AEEMAC: Adaptive Energy Efficient MAC Protocol for Wireless Sensor Networks Alak Roy
Nityananda Sarma
Department of Computer Science and Engineering National Institute of Technology Agartala, India
[email protected]
Department of Computer Science and Engineering Tezpur University, India
[email protected]
very important. Energy efficiency is a critical issue in WSNs since batteries are the only energy source to power the sensor nodes. Energy efficiency is a fundamental theme pervading the design of Medium Access Control (MAC) layer protocols developed for WSNs. One of the primary mechanisms for achieving low energy operation in energy-constrained WSNs is duty cycling. In a sensor node sensing, computation and radio operations are the main sources of energy consumption [2, 3, 4]. Out of those three sources, energy loss due to radio operation is the maximum one. Not only transmitting costs energy; receiving, or merely scanning the wireless channel for communication can use up to half as much depending on the type of radio. Since, in WSNs, communication of sensor nodes is more energyconsuming than their computations; it is a primary concern that the communication is minimized while achieving the desired network operation. In particular MAC [1] protocols must minimize the radio energy costs in sensor nodes. Energy I. INTRODUCTION conservation in communication can be performed in different Wireless sensor network (WSNs) is a special network with layers of the TCP/IP protocol suit, but energy conservation at large numbers of nodes equipped with embedded processors, MAC layer is most effective one due to its ability to control the battery powered sensors and low power radios. WSNs are used radio directly [2, 3, 4]. To ensure a long-lived network of in a wide range of applications to capture, gather and analyse wireless communicating sensors, we are in need of a MAC live environmental data, also used in many fields such as target protocol that is able to improve energy efficiency by detection and tracking, environmental monitoring, industrial maximizing sleep duration, minimizing idle listening and process monitoring, defence, smart spaces, scientific application, overhearing, and eliminating hidden terminal problem or collision of packets. medical systems and robotic exploration. While traditional MAC protocols are designed to maximize Wireless sensor network typically consists of a base station and a group of sensor nodes. The sensor nodes are capable of packet throughput, minimize latency and provide fairness, communicating with each other and the base station through protocol design for WSNs focuses on minimizing energy radios. The base station, on the other hand, serves as a gateway consumption. The application determines the requirements for for the sensor network to exchange data with applications to the minimum through-put and maximum latency. Fairness is accomplish their missions. While the base station can have usually not an issue, since the nodes in a wireless sensor continuous power supply, the sensor nodes are usually battery network are typically part of a single application and work powered. The batteries are inconvenient and sometimes even together for a common purpose. impossible to replace. When a sensor node runs out of energy, A. Source of Energy Waste in WSNs its coverage is lost and also when the energy level at the node The major sources of energy waste in a MAC [1] protocol for goes down to zero, no more packets can be received or wireless sensor networks are the following: transmitted by the node. Hence, to successfully cover the target 1) Collision: When transmitted packet is corrupted, it has to be area, sensor networks are composed of large number of nodes. Nodes in WSNs typically operate unattended with a limited discarded and follow-on retransmissions increase energy. power source; hence energy efficient operations of the nodes are
Abstract— In this paper, we investigate the available energyefficient Medium Access Control protocols for wireless sensor networks emphasizing on their energy saving methods and present a simple but effective energy efficient MAC protocol named AEEMAC (Adaptive Energy Efficient MAC protocol). Like SMAC, AEEMAC also employs a duty cycling to save energy by avoiding idle listening, but incorporates three additional optimizations to further improve energy efficiency at MAC layer. These optimizations are – (i) adaptive sleeping and reusing of channel, (ii) use of combined ‘SYNC-RTS’ control packet, and (iii) use of combined ‘ACK-RTS’ control packet in bidirectional and multihop data transmission. The energy efficiency of AEEMAC is demonstrated for single hop as well as multihop scenarios through a detailed simulation study in NS-2. Simulation results show the suitability of AEEMAC in extending network lifetime of WSNs as compared to SMAC. Keywords— MAC Protocols, Energy efficiency, Idle Listening, Adaptive Listen, Sleep mode, AEEMAC, Reuse of Channel, Combined SYNC-RTS, Combined ACK-RTS
2) Control Packet Overhead: Sending and receiving control packets consumes energy too, and less useful data packets can be transmitted. 3) Idle Listening: The major source of inefficiency is idle listening i.e. Listening to receive possible traffic that is not sent can consume extra energy. 4) Overhearing: Meaning that a node picks up packets that are destined to other nodes can unnecessarily consume energy. The main goal of any MAC protocol for wireless sensor network is to minimize the energy waste due to idle listening, overhearing and collision. In this paper, we investigate the main causes of energy waste in the MAC layer of WSNs and their existing solutions and we present a protocol named ‘AEEMAC’ which employs duty cycling along with three additional optimizations to reduce overall energy consumptions. The proposed AEEMAC is originally inspired by SMAC [5]. In the remainder of the paper, a brief survey of related work is presented in Section II. The proposed AEEMAC is presented in Section III. For performance evaluation, we have implemented the AEEMAC over Network simulator 2 [10] and compared it with the existing SMAC protocol which is explained in section IV. The experimental results demonstrate that our AEEMAC is superior in terms of energy efficiency. Finally, the conclusions and future works are presented in Section V. II. RELATED WORK Many protocols have been proposed for wireless sensor networks that aim to improve energy efficiency. Most of them aim to achieve low energy consumption in transmitting packets between nodes. These protocols also have the goals of low delay and minimum packet loss. A MAC protocol decides when competing nodes may access the shared medium and tries to ensure that no two nodes are interfering with each other’s transmissions. In many WSNs, the traffic loads are low. For continuous monitoring applications nodes generate traffic periodically, while in event driven application, traffic tends to be bursty. The most common method of saving power is to use a periodic duty cycling mechanism; by turning off the radio when there is are no packet exchanges. Our proposed scheme, AEEMAC, also works based on the duty cycling mechanism; in this section we summarize existing duty-cycling MAC protocols. Existing work fits into the asynronous or preamble-sampling approaches and synchronous or scheduling approaches. Furthermore, some approaches like [12] are designed to adjust schedules to aggregate more packets and are used in data aggregation techniques of WSNs. A. Asynchronous MAC Protocols Asynchronous MAC protocols like LPL [6, 11], BMAC [7], XMAC [8] uses randomization and nodes do not synchronize time and contend for access to the radio channel. To reduce idle listening, protocols in this class shift the costs from the receiver to the sender by extending the MAC header, it allows nodes to check the channel periodically and sleep most of the time. Asynchronous MAC protocols minimize the uptime by using Low Power Listening (LPL) also called as Preamble sampling
[6,11]; however, the use of a long preamble limits the possible energy savings at long wake-up intervals. One of the disadvantage of LPL is preamble occupies the medium for much longer than actual data, it simply waste energy and accomplish nothing. And also preambles from hidden nodes continue Colliding for a long time hence waste time and energy. The preamble-sampling MAC protocols like BMAC, XMAC exploit LPL for sampling the preambles of the packets. LPL minimizes the duty cycle when there are no packet exchanges [11], but during transmissions the preamble needs to be longer than the wake-up interval to guarantee that the receiver detects the channel activity. Thus, the overhead of preambles becomes large as the wake-up interval increases. In XMAC, the overhead of transmitting the preamble still increases with the wake-up interval, limiting the efficiency of the protocol at very low duty cycles. B. Synchronous MAC Protocols Synchronous MAC protocols are in general require a mechanism to establish a non conflicting schedule regulating which participant may use which resource at which time. Schedule can be fixed or computed on demand. Time synchronization is needed and time is divided into slot. SMAC [5] also known as basic SMAC as depicted in Figure.1, and TMAC [9] are example of synchronous MAC protocols that synchronize the wake-up schedules of sensor nodes in a neighborhood. In SMAC and TMAC periodic sleeping supported by some means to synchronize wake up of nodes, to ensure meeting between sender and receiver. To synchronize the wake-up schedule, nodes periodically exchange SYNC packets. SMAC was the first duty cycling WSN MAC protocol where all nodes in a neighborhood simultaneously wake up and listen to the channel. A drawback of this scheme is the need for a long uptime that has to include the collision avoidance backoff, RTSCTS [1] exchange and compensation for clock drift as well as waiting for eventual transmissions from the neighbors. TMAC reduces the uptime of SMAC by using a timer that shortens the uptime if the channel is idle; however its uptime is also much longer than LPL [6] time because the timeout should be longer than the summation of the length of the contention interval, the length of an RTS [1] packet and the turn-around time. C. Problem with basic SMAC The first problem with basic SMAC [5] is that since all nodes in a neighbourhood wake up at the same time, nodes cannot avoid overhearing the packets from their neighbours. SMAC prevent overhearing by using RTS/CTS; however RTS/CTS have relatively high overheads. AEEMAC provides a mechanism to avoid overhearing by sleeping upon receipt of CTS [1] for a different destination and reusing of channel. The second problem is the increased contention. At each synchronized wake-up time, every sender in a neighbourhood has to contend to acquire the channel twice (one for SYNC and the other for RTS). This high contention increases packet loss and degrades the energy efficiency and throughput due to the resulting collisions. It can also result in network layer congestion, which, in turn, deteriorates application-level
reliability. In basic SMAC, sleep and listen periods for all nodes are predefined and constant which decreases the efficiency of the algorithm under variable traffic load. In basic SMAC, control packets like RTS occupies the medium for much longer time than actual data, which in turn blocks transmissions from neighbours. RTS from hidden nodes continue to collide for a long time, which wastes time and energy, and accomplishes nothing. Therefore, as a solution to this problem caused by hidden node is reduced by using optimizations in AEEMAC. Our proposed AEEMAC protocol aims at solving all the above mentioned problems of SMAC while inheriting many of its advantages.
Figure.1 Basic SMAC without reusing of channel
III. AEEMAC PROTOCOL We propose a MAC protocol, named AEEMAC (Adaptive Energy Efficient MAC), which is a modification of SMAC [5] protocol and uses scheduling concept as in SMAC. Like in basic SMAC, AEEMAC employs duty cycling to save energy by avoiding idle listening, but incorporates three additional optimizations to further improve energy efficiency at MAC layer. These optimizations are – (i) adaptive sleeping and reusing of channel, (ii) use of combined ‘SYNC-RTS’ control packet, and (iii) use of combined ‘ACK-RTS’ control packet. In AEEMAC schedule updating is accomplished by sending a SYNC packet. The SYNC packet is very short, and includes the address of the sender and the time of its next sleep. The next sleep time is relative to the moment that the sender starts transmitting the SYNC packet. When a receiver gets the time from the SYNC packet, it subtracts the packet transmission time and use the new value to adjust its timer.
Figure.2
First optimization over SMAC; using reuse of channel
First optimization, Optimization 1 is based on the concept of adaptive sleeping and reusing of channel. Motivation behind Optimization 1 is that, in basic SMAC due to overhearing and collision of RTS packet, nodes stay awake needlessly long time although there is no data to transmit. In basic SMAC, when two nodes send to a common receiver almost at the same time, collision occurs at the beginning of the cycle, as shown in Figure.1, when a new node, ‘node 3’ wants to send data in the middle of an ongoing data transmission between ‘node 1’ and a common receiver, ‘node 2’, then RTS of ‘node 3’ fails because
it finds the channel as busy, and hence radio of ‘node 3’stay awake (or stay in reception mode) for a period equal to the length of the size of ongoing data transmission. As soon as ‘node 2’ completes data reception, it observes there are no neighbouring nodes that want to transmit data into it. It means that channel is idle, although there is a node i.e. ‘node 3’ that wants to transmit data to the ‘node 2’. Therefore, all the nodes will go to sleep mode for the rest of the period, i.e. up to next cycle. In this case, as shown in Figure.2, at the beginning of cycle, ‘node 3’ will wait for CTS reply for a time period equal to ‘RTStime + Latency time + CTStime’. It is to be noted that ‘node 3’ will send RTS at most 3 times. ‘Node 3’ overhears CTS reply from ‘node 2’, which is destined for ‘node 1’ and copies the ‘duration’ field from CTS control frame, where ‘duration’ represents the length of the ongoing data transmission. Since no communication is possible for ‘node 3’ during this ‘duration’, it will go to sleep mode i.e. radio will be in off state for a period of ‘sleep time’ equal to ‘duration’. ‘Node 3’ will wake up after that ‘duration’, and its radio will be in ON state. It overhears ACK from ‘node 2’ which was destined for ‘node 1’, ‘node 3’ sends RTS to ‘node 2’and receives a ‘CTS’ reply from ‘node 2’. Now normal data transmission will go on. After data reception is over, ‘node 2’ acknowledges to ‘node 3’ with ‘ACK’. Before going to sleep mode, nodes will wait for a time period equal to ‘timeout’ and after every cycle, time synchronization takes place by broadcasting SYNC packet. For smaller data size, node requires less data transmission time, as compared to cycle period. Hence, the time gap between ‘data transmission time’ and ‘next cycle period’ can be used for new data transmission in between ‘node 3’ and ‘node 2’.This can be termed as reuse of channel, which will lead to better channel utilization, and saves more energy. The reuse of channel has a requirement that the receiver node must have sufficient remaining energy. Optimization 1 leads to less number of packet collisions and avoids overhearing, and nodes periodically go to sleep mode. Hence, Optimization 1 can improve channel utilization and can reduce the time a pair of node occupy the channel. This optimization is used for channel utilization. Successful exchange of RTS/CTS packets between two nodes imply that they should stay awake in the whole sleep period, followed by the current listen interval, for the completion of their data communication. The problem is that, while no nodes have data traffic to send during some time frame, and hence no RTS/CTS packet transmissions may occur in the corresponding listen period, every node still has to be awake and just waste their energies. Such inefficiency is caused mainly by the fact that SMAC and TMAC does not consider the actual traffic information in the network. This observation leads us to propose a new energy efficient sensor MAC protocol AEEMAC with second optimization that allows the nodes to go to sleep early even in the listen period when they are aware that nobody has data packets queued at the current time frame. Second optimization, Optimization 2 works based on the concept of combining control packets “SYN” and “RTS” in to a single control packet “SYNC-RTS’ and then transmit, as shown in Figure.7. Figure.3 and Figure.4 shows ‘SYNC’ and ‘RTS’
packet format that are used in basic SMAC. Note that if a sensor node wants to win the channel by sending SYNC firstly, this node is assumed to send RTS subsequently for data transmission. From this point of view, it is possible to combine SYNC and RTS to a single ‘SYNC-RTS’ packet. If there are any data burst at the beginning of a cycle, RTS packet is piggybacked into SYNC packet – refer to Figure.5, and source node initiates transmission process by sending a ‘SYNC-RTS’ to destination node. The destination node replies with CTS [1]. After receiving CTS, sender node sends data. After successful reception, destination node replies with an acknowledgement frame (ACK). Therefore, using ‘SYNC-RTS’, AEEMAC results in much reduced number of control packets than SMAC, which is similar to 802.11. There are at least two advantages of it: First, less control packets contribute to reducing the control overhead wastage and lessen the probability of collision; Second, using ‘SYNC-RTS’ can strive more phases for AEEMAC to content usable channels for each time-slot, and hence is very helpful to improve the channels utilization. This optimization is used for collision avoidance. Length
Type
State
Figure.3
Sync node
Source address
Sleep time
CRC
‘SYNC’ packet format used in basic SMAC
LengthType State Source Address Dest Address Duration (NAV) CRC Figure.4
‘RTS’ packet format used in basic SMAC Source Dest Sync Sleep Duration CRC Length Type State node Address Address Time (NAV) Figure.5 Combined ‘SYNC-RTS’ packet format used in AEEMAC LengthType State Source Address Dest Address Duration (NAV) CRC Figure.6
Combined ‘ACK-RTS’ packet format used in AEEMAC
Use of combined ‘SYNC-RTS’ control packet in between two cycle as in a scenario like in Figure.1 will cause resynchronization of nodes and it will waste lots of energy. For such cases only ‘RTS’ will be used in place of ‘SYNC-RTS’, this is an exception in AEEMAC. So control packets used in AEEMAC protocol are ‘SYNC-RTS’ for beginning of cycle, ‘RTS’ for rest of the cycles, ‘CTS’ and ‘ACK’ only. Using the similar concept of using combined ‘SYNC-RTS’, there is another scope for improvement by using the concept of combining ‘ACK’ and ‘RTS’ control packet in to a single ‘ACK-RTS’ control packet. Finally, the third optimization, Optimization 3, is based on the concept of combining ‘ACK-RTS’ control packet. Motivation behind Optimization 3 is that, when two nodes engage in bidirectional data transmission, then instead of sending an independent ACK packet, the receiver side can combine ACK packet with an RTS of the reverse direction. Generally independent ‘ACK’ and ‘RTS’ control packets are used as an acknowledgment and ‘Request To Send’, but as an optimization instead of sending independent ACK and RTS, receiver side can combine control packet ‘ACK’ and ‘RTS’ in to a single control packet ‘ACK-RTS’ and then transmit, as depicted in Figure.7 Since ‘ACK’ and ‘RTS’ have common fields, so there is a possibility to combine control packets ‘ACK’ and ‘RTS’ to a single ‘ACK-RTS’ as shown in Figure.6. Such combination can be achieved by allowing a node to embed the RTS into ACK packet. Therefore, Optimization 3 results in reduced number of
control packet then basic SMAC. Hence reduced no of control packets contribute to reducing the control overhead wastage and lessen the probability of collision and can improve channel utilization by striving more phases for AEEMAC to content usable channels for each timeslot. Optimization 3 is applicable to multihop communications. The concept of combined ‘ACKRTS’ will strive more time for channel contention, and will further save energy of the sensor nodes.
Figure.7 Second and Third optimization; using combined control packets
Using all the above optimizations together saves lots of energy by reducing hidden terminal problem, collision and overhearing and increase channel utilization. Finally, nodes in AEEMAC protocol periodically go to sleep mode and spend much time in sleeping mode, hence spend less energy in idle state. From the above discussion, we can predict that AEEMAC will outperform SMAC in terms of energy saving. We evaluate AEEMAC and compare its performance with basic SMAC through a simulation study in section IV. IV. PERFORMANCE EVALUATION For the purpose of determining energy efficiency of the proposed AEEMAC protocol, we have carried out simulation studies in different network topologies including both single hop and multihop environments. We have incorporated the proposed optimizations in the basic model of SMAC using Network Simulator 2 [10]. For performance evaluation, we compare the energy efficiency of AEEMAC with basic SMAC [5]. The aim of this simulation study is to evaluate how much energy efficiency AEEMAC can provide and whether it can conserve energy without degrading service quality in terms of end-to-end delay, average throughput, and packet delivery ratio compared to SMAC protocol. A. Simulation Setup and Parameters To evaluate the performance of AEEMAC protocols, we perform simulation studies in the networks of grid, simple and linear topologies as shown in Figure.8, Figure.9, and Figure.10 respectively.
Figure.8
A Multihop GRID Network
1) Grid Topology: We have chosen a sample grid topology, in which both single hop as well as multihop communication is required to deliver packets from source to destination. Due to
multihop transmission, rate of packet drop due to collision is higher. It consisting of 15 nodes, arranged in a 3x3 grid, in which 9 nodes actively participates in data transmission where as rest six nodes are idle nodes. Centre node 2 acts as data gathering point or sink to which all other nodes send sensed data. There is a possibility of collision at the nodes 2, 6 and 9, but collision rate is much higher at node 2 as compared to nodes 6 and 9. This topology represents the data gathering application runs on a densely deployed WSN.
Figure.9
B. Simulation Results We choose energy consumption to evaluate the performance of AEEMAC protocol expressed in unit of Joules. To measure the energy consumption, we monitor changes in the state of the radio. We used counters that accumulate time in each state of the radio (e.g., transmit, receive, listen, sleep and wakeup). At the end of the experiment, considering the energy consumption in each state in “Table-II”, we compute the total energy consumption. The metric shows the energy efficiency of the MAC protocols.
A Linear network topology
Figure.11 Figure.10
A simple network topology
2) Linear and Simple Topology: We have chosen linear and simple topology of 5 nodes. Linear topology represents a linear network with lower contention level, and simple topology represents a simple network with higher contention level. For both topologies, we choose two source nodes which generate CBR packets at the rates of 512KB/s and one destination node, which are in the communication range of each other. The grid, simple and linear topologies was chosen because information from sensor nodes are usually collected at a central node for processing, typically a sink node. The sink node collects the information from sensor nodes, processes it and decides what actions to take. Apart from the sensed data, the information that is exchanged by the sensor nodes is the routing information, we computed the energy consumed at the all nodes by keeping track of all the transmission. 3) Simulation parameters “Table-I” shows the values of different parameters used in our simulation study which are same as in [2] to facilitate comparison of AEEMAC and basic SMAC. For performance evaluation, we measure total remaining energy, energy consumption in idle and sleep state, energy consumption in transmission and reception, of source node when using different MAC protocols.
Remaining energy analysis of AEEMAC for grid networks
Figure.11 shows the total energy consumption results obtained for AEEMAC protocol with respect to SMAC protocol through the whole simulation time. According to the Figure.11, we can see that for every round of simulation time the energy saving ratio is above two, which is 2.37 in average. It means that AEEMAC saves double the energy as saved by basic SMAC. Hence we can conclude that AEEMAC outperforms SMAC by a factor of 2.37 times. Overall, our AEEMAC can save energy significantly and works more efficiently. For instance, with grid topology as in Figure.8, and with the configuration as explained in Table-I, AEEMAC saves as much as 57% of the energy over SMAC.
Figure.12
Idle state energy analysis for grid networks
Figure.13
Sleep state energy analysis for grid networks
TABLE I. SIMULATION PARAMETERS Parameters Radio propagation model Routing protocol Initial energy (Joule) Receive power (Joule) Transmit power (Joule) Transition power (Joule) Idle power & Sleep power (Joule) Transition time (in sec) Total simulation time (in sec) Traffic rate (in kbps), packet size (B) Type of Traffic
Values TwoRayGround DSDV 1500 1.4 1.7 0.055 1.0, 0.002 0.015 1400 512, 512 CBR
Figure.14
Transmission and Reception energy analysis for grid networks
Figure.12 and Figure.13 shows the energy consumption for AEEMAC and SMAC in idle and sleep state for multihop grid network scenario. Due to overhearing avoidance and collision avoidance using RTS packet as explained in Optimization 1 leads to less number of packet collision, and using the concept of combined SYNC-RTS packet as explained in Optimization 2 results in much lower number of control packets contribute to reducing the control overhead wastage and lessens the probability of collision and saves more energy. When node have collision and overhear RTS of other nodes then nodes go to sleep mode by overhearing RTS, and hence saves energy by going to sleep mode and hence spend less energy in idle state. Since in AEEMAC less packet collision and overhearing avoidance takes place, hence less energy are used for data transmission and reception between nodes as depicted in Figure.14, which saves over all energy of all nodes. C. Energy Efficiency with respect to Delay, PDR and Throughput “Table-II” shows the energy efficiency comparison of AEEMAC and SMAC with respect to other metrics for performance evaluation, i.e. delay, packet delivery ratio (PDR), throughput parameters. As expected, the delay of AEEMAC is very close to SMAC for simple and linear topology, and delay for AEEMAC protocol is less than that of SMAC for grid topology. Moreover, the AEEMAC protocol has a moderately lower average message delay. This is because the combined transmission scheme reduces the collision probability of RTS burst and saves more slots, especially unused slots, than the original protocol. In addition, the retransmission mechanism adopted in the AEEMAC protocol also reduces the queuing time of data messages. The PDR of AEEMAC is very close to SMAC for simple and linear topology and higher for grid topology. The throughput of the AEEMAC protocol is almost the same as that of the SMAC protocol for simple and linear topology. AEEMAC achieves a higher throughput than the SMAC, and the maximum throughput of the improved protocol is 1.09 kbps higher than that of the SMAC protocol which is 0.39. This is because there always are some DATA bursts queuing to transmit and consequently there are controls messages waiting for transmission when sending messages in reserved slot(s) and these control messages can be piggybacked in the message transmission with reservation slots. TABLE II. DELAY, PDR, THROUGHPUT COMPARISON Parameter Total Remaining Energy (J) End to End Delay (s) Packet Delivery Ratio (PDR) (%) Throughput (kbps)
Topology Simple Linear Grid Simple Linear Grid Simple Linear Grid Simple Linear Grid
SMAC 1270.33 1273.25 957.37 154.864 139.728 689.670 40.0 39.8 6.236 1.82 1.89 0.39
AEEMAC 1285.31 1285.33 1289.94 163.555 140.188 464.438 39.8 39.2 14.719 1.77 1.87 1.09
From the above discussion and experimental results as shown in above figures (Figure 11-14) and Table-II, we can conclude
that AEEMAC outperforms SMAC in terms of energy saving. Overall, AEEMAC can provide energy efficiency and it can conserve energy without degrading service quality in terms of end-to-end delay, average throughput, and packet delivery ratio compared to SMAC protocol. V. CONCLUSION In this paper we proposed an energy-efficient MAC protocol namely, Adaptive Energy Efficient MAC (AEEMAC) protocol, as an optimization over SMAC. Incorporation of three optimization schemes gives better energy efficiency for AEEMAC. In the protocol, adaptive sleeping and reusing of channel scheme and two ‘combined transmission’ schemes are proposed, in which control messages can be piggybacked in the messages with reservation slot(s). These schemes save slots resource and reduce the collision probability of RTS. The simulation studies conducted in different network topologies show that AEEMAC achieves better energy performance than SMAC. Furthermore, AEEMAC considerably reduces energy consumption while providing good end-to-end delay, packet delivery ratio and throughput in comparison with SMAC. Future work will include comparison of performance with TMAC [9], as well as finding optimal parameters for further reduction in energy. REFERENCES [1]
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