Priority-MAC: A Priority based Medium Access Control solution with QoS for WSN

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1 Priority-MAC: A Priority based Medium Access Control solution with QoS for WSN Soumaya Argoubi, Karima Maalaoui, Mohamed Houcine Elhdhili, Leila Azouz Saidane RAMSIS Team, CRISTAL Laboratory, National School of Computer Science University of Manouba, Manouba, Tunisia med Abstract WSNs are composed of sensors that collect, process, and send data to a sink. To communicate, sensors use a shared medium. Thus, a robust MAC layer protocol has to be implemented for transmission management. This paper presents a QoS based WSNs MAC protocol that ensures service differentiation and less energy consumption. It is based on a duty-cycle approach that combines TDMA and CSMA/CA schemes. The proposed Priority-MAC protocol introduces also an EDF queue scheduling policy that aims to give priority to the urgent traffic taking into consideration the packet deadline. Simulations were conducted to evaluate the performances of our solution. Results have shown better performances in terms of energy consumption. Keywords MAC, QoS, Energy, Priority, WSN I. INTRODUCTION Massive development of the embedded systems and wireless communication technologies has led to the emergence of Wireless Sensor Network as an active field of research. The latter is composed of tiny sensor nodes which can be integrated in different fields where data with different QoS requirements can be transported. Therefore, a QoS policy is required to carry the data traffic based on their degree of importance. Traditional networks features, such as limited energy and memory resources, make the developed QoS solutions unsuitable for WSN. In fact, sensor nodes can be randomly deployed in inaccessible and hostile areas. Thus, ensuring a QoS support for WSNs becomes an emerging area of research which presents many challenges. The radio channel is a shared medium between all WSNs nodes. Hence, the MAC layer design must ensure QoS medium access to guarantee an optimal use of this resource. Thus, to ensure a QoS support for different applications, WSN protocol stack low levels have to take into consideration the WSNs limitations. In this work we focus on how to implement a QoS mechanism in MAC layer as it offers many services to the upper layers. This paper is organized as follows. In section 2, we give the most common classification of WSN MAC protocols presented in the literature, and illustrate examples of each category, especially CoSens [1] and Queue-MAC [2]. Section 3 is dedicated to expose the simulations we conducted to evaluate and compare the performance of CoSens [1] and Queue-MAC [2] protocols. In section 4, we describe our new QoS based MAC solution, and evaluate its performances. We end up this paper with some concluding remarks, and outline our future work. II. STATE OF THE ART The main goal of researchers, carried in the field of medium access control for WSN, is to find a compromise between energy conservation and guarantees in terms of throughput and transmission reliability. In WSNs, nodes consume energy especially for Channel overhearing, idle listening, repetitive retransmission due to collision, protocol overhead and the decreased ratio of channel use. In the literature, we can find three main categories of MAC protocols for WSN, namely: contention-based, time sequencing-based and hybrid approaches. A. Contention-based MAC protocols In this approach, all nodes compete to use the radio channel. Thus, collision probability will increase and the medium access is not guaranteed. Consequently, a node can wait for an undefined period of time before sending its packets, especially for large networks, like WSNs. In fact, each node has to use listen before talk technique. If the medium is busy, the node must wait for a certain period of time (back off) until it becomes free. Then, it retries again to send its packet. This waiting time requires that the node is still wake up. Thus, energy consumption will increase. Nevertheless, protocols using these techniques have some advantages, such as scalability. To deal with collision problems, they generally use a CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) algorithm. In fact, many contention-based protocols have been proposed in the literature. For instance, we can mention [3] which is very similar to IEEE , and uses a CSMA/CA and RTS/CTS (Request-To-Send, Clear-To- Send) medium access mechanism to avoid collision and hidden terminal problems. It defines a sleeping period in which all nodes turn off their radio transceiver for energy conservation and an active period for node synchronization using a SYNC broadcasted packet followed by data transmission. D-MAC [4] has introduced a data gathering tree. In this approach, nodes of the same level are wake up at the same time. The authors have supposed that children of the same node can detect each other. Therefore, if they access the medium at the same time using /16/$ IEEE

2 random back-off, collisions will be avoided. Other protocols have been proposed to reduce the idle listening using LPL approaches (LOW Power Listening), such as B-MAC [5], WiseMAC [6] and X-MAC [7]. In [8], authors have proposed ContikiMAC where packet transmission is reported until the wake-up time of the receiver becomes closer. This protocol carries only useful information. It ensures energy conservation thanks to the so-called fast-sleep technique. Indeed, it uses learning mechanisms to know the wake-up time of the different nodes associated with Clear Channel Assessment (CCA). RI- MAC [9] is an example of asynchronous MAC protocols category which is based on the Receiver-initiated paradigm. Nodes using such protocols should wait for a probe from the receiver before sending any data; this is called Low Power Probing (LPP). So, this probe will tell the sender that the receiver is woken up and is waiting for the sent information. This technique aims to decrease the radio channel occupation rate, so that it will be possible to reduce collision probability. To present a QoS support for WSN in MAC Layer, in [1], authors have presented a new protocol, called CoSens (Collect and Send as a burst). The first stage of this protocol is the waiting period (WP) where the coordinator collects packets from its child. The duration of the WP is variable to ensure an auto-adaptation by estimating the traffic load. When the WP is finished, the second stage, called transmission period (TP), begins. In this step, the router sends the collected data as a single burst. In the TP, this protocol uses CSMA/CA to transmit the first packet. Then, it continues sending the rest of the waiting data after receiving the ACK. B. Scheduled MAC Protocols Nodes, using a scheduled MAC protocol, do not compete to access the medium, because each one of them already has its mean to gain the radio channel. The resource, used to access the medium, can be a time slot, a frequency band or a code depending on the scheduled protocol category, if it is TDMA (Time Division Multiple Access), FDMA (Frequency Division Multiple Access) or CDMA (Code Division Multiple Access). Each node, that has not yet got its resource, will be in sleeping mode. Thus, idle listening is reduced, and energy consumption decreases because there is no more collision or overhearing problem. Such protocols require synchronization and central management. They are not suitable for large, dynamic and mobile networks. Nodes, using FDMA based protocols, have to be equipped with high cost transceiver. So, these protocols are not very suitable for WSNs. In protocols using CDMA technique, codes are assigned to the network members by the BS. Thus, this centralized method cannot be applied to WSNs. Most scheduled Mac protocols, proposed for WSNs, are TDMA-based ones. The common point between them is the static time slot allocation for all network nodes. However, if a node does not have any data to transmit during its time slot, there will be energy and bandwidth waste. Time slot allocation can be centralized or distributed. Centralized allocation is not recommended for WSNs because if synchronization signal is lost, the whole network will be affected. Despite the clock drifts and the synchronization failure risk, distributed allocation is more suitable for WSNs. In [10], the authors have proposed a TDMA-based protocol where slot allocation is centralized at a gateway node. SMACS [11] is a scheduled and distributed MAC protocol. Thus, there is no need for a central node to ensure synchronization. Each node has to carry a neighbor discovery phase, and then channels are assigned. Another example is TRAMA [12] which uses three mechanisms. The first one is a neighbor protocol to know each node two hop neighbors. The second one is a schedule exchange protocol allowing each node to publish data waiting for transmission and involved receivers. The last one is an adaptive election algorithm which aims to identify senders and receivers for a certain time slot. TRAMA alternates between random and planned medium access periods. LMAC [13] is another distributed scheduled MAC protocol. Each node sends, in its time slot, a control message which has to be received by all nodes. Then, only the receiver has to be in active mode waiting for the data message if it exists. C. Hybrid Protocols Protocols of this class combine the advantages of the aboveexplained protocols categories. In fact, they alternate different proposed techniques to ensure auto-adaptation depending on the traffic. In [14], the authors have suggested a solution for the bottleneck problem faced when a large number of nodes try to send their data to one destination node, such as the sink. This problem is very common in WSNs. Nodes, using the Funneling-MAC; utilize CSMA/CA to access the medium in normal situation. The sink sends a Beacon to nodes which are in the high load area to tell them to switch for the TDMA medium access technique. Time slot sizing and allocation are also done by the sink depending on the route traffic load of each received packet. Another example of hybrid WSNs MAC protocols is IEEE MAC layer [15]. As shown in Figure 1, this protocol defines an active period which lasts 16 time slots, and inactive period to save the sensor energy. The first phase contains a contention access period (CAP), based on CSMA/CA techniques, and a contention free period (CFP) which offers guaranteed time slots (GTS) for each node. Fig. 1. IEEE MAC Layers Superframe Structure. The major limitation of this protocol is that it uses a fixed duty-cycle. Besides, the TDMA slots request and reservation, which are done during CSMA/CA phase, are complicated. In addition, it is designed to be used only in star topology networks. So it does not offer a support for multi-hop routing. However, it remains the standard implemented in the WSNs protocol stack low layers. In [2], authors proposed a solution called Queue-MAC which is inspired from IEEE

3 MAC layer protocol. It uses CSMA/CA and TDMA schemes to manage traffic variation and ensure auto-adaptation. To reduce energy consumption, nodes, using this protocol, switch to sleep mode during the inactive period. To reduce collision, this protocol inverses the CAP and CFP periods of the IEEE superframe. Thus, the absolute majority of traffic load is transported during the variable TDMA period. Then, nodes compete to access the channel during the CAP using the CSMA/CA technique. When a node gains the medium, it indicates the number of its waiting packets in the queue of the transmitted data so that the coordinator will be able to calculate the needed guaranteed time slots. To do so, authors changed the IEEE beacon structure by adding two new fields. The first one is to indicate the ID list of nodes for which the coordinator has allocated time slots. The second one is to save the number of time slots allocated for each node. Fig. 3. traffic. Average delay depending on the number of nodes under Poisson III. COMPARISON BETWEEN QUEUE-MAC AND COSENS The Queue-MAC [2] and CoSens [1] are two interesting MAC protocols, proposed to ensure QoS for WSNs. Both protocols have shown better performances compared to IEEE MAC layer protocol [1] [2]. Regarding the innovative techniques used by these protocols, we implemented them using Omnet++. Then, we compared their performances by considering under periodic and Poisson traffic. To do so, we used a star topology composed of one sink, one coordinator and 5 to 35 sensor nodes. The throughput was fixed to 20kb/s and the superframe duration was fixed to 400s. The number of runs was equal to 30. Simulation results are shown below. Fig. 4. Number of the received packets by the coordinator depending on the nodes number under periodic traffic. A. Simulation results Fig. 5. Number of received packets by the coordinator depending on the nodes number under Poisson traffic. Fig. 2. traffic. Average delay depending on the number of nodes under periodic Figure 2 and Figure 3 show the average delay of the received packets by the coordinator. We notice that for a low number of nodes both protocols have a similar behavior. However, unlike CoSens, Queue-MAC average delay increases with the increase of nodes number in the network. In fact, when the traffic load increases, Queue-MAC collects the majority of the packets during the the variable TDMA period. Nevertheless, CoSens tries to collect the maximum of packets by extending the waiting period, then it sends all collected data as a burst. Figure 4 and Figure 5 highlight that Queue-MAC ensures a better packet delivery compared to CoSens. This can be explained by the high rejection rate of packets due to collisions, in CoSens. Figure 6 and Figure 7 show that CoSens guarantees less energy consumption than Queue-MAC because this latter transports more packets. We conclude that CoSens shows more energy conservation and less average delay, while, Queue-MAC ensures better packet delivery.

4 Fig. 6. Network energy consumption depending on the number of nodes under a periodic traffic. A. Slot reservation strategies on Priority-MAC To design our approach and implement it, we supposed that the network is composed of N nodes and one coordinator. Sensor nodes are identical. Each one of them has a queue for periodic traffic, and another one for event-driven traffic. The maximum number of slots that the coordinator can reserve is Nslots max. There is equity between all sensor nodes. However, the highest priority is given to event-driven traffic in detriment of periodic one. When the coordinator receives a packet during the CSMA/CA phase, it extracts three fields: Packet deadline T periodic and T event referring respectively to the current size of the sender node periodic and event driven queues. This will lead to two situations presented by inequalities (1) and (2). N T periodic i + T event i Nslots max (1) i=1 N T periodic i + T event i > Nslots max (2) i=1 Algorithm 1 Congestion Avoidance Technique Require: Node Table[x] = node i, T periodic i, T event i, T periodic j, T event j, i < j Fig. 7. Network energy consumption depending on the number of nodes under Poisson traffic. if T event i < T event j or (T event i = T event j and T periodic j > T periodic i) then IV. PROPOSED PRIORITY-MAC PROTOCOL Based on real situations, we observe that WSNs are characterized by periodic or event-driven traffic. Our approach aims to offer QoS mechanisms on MAC layer for WSN. To do so, we propose to implement service differentiation based on the traffic type using a CSMA/CA-TDMA hybrid medium access control schemes. Indeed, as shown in Figure 8, the superframe is composed of a CFP to give a guaranteed time slot for each node, then a CAP where each node tries to access the radio channel using CSMA/CA. In each superframe cycle, depending on traffic load, the CAP can be followed by inactive period where nodes switch off their radio, and go to sleep mode. Thus, if we have an important traffic load, the inactive period has to be decreased and can become null. This approach aims to combine an adaptive duty-cycle with service differentiation to guarantee a better QoS support under MAC layer for WSNs. Our perspective deals also with the problem of slot reservation during TDMA period and queue scheduling strategies. Fig. 8. Priority-MAC Superframe. Node Table[x + 1] := node i Node Table[x] := node j sort insertion else if T event i = T event j and T periodic i = T periodic j then equity between nodes else Node Table[x] := node i Node Table[x + 1] := node j end if If inequality (1) is verified, there will not be a slot reservation problem. Nevertheless, we have to deal with congestion issue in the nodes queue as shown in Algorithm 1. As known, sensor nodes queue have small sizes, which may result in packet destruction before transmission. Furthermore, eventdriven traffic comes as a burst. If inequality (2) is verified, we will prioritize event-driven traffic as shown in Algorithm 2. B. Queue management policies on Priority-MAC To guarantee service differentiation, we opted for the use of EDF (earliest deadline first) queue management policy. In fact, if we are in the worst possible case as in Figure 9 and we have a packet that reaches the MAC layer at the end of CSMA period, it has to wait for its TDMA time slot. We consider that a packet respects its deadline when T coordinator Deadline; where T coordinator is given by equation (3).

5 Algorithm 2 Slot Reservation Technique Require: Node Table[x] = node i, T periodic i, T event i, T periodic j, T event j, i < j if N T event i Nslots max then i=1 ROUND-ROBIN equity between nodes else slot reserve := Nslots max petitioner number rest slots := Nslots max mod petitioner number for I waiting node do node i := slot reserve end for reallocate-rest-slot() Congestion Avoidance algorithm end if T coordinator = T node + T sleep + Nslots max T slot (3) T coordinator : Arrival time to the coordinator MAC layer. T node : Transmission time from the node network layer to its MAC layer. T sleep : Inactive period. Nslots max : Maximal reserved slot number. We assume that the packet will allocate the last TDMA time slot. T slot : One slot duration. also tried to study the approach reaction depending on the traffic variation. To do so, we used a star topology composed of one sink, one coordinator and 5 to 35 sensor nodes. The throughput was fixed to 20kb/s and the superframe duration was fixed to 400s. The number of runs was equal to 30. Fig. 10. Successful packet delivery rate depending on the nodes number for ordinary and urgent packets. Based on Figure 10 we notice that Priority-MAC ensures successful packet transmission without perturbation for urgent packets (P-U). However, packet successful delivery rate is low for ordinary traffic (P-O) due to the collisions and various attempts to listen to the medium. Fig. 9. Worst case of packet arrival. To ensure that a simple node sends rapidly an urgent packet during the CSMA/CA period, we have changed some parameters used in CSMA/CA technique of IEEE Namely, macminbe equals 2 if we have an urgent packet. Otherwise it is equal to 3. This will increase the chance to win the medium access. The maximum number of channel listening attempts, before deleting the packet macmaxcsmabackoffs, is modified to have the value 6. The maximum number of authorized retransmission of each packet macmaxframeretries is fixed to 4. Then, the coordinator will order them according to their priorities, and based on EDF policy. For example, is the remaining time before the deadline of the packet 1 p. So, its priority will be equal to. T rem p Tp rem C. Priority-MAC Performance evaluation We conducted simulations to evaluate the Priority-MAC performances and study successful packet delivery rate. We Fig. 11. Priority-MAC reaction under urgent traffic. Fig. 12. Comparison between energy consumed by Queue-MAC and Priority- MAC. Figure 11 shows Priority-MAC behavior under different percentages of urgent packets in the ordinary traffic. We

6 remark that our approach ensures a good packet delivery rate when 10% of the traffic packet is urgent (P-Q-0.1) even if the number of nodes increases. If the number of urgent packets exceeds 10%, the performance of Priority-MAC degrades until the successful packet delivery rate reaches 78%. We tried to compare our approach with an existing protocol that uses hybrid medium access schemes. Thus, we have chosen Queue-MAC [2] because it gives better results in terms of energy consumption compared to IEEE MAC layer. Based on simulation findings, presented in Figure 12, we can conclude that Priority-MAC shows better energy consumption results than Queue-MAC. V. CONCLUSION Autonomous WSNs have low cost, and are easy to deploy. However, these advantages make them very challenging in terms of each layer implemented protocols. In this paper, we were interested in the WSNs MAC layer. We stated the art of different existing protocols by describing the most-known categories, and giving some examples. Then, we compared two interesting approaches, namely CoSens [1] and Queue-MAC [2] to observe the different behaviors of a CSMA/CA-based WSNs MAC protocol and a hybrid one. Finally, we presented our approach Priority MAC that uses a duty-cycle concept with CFP and CAP. The proposed protocol aims to introduce a QoS mechanism using service differentiation, based on the traffic type, by taking into consideration the packet deadline. In our future works, we plan to do more simulations to evaluate our approach in terms of delay and packet successful delivery rate. Then, we will aim to propose a routing protocol for WSNs that uses the QoS support offered by Priority MAC in order to design a cross-layer QoS solution for WSN. REFERENCES [1] B. Nefzi and Y.-Q. Song, Cosens: A collecting and sending burst scheme for performance improvement of ieee , in Local Computer Networks (LCN), 2010 IEEE 35th Conference on. IEEE, 2010, pp [2] S. Zhuo, Y.-Q. Song, Z. Wang, and Z. Wang, Queuemac: A queue-length aware hybrid csma/tdma mac protocol for providing dynamic adaptation to traffic and duty-cycle variation in wireless sensor networks, in Factory Communication Systems (WFCS), th IEEE International Workshop on. IEEE, 2012, pp [3] W. Ye, J. Heidemann, and D. Estrin, An energy-efficient mac protocol for wireless sensor networks, in INFO- COM Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, vol. 3. IEEE, 2002, pp [4] G. Lu, B. Krishnamachari, and C. S. Raghavendra, An adaptive energy-efficient and low-latency mac for data gathering in wireless sensor networks, in Parallel and Distributed Processing Symposium, Proceedings. 18th International. IEEE, 2004, p [5] J. Polastre, J. Hill, and D. Culler, Versatile low power media access for wireless sensor networks, in Proceedings of the 2nd international conference on Embedded networked sensor systems. ACM, 2004, pp [6] A. El-Hoiydi and J.-D. Decotignie, Wisemac: An ultra low power mac protocol for multi-hop wireless sensor networks, in Algorithmic Aspects of Wireless Sensor Networks. Springer, 2004, pp [7] M. Buettner, G. V. Yee, E. Anderson, and R. Han, Xmac: a short preamble mac protocol for duty-cycled wireless sensor networks, in Proceedings of the 4th international conference on Embedded networked sensor systems. ACM, 2006, pp [8] A. Dunkels, The contikimac radio duty cycling protocol, [9] Y. Sun, O. Gurewitz, and D. B. Johnson, Ri-mac: a receiver-initiated asynchronous duty cycle mac protocol for dynamic traffic loads in wireless sensor networks, in Proceedings of the 6th ACM conference on Embedded network sensor systems. ACM, 2008, pp [10] K. Arisha, M. Youssef, and M. Younis, Energy-aware tdma-based mac for sensor networks, in System-level power optimization for wireless multimedia communication. Springer, 2002, pp [11] K. Sohrabi, J. Gao, V. Ailawadhi, and G. J. Pottie, Protocols for self-organization of a wireless sensor network, IEEE personal communications, vol. 7, no. 5, pp , [12] V. Rajendran, K. Obraczka, and J. J. Garcia-Luna- Aceves, Energy-efficient, collision-free medium access control for wireless sensor networks, Wireless Networks, vol. 12, no. 1, pp , [13] L. F. Van Hoesel and P. J. Havinga, A lightweight medium access protocol (lmac) for wireless sensor networks: Reducing preamble transmissions and transceiver state switches, [14] G.-S. Ahn, S. G. Hong, E. Miluzzo, A. T. Campbell, and F. Cuomo, Funneling-mac: a localized, sink-oriented mac for boosting fidelity in sensor networks, in Proceedings of the 4th international conference on Embedded networked sensor systems. ACM, 2006, pp [15] I.. W. Group et al., Ieee standard for local and metropolitan area networkspart 15.4: Low-rate wireless personal area networks (lr-wpans), IEEE Std, vol. 802, pp , 2011.

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