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Dynamic Power-Conscious Routing for MANETs: An Initial Approach Madhavi W. Subbarao, Member, IEEE National Institute of Standards and Technology 100 Bureau Drive Stop 8920 Gaithersburg, MD, USA 20899-8920 Phone: 301-975-4974 FAX: 301-590-0932 Email: subbarao@nist.gov October 12, 1999 use just that amount needed to maintain an ac- ceptable signal-to-noise ratio SNR at the re- Abstract | We develop an initial dynamic power- ceiver. Reducing the transmitter power allows conscious routing scheme MPR that incorporates spatial reuse of the channel and thus, increases physical layer and link layer statistics to conserve network throughput 1 . Altering the transmis- power, while compensating for the channel condi- sion power also reduces the amount of interfer- tions and interference environment at the intended ence caused to other networks operating on ad- receiver. The aim of MPR is to route a packet on jacent radio frequency channels. In networks a path that will require the least amount of total where nodes operate on battery power, conserv- power expended and for each node to transmit with ing power is crucial since battery life determines just enough power to ensure reliable communication. whether a network is operational or not. Mili- We evaluate the performance of MPR and present tary networks desire to maintain a low probabil- our preliminary results. ity of intercept and or a low probability of detec- tion 4 . Hence, nodes prefer to radiate as little I. Introduction power as necessary and transmit as infrequently A mobile ad hoc network MANET is an au- as possible, thus decreasing the probability of tonomous collection of mobile nodes that com- detection or interception. municate over relatively bandwidth-constrained The bene ts of power conservation control wireless links. Signi cant examples of MANETs for MANETs prompt the important question: include establishing survivable, dynamic com- What is the most power e cient way to route munication for emergency rescue operations, a packet from a source to a destination such disaster relief e orts, and military networks. that the packet is received with an acceptable MANETs need e cient distributed algorithms packet success rate 5 ? Since channel conditions to determine network organization connectiv- and multiuser interference levels are constantly ity, link scheduling, and routing. Message rout- changing with time, the transmitter power nec- ing in a decentralized environment where net- essary on a particular link must be determined work topology uctuates is not a well-de ned dynamically. In 7 , Wieselthier, Nguyen, and problem. Factors such as variable wireless link Ephremides address this problem in the context quality, propagation path loss, fading, multiuser of wireless multicasting, and in 3 , Pursley, Rus- interference, and topological changes, become sell, and Wysocarski consider this problem in a relevant issues. frequency-hopping ad-hoc network. In addition to the characteristics mentioned, In this paper, we conduct an initial inves- an important issue in network routing for tigation on the e ects of energy-e cient wire- MANETs is to conserve power while still achiev- less routing in MANETs. We develop an initial ing a high packet success rate. This can be ac- dynamic power-conscious routing scheme min- complished by altering the transmitter power to imum power routing -MPR that incorporates physical layer and link layer statistics to con- serve power, while compensating for the propa- 1 gation path loss, shadowing and fading e ects, power expended and for each node to transmit and interference environment at the intended with just enough power to ensure that the trans- receiver. The main idea of MPR is to select mission is received with an acceptable bit error the path between a given source and destina- rate . Threshold is a design parameter and tion that will require the least amount of total may be selected according to the network perfor- power expended, while still maintaining an ac- mance desired. Let E be the bit-energy-to-noise- ceptable SNR at each receiver. A cost" function density ratio, Eb =N0ef f , necessary at a node to is assigned to every link re ecting the transmit- achieve . ter power required to reliably communicate on Without loss of generality, consider a trans- that link. As an initial approach, the distributed mission from node i to node j , where i 6= j , Bellman-Ford algorithm can be used to perform and i; j 2 f1; : : :; N g, where N is the number of shortest" path routing with the cost functions nodes in the network. The received Eb =N0ef f is as the link distances. The resulting shortest given by path" is the MPR path from a given source to " a destination. We compare the performance of Eb PRij =D = N + P =W ; 1 MPR to that of shortest distance routing with N0ef f ij 0 Iij power control SD-PC and minimum hop rout- ing with power control MH-PC, and present where D is the data rate in bits per second, W our preliminary results. is the system bandwidth in Hertz, N0 =2 is the power spectral density of the thermal noise, PIij II. Power-Conscious Routing is the power of the interference at node j due A. System Model to all nodes excluding node i, and PRij is the received power at node j due to node i. From Consider a transmitter communicating with a the description in Section II-A, it follows that receiver at a distance of r0 in a MANET. As the the received power is given by transmitted signal propagates to the receiver, it , is subject to the e ects of shadowing and multi- PRij = KFij PTij rij ; 2 path fading, and its power decays with distance, i.e., PR KFPT r0 , where K is a constant, where PTij is the transmitter power used at , F is a non-negative random attenuation for the node i to communicate with node j , Fij is a non- e ects of shadowing and fading, PT is the trans- negative random attenuation for the e ects of mitter power, and is the path loss exponent. shadowing and fading on link ij , and rij is the At the receiver, the desired signal is corrupted by distance between node i and node j . Substitut- interference from other active nodes in the net- ing 2 into 1, we obtain work. We assume that nodes know the identity " of all other nodes in the network and the dis- Eb , tances to their immediate neighbors, i.e., nodes N0ef f ij = Sij PTij rij ; 3 that are within transmission range. Interfering nodes use the same modulation scheme as the where transmitter and nodes can vary their transmit power up to a maximum power Pmax . We as- Sij = DN KFij =W ; 4 0 + PIij sume that the multiuser interference is a Gaus- sian random process. At the receiver, the de- may be interpreted as a dynamic link scale factor coder maintains an estimate of the average SNR. re ecting the current channel characteristics and interference on link ij . These scale factors re- B. Minimum Power Routing Protocol ect a link's most recent reception environment. The aim of MPR is to route a packet on a Note that Sij 6= Sji since channel conditions are path that will require the least amount of total not symmetric. 2 It is desirable for Eb =N0eff ij to equal the en- ^ mission interval, and hence the value for Sij is ergy ratio E , since this is the minimum Eb =N0ef f valid for many packet transmissions. necessary to achieve the bit error rate . Hence, For every pair of nodes i and j , a cost Cij with knowledge of scale factor Sij , node i can given by easily determine the power PTij necessary to achieve this goal using Eq. 3, i.e., Cij = PTij 1 + if PTij 1 + Pmax ; 7 1 otherwise; PTij = E : 5 , Sij rij is assigned, where is a dampening constant to inhibit oscillations. The inequality in 7 is Let Eb=N0eff ij be an estimate of the re- necessary since the transmitter power is limited ceived bit energy ratio at the output of the de- by Pmax . The cost Cij is the power necessary coder at node j . Many methods may be used to communicate from node i to node j to com- to determine Eb =N0eff ij , e.g., using side infor- pensate for channel conditions and interference. mation by embedding known test symbols in Since nodes only know estimates of the link scale packet transmissions 2 . Although PTij was se- factors, the power required on a link must be lected to achieve energy ratio E at the receiver, overplayed. Thus, provides an extra margin since network conditions are changing, the ac- for the transmission power and is a design pa- tual received Eb =N0eff ij may di er from E . If rameter that must be selected. As an initial ap- node j has knowledge of the transmitter power proach, the distributed Bellman-Ford algorithm PTij which can be accomplished by including can be used to perform shortest" path routing PTij in the packet header, it can update its es- with the Cij s as the link distances. The resulting timated scale factor using a smoothing function shortest path" is the MPR path from a given as follows, source to a destination. If there is more than one path with the same minimum total cost, the ^ Eb=N0eff ij ^ MPR path is chosen as the one with the small- Sij = 1 , , + Sij ; 6 est maximum cost on any one link. MPR avoids PTij rij congested areas and is also minimax optimal, which mitigates the uctuations due to mul- i.e., given some uncertainty in the link scale fac- tiuser interference and is a smoothing fac- tors, it minimizes the worse case total path cost. ^ tor. An initial value for Sij may be computed as described in Section II-C. The estimated link C. Network Implementation ^ scale factor Sij accounts for variable channel Initially, nodes transmit using power Pmax , conditions and for all types of Gaussian inter- and the cost of every link is set to a constant d, ference, e.g., multiuser interference and partial- where d = Pmax 1+ . This will result in nodes band jamming. If the received bit error rate initially routing packets according to the mini- ij on link ij is less than threshold , the ef- mum number of hops to the destination. The ^ fect of 6 is that node j decreases its link Sij rst time node j for j 2 f1; : : :; N g, receives a value, indicating an increase in its interference transmission from another node, say node i, it noisy channel level, and thus, an increase in ^ will compute its link scale factor Sij , i.e, the power necessary to communicate on link ij as computed by 5. The opposite behavior oc- ^ Eb=N0ef f ij Sij = , : 8 curs when ij is greater than . Pmax rij Each time node j receives a packet from a node i, it computes and stores a value for The link costs will be computed as described in ^ Sij that accurately re ects its current SNR on Section II-B and propagated throughout the net- link ij . We assume that the rate of change of work. If the cost of a particular link has not the network is much slower than a packet trans- yet been computed within a speci ed amount of 3 time because no data packet was transmitted on put, end-to-end delay, e ciency, and average that link, a boost" packet is transmitted on the power expended are used to analyze the per- link and the link cost is computed. Once all of formance of the routing protocols. End-to-end the link costs have been computed, the routing throughput is de ned as the number of pack- protocol is now MPR. ets that successfully reach their nal destination The MPR path costs must be periodically cir- per unit time. End-to-end delay is based only culated around the network. This information on successful packets and is de ned as the av- can be passed around via data packets, acknowl- erage time required for a packet to arrive at its edgments, and special control packets known as destination. E ciency is the number of received packet radio organization packets PROPs 6 . data packets divided by the total number of data For this initial implemenation, we assume an un- packets and control packets transmitted. Aver- derlying information dissemination scheme. age power expended is the average power con- A dynamic routing table is maintained by each sumed in the network relaying successful packets node. For each destination, a node stores the including necessary control packets from their outgoing link for the most power-e cient route source to their nal destination per unit time. and the corresponding path cost, distance to First, we consider a 16 node static network the destination, and the necessary transmitter with packet generation rate = 10 pack- power. Since network conditions are changing, ets second node and a total of 10; 000 packets routing tables are continually updated based on being exchanged. The routing table update in- an update interval, and the transmission power terval is 10s, and the shadowing parameters are is altered on a per packet basis according to Eq. = 0:8 and TS = 5s. From Table II, we see 5. Before an update, if a link cost is deemed that MPR achieves approximately double the out-dated, i.e., the cost has not been recomputed throughput for similar power consumption lev- within a speci ed interval before an update, a els, or alternatively, requires approximately 2:5 boost" packet is transmitted on that link in or- times less power for similar throughput levels. der to compute a current link cost. The overall end-to-end delay is comparable for all schemes. While MPR does not optimize on III. Performance of Power Conscious the number of hops, it routes around undesir- Routing able links and hence, requires overall lower power consumption. Next, with the same network We compare the performance of MPR to that of SD-PC and MH-PC, and present our prelimi- nary results. The transmission power for SD-PC Parameter Value and MH-PC is altered to overcome the distance Network area 900 m x 600 m between the transmitter and intended receiver. Data rate 1 Mbps We use the modeling and simulation tool OP- Max TX power range 500 mW 250 m Min frequency 2.4 GHz NET to build a network prototype and execute Bandwidth 83 MHz the simulations. We assume a MANET using Modulation Direct-Sequence BPSK the ALOHA random access protocol. We con- Processing Gain 20 dB sider a slow fading log-normal shadowing en- Packet length 100 bits vironment, and vary the random attenuation ef- Shadowing 10 log F N 0; 64dB 2 , , , 3 x 10,4 ; 2:6; 0:8; 0:2 fects on a link every TS seconds according to a correlation factor. We assume that a node has Table I: Network simulation parameters. knowledge of the transmitter power used to com- con guration, we vary the packet generation rate municate with it and hence, uses 6 to update and plot the e ciency and average power ex- the estimate of its link scale factor. A list of the pended in Figures 1 and 2 respectively. We simulation parameters is given in Table I. see that as increases, the e ciency increases Performance measures of end-to-end through- until the point where further packet generation 4 Measure MPR SD-PC SD-PC MH-PC MH-PC Hops 30682 24945 15321 25075 17485 Overhead 0.0077 0 0 0 0 Pk delay*s 28.5 24.5 26 24.8 27.6 Pk pwr*mW 305 660 279 702 266 Hop pwr*mW 91.3 244 94.1 255 91.3 E ciency 0.95 0.92 0.51 0.92 0.6 Thruput pk s 9.58 9.2 5.15 9.13 5.7 Table II: Simulation results for a 16 node static network. * mean value of three trials causes excess levels of network tra c, and thus, a decrease in e ciency. MPR achieves approxi- mately double the e ciency as SD-PC and MH- PC for low values of and approximately a strik- ing 4:5 times higher e ciency for larger values of , since MPR adapts to changing interference Figure 1: E ciency vs. Packet generation rate levels. For low values of , MPR utilizes from . 30 , 50 less power relaying successful packets than SD-PC and MH-PC. For higher values of IV. Conclusion , although MPR utilizes approximately 50mW more power than SD-PC and MH-PC, since both We conducted an intitial investigation of MH-PC and SD-PC achieve low e ciency, most energy-e cient wireless routing in MANETs. of the total power expended in those schemes is We presented our preliminary results and con- on unsuccessful transmissions. clude that MPR shows promise as a power Finally, we introduce mobility into the net- conscious routing scheme for MANETs. MPR work with nodes moving at a speed of 4m=s and adapts to the changing channel conditions and investigate the e ect of di erent routing table interference environment of a node. The power- update intervals on MPR. The packet generation conscious concepts developed herein can be rate is = 10 packets second node. In Figure 3, adopted in other MANET routing algorithms. we plot the network e ciency verses update in- Acknowledgements terval frequency s. We consider the e ciency of only data transmissions, and the global ef- I would like to thank Jean-Sebastien Pegon ciency of both data and control packets, i.e., for his hard-work and diligent e orts in creating data packets received divided by total commu- the simulation environment in OPNET, execut- nication packets - both data and control. We ing the simulations, and producing the plots. see that as the update interval decreases, the data e ciency increases since the routing infor- References mation utilized is more current. However, the 1 L. Kleinrock and J. Silvester, Spatial reuse global e ciency increases until it reaches a point in mutlihop packet radio networks," Proc. where further updates cause too much overhead IEEE, vol. 75, pp. 156 167, Jan. 1987. communication, and hence, a decrease in net- work e ciency. Clearly, there is a trade-o be- 2 M. B. Pursley, The derivation and use of tween utilizing current routing information and side information the communication overhead generated. It is our in frequency-hop spread spectrum commu- conjecture, that the optimum update interval is nications," IEICE Trans. Commun., Special the same as the slow fading duration TS . Issue on Spread Spectrum Techniques and 5 Applications, vol. E76-B, pp. 814 24, Aug. 1993. 3 M. B. Pursley, H. B. Russell, and J. S. Wysocarski, Energy-e cient routing in frequency-hop packet networks with adap- tive transmission," in Proc. IEEE MILCOM, 1999. 4 F. J. Ricci and D. Schutzer, U.S. Military Communications. Rockville, MD.: Com- puter Science Press, 1986. 5 M. W. Subbarao, On Optimizing Perfor- mance in Mobile Packet Radio Networks. PhD thesis, The Johns Hopkins Univer- sity, Dept. Electrical Engineering, Baltimore, MD, Mar. 1998. 6 L. Westcott and J. Jubin, A distributed routing design for a broadcast environment," Figure 2: Average power expended vs. Packet in Proc. IEEE MILCOM, vol. 3, Boston, generation rate . MA, pp. 10.4.1 5, Oct. 1982. 7 J. Wieselthier, G. D. Nguyen, and A. Ephremides, Multicasting in energy- limited ad-hoc wireless networks," in Proc. IEEE MILCOM, Bedford, MA, Oct. 1998. Figure 3: MPR: E ciency vs. Update frequency s. 6

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