we can see that under channel reservation, TYPE I flows have significantly lower end-to-end latency than TYPE II flows. This is due to two reasons: 1) HMAC provides higher priority channel access to TYPE I flows over TYPE II flows, and 2) the proposed channel-reservation scheme at the MAC layer allows TYPE I flows to travel across multiple hops within a MAC frame. The figure also shows that our analysis results match well with the simulation results. D. Delivery Ratio Comparison Next, we evaluate the performance in terms of delivery ratio. Figs. 13 and 14 show the delivery ratio under different traffic
Fig. 13.
Delivery ratio in a ten-hop chain topology.
Fig. 14.
Delivery ratio in a ten-hop cross topology.
loads in chain and cross topologies, respectively. We change the CBR traffic rate from 1 packet/s to 1 packet/40 s to evaluate the performance of these three MAC protocols. For HMAC, we only test TYPE I traffic flows in both topologies. Different from the previous tests, to increase the delivery ratio of S-MAC and RMAC, we adopt a 10% duty cycle for both protocols instead of the 5% listed in Table I. In our simulation, we assume that the MAC layer does not cache more than one packet. If a new packet arrives at the MAC layer for delivery, then the old packet will be dropped if it is still not delivered. Same as in RMAC, we intentionally let the two sources generate CBR traffic flows at exactly same time to create the packet-collision situation at the middle node in cross topology. Both Figs. 13 and 14 demonstrate that the HMAC network provides higher delivery ratio than S-MAC and RMAC when the network experiences high traffic load. This is quite reasonable because HMAC has a short frame size, which helps nodes to quickly move packets to their next hops and, hence, significantly reduces the packet drop rate due to buffer overflow or channel contention. This fast packet delivery is particularly important when the network experiences heavy traffic load. For example, when an event is detected within an area, the nodes in this area may simultaneously report the event’s data, which potentially creates much more traffic. Fig 14 shows that HMAC significantly reduces packet collisions under heavy traffic load.
WANG et al.: CROSS-LAYER OPTIMIZED MAC TO SUPPORT MULTIHOP QOS ROUTING FOR WIRELESS SENSOR NETWORKS
VI. C ONCLUSION Providing coarse-grained end-to-end QoS support for multihop routing in WSNs is important for several delay-sensitive applications. This paper has investigated QoS-based routing at the MAC layer. It presents a cross-layer optimized MAC protocol referred to as HMAC, which is particularly suitable for WSNs in terms of energy efficiency, latency, and packet-delivery ratio. HMAC combines energy-efficient schemes from existing contention-based and TDMA-based MAC protocols for WSN to improve network performance. A channel-reservation technique is proposed to drastically improve the end-to-end latency for TYPE I traffic flows. Through extensive simulation, we prove that HMAC provides superior performance in end-to-end latency, throughput, and per-node fairness while maintaining high energy efficiency of the network compared with existing MAC protocols for WSNs.
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[19] M. Xu, M. Zhao, and S. Li, “Lightweight and energy efficient time synchronization for sensor network,” in Proc. Int. Conf. WCNM, Sep. 2005, pp. 947–950. [20] S. C. Ergen and P. Varaiya, “On multi-hop routing for energy efficiency,” IEEE Commun. Lett., vol. 9, no. 10, pp. 880–881, Oct. 2005.
Heping Wang received the B.S. degree in computer science from the University of Electronic Science and Technology of China, Chengdu, China, the M.E. degree in computer engineering from Beijing University of Posts and Telecommunications, Beijing, China, and the Ph.D. degree in electrical and computer engineering from the University of Illinois at Chicago in 2009. He has seven years of industry R&D experience in embedded system design and network protocol design. He is currently a Lead Software Engineer with Lemko Corporation, Schaumburg, IL. His current research focuses on scalable and energy-efficient medium-access control and routing layer protocol designs and cross-layer performance optimization for wireless sensor networks.
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Xiaobo Zhang received the B.S. degree from the University of Science and Technology of China, Hefei, China, in 2003 and the M.S. degree and the Ph.D. degree in electrical and computer engineering from the University of Illinois at Chicago in 2006 and 2009, respectively. He is currently a Senior Engineer with CISCO Systems, San Jose, CA. His research interests include data gathering and distortion analysis in wireless sensor networks.
Farid Naït-Abdesselam (M’06) received the engineer degree in computer science from the University of Sciences and Technologies Houari Boumediene, Algeria, in 1993 and the Ph.D. degree in computer science from the University of Versailles Saint Quentin, Versailles, France, in 2000. He was previously with INRIA Lille Nord Europe. He is currently an Associate Professor with the University of Sciences and Technologies of Lille, Villeneuve d’Ascq, France. His research interests lie in the field of computer and communication networks with emphasis on architectures and protocols for quality of service and security in internet protocol-based networks, mobile ad-hoc, sensor, vehicular, and mesh networks, and overlay networks. Dr. Naït-Abdesselam is a member of the IEEE Communications and Computer Societies.
Ashfaq Khokhar (F’09) received the B.Sc. degree in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan, in 1985 and the Ph.D. degree in computer engineering from the University of Southern California, Los Angeles, in 1993. He is currently a Professor with the Department of Electrical and Computer Engineering, University of Illinois at Chicago. His research interests include wireless and sensor networks, multimedia systems, data mining, and high-performance computing. Dr. Khokhar was the recipient of the National Science Foundation CAREER award in 1998. His paper entitled “Scalable S-to-P Broadcasting in Message Passing MPPs” won the Outstanding Paper Award at the International Conference on Parallel Processing in 1996. He is an IEEE Fellow for his contributions to multimedia computing and database systems.
