In Recent Years Advances in Semiconductor Technology Coupled with Reduced Cost of Wireless

Energy Efficient Arbitration of Medium Access in Wireless Sensor Networks

Gaurav Jolly and Mohamed Younis Dept. of Computer Science and Elec. Eng. University of Maryland Baltimore County 1000 Hilltop Circle Baltimore, MD 21250 [email protected] and [email protected] Abstract same transmission slots. However the TDMA scheme can be Networking of unattended sensors has become very complicated by the routing scheme employed at the upper attractive for many civil and military applications such as layers. Generally the energy consumed in transmitting disaster management and remote surveillance. Sensors in wireless data is directly proportional to dn, where d is the such applications are usually equipped with radio and distance between the transmitter and the receiver and n operated by limited energy supply. Such energy-constrained typically takes values between 2 and 4. Therefore, energy environment requires careful design in order to extend the consumption can be attenuated if packets are transmitted in life of the network. Time based arbitration of radio multiple hops of small distance instead of one longer range transmission among the sensors is one of the effective of transmission. techniques for energy conservation since it limits collision In a multi-hop routing scheme some sensors will receive and allows for turning off the sensor’s radio circuitry when multiple packets, and if the reception slots of these packets message reception is not expected. In this paper we propose are spread over the duration of the frame then the sensor will a Tabu search based time-slot assignment algorithm to have to be in the active state for extended duration of time. reduce energy consumption of the radio and eliminate packet Being in active state consumes excessive energy, and drop due to buffer overflow. This algorithm strives to consequently the advantage of TDMA diminishes. allocate contiguous transmission (reception) slots to each Alternatively to conserve energy a sensor should switch to sensor and thus minimizes both radio’s active time and low energy (sleep) mode when idle. number of transitions between active and sleep modes. The slot assignment issue is very challenging because it Reported simulation results demonstrate the efficiency of deals with two conflicting attributes. First, the sensors have our approach. small buffer size and hence they cannot buffer all the Keywords: Energy-Aware Communication, Sensor packets. If the buffer gets full any packets arriving after that networks, Energy-efficient design, TDMA slot scheduling. will have to be dropped and hence have to be retransmitted 1. Introduction thus causing energy wastage. Second, the active to sleep transitions consume considerable amount of energy and In recent years there have been major advances in the should be minimized by making the sensors transmit development of low power micro sensors. The emergence of (receive) all packets in contiguous time slots, but with small such sensors has led practitioners to envision networking of buffer sizes this is easier said than done. a large set of distributed low power sensors scattered over a Breadth first and depth first techniques have been wide area of interest. However, these sensors are usually applied to this problem 4. We propose a novel approach that powered using small batteries and in many applications of uses the Tabu search optimization algorithm. Simulation sensor networks replacing sensor’s battery is not possible or results show that the new algorithm outperforms BFS and not practical. Such energy constraints limits sensors’ lifetime DFS and achieves significant energy savings. and thus makes efficient design and management of sensor In the balance of this section we define the architectural networks a real challenge. Therefore a lot of the research model, the energy consumption model and summarize the related to sensor networks has focused on energy-awareness related work. Section 2 describes our approach to energy- and minimization 123. In this paper we concentrate on the aware scheduling of slots in sensor networks. Description of minimization of energy consumption at the MAC layer the simulation environment and analysis of the experimental through time-based arbitration of the sensor’s medium results can be found in section 3. Finally section 4 concludes access. the paper and discusses our future research plan. Since in TDMA sensors transmit and receive for only certain duration of time, the radio can be turned off when not 1.1 System Model in use making energy consumption to be much less The system architecture for the sensor network is depicted in compared to other MAC schemes. Moreover unlike other Fig. 1. In the architecture sensor nodes are grouped into techniques where collisions might occur because two clusters controlled by a single command node. Every cluster sensors, within the transmission range of each other may has a gateway node that manages sensors in the cluster. transmit at the same time. TDMA does not suffer from Clustering the sensor network is performed by the command collisions since any two adjacent sensors are never assigned node and is beyond the scope of this paper. Sensors are only with the increasing interest in the applications of unattended sensor networks 8. Power management of the radio gains significant importance in sensor networks since the radio is a major of Command Node consumer of sensor’s energy. Several methods have been suggested to reduce the energy consumption of the RF circuitry. One such technique is to power off the sensor

Sensor nodes when it is idle, by making active to sleep transition 911.

Gateway Node However time taken to make a transition from sleep to active mode consumes a considerable amount of energy. With Fig 1. Architecture of unattended sensor network small packet sizes the energy consumed due to transitions capable of radio-based short-haul communication and are becomes even more prominent and dominates the active responsible for probing the environment to detect a mode’s energy consumption 10. An approach to reduce such target/event. startup time in the radio circuitry was suggested in 11. The gateway node interfaces the command node with Energy saving through the use of time-based MAC in the sensor network via long-haul communication links. wireless sensor networks was explored in 4 12 13. The idea Sensors receive commands from and send readings to their is to schedule when to activate the radio receiver so that it gateway node, which processes these readings and transmits can be turned off while not expecting a message. Turning off the fused information to the command node. The command the receiver has been shown to achieve saving of up to 70% node performs system-level fusion of collected reports for in energy consumption 12. Approaches for determining overall situation awareness. Unlike sensors the gateways are when to turn off the receiver varies. While slots are significantly less energy constrained. Hence the gateway is prescheduled in 4, the decision for deactivating the receiving assigned the responsibility of organizing the sensors and circuit is made autonomous in 12 by probing the routing generated data. Sensor organization refers to environment. A reservation-based approach for scheduling activating a subset of available sensors in the cluster to medium access is pursued in 13. Nodes make a request to a probe the environment based on the application and sensor’s base station, which responds with a traffic control message capabilities. The gateway sets multi-hop routes and indicating medium access schedule. Nodes not included in periodically sends route updates to the sensors calculated the traffic control message can turn off their receiver. In this based upon the current state of the network. Route paper we present an approach for optimally assigning slots assignment will designate some sensors to act as relays. The with the consideration of routing paths. We believe that sensors then adjust their transmit power based upon their probing the environment or using reservation requests do not next hop neighbor. capture all the potential energy saving that time-based MAC Radios are assumed to have the ability to operate in four can achieve in sensor networks. distinct modes transmit, receive, idle and sleep. The energy Since long transmissions require more power, energy consumed in idle mode is almost equivalent to that in can also be saved if sensors transmit in multiple hops of receive mode 5. The energy consumed by the radio is: small distances instead of one long transmission. It has been Eradio = Ntx [Ptx (Ton-tx+Tst) +PoutTon-tx] +Nrx [Prx (Ton-rx+Tst)] shown in 14 that majority of packets received by the sensors …… (1) are for forwarding to other destinations. Where Ntx/rx is the average number of times per second Though akin to the above work in some aspects, the transmitter/receiver is used. Tst is the transition time from Tabu Search based technique presented in this paper is sleep to active mode. Ton-tx/rx is the on time of distinct since it deals with energy conservation through transmitter/receiver. Pout is the output transmission power. intelligent slot assignment with an objective of minimizing Ptx/rx is the power consumed by transmitter/receiver 2 6. the transition between active and sleep modes and the time The on-board clocks of both the sensors and the for which the radio is idle. Scheduling time slots can be NP- gateway are assumed to be synchronized, e.g. via the use of Hard especially when considering flow constraints and GPS. While the GPS consumes significant energy, it has to sensor’s capabilities limitations such as buffer size. be turned on for a very short duration during network 2. Slot Assignment in TDMA startup. TDMA based MAC enables the maintenance of clock synchronization afterward. It is worth noting that most Based on the current application mission, the gateway of these capabilities are available on some of the advanced selects a set of sensors to probe the environment. There are sensors, e.g. the SenTech Acoustic Ballistic Module 7. many energy aware approaches that the gateway can use in route setup, e.g. 5. Contingent upon these routes and the 1.2 Related Work buffer size of the sensors, the gateway then calculates the In wireless networks, signal interference has received the order in which transmission slots are assigned to active most attention from the research community. Only recently sensors, both probing and relaying. In order to conserve energy efficiency has started to receive attention, especially energy, active sensors should shut down their radio when to other optimization techniques Tabu search employs an they are not transmitting or receiving. iterative procedure in order to find a better solution in the Since the number of nodes managed by the gateway is neighborhood of the initial (current) solution. The search large, the number of possible schedules can increase process is concluded when a terminating condition, such as exponentially with the increase in sensor count. Therefore to maximum numbers of iterations or limited enhancements in overcome this limitation we propose a Tabu search based the solution, is met. Unlike other techniques Tabu search optimization algorithm for slot assignment. employs an evolving memory to prevent getting trapped in a Tabu search was introduced in 15 16 and subsequently local minimum. In the balance of this section we formulate has been used to solve many optimization problems. Tabu the slot assignment problem and discuss our approach to search has become an accepted technique that in some cases solve it. surpassed conventional optimization techniques. Analogous Table 1: Using BFS, some packets will not reach the gateway (maximum buffer size = 2). A total of 9 state transitions are needed. Sensor A and C are idle for one slot. (Tr = Transmit, Rec = Receive, Sl = Sleep)

Slot No. / Sensor ID 1 2 3 4 5 6 7 8 9 10 A Sl Sl Sl Sl  Rec Rec Rec(Drop) Tr Tr idle B Sl Sl Sl Sl  Tr  Sl Sl Sl Sl Sl C Sl Sl  Rec Rec idle Tr Tr  Sl Sl Sl D Rec Rec Tr Tr  Sl Sl Sl Sl Sl Sl E Sl  Tr  Sl Sl Sl Sl Sl Sl Sl Sl F Tr  Sl Sl Sl Sl Sl Sl Sl Sl Sl Gateway ------Rec Rec -

Table 2: Using Tabu search, there is no packet drop and a total of 9 transitions. No node is in idle mode for any of the slots (Tr = Transmit, Rec = Receive, Sl = Sleep)

Slot No./ Sensor ID 1 2 3 4 5 6 7 8 9 10 A Sl Sl Sl Sl  Rec Rec Tr Tr Rec Tr B Sl Sl Sl Sl Sl Sl Sl Sl  Tr  Sl C Sl Sl  Rec Rec Tr Tr  Sl Sl Sl Sl D Rec Rec Tr Tr  Sl Sl Sl Sl Sl Sl E Sl  Tr  Sl Sl Sl Sl Sl Sl Sl Sl F Tr  Sl Sl Sl Sl Sl Sl Sl Sl Sl Gateway ------Rec Rec - Rec

Table 3: Using DFS, total of 15 transitions take place. (Tr = Transmit, Rec = Receive, Sl = Sleep)

Slot No./ Sensor ID 1 2 3 4 5 6 7 8 9 10 A Sl Sl  Rec Tr  Sl Sl  Rec Tr Rec Tr B Sl Sl Sl Sl Sl Sl Sl Sl  Tr  Sl C Sl  Rec Tr  Sl Sl  Rec Tr  Sl Sl Sl D Rec Tr  Sl Sl  Rec Tr  Sl Sl Sl Sl E Sl Sl Sl Sl  Tr  Sl Sl Sl Sl Sl F Tr  Sl Sl Sl Sl Sl Sl Sl Sl Sl Gateway - - - Rec - - - Rec - Rec 2.1 Initial Solution sensors can be grouped based upon routes assigned to them. Fig. 2a represents a sample sensor network topology. It This observation significantly reduces the complexity of the consists of two clusters. Each cluster has its own gateway slot-scheduling problem since now the gateway has to deal that is responsible for assigning slots to sensors in the with smaller groups of sensors instead of one large set of all cluster. In the rest of this section we will concentrate on sensors in the cluster. For example in Fig. 2b two graphs are cluster #1 to illustrate our slot scheduling approach. The generated after the grouping the sensors of cluster gateway of cluster #2 follows the same methodology. In Fig. #1.Thereafter, one of these graphs is selected and 2a, nodes B, E, F, G and H are sensing nodes that generate transmission slots are initially allocated to its nodes using their own packets, while nodes A, C, D and I are relays. BFS. The paths followed by the packets of different branches For example, for graph #1, the first two slots are of the gateway are independent of each other. Therefore, assigned to nodes E and F, followed by slots # 3 and 4 allocated to D. Nodes B and C are allocated slots # 5, 6 and 2.2 Search Heuristic 7. Finally node A is assigned slots 8 to 10. However as shown in table 1, with a maximum buffer size of two this will result in one packet being dropped at node A forcing slot # 10 to be idle. Additionally if the latency in going from active to sleep and then going back from sleep to active is greater than one slot size then node C has to remain idle for slot number 5. In graph #2 nodes G, H can be allocated slots 11 and 12, with node I getting slots 13 and 14 for transmitting to the gateway. Hereafter we will only concentrate on graph #1 since graph #2 is dealt with in a similar fashion. To generate the initial solution for Tabu search an approach similar to BFS is employed. However at any stage if the buffer of any node gets full, it is assigned next few transmission slots equivalent in number to its buffer size. As shown in Fig 2c, node A is assigned slots 7 and 8 ahead of node C, when its buffer (buffer size = 2) gets full. This will prevent the buffer overflow at this node since the buffer will be flushed as soon it gets filled up. To increase the efficiency of the search, a divide and new area when trapped in local optima. This is implemented conquer scheme is employed. Tabu search is partitioned into by exiting each level if no improvement is made for a certain three distinct levels, each having individual Tabu memory. number of iterations. The algorithm is sketched in Fig. 3.

J a) G H I K Gateway-1 P M Gateway-2 A C N B L D E O F Cluster #2 Cluster #1 Sensor (Sensing A C mode) b) B G D I Sensor E H (Relay mode)

Graph #1 Level - 1 Graph #2 c) Slot No. 12345678910ReceiveDDCCAAGatewayGatewayAGatewayTransmitFEDDBCAACA

Level - 2 d) Slot No. 12345678910ReceiveDDCCAAGatewayGatewayAGatewayTransmitFEDDCCAABA

Level - 3 Fig 2: a) Initial Topology represented as graphs b) Cluster-1 after partitioning into distinct graphs c) Node A is selected at level-2 of Tabu Search d) At level-3 slots of B and C are exchanged In the first level, one of the graphs generated by the initial Table 2 shows a transmission schedule when applying solution is selected and passed to second level for our approach. For the sake of comparison we include the optimization. This process is repeated until all graphs have schedule using DFS in table 3. Comparing table 2 to tables 1 been optimized. Moreover the selected graph is added to the and 3 demonstrates the superiority of our approach to BFS Tabu list so that it will not be selected again. For example in and DFS, both in terms of packet drop count and energy Fig 2b graph 1 is selected. consumption due to both transitions and idle time. In level two, one of the nodes of the selected graph is 3. Experimental Validation picked and passed to the third level for optimization. The The effectiveness of our approach is validated through second level is repeated until all nodes have been optimized simulation. This section describes performance metrics, or the maximum number of iterations has been reached. This simulation environment and experimental results. node is then added to the Tabu list of this level. For example in Fig 2c out of nodes A, B, C, D, E and F, node A is 3.1 Performance Metrics selected.  Buffer-caused packet drop count: the total number of In level 3, slots assigned to in-bound branches (links) of packets dropped by the nodes due to buffer overflow. This the selected node are swapped. For example slots assigned to should ideally be zero to avoid retransmission. nodes B and C are swapped in Fig 2c to get a new schedule  Sensor’s energy unnecessarily consumed: This measures in Fig 2d. Thereafter the energy consumed by the new energy consumed by sensors while turning the radio solution is compared with the energy of the current (best) circuitry on and staying idle and due to transitions solution. If new solution consumes less energy, it will between active and sleep modes. become current solution. The swap move is saved in to the  Total gateway energy consumed for slot scheduling: This Tabu list of this level so that it is not repeated again. This metric quantifies the price that the gateway pays for level is terminated either when all the swap moves are in the energy saving at the sensor level. Tabu list or maximum numbers of iterations is reached.  Number of search iterations: It is used to study the trade- Since most improvements are found at the branches of off between energy saving at the sensor level and the cost the nodes, level-3 searches extensively at the branches. at the gateway level. Diversification is the procedure of shifting the search to a 3.2 Environmental Setup approach against DFS and BFS. The results are shown in In the experiments varying number of nodes are randomly figures 5 and 6. As can be seen from Fig. 5 our approach placed in a 10001000 meter square area. The gateway is eliminates packet drop. randomly positioned within this area. A free space Packet drop count propagation channel model is assumed 17 with the capacity 160 t

set to 2Mbps. Packet lengths are 10 Kbit for data packets. u Tabu Search o 120 c Breadth For a node in the sensing state, packets are generated at a p 100 o

r Depth

constant rate of 1 packet/sec 7. The time taken in making a t

e 60 k c

transition between the sleep and active states is assumed to a 40 be 470µsec. The power consumed at the circuit level in P 20 0 transmission and reception of a packet is set to 81mW and 2 4 6 8 10 12 180mW respectively 2. The energy consumed in the Buffer Size transition is obtained by multiplying the transition time by Fig. 5: Effect of Buffer Size on Packet Drop Count. the average of the power consumed while the radio is in active and sleep states. A radio circuit in a sleep mode is Fig. 6 displays the energy consumed by active sensors assumed not to consume any power. Routes are computed due to transitions and idle state as an average of multiple based upon the approach proposed in 5. experiments. The results corroborate the practicality of our We assume that the sensors are tasked with a target- approach, since it combines the advantages of the other two tracking mission. The initial set of sensing nodes is chosen approaches. to be the nodes on the convex hull. The set of sensing nodes changes as the target moves. Since targets are assumed to Energy consumed by sensors ) come from outside, the sensing circuitry of all boundary J 60 m (

d 50 nodes is always turned on. Targets are assumed to start at a e m

u 40 Tabu Search random position outside the convex hull. These targets are s n

o 30 Breadth c characterized by having a constant speed chosen uniformly y 20 Depth g r between 4 and 6 meters/s. e 10 n E 3.3 Performance Results 0 100 150 200 250 300 We have studied the performance of our approach using the Number of Sensors above metrics. It should be noted that the reported energy consumption is for transitions between sleep and active Fig.6: Effect of number of sensors on the average energy consumed modes and for being in the idle state. Energy consumed in by a sensor in idle state transmission and reception has not been presented here Cost and benefit of algorithm: In order to examine the pay- because the number of transmission/reception slots remains off of the algorithm at the system’s level, we conducted a set the same and our algorithm only changes the ordering of of experiments and calculated the energy consumed at the these slots. gateway and corresponding energy conserved by a group of Appropriateness of our Approach: For this experiment we 15 active sensors monitoring a moving target. The varied the packet sizes and observed its effect on the energy experiments were conducted on a Pentium 850MHz processor where the power consumption of the CMOS consumed by the system due to transitions. As the packet 2 sizes were reduced the energy contributed due to transitions circuitry is given by P= 1/2CV f, where C is the load increased manifold. Therefore as shown in Fig. 4 for smaller capacitance and taken to be 10 pico Farads, V is the supply packet sizes effect of transitions becomes more conspicuous voltage and equals 3.3 Volts and f is the clock frequency in and hence the significance of our approach increases. Hertz18. The execution time is measured and then and )

J multiplied by the power consumed in order to calculate the m (

r Energy consumed versus the packet size

o depleted energy in running the algorithm. The results in Fig. s n

e 4 7 show that increase in the number of iterations performed in s / 3.5 d

e 3 the Tabu search reduces the energy consumption of the m 2.5 u

s sensors to almost 50 % at a reasonable cost. After a certain 2 n

o 1.5 c

number of iterations there is no improvement in the solution

y 1 g r 0.5 and the gateway energy is unnecessarily wasted. Fig. 7 can e

n 0 e 100 1000 10000 100000 be used to perform trade-off analysis between the energy packet size(bits) conservation at sensor and gateway level. Depending on the energy reserve at sensors and the importance of their role it Fig. 4: Effect of packet size on transition energy might be justifiable to consume additional gateway energy to Comparison between time slot assignment algorithms: We run more search iterations. ran a set of experiments to compare the performance of our 4. Conclusion and Future Work [7] "Data sheet for the Acoustic Ballistic Module", SenTech In this paper we have introduced a novel approach that Inc., http://www.sentech-acoustic.com/ employs the Tabu search optimization technique for [8] J. M. Kahn, R. H. Katz and K. S. J. Pister, “Mobile assigning time slots in sensor networks. The approach Networking for Smart Dust”, in the Proceedings of the 5th conserves sensor’s energy by minimizing the number of ACM Mobile Computing and Communication (MobiCom transition between active and sleep modes and the duration 99), Seattle, WA, August 1999. in which active sensors are idle. In addition, our approach [9] V. Raghunathan, et al., “Energy aware wireless observes the buffering limitation at sensor’s node and microsensor networks”, IEEE Signal Processing prevents packet drop. Simulation results demonstrate that Magazine, March 2002. our approach outperforms contemporary approach such as [10] E. Shih, et al., "Energy-Efficient Link Layer for DFS and BFS. Wireless Microsensor Networks", in the Proceedings of In this paper we have assumed that the sensor network the Workshop on VLSI 2001 (WVLSI '01), Orlando, employs a TDM-FDM scheme where the nodes in different Florida, April 2001 clusters within transmission range or each other use different [11] A. Wang, et al., "Energy-Efficient Modulation and frequencies. We however believe that energy can further be MAC for Asymmetric Microsensor Systems", in the conserved, if nodes in each cluster can use the full Proceedings of ISLPED 2001, Huntington Beach, CA. bandwidth. We would like to investigate a scheme where August 2001. gateways could arbitrate among themselves and then assign [12] S. Singh and C.S. Raghavendra, “PAMAS: Power slots in a manner that despite using the same frequency the Aware Multi-Access protocol with Signaling for Ad Hoc sensors in distinct clusters that are in transmission range of Networks”, ACM Computer Communications Review, each other do not transmit in the same slot. July1998. References [13] P. Havinga, G. Smit, “Energy-efficient TDMA [1] A.A. Abidi, G.J. Pottie, and W.J. Kaiser, “Power- medium access control protocol scheduling,” in the Conscious Design of Wireless Circuits and Systems,” Proceedings of the Asian International Mobile Computing Proceedings of the IEEE, vol. 88, no. 10, pp. 1528-45, Conference (AMOC 2000), November 2000. October 2000. [14] V. Tsiatsis, S. Zimbeck, and M. Srivastava, [2] E. Shih, et al., "Physical Layer Driven Algorithm and “Architectural strategies energy efficient packet Protocol Design for Energy-Efficient Wireless Sensor forwarding in wireless sensor networks,” in the Networks", in the Proceedings of the 7th ACM Mobile Proceedings of ISLPED 2001, Huntington Beach, CA. Computing and Communication (MobiCom 2001), Rome, August 2001. Italy, July 2001. [15] F. Glover “Tabu Search, Part I,” ORSA Journal on [3] A. Woo and D. Culler, “A transmission control scheme Computing 1, pp. 190-206, 1989. for medium access in sensor networks,” in the [16] F. Glover “Tabu Search, Part II,” ORSA Journal on Proceedings of the 7th ACM Mobile Computing and Computing 2, pp. 4-32, 1990. Communication (MobiCom 2001), Rome, Italy, July 2001. [17] J. Andresen, et al., “Propagation Measurements and [4] K. Arisha, M. Youssef, M. Younis, “Energy-Aware Models for Wireless Communications Channels,” IEEE TDMA-Based MAC for Sensor Networks,” Proceedings of Communications Magazine, Vol. 33, No. 1, January 1995. the IEEE Workshop on Integrated Management of Power [18] J. Pouwelse, K. Langendoen and H. Sips, “Dynamic Aware Communications, Computing and Networking Voltage Scaling on a Low-Power Microprocessor,” in the (IMPACCT 2002), New York City, New York, May 2002. Proceedings of the International Symposium on Mobile [5] M. Younis, M. Youssef, K. Arisha, “Energy-Aware Multimedia Systems & Applications (MMSA'2000), Delft, Routing in Cluster-Based Sensor Networks”, in the The Netherlands, November 2000. Proceedings of the 10th IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS2002), Fort Worth, Texas, October 2002. [6] National Semiconductor Corporation, LMX3162 Evaluation Notes and Datasheet, April 1999.

Energy Consumption Versus No. of Iterations Sensors

n 1.6 600 Gateway i

1.4 J J e d 500 m m n m m ( u

( 1.2 a

s 400 a n e 1 n n o d w o o e o C i t

t 0.8 300 C i m a y

s y g G

e 0.6 r n

l g 200 r e a y d r i e

0.4 n b t n 100 E

E 0.2 0 0 0 13 31 34 67 Number of Iterations Fig 7. Effects of the number of search iterations on energy consumed by the gateway and the sensors.