LL-MAC: A low latency MAC protocol for wireless self-organised networks

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1 Available online at Microprocessors and Microsystems 32 (2008) LL-MAC: A low latency MAC protocol for wireless self-organised networks I. Marín a, *, J. Arias b, E. Arceredillo a, A. Zuloaga b, I. Losada b, J. Mabe a a Electronics and Communications Department, Tekniker Foundation, Eibar 20600, Spain b Electronics and Telecommunications Department, U.P.V./E.H.U., Bilbao 48013, Spain Available online 24 October 2007 Abstract This paper proposes LL-MAC, a medium access control (MAC) protocol specifically designed for wireless sensor network applications that require low data latency. Wireless sensor networks use battery-operated computing and sensing devices and their main application is environmental monitoring. In order to achieve such requirements, the whole network must work autonomously and collaborate in periodically sensing the surrounding environment and sending data to the sink. LL-MAC uses novel techniques to offer a low end-toend data transmission latency from the furthest away nodes to the sink in a unique working cycle while offering a low duty cycle operation in a multi-hop fashion. Key features of this protocol include a synchronised sleep schedule to reduce control overhead along with a mechanism to avoid overhearing unnecessary traffic and elude collisions. Finally, control interval adjustment enables power-aware topology management in changing environments. Ó 2007 Elsevier B.V. All rights reserved. Keywords: Medium access control (MAC); Wireless sensor networks (WSN); Energy efficiency; Low latency 1. Introduction A distributed wireless sensor network is formed by several scattered nodes, from hundreds to thousands, in a sensor field. Each node contains both processing and communication elements and has event-oriented environment monitoring as main functionality. Collected data from the environment are sent to the base station to be processed. Thanks to the high node density in this kind of networks, collaboration among them, allows creating a high quality and failure resistant environment monitoring system [1 3]. Recent advances in low power radio electronics, in micro-electromechanical systems (MEMS) and in wireless communications, have contributed to the development of hardware affordable sensor nodes. With this cost reduction, * Corresponding author. Tel.: ; fax: addresses: imarin@tekniker.es (I. Marín), jagoba.arias@ehu.es (J. Arias). URLs: (I. Marín), (J. Arias). sensor networks have emerged as an ideal solution to a number of applications, in both civilian and military scenarios, including monitoring and surveillance of large, remote or inaccessible areas over extended periods of time. Unlike standard wireless/ad hoc networks, wireless sensor networks (WSN) are severely resource constrained and energy conservation is of paramount importance. The lifetime of the sensor network is hence limited by the lifetime of the nodes battery. Needless to say, low power consumption is a major requirement in the design of communication protocol for sensor networks. As the wireless radio-communication interface consumes a significant fraction of node energy, energy efficiency can only be achieved through the design of energy-aware communication protocols. 2. Background Communication protocols in WSNs can be divided into several layers. The medium access control (MAC) is the layer responsible for managing the shared medium access /$ - see front matter Ó 2007 Elsevier B.V. All rights reserved. doi: /j.micpro

2 198 I. Marín et al. / Microprocessors and Microsystems 32 (2008) of all the nodes in the network. Its main functionality is avoiding the access of two nodes to the medium at the same time and offering a solution when it happens. MAC protocols in wireless sensor networks must fulfil some design features, such as energy efficiency, as battery replacement is not feasible, effective collision avoidance, minimum latency and efficient channel bandwidth utilisation. In trying to achieve these objectives, MAC protocols face some negative effects that lead nodes to waste part of their energy uselessly. Overhearing occurs when one node listens to packets that are destined to other nodes and therefore wastes its own energy in receiving and processing useless packets. Collision, that occurs when a node is transmitting its packet and other node starts transmitting, both packets collide and consequently sources must re-transmit. Control packet overload, usually in a Request- To-Send/Clear-To-Send (RTS/CTS) fashion, is necessary when the medium is shared among all the nodes. And finally, idle listening that is defined as listening to possible traffic that is never sent. In a first approach, MAC protocols can be categorised as contention-based and scheduled. Contention-based protocols, usually Carrier Sense Medium Access/Collision Avoidance (CSMA/CA), are easy to deploy and have been the most used ones in wireless sensor networks due to their simplicity, flexibility and robustness. Nodes do not need synchronisation information or global topology knowledge in order to access the medium and send their information. Moreover, nodes can get in and out of the network without major complications. Nevertheless, this kind of medium access generates time and energy waste due to packet collisions and generally needs an additional control mechanism. On the other hand, Time Division Medium Access (TDMA) protocols program medium access for each node into different time slots and this way, transmissions are free of collision and re-transmissions. However, this kind of medium access control has some drawbacks: synchronisation among nodes is needed and it cannot get adapted to dynamic changes in a sensor network, as fast as CSMA does. However, TDMA protocols present the natural advantage of having no collision or control packet overload from which the contention-based MAC protocols suffer. Many solutions have been proposed combining both random and scheduled access approaches. These protocols divide the time in working cycles (same behaviour every T c seconds) and these, in turn, are divided into sub-intervals for different purposes (synchronisation, packet reception and packet transmission). These protocols work in CSMA fashion, sharing the medium among all the nodes. So far, many approaches have analysed the energy constraints of sensor network nodes and there are many MAC protocols that offer a good solution for that need. However, there is no solution for a MAC protocol with a global latency reduction in a tree-based data gathering sensor network combined with low power consumption, a collision free data transmission mechanism and efficient topology management. This requirements, especially the low latency, is crucial in some applications where major traffic is convergecast, and data is routed through tree-topology networks. In this kind of applications, data must be coherent, sampled in the same instant, so the age of all the values is the same in every cycle. This paper presents a new MAC protocol called LL- MAC (Low Latency MAC) that offers the following characteristics: Reduced network global data transmission latency. A topology management technique that allows the network to lose no data packet due to topology changes and offers a reduction in power consumption thanks to a control interval adjustment. Idle listening and overhearing avoidance, as a receiver only listens to its transmitter when required. A collision free approach without additional control packets (RTS/CTS messages). Additionally, this paper offers experimental measurements and evaluation of LL-MAC performance on latency, synchronisation and energy consumption using real sensor nodes. 3. Related work Most MAC protocols for wireless sensor networks have been based on conventional wireless protocols, especially IEEE [4], and IEEE [5 7]. Low duty cycle MAC protocols, whose objective is battery consumption reduction work in a similar way: nodes are sleeping most of the time and only wake up whenever is required for receiving or transmitting information. This approach that trades latency or throughput for energy saving, is quite effective in stationary and latency-tolerant networks. The starting point of our research was the protocol called S-MAC [8]. It is the first real MAC protocol for WSN that offers low power consumption thanks to a sleep/awake scheme. Inspired by PAMAS [9] and IEEE , at the beginning of each active period, nodes get synchronised and during the remaining active period, data may be transferred using control packets. In order to reduce the probability of collisions, it uses RTS/CTS to ask for the medium access. This way, nodes not only negotiate a transmission but also try to avoid the hidden terminal problem [10]. Directly modifying the S-MAC protocol, the same authors presented a follow up paper [11] with an enhanced packet forwarding capacity, and GSA-FPA [12], that offers lower latency and energy consumption. At the same time, some other protocols based on S-MAC, tried to solve some shortcomings: DSMAC [13] tries to reduces latency varying the working cycle; and T-MAC [14] decreases idle listening period by increasing the latency. As a simplified solution, Polastre et al. presented B-MAC [15], which is a lightweight link protocol that does not offer synchronisation, organisation, or hidden terminal support but allows very

3 I. Marín et al. / Microprocessors and Microsystems 32 (2008) easy utilisation for integration with user s defined application modules in TinyOS [16]. Following a similar philosophy to S-MAC, Wei Ye et al. presented in [17] an alternative, called SCP-MAC. This protocol is based on WiseMAC [18] and B-MAC and proposes a programmed polling medium access. It offers a different approach: instead of being the receiver responsible of switching on its radio interface when the emitter is going to transmit, it is the transmitter which must wait until the receiver is ready and wakes up. Another approach is Sift [19] that is based on CSMA medium access control with a contention window and a non-uniform probability distribution. It offers a very low latency to the first R messages out of a total of N. If no node transmits in the first time slot, the transmission probability of the rest of the nodes increases exponentially in the next time slot, as there are fewer nodes to compete with. TRAMA [20] and ER-MAC [21] offer a TDMA approach. TRaffic-Adaptive Medium Access (TRAMA) protocol tries to solve the collision and low consumption problem with another strategy: it does not assign transmission slots to those nodes that have nothing to send, which do not wake up and keep on sleeping saving energy. ER-MAC, divides nodes in the network into two categories: common nodes and critical nodes. Its main feature is the so-called leader election method that allows the most critical nodes of the network not to waste energy in idle listening task. Finally, there are two hybrid protocols, Z-MAC [22] and P-TDMA [23]. Z-MAC mixes TDMA and CSMA techniques depending on information flow characteristics. Each time slot has its owner and therefore, nodes are classified as slot owners or no-owners for every time slot. Owners have a higher priority but not the exclusiveness for their slot, and therefore collisions may appear. On the other hand, P-TDMA offers a combined behaviour between TDMA and CSMA in different variable degrees. However, none of the presented MAC protocols offers either a global solution for latency-aware data transmission from each node in the network to the sink through several hops, or efficient topology management. Although several routing protocols have focused their research in low latency data collection [24 28], MAC protocol implementations have not offered good enough integrated solutions yet. As comparative references there are only four, although they are just simulations and there is no real implementation of them so far: DMAC [29], Distributed Minimal Time Convergecast Scheduling (which will be referred to as DMTCS in the rest of the paper) [30] and MERLIN [31], which are three examples of the very few approaches that take network latency as a main goal; and MS-MAC [32] that is a MAC protocol applied in a infrastructure with mobile sensors. The DMAC protocol offers an information routing mechanism for WSN that leads traffic from the branches to the sink. Nodes wake up sequentially in a chain reaction fashion, in order to transmit information from one another along the different hops towards the destination. It does not implement RTS/CTS flow control mechanism but all the nodes in the same level of the network (i.e., in the same hop number) have the same time scheme and consequently, all of them will transmit in the very same moment. So, although it offers a slotted solution, it does not avoid the hidden terminal problem, common to most CSMA approaches: if two nodes of the same level can not hear each other, their transmissions could collide and get lost forever as this protocol neither allows retries nor offers a mechanism to avoid this kind of situations. MERLIN s routing mechanism is very similar to DMAC s: divides the area in time-zones (the same concept as hops) and nodes within the same time zone own the same slot to transmit. Consequently, MERLIN also suffers from the hidden terminal problem and collisions occur often in the network. Moreover, it needs more than one base station in the network in order to manage the input of user data into the network and vice versa. Apart from offering routing solutions, this protocol integrates localisation capabilities as well. DMTCS is a TDMA solution with no collision or hidden terminal possibility, that offers a solution for data collecting in a tree network. It studies different approaches to solve the problem and offers good simulation results. However, too many assumptions are made: a bound clock drift, permanent connectivity among nodes and static nodes. Finally, it has been compared with no other similar protocol, no real implementation is presented and how low duty cycles are achieved is not explained either. Finally, MS-MAC protocol is based upon S-MAC and its objective is adapting that protocol to a sensor network with certain mobility, offering some kind of changing topology management. 4. Low Latency MAC design overview LL-MAC is a protocol aimed to a specific application of WSN: periodic data collecting from all the nodes to the sink through multi-hop paths (commonly known as convergecast) as fast as possible, in order to have the values of the network with similar age, as stated before. It offers a brand new performance planning for nodes to transmit information divided into time slots, apart from topology management, energy consumption reduction and global network latency improvements. The network is supposed to be formed by a number of nodes scattered in the working area. They all are sensing the environment and sending that information to the sink via a multi-hop route. In order to understand the nomenclature, some parameters must be defined: T c : Working cycle period. t slot : A time slot is the required time for sending one packet with a MAC ACK included. Current optimisation is 10 ms.

4 200 I. Marín et al. / Microprocessors and Microsystems 32 (2008) t sleep : Each node sleeps during this period of time. C: Control interval adjustment (ratio data intervals/control intervals). M: Maximum number of hops of the network. Must be defined before deployment. N: Maximum number of nodes in the network (excluding the base station). Must be defined before deployment. P i : Maximum number of children of each node of the hop i. Each node in hop m can accept P m children, each node in hop number n can accept P n children and so on. Must be defined before deployment. S i : Maximum offspring of each node of the hop i. Each node in hop m has S m descendants, each node in hop number n has S n descendants and so on. It is important to remark the difference between child/children and offspring. Its children are the nodes, belonging to the next hop, that are directly connected to it and its offspring are the nodes of the next hops that are connected to it or to its children or to the children of its children and so on. Similar to most of the presented protocols in Section 3, the working cycle T c is divided into two periods: active period (AP) and sleep period (SP). The AP is also divided into two intervals: Control interval and Data interval. In the Control interval topology information is shared, and in the Data interval collected information is routed to the destination. A general overview of a working cycle of LL- MAC protocol is shown in Fig. 1. Control interval in LL-MAC is quite different from most of the presented protocols, as it does not share the medium access, although all the nodes are listening all the time. It is formed by three sub-intervals, named as follows: (1) Node advertisements (NA): Each node publishes its own advertisement in this sub-interval. (2) Child adoption request (CAR): This sub-interval will only be used for nodes that want to join the network because they are new to it or due to a parent loss or change. (3) Child confirm (CC): This sub-interval is used by the parents to confirm to the newly adopted children. Advertisement messages include all the information needed for the nodes to get synchronised, know their hop number and choose a parent. The second and third subintervals (CAR and CC) only have traffic when any node decides to change its parent relationship (due to topology changes or node movement) or new nodes appear in the network. Although each node must wait for its time slot to publish its own information, every node is listening to every transmission in the air. Fig. 2 shows the Control interval. Each one of these sub-intervals (NA, CAR and CC) is divided into M non-uniform divisions. As there are different amount of nodes in each hop, there are different amount of time slots reserved in each hop division. K m represents the number of time slots included in hop m. Eq. (1) offers the distribution of the N + 1 time slots inside each sub-interval. In each sub-interval, each node plus the base station has a unique time slot assigned (N + 1 time slots). X M m¼0 Y m i¼0 P i ¼ XM m¼0 Fig. 2. Control interval scheme. K m ¼ N þ 1 The data interval is divided into M divisions (one for each hop number), and each of them divided into N time slots sub-divisions, each one for each node s transmission, as it will be further discussed in Section 6. Eq. (2) represents the working cycle period and limits the collected data resolution, as environment data is sampled every T c. T c ¼½ðM þ 3ÞN þ 3Št slot þ t sleep ð2þ ð1þ 5. Synchronised performance Fig. 1. Working cycle scheme. As a sensor network is formed by a great amount of nodes scattered in a field and they are not supposed to be switched on in a predefined order (base station first, then the surrounding nodes and so forth), LL-MAC has been designed in order to overcome random start-up procedures and nodes get adapted to the network as long as they listen to advertisements.

5 I. Marín et al. / Microprocessors and Microsystems 32 (2008) The basic behaviour of every node is quite simple: each node has to publish its advertisements to the rest of the nodes, receive information from its children and re-transmit it to its parent. When a node wakes up for the first time, it is not synchronised and it has no real parent. As long as a node does not have a functional parent, it can send neither advertisements nor data because it knows neither when nor who send them to. Moreover, orphan nodes keep awake and listening all the time, waiting for an advertisement. Base station behaviour is a bit different: wakes up with an operative parent (the sink), so it does not have to wait for any advertisement. As expected, the base station is the node that establishes the working cycle (T c ) and the active/sleep scheme from the beginning Changing topology management As stated in Section 4, every node in hop i could be parent of a number of P i children, and it will address them from #0 to #P i 1. Each time that it receives a CAR, it will check if it has enough free space to adopt that child. If so, the parent will allocate that child with the smallest ordinal number, beginning from #0. In that moment, that node will be the child number #0 for that parent, regardless of its ID. The next child that would ask that parent to be his, will be child number #1 for the parent, and so on, up to P i children. As indicated before, when a node wakes up for the first time it has no real parent. In order to update its parentrelationships, every time the Control interval is executed, all the nodes analyse every advertisement received. All the packets are analysed in order to determine if the current parent is the best out of the total of the available parents. Once the node decides which one is the most suitable parent (the best link quality), it will ask for its child adoption in the CAR sub-interval. Following the process explained before, the parent-to-be decides whether it can adopt that child or not, and if so, it will answer a CC message. When a parent has its maximum number of children allocated, he will not send an answer. In a CC message, the parent informs to its new child the number of the data slot in which it has to transmit, which had been chosen according to the child number assigned before. With this information, the child can calculate the exact moment when it has to transmit the data to its parent and its own hop number. If a child does not receive a CC message in the same Control interval that it had asked for, that child keeps the current parent and forgets about the parent-to-be. In every working cycle, each node sends its own data to its parent in the time slot number that had been assigned before. A parent change (and therefore, a topology change) can be completely done within a unique Control interval. Thus, in the Data interval of the same working cycle, the node can send its data to its new parent, being the new topology functional in the moment that it has been established. The former parent will not listen to the current transmissions of the recently moved node. In order to release the child number it was occupying in the former parent, if a node does not listen to a child s transmission in its time slot for three consecutive cycles, it decides to delete it. The very same process explained in this Section, is followed when a node has a functional parent but discovers a better one and decides to change it Cycle synchronisation As explained in Section 4, advertisements also offer information for synchronisation purposes: a synchronised time-stamp and the control interval adjustment parameter (C). Every child processes advertisements received from its parent in order to extract the synchronisation information. Once it has updated its own variables, it will include that information on its own advertisements and transmit it. Thanks to this, every information a node sends is updated with the information of its parent. This is possible due to the time slot order: the first node to talk is the base station and its children hear it (NA sub-interval, BS division). Then, in the next division (hop 0 division), base station s children talk with their own information, updated with the information received from the base station and so on, as shown in Fig. 2. The synchronised time stamp allows every node to adjust its own clock to its parent s. With this synchronisation method, all the nodes in the network wake up simultaneously at the beginning of a working cycle and listen to each other at the right time. Further explanation of the synchronisation method can be found in [33]. It must be stressed that the synchronisation, as well as topology management, is performed with the information attached in advertisements so it can only be done every Control interval. C is the ratio that indicates how many times there is a Data interval for one Control interval. Fig. 3 presents an example of this modified performance for C = 2. It can be seen that in the second T c, when it was supposed to be a Control interval, node keeps on sleeping until the Data interval arrives. Fig. 3. Working cycle scheme with control interval adjustment C = 2.

6 202 I. Marín et al. / Microprocessors and Microsystems 32 (2008) If C is high, there is a Control interval for many Data intervals and this means that topology information might not be updated as often as necessary. For this reason, C must be carefully chosen for each network s requirements of topology dynamics. BS HOP 0 A B 6. Low latency mechanism The Data interval is not a simple TDMA period of time. Time slotting has been carefully analysed in order to achieve minimum latency performance at a low computational cost. As mentioned in Section 4, Data interval is divided into M divisions, and each one of them is, in turn, divided into N time slots sub-divisions. Each node will talk to its parent in the time slot sub-division assigned inside the division corresponding to the hop number it is in. The Data interval is presented in Fig. 4. The information from the nodes is transmitted hop-byhop from the furthest hop to the sink. The first nodes to talk belong to the highest hop number (in the division M 1), then the following hop M 2 nodes and so on. Every parent listens to all its children, each in a different time slot and then store that information. If a parent is in the hop 1, it will listen to its children in the hop 2 in the preassigned time slots. In the next hop division (hop 1), the parent will send its own data along with the stored data from its children in the previous hop division to its parent, and so on. It must be stressed that no data aggregation mechanism has been implemented in order not to increase nodes complexity. Let s illustrate it with an example (see Fig. 5): let node B (in hop 0) have two children (C and D, both in hop 1) and a parent A (BS). Child C will transmit in slot 0 of hop 1. Child D will transmit in slot 1 of hop 1. Node B will be listening in slots 0 and 1 of hop 1 to their children s transmissions, will store them and will transmit them, along with its own data, to its parent in the slots 0, 1 and 2 of hop 0. Its parent, node A, will have been listening to its child B during slots 0, 1 and 2 of hop 0, storing the packets and will transmit them, along with its own data, to the sink. As shown in Fig. 4, divisions are numbered in reverse order compared with the Control divisions (see Fig. 2). The explanation is quite simple: topology management information HOP 1 C is updated from the base station to the nodes but data must be usually collected from the branches to the sink. The hop-latency, is defined as the time duration between a packet reception and the same packet transmission in a node. As it is described in Fig. 4, the time between packet reception and transmission is equal to one of the M total divisions. Therefore, the corresponding latency can be calculated using Eq. (3). L hop ¼ N t slot ð3þ The end-to-end latency, can be defined as the time that it takes a message to reach the sink since it was generated in the furthest node of the network. This term will be referred to as latency unless otherwise stated. This latency, that takes into account the hop-latencies of the M 1 divisions, is depicted in Fig. 4, as the time between the beginning of the division M 1 and the beginning of the hop 0. This is presented mathematically in Eq. (4). L end ¼ðM 1ÞL hop ¼ðM 1ÞN t slot ð4þ The global latency, defines the latency of the whole network. This is the time period between the first node starts sending its own message until the sink receives the last message of the session. This latency, that takes into account the hoplatencies of the M divisions, is depicted in Fig. 4, as the time between the beginning of the division M 1 to the end of division 0. This can be expressed using Eq. (5). L g ¼ M L hop ¼ M N t slot ð5þ All the defined latencies are determined in the moment the topology is established and they do not depend on nodes input and/or output. D Fig. 5. An example of a simple topology. 7. Protocol implementation The purpose of our implementation is to demonstrate the efficiency of LL-MAC and to compare it with other similar MAC protocols. We used Tmote sky motes 1 as our development platform and testbed. These motes are running TinyOS, an efficient event-driven operating system for sensor nodes [16]. Tmote sky motes have the low power TI MSP430F1611 microcontroller with 48 kb of flash and 10 kb of RAM memory. These motes are equipped with the Chipcon Fig. 4. Data interval scheme. 1 [Online] Available:

7 I. Marín et al. / Microprocessors and Microsystems 32 (2008) Fig. 6. Tmote sky mote. CC2420 radio transceiver and an integrated antenna for working in 2.4 GHz (see Fig. 6). Some important parameters of our protocol implementation are listed in Table 1 [34]. The goal of the experimentation is to reveal the improvements achieved by LL-MAC in latency in comparison with energy consumption, synchronisation and network topology management. However, our most important parameter latency, and almost every parameter, cannot be directly compared with the results of some other MAC protocols, as they consider only one packet source and the rest of the nodes as routers of that information, so there is no increase in the amount of data to transmit as hop number decreases. Most implementations so far, have only tried to reduce latency in packets (one by one) from one unique source to the sink [8,15,29,31,32], whereas LL-MAC offers low latency for each and every packet from all the nodes in the network. Protocol experimentation was made with a non-linear hierarchy multi-hop network with eight nodes (N =8) and two hops to the sink (M = 2). The election of the values of the parameters P i, M and N was not made randomly: the best latency performance complexity trade-off for our environment was selected. Similar to B-MAC, our work was tested along with a modification of Surge application, 2 in the network scheme presented in Fig. 7. We assume that nodes will listen to any advertisement in a reasonable lapse of time from its initial awakening. Moreover, all the Data and Control packets that belong to the same T c are numbered the same, for better identification. 2 [Online] Available: Table 1 Parameters of LL-MAC implementation on Tmote sky motes Parameter Time slot (t slot ) Duration of Control interval (t ctrl ) Duration of packet transmission (t tx ) Duration of packet reception (t rx ) Duration of radio module start-up (t on ) Cycle repetition (T c ) Packet length Transmission current (I tx ) Reception current (I rx ) Sleep current (I sleep ) Start-up current (I on ) A BS HOP 0 Value 10ms 3Æ N Æ t slot 5ms 5ms 5ms 30s 120 bytes 12.5 ma 22mA 6lA 2.5 ma All tests occurred in an unobstructed area of a laboratory with line of sight to every other node and three meters of separation. A picture with a reduced deployment of the sensor network used in the tests is presented in Fig. 8. Opposite to most of the presented protocols, we know exactly the number of transmissions and receptions each node is making because there is no re-transmissions due to packet collisions. Other error sources, such as noise, mul- B HOP 1 C D E F G H Fig. 7. Tested topology.

8 204 I. Marín et al. / Microprocessors and Microsystems 32 (2008) Fig. 8. Reduced laboratory deployment. tipath or interference have not been considered, as in the rest of the approaches. Moreover, throughput analysis does not apply because LL-MAC is been designed for constant workload as each node sends its captured data every T c Measurement of network synchronisation All LL-MAC schemes are based upon global synchronisation of the network for hearing advertisements and for transmitting (and correctly receiving) data. To measure synchronisation, each node is wired to a common oscilloscope. Upon transmission of data packet and upon listening to children, we toggle a hardware pin. Using the oscilloscope, we capture the sequence of the happenings, as shown in Fig. 9. Measurements along 6 hours of performance, demonstrated that synchronisation among nodes is in the boundaries of ±200 ls. In Fig. 10 maximum, minimum and mean values of synchronisation values between each node and base station are shown (as BS imposes the T c of the network). One-sample Kolmogorov Smirnov test is a non-parametric test that studies the normality of a distribution. This test indicates that 95% of the samples of each node satisfies Eq. (6) with m = 6.3 (mean value) and r = (standard deviation), obtaining a value of synchronization 6.3 ± (ls), which offers a deviation of approximately 75 ls around base station s T c. Synchronisation ðlsþ ¼m 2 r ð6þ The measured syncronisation value is negligible in comparison with the time slot duration (10 ms, see Table 1), assuring therefore the correct performance of the protocol Measurement of end-to-end latency When topology is established, in this case N = 8 and M = 2, the latency of all the transmissions of each node will be the same regardless of whether all the topology is fulfilled or not. At this point, it s important not to confuse latency with T c. Latency is the time that a message spends from its source to the sink and the working cycle (T c ) is the period of repetition and determines the data resolution (data is taken every T c ). Using the end-to-end latency equation defined in Section 6, the theoretical maximum latency is L end = 80 ms. Fig. 9 presents a real measurement of the performance of the network and the latency achieved. Since C starts transmitting until the base station receives its message, there s a gap of ms. It can be seen that the real latency fulfils theoretical estimation Measurement of energy consumption A node s lifetime is determined by its overall energy consumption. To measure the consumption of the radio, which is, by far, the most consuming part of the node, we measure the amount of time the radio is in sleep, transmitting or receiving modes. The energy consumption in each mode is then calculated by multiplying the time

9 I. Marín et al. / Microprocessors and Microsystems 32 (2008) Fig. 9. Network performance and end-to-end latency (between markers). Synchronization (µs) Maximum Minimum Mean Mote Identifier Fig. 10. Synchronisation between each node and the base station. spent in each mode by the required power to operate the radio in that mode. We measure the energy directly but in a non-intrusive way, thanks to a Mobile Communication DC Source 66319B by Agilent Technologies that offered high resolution and sample rate (0.5 la and 64 khz, respectively). Fig. 11 shows the current drawn from the DC Source that represents a node s consumption during data transmission. This measure was done directly by the DC Source without any external equipment. In wireless sensor network applications, like in most burst communications, the consumed current can be expressed by Eq. (7). In our MAC implementation, data sampling is assumed instantaneous and it does not add extra power consumption to the total amount. In the following equations, V is the power supply voltage. I c ¼ E ctrl þ E rx þ E tx þ E sleep ð7þ V T c E ctrl is the consumed energy during the Control interval, in which all the nodes switch the radio module once, keep on listening all the time, and, in an average situation, all the nodes will listen to the same amount of advertisements and will have to send its own one. For this general analysis, it is assumed that no traffic will be in CAR and CC subintervals (see Section 4). E ctrl ¼ V ði on t on þ I tx t tx þ I rx ðt ctrl t tx ÞÞ ð8þ E rx depends on the offspring of each node, as every node listens to all the packets its own children send which include the packets of the rest of the offspring below those children. Every node starts up the radio module as many times as children has and keeps on listening during as many time slots as descendants. E rx ¼ V ði on t on P i þ I rx t slot S i Þ ð9þ E tx depends on the number of packets to send that in turn depends on the offspring of each node. For each transmission, a node must listen to a MAC acknowledge message. Every node switches on the radio module once and transmits as many packets as descendants. E tx ¼ V ði on t on þði tx t tx þ I rx ðt slot t tx ÞÞ ðs i þ 1ÞÞ ð10þ E sleep is the current consumption during the time the node is doing nothing but sleep. It depends on T c and the transmission, reception and Control intervals duration.

10 206 I. Marín et al. / Microprocessors and Microsystems 32 (2008) Fig. 11. Current consumption during data transmission. E sleep ¼ V ½T c t ctrl ð2 S i þ 1Þt slot ðp i þ 2Þt on ŠI sleep ð11þ Once studied every part of Eq. (7), it is important to analyse the contribution of each of them to the total amount of consumed current. This way, E ctrl is the most consuming part of every T c with the 87.71% of the global consumption, whereas Data (E rx + E tx ) consumes the 12.21% and the sleep period just draws the 0.08% of the current. Finally, the lifetime of the node, t L, is dependent on the total current consumed, I c (7) and the battery capacity, C batt. Eq. (12) presents lifetime in days. t L ¼ C batt=i c ð12þ 24 In order to calculate nodes lifetime, it is been assumed two typical AA batteries (V = 3 V) as power supply with a C batt of 2500 mah Life time versus data resolution As shown in Section 7.2, after establishing the network topology, the latency for each packet is fixed and only depends on the maximum number of hops (M) and nodes (N) in the network. Therefore, given these two values, the end-to-end latency can easily be computed using Eq. (4). However, power consumption (and consequently, nodes lifetime) does change depending on other parameters such as the control interval adjustment (C), the node offspring or the desired data rate. Fig. 12 shows the relationship between nodes lifetime and the lapse of time between samples (data resolution see Eq. (2)). The longer these wait periods are, the less data rate will be required to send the information and, hence, nodes will remain longer in sleep slots. Thus, power consumption is reduced and lifetime, increased. On the other hand, low values of C require that more sleep intervals are occupied with control slots, which produces higher power consumptions. The position occupied by the node in the network topology (its offspring, S i ) will also alter the amount of energy consumed by that node: those nodes, which are placed closer to the sink will Lifetime (years) C=1 Minimum Offspring C=1 Maximum Offspring C=6 Minimum Offspring C=6 Maximum Offspring X: 12 Y: X: 36 Y: X: 12 X: 36 Y: 1.48 Y: Data resolution (sec) Fig. 12. Lifetime versus data resolution.

11 I. Marín et al. / Microprocessors and Microsystems 32 (2008) have more traffic to process, which means that will consume more power than much further placed nodes, and therefore, they will have a shorter lifetime. In the selected topology, the furthest node (in hop 1) has no offspring while the closest (in hop 0) has three descendants. For the selected data resolution (36 s) and C = 1, Fig. 12 offers a lifetime of years for the closest node to the sink and for the furthest node, almost 2 years of life with a completely synchronised and low latency performance. As in most wireless sensor networks applications, the achieved duty cycle with this data resolution is around 1% for every node in the network Control interval adjustment In Section 7.4 it is shown that data resolution is constrained by the node s lifetime. On the other hand, Section 7.3 presented that more than the 85% of the total consumption of every node is due to the Control interval of every T c. If the contribution of the Control interval to the total consumption could be reduced, data resolution would be increased while maintaining the same lifetime of the network. As explained in Section 5.2, C parameter represents the ratio between Data periods and Control periods. Eq. (13) presents the current consumption due to the inclusion of parameter C. It is similar to Eq. (7) and it can be seen that every consuming part is multiplied by C except for E ctrl. Every C Æ T c, sleep period, data transmission and data reception phases are repeated C times but Control interval is executed once. The remaining C 1 times that Control interval is not present, the node is sleeping and consumes the I sleep current I c ¼ E ctrl þ C ðe rx þ E tx þ E sleep ÞþV ðc 1ÞI sleep t ctrl V C T c ð13þ Assuming a fixed lifetime (1 year and a half), if C is high, Control interval influence in the total consumption decreases and data resolution could get improved. Needless to say, reducing the number of Control intervals decreases the speed reaction to network topology changes. If C is 6 and lifetime 1.5 years, a data resolution of 12 s can be achieved, providing a topology update of 72 s (C Æ T c ). With this configuration, data can be captured and collected three times faster (from 36 to 12 s) than in Section 7.4 but with the double of topology management period (from 36 to 72 s), as also shows Fig. 12. These results outperform any others presented so far, taking into account that the data latency is just 80 ms for the furthest node Protocol results comparison As stated in Section 3, the only four MAC protocols that are aimed to our two main goals are D-MAC, MER- LIN, DMTCS and MS-MAC. Besides, S-MAC has been added to the comparison as the reference MAC protocol in WSN. Nevertheless, S-MAC s and MS-MAC s results have been adapted to a tree-topology, as they were designed for linear topologies. End-to-end latency is one of our major objectives. In every presented protocol, latency depends on the number of data sources in the network. However, in LL-MAC, there is no additional delay due to collisions and re-transmissions as every node has its own time slot to transmit. Moreover, there is no possibility of appearance of the hidden terminal problem. In Fig. 13, end-to-end latency for one message from the furthest node to the sink in a 100 nodes network is presented. For any quantity of sources, LL-MAC suffers from a lower latency, but as the number of nodes in the network increases, the difference becomes more obvious. This is due to the collisions and re-transmissions that S-MAC, MS- MAC, D-MAC and MERLIN have to face and lead to a higher end-to-end latency. Moreover, the last graph represents the latency of the whole network with LL-MAC, explained in Section 7.2 and Eq. (5). Although DMTCS offers similar results, the end-to-end latency can only be compared with LL-MAC s global latency results, not with LL-MAC s end-to-end latency. Except for the DMTCS, a packet of any of the rest of the presented MAC protocols will take twice as long as LL-MAC to reach the sink. On the other hand, topology management is the other goal of LL-MAC. Our protocol is compared with S-MAC and MS-MAC, assuming a common data resolution of 5 s. For S-MAC and MS-MAC, as stated before, the values have been estimated for a tree-topology. The obtained results are depicted in Fig. 14. As it can be seen, D-MAC, MERLIN and DMTCS are not included in this comparison as they do not offer topology management capabilities. LL-MAC with C = 1 is the only combination that offers a shorter lifetime than S-MAC, but its topology management update (2 min) is not comparable with LL-MAC s Latency (s) LLMAC DMAC SMAC, MSMAC MERLIN DMTCS LLMAC global Number of sources Fig. 13. End-to-end latency comparison.

12 208 I. Marín et al. / Microprocessors and Microsystems 32 (2008) Lifetime (years) (5 s). Taking a data resolution of 5 s with C = 6, topology is updated every 30 s, the same period as MS-MAC. However, if C is reduced, data resolution is maintained the same but topology can be updated more often. Even with C =1 (5 s of data resolution and 5 s of topology update repetition), LL-MAC s lifetime is longer than MS-MAC s. So, for the same topology update period, LL-MAC offers the best results for lifetime. 8. Conclusions This paper presents LL-MAC, a medium access control protocol specifically designed for wireless sensor networks. Apart from energy efficiency, low end-to-end latency and efficient topology management are the main goals of the protocol design. Together with control messages (RTS/ CTS) avoidance, LL-MAC outperforms other sensor networks MAC protocols in latency reduction, topology management and energy consumption, thanks to a meticulous time slot structure. Moreover, LL-MAC evades hidden terminal problem and improves channel utilisation, becoming a resilient protocol to packet collision and network dynamics, apart from reducing dramatically power consumption and global latency. LL-MAC has been implemented on the Tmote sky hardware and experimental results have verified the design goals. References LLMAC C= 1 LLMAC C= 2 LLMAC C= 3 LLMAC C= 4 LLMAC C= 5 LLMAC C= 6 SMAC MSMAC Number of sources Fig. 14. Topology management comparison. [1] E. Shih, S. Cho, F.S. Lee, B.H. Calhoun, A. Chandrakasan, Design considerations for energy-efficient radios in wireless microsensor networks, Journal of VLSI Signal Processing Systems 37 (2004) [2] M. Tubaishat, S. Madria, Sensor networks: an overview, IEEE Potentials 2 (22) (2003) [3] S. Roundy, P.K. Wright, J.M. Rabaey, Energy Scavenging for Wireless Sensor Networks with Special Focus on Vibrations, Kluwer Academic Publishers, [4] Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, IEEE Std , [5] Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR- WPANs). < [6] G. Lu, B. Krishnamachari, C.S. Raghavendra, Performance evaluation of the IEEE MAC for low-rate low-power wireless networks, in: Proceedings of the IEEE Conference on Performance, Computing, and Communications, 2004, pp [7] A. Koubaa, M. Alves, E. Tovar, Modeling and worst-case dimensioning of cluster-tree wireless sensor networks, in: Proceedings of the IEEE International Real-Time Systems Symposium, RTSS 06, 2006, pp [8] W. Ye, J. Heidemann, D. Estrin, An energy-efficient MAC protocol for wireless sensor networks, in: Proceedings of the International Annual Joint Conference of the IEEE Computer and Communications Societies, [9] S. Singh, M. Woo, C.S. Raghavendra, Power-aware routing in mobile ad hoc networks, in: Proceedings of the ACM/IEEE Conference on Mobile Computing and Networking, MobiCom, ACM Press, [10] J. Yoo, C. Kim, On the hidden terminal problem in multi-rate ad hoc wireless networks, Lecture Notes in Computer Science (LNCS) 3391 (2005) [11] W. Ye, J. Heidemann, D. Estrin, Medium access control with coordinated adaptive sleeping for wireless sensor networks, IEEE/ ACM Transactions on Networking 12 (3) (2004) [12] Y. Li, W. Ye, J. Heidemann, Energy and latency control in low duty cycle MAC protocols, in: Proceedings of the IEEE Wireless Communications and Networking Conference, WCNC, New Orleans, LA, USA. URL < [13] P. Lin, C. Qiao, X. Wan, Medium Access Control with a Dynamic Duty Cycle for Sensor Networks, in: Proceedings of the IEEE Wireless Communications and Networking Conference, WCNC, vol. 3, 2004, pp [14] T. van Dam, K. Langendoen, An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks, in: Proceedings of the ACM Conference on Embedded Networked Sensor Systems, SenSys, [15] J. Polastre, J. Hill, D. Culler, Versatile Low Power Media Access for Wireless Sensor Networks, in: Proceedings of the ACM Conference on Embedded Networked Sensor Systems, SenSys, Baltimore, MD, USA, [16] TinyOS home page, < [17] W. Ye, J. Heidemann, Ultra-Low Duty Cycle MAC with Scheduled Channel Polling, Tech. Rep. ISI-TR , USC/Information Sciences Institute (July 2005). URL < PAPERS/Ye05a.html/>. [18] C.C. Enz, A. El-Hoiydi, J.-D. Decotignie, V. Peiris, WiseNET: an ultralow-power wireless sensor networks solution, IEEE Computer 37 (8) (2004) [19] K. Jamieson, H. Balakrishnan, Y.C. Tay, Sift: A MAC protocol for event-driven wireless sensor networks, Tech. Rep. MIT-LCS-TR-894, MIT Laboratory for Computer Science, May [20] V. Rajendran, K. Obraczka, J. Garcia-Luna-Aceves, Energy-efficient, collision-free medium access control for wireless sensor networks, in: Proceedings of the ACM Conference on Embedded Networked Sensor Systems, SenSys, Los Angeles, California, USA, [21] R. Kannan, R. Kalidindi, S.S. Iyengar, Energy and rate based MAC protocol for wireless sensor networks, ACM SIGMOD Record 32 (4), December [22] I. Rhee, A. Warrier, M. Aia, J. Min, Z-MAC: a Hybrid MAC for wireless sensor networks, in: Proceedings of the ACM Conference on Embedded Networked Sensor Systems, SenSys, San Diego, USA, [23] A. Ephremides, O.A. Mowafi, Analysis of a hybrid access scheme for buffered users-probabilistic time division, IEEE Transactions on Software Engineering 8 (1) (1982) [24] C.T. Ee, R. Bajcsy, Congestion control and fairness for many-to-one routing in sensor networks, in: Proceedings of the Second International Conference on Embedded Networked Sensor Systems, SenSys, ACM Press, New York, NY, USA, 2004, pp

13 I. Marín et al. / Microprocessors and Microsystems 32 (2008) [25] O. Chipara, Z. He, G. Xing, Q. Chen, X. Wang, C. Lu, J. Stankovic, T. Abdelzaher, Real-time Power Aware Routing in Wireless Sensor Networks, Tech. Rep. WUSEAS , Washington University in St. Louis, [26] W.-Z. Song, F. Yuan, R. LaHusen, Time-optimum packet scheduling for many-to-one routing in wireless sensor networks, in: Proceedings of the International Conference on Mobile Ad-Hoc and Sensor Systems, MASS, [27] S.R. Madden, M.J. Franklin, J.M. Hellerstein, W. Hong, TinyDB: an acquisitional query processing system for sensor networks, ACM Transactions on Database Systems 1 (30) (2005) [28] Q. Cao, T. Abdelzaher, Scalable logical coordinates framework for routing in wireless sensor networks, ACM Transactions on Sensor Networks 2 (4) (2006) [29] G. Lu, B. Krishnamachari, C.S. Raghavedra, An adaptive energyefficient and low-latency MAC for data gathering in wireless sensor networks, in: Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS, [30] S. Grandham, Y. Zhang, Q. Huang, Distributed minimal time convergecast scheduling in wireless sensor networks, in: Proceedings of the International Conference Distributed Computing Systems, ICDCS, 2006, p. 50. [31] A.G. Ruzzelli, R. Tynan, G. O Hare, An energy-efficient and lowlatency routing protocol for wireless sensor networks, in: Proceedings of the Systems Communications, ICW, 2005, pp [32] H. Pham, S. Jha, An adaptive mobility-aware mac protocol for sensor networks (MS-MAC), in: Proceedings of the IEEE International Conference on Mobile Ad hoc and Sensor Systems, MASS, Florida, USA, [33] S. Ganeriwal, R. Kumar, M.B. Srivastava, Timing-sync protocol for sensor networks, in: Proceedings of the ACM Conference on Embedded Networked Sensor Systems, SenSys, Los Angeles, California, [34] CC2420 RF Transceiver Datasheet. < Itziar Marín Saldaña was born in San Sebastián Donostia, Spain, in She received the M.Sc. degree in telecommunication engineering in 2001 from the University of the Basque Country, Spain. She was with the Radio-communication and Signal Processing Research Group at the Faculty of Engineering in Bilbao (Spain), working on Digital Radio Mondiale (DRM), from 2001 to Since 2003, she has been with Tekniker Foundation Research Centre as a researcher. She has been working on low consumption wireless systems and technologies and pursuing her Ph.D. degree. Ms. Marín s research interests include low power design, wireless communications and specially, wireless sensor networks (WSNs). Jagoba Arias Pérez was born in Bilbao, Spain in He received the M.Sc. (2001) and Ph.D. (Honors, 2005) degrees in telecommunication engineering from the University of the Basque Country, Spain. He has worked as a researcher for the University of the Basque Country for 5 years now. Dr. Arias research interests are communication hardware, machine intelligence and, specially, wireless sensor networks (WSNs). Eduardo Arceredillo Santamaría was born in Burgos, Spain in He received the B.Sc. degree in electronic engineering in 1983 from the University of the Basque Country, Spain. He worked in the R&D department of an electro medical company specialised in defibrillator and monitoring from 1985 to 1990, and was the head of the department from 1990 to Since 1992 he has been with Tekniker Foundation Research Centre as a senior researcher. He is specialist in electro medical equipment, embedded design, low power, communications, and real time operating systems. He shares a patent of an electronic door lock. Mr. Arceredillo s research interests include energy scavenging, wireless communications and wireless sensor networks (WSNs). Aitzol Zuloaga Izaguirre was born in Caracas, Venezuela. He received the M.Sc. in electronic engineering in 1985 from the Simon Bolivar University, Caracas. In 2001, he received the Ph.D. degree in Information Technologies from the University of the Basque Country, Spain. He worked for several years in private R&D departments designing consumer telecommunication systems. After that, he has worked as researcher for the University of the Basque Country up to now. Dr. Zuloaga s research interests FPGA-based digital communications and image processing systems. Iker Losada Corderí was born in Ermua, Spain in He received the M.Sc. in Telecommunication engineering in 2003 from the University of the Basque Country, Spain. From 2003 to 2005, he was with the communications department of Ikerlan Research Centre, working on RF design and low consumption wireless technologies. Since 2005, he was with the Radio-communications and Signal Processing Research Group at the Faculty of Engineering in Bilbao (Spain), working on the radio channel characterisation of the Digital Radio Mondiale (DRM) system and pursuing his Ph.D. degree. Mr. Losada s research interests deal with wireless communications, radio channel propagation characterisation, low power design and statistical signal processing. Jon Mabe Álvarez was born in Bilbao, Spain in He received the M.Sc. in Telecommunication engineering in 2005 from the University of the Basque Country, Spain. He was with the Applied Electronics Research Team at the faculty of Engineering in Bilbao (Spain), working on FPGA-based image processing systems, from 2003 to Since 2005, she has been working with Tekniker Foundation Research Centre as researcher and pursuing his Ph.D. degree. Mr. Mabe s research interests deal with FPGA-based industrial control systems and digital signal processing hardware.