DYNAMIC RESPONSE ZONE ROUTING FOR MANET

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1 DYNAMIC REPONE ZONE ROUTING FOR MANET Rimantas Plestys, Rokas Zakarevicius Kaunas University of Technology, Department of Computer Networks, tudentu str. 50-4, Kaunas, Lithuania, Abstract. A mobile Ad Hoc network (MANET) is made of mobile nodes connected to each other via wireless links. The nodes function both as routers and as host devices. Routing protocols are responsible for reestablishing network routes that break off due to topology changes. Any routing protocol generates the additional stream of control packets the overhead. A response zone is a network space, where nodes send response control packets or forward request control packets further to the network. In this paper, the Dynamic Response Zone Routing algorithm is proposed, which operates by changing the response zone size according to the network structure in separate steps of routing process. Different cases of dynamic routing are simulated and results are presented in this paper. Keywords: Ad Hoc networks, response zone, location-based routing, signal strength. Introduction A mobile Ad Hoc network (MANET) is made of mobile nodes capable to communicate to each other via wireless links. Ad hoc network nodes function simultaneously as routers performing packet routing functions and as hosts sending and receiving data packets. The nodes can move freely or stay fixed in limited area and therefore the network may take different topology. The applications of MANETs include corporate, home and personal area networking, sensor networks, emergency services, military communications and etc. Ad Hoc network routing protocols are responsible for reestablishing network routes that break off due to topology changes. Any routing protocol generates the additional stream of control packets the overhead, which temporarily reduces the network bandwidth. It is desirable to minimize the amount of control packets and at the same time to get routes reestablished as soon as possible. Up to now, the definition response zone was not mentioned in any mobile Ad Hoc network research. Response zone is a space, where nodes send response packets or forward route control packets further to the network, i.e. the nodes react to the request packets they receive. Request zone is a space within the wireless signal transmission range of the node ; therefore, all the neighbour nodes inside this space receive all the packets sent. In this paper, the dynamic response zone routing algorithm for mobile Ad Hoc networks is proposed, which operates by dynamically changing the response zone in separate steps of the routing process in order to reduce the routing overhead. 2 Related work Depending on routing protocol activity, they can be categorized as table driven (proactive) and ondemand (reactive) routing protocols []. Table driven (proactive) protocols maintain consistent routing information about each node in the network. This information is updated regularly and stored on each node. Ondemand (reactive) routing protocols create routes only when desired by the source node. Ad-Hoc On Demand Distance Vector (AODV) [2] and Dynamic ource Routing (DR) [3] are reactive routing protocols for Ad Hoc networks, operating on the on-demand basis [], [2], [3]. They request a route only when needed and does not require nodes to maintain routes to the destinations that are not currently communicating. On-demand routing protocols operate by flooding the network with route request (Rreq) packets in all directions. uch floodingbased routing protocols (AODV and DR) generate a big network overhead, especially when the network is more dynamic and dense. There is a number of routing protocols proposed, seeking to achieve efficient routing by decreasing the overhead of route discovery. ome of these routing protocols use network node location information to find the route LAR [4], NB-GEDIR [5], GPR [] etc. The signal strength is also used in some routing protocol proposals [9], [0]. Location-based routing protocols use node location information to reduce the routing overhead of a network [4], [5], [], [7]. The assumption is made that each node knows the current locations of all other network nodes. Location-aided routing- (LAR-) [4] algorithm operates by flooding a fixed rectangular response zone with route search packets. The nodes inside the response zone forward the Rreq packets to other nodes, while nodes outside the response zone ignore the Rreq packets. In LAR-2 [4] case the response zone contains only the nodes that are closer to the destination node D than the node from which they received the route request packet. Each node in the request zone has to calculate the distance to the destination D to detect if it is inside the

2 response zone. Another location-based routing protocol No-Beacon Geographic Distance (NB-GEDIR) [5] also operates by calculating distances to the destination D. The source node or some intermediate node requests location information from neighbour nodes. The nodes in the request zone respond by sending their coordinates to the requesting node. After receiving the location reply packets, the source (or intermediate) node determines its next-hop node with the minimum distance to the destination D. Greedy On-demand routing using location information (GOLI) [7] protocol operates in a similar way as NB-GEDIR, but it also complements the route discovery process by defining a certain threshold within the radio range. The threshold helps to avoid selecting a next hop node that is very close to the boundary of the radio range in order to find the more stable route to the destination. The routing overhead can be even more reduced by making response zone limitations during the routing process [8]. The Limited Response Zone Routing (LRZR) [8] algorithm is based on the NB-GEDIR protocol, and operates by applying the limit radius r inside the request zone radius R in order to reduce the response zone and thus decrease the routing overhead. The radius r is inserted into the location request packet, and neighbour nodes check for their existence in the response zone by using distance calculations. I.e. location reply packets are being sent from the nodes that are farther from the source node than the distance r. The ignal tability-based Adaptive Routing (A) protocol [9] uses signal strength and stability of individual hosts as route selection criteria. Every node maintains the signal stability table by recording the signal strength values of its neighbour nodes and classifying the records to strongly connected and weakly connected. The signal strength is retrieved from link layer beacons that are being sent once every time quantum. The strongly connected nodes also have entries in the routing table, which is being dynamically updated by route search packets. The historical signal strength has been added as a factor into the location-based Beacon-Less Routing Algorithm (BLR), which improves in avoidance of routing into sparse area [0]. The signal strength is obtained from neighbouring nodes within a latest historical period, and is considered as a measure for the neighbouring density. It is assumed that the stronger the neighbouring signal strength, the more dense area the node is possibly in. As the BLR routing algorithm is efficient mostly in dense area, the use of signal strength allows improving it to choose the route direction to a more dense instead of sparse area. Excluding the sources mentioned the network node signal strength is not used as much in Ad Hoc network routing as other techniques, such as location-based or flooding-based routing. Therefore, there is a lot of space for making research in this field. 3 Dynamic Response Zone Routing (DRZR) algorithm As mentioned in the introduction of this paper, a request zone is a space within the wireless signal transmission range of the node. When the network nodes are distributed in an open space without surrounding obstacles and every Ad Hoc network node has the same transmitter power, receiver sensitivity and antennas, the request zone of a node is a circle around the node with the radius R s (Figure a). In such ideal case the request zone radius R is equal for every node. In Figure a, the signal strength of the node reduces evenly in all directions as the distance increases, and x > x2 >. x min and x 2 are the received signal strength values of the node (or at the corresponding points in the request zone. min is the marginal signal strength, corresponding to the request zone, i.e. it is the lowest signal strength possible for successful radio communication. However, often there are cases when terrain, transceiver and antenna diversity have a significant impact on the actual request zone of a particular network node. Therefore, the request zone can become irregularly-shaped, and even slight distance among the nodes may lower the signal strength significantly (Figure b). min dbm x 2 dbm min dbm x 2 dbm x dbm x dbm D R d R s a) b) Figure. Request zones: circles (a) and irregularly-shaped (b)

3 The mobile Ad Hoc network node density can be heterogeneous. When route request packets are being sent into the sparse network area, the use of fixed response zone limitations for location-based routing (as in [8]) can lead to failed route search as there can be no nodes sending back reply packets due to low density. Therefore, the routing algorithm has to change the response zone dynamically in order to adapt to network density changes. Most of location-based routing algorithms use only geographical distances among the network nodes during the route search process. Request zones can become irregularly-shaped in the networks with surrounding obstacles. Therefore, routing towards the shortest distance to a destination is not always the best choice, as it may lead to choosing the next-hop node with weak signal level. The received signal strength values could be used to avoid routing to the network nodes with low quality radio links. In order to implement all these features in routing, the Dynamic Response Zone Routing (DRZR) algorithm for mobile Ad Hoc networks (MANETs) has been developed. It is a location-based routing algorithm, which operates by dynamically changing the response zone in different steps of the routing process. The request zone nodes make decisions either being in a response zone or not, by evaluating the received signal strength levels of network nodes. The node location information is needed for DRZR operation. Initially it is assumed that the source knows the geographic location of the destination node D, and each network node knows its own location. The techniques of receiving and distributing the location information are not discussed in this paper, because they are beyond the scope of this research. In DRZR the response zone is set by applying the signal strength range [ k ; s k ], where < s and k is the current network node. The signal strength s limits the response zone from inside and from outside (Figure 2 and Figure 3). The signal strength values and s are calculated by the sending node according to the Free pace loss model. k_min k k The DRZR algorithm operates according to the steps below: a) The source node broadcasts the location request (Lreq) packet to all neighbour nodes within a wireless signal transmission range. The request contains the following data: (x ; y ), (x D ; y D ), [ ; s ], where (x ; y ), (x D ; y D ) is the location information of both source and destination D. b) On receipt of Lreq packets every node M in the request zone check its existence in the response zone by measuring the sender s received signal strength value p M and comparing with the signal strength range [ ; s ]. If ( M, (,, and pm s, the node transmits its location information (x M ; y M ) to the source in a location reply (Lrep) packet. c) After the receipt of Lrep packets the source chooses the node M i, which is closest to the destination D, i.e. ( M i, = min ( M,, and sends route request (Rreq) packet to the node M i. Now the node M i becomes the next-hop node and the route search process is repeated. The node M i is added to the routing table as a next-hop node for the destination D. If there are no nodes sending reply packets, the signal strength limit value s is increased and set to some new value s = s, where n s n > s n. Then actions from step a) are repeated. d) There are a number of different schemes for changing s and values. Usually s is being changed and is being fixed. For example, scheme { s = ( s ) ( s+ ) ( s+ 2) ( P ) works by changing s values in s = s has only one big step. In all cases of increasing s values, three smaller steps, as scheme { ( ) ( ) P the algorithm finally transforms into NB-GEDIR, where s = P and _ min =. P is the signal transmitting power of the node. However, it is desirable to keep higher than _min as long as possible to avoid selecting a next hop node with low signal strength, as signal receiving errors can occur in such case. If there are still no nodes sending reply packets, the route search process is aborted considering that the path was not found. e) Then the Rreq packet is received by the destination D, it is considered that the path has been found. As the Rreq packets have travelled all the way through a number of intermediate nodes, this circuit of nodes is considered the shortest route from the source to the destination D. There are cases then routes will not be found by using DRZR algorithm, even that they exist in the network. It happens when there is no any device M i, that ( M i, (,, even though some nodes exist in an opposite direction that could be used for route creation. In such cases, DRZR aborts the route search process considering that the route was not found, even when the route exists in the network. Here the flooding-based protocols (AODV or DR) should be used, because they will always find the route, if it exists in the network, although flooding the network with a large number of route request packets can reduce the quality of some network services

4 Figure 2. DRZR algorithm. Response zone is the shaded area. Request zone is circle-shaped. In Figure 2, ρ, ρ 2, ρ 3 are the distances from the nodes to the destination D, i.e. the radii of the arcs that limit the response zone from inside the request zone. The node M j will not send its location information since it is outside the zone, i.e. > s. The nodes M a and M b will not send their location information, because pm j ( M a, > (, and ( M b, > (, the signal threshold, i.e. pm k ( M i, (, p < s i and M. The node M k will not send its location information since it is outside <. The nodes M i and M f will reply with Lrep packets, because <, and ( M f, (, and < pm < s. The node M f i is elected to be a next-hop node, because it is closest to the destination D, i.e. ( M i, = min ( M,. Figure 3. DRZR algorithm. Response zone is the shaded area. Request zone in bold is irregularly-shaped. Due to surrounding obstacles, request zones are irregularly-shaped (Figure 3). The node M f will not send its location information since the node s received signal strength value at the node point M f is lower than the threshold specified in the Lreq packet, i.e. <. If the distance was used to set the response zone pm f instead of signal strength (as in LRZR algorithm [8]), the node M f would get into the response zone even having a weak signal level. Thus, limits s and the use of signal strength for response zone reduction helps to avoid routing to the network nodes with low quality radio links. The node M i will reply with Lrep packet, because ( M i, (, and < pm < s. It is elected to be a next-hop node, because it is the only node i that replied to the location request query

5 4 Routing protocol simulations The simulation programs have been written using MatLab to implement the newly proposed DRZR (Dynamic Response Zone Routing) algorithm. The operation of the NB-GEDIR routing algorithm was also implemented in the simulator, according to authors [5]. The purpose of the research was to perform routing algorithm simulations on the Ad Hoc network model in order to analyze the routing overhead and algorithm dynamics in separate steps of the routing process. 4. The network model It is required to create a universal network model in order to evaluate Ad Hoc network operation and simulate the performance of network routing protocols. A rectangular grid structure was chosen, which can be described by the matrix T= ( t ), where i=, m, j=, n. Network nodes can be in two states: On ( t = ) or Off ( t = 0). The Off state can also indicate the absence of the node in the network. Two main network model types should be emphasized: regular grid structure and shaped network structure. The regular grid network can be described by matrix T ( t ) =, where i=, m, j =, n =. Each matrix element corresponds to a network node, and the distances among adjacent nodes in perpendicular directions are equal. The network nodes are fixed. The request zone radius R is initially set before the simulation as well as the distances d among the network nodes. In shaped network case, some nodes can be in Off state, i.e. t = 0. Therefore, the network model can imitate different network topologies: circle, line, scattered network etc. imple shapes can be built from the regular grid network by setting appropriate nodes to the Off state, i.e. t = 0. In the scattered network case such network structure can be created by using uniformly distributed pseudorandom numbers. The matrix A elements a are pseudorandom numbers from the range [0; ]. uppose the number of matrix A elements is N = m n, and Z is the approximate desirable number of network nodes. Then the threshold value h=z/n is set, and the network matrix T is build using the formula (). t, = 0, when a when a The network node exists in the network when t =, and does not exist when t = 0. The network mobility can be simulated by changing the coordinates of each network node in every step of the routing process. 4.2 The simulations of routing dynamics In order to analyze and illustrate the performance of the DRZR algorithm the simulations were made on a randomly generated network. This network model imitates the network with a circle-shaped response zone. The signal strength threshold value was set to the minimum, i.e. = min dbm, so only the limiting signal strength s (db) was being dynamically changed during the simulations. and s are calculated by the sending node: s = P L( d ) and = P L( d 2 ). P is the transmitting signal power in dbm. L(d n ) is a path loss (in db) for a particular distance d n in free space, calculated using the formula (2), where d is a distance in kilometres, and f is radio frequency in MHz, and constant A= < h h ( d) 20 ( f) L( db) = A+ 20log0 + log (2) 0 The purpose of this simulation is to analyze the number of control packets (the overhead) in the network, generated by the operation of the DRZR algorithm, depending on the scheme used for maintaining the response zone size. Three DRZR algorithm operation schemes as well as NB-GEDIR algorithm have been simulated on two network cases, when R=500m and R=300m, in the same randomly generated network with approximately 400 network nodes. If there is assumed, that the radio signal transmission range is constant, then the size of the request zone corresponds to the density of the network. Therefore, the network when R=500m is more dense than the case with R=300m. The source node was in the middle of the network matrix, and the destination node D was at the upper right corner. The simulation results, when R=500m, are presented in Figure 4. The simulation results, when R=300m, are presented in Figure 5. The diagrams show the cumulative number of packets generated during the single route search process. As seen in the figures, there are three schemes of DRZR algorithm operation. s is the initial signal strength value, used to reduce the response zone from inside. The DRZR { s= ( s ) ( P) and DRZR { s= ( s ) ( s + ) ( s + 2) ( P) algorithm schemes can change the response zone size only in one direction the signal strength limit value s is being doubled (+db) in case of failure in getting any Lrep s= s s + s + 2 P packets, thus the response zone size is increases. However, the DRZR { ( ) ( ) ( ) ( ) ()

6 algorithm scheme changes the response zone size in two directions the s is being increased in case of failure in getting any Lrep packets, and s is being decreased backwards in case of a successful receipt of any Lrep packet. Therefore, the algorithm seeks to maintain the optimal size of the response zone by decreasing s value after it has been increased in the previous step of the routing process. The DRZR algorithm schemes differ in the number of steps the algorithm performs until it finally transforms into NB-GEDIR algorithm, where s= P and =. min 70 0 NB-GEDIR (s=p, =') DRZR { s ( s ) ( P) = Number of packets DRZR { s= ( s ) ( s + ) ( s + 2) ( P) DRZR { s= ( s ) ( s + ) ( s + 2) ( P) teps of the routing process Figure 4. The simulation results of the DRZR algorithm, when the request zone R=500. The routing overhead of the DRZR algorithm in all cases was smaller than NB-GEDIR algorithm. However, the route search process usually takes longer, becau se the location requests are re-sent when response zone size is changed. The algorithm case DRZR { s= ( s ) ( s + ) ( s + 2) ( P) creates lower overhead when comparing with case DRZR { s= ( s ) ( P), so it is more suitable to increase the size of the response zone gradually rather than removing response zone limitations on the first failure of getting a Lrep packet from neighbour network nodes. The DRZR algorithm with operation scheme { s= ( s ) ( s + ) ( s + 2) ( P) performed best in this simulation as the response zone was kept as small as possible during all the steps of the route search process. However, the route search takes the longest time when comparing with other algorithm cases simulated. This is because it takes more route search steps when often switching from smaller to bigger response zones and vice versa, as Lreq packets are being re-sent after each change DRZR { { s= ( s ) ( P) DRZR s= ( s) ( s + ) ( s + 2) ( P) 50 NB-GEDIR (s=p, =') Number of packets DRZR { s= ( s ) ( s + ) ( s + 2) ( P) teps of the routing process Figure 5. The simulation results of the DRZR algorithm, when the request zone R=

7 It can be clearly seen from Figure 4 and Figure 5 that the efficiency of dynamic response zone routing algorithm depends on the request zone size i.e. the network density. The denser the network, the more significant reduce in overhead can be achieved by changing the response zone forwards and backwards in every step of the route search process, when comparing with other routing protocols. 5 Conclusions The routing control packet stream is generated in the network during the route search process. It is desirable to minimize the amount of control packets and at the same time to get routes reestablished as soon as possible. A lot of research is being made to achieve efficient routing by decreasing the overhead of route discovery. ome of these routing protocols use network node location information to find the route, but the response zone is fixed during a route search. In this paper, the location-based Dynamic Response Zone Routing (DRZR) algorithm for mobile Ad Hoc networks is proposed, which operates by dynamically changing the response zone in separate steps of the routing process. As mobile Ad Hoc networks can be affected by surrounding obstacles or other factors, it is not always effective to rely only on geographical distances among the network nodes. Therefore, the signal strength is used in DRZR to reduce response zones. The signal strength values are calculated according to the Free pace loss model. The network nodes make decisions either being in a response zone or not, by evaluating the received signal strength levels of network nodes. The software simulations were made on the randomly generated network model in order to analyze and illustrate the performance of the DRZR algorithm, depending on the scheme used for maintaining the response zone size. They indicate that using the DRZR algorithm to adapt the response zone size in every step of the routing process results in lowest routing overhead. Adaptation is achieved by increasing or decreasing the response zone, depending on success or failure of getting the location information. However, the route search delay may increase, because of additional re-sending of location request packets after each change of a response zone. The efficiency of the DRZR algorithm depends on network density, and it is higher in denser networks. References [] Jayakumar G., Gopinath G., Ad Hoc Wireless Networks Routing Protocols A Review, Journal of Computer cience 3 (8): 2007, pages [2] Perkins C. E., Royer E. M., Ad-Hoc On-Demand Distance Vector Routing, Mobile Computing ystems and Applications, 999. Proceedings. WMCA '99. econd IEEE Workshop, Feb. 999, pages [3] Johnson D. B., Maltz D. B., Dynamic ource Routing in Ad Hoc Wireless Networks, Mobile Computing, T. Imielinski and H. Korth, Eds. Kluwer Academic Publishers, 99, ch. 5, pages [4] Ko Y-B., Vaidya N.H., Location-Aided Routing (LAR) in Mobile Ad Hoc Networks, Conference Proceedings, Mobile Computing MOBICOM, 998, pages -75. [5] Watanabe M., Higaki H., No-Beacon GEDIR: Location-Based Ad Hoc Routing with Less Communication Overhead, ITNG '07. Fourth International Conference on Information Technology, 2007, pages [] Karp B., Kung H.T., GPR: Greedy Perimeter tateless Routing for Wireless Networks, Proceedings of the ixth Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom 2000), August, 2000, pages [7] Nakagawa, H. Ishida, K. Ohta, T. Kakuda, Y., GOLI: Greedy On-Demand Routing cheme Using Location Information for Mobile Ad Hoc Networks, 2th IEEE International Conference on Distributed Computing ystems Workshops (ICDCW 0)., 200. [8] Plestys R., Zakarevicius R., Variable Response Zone Routing for Ad Hoc Networks, Information Technologies 2009: proceedings of the 5th International Conference on Information and oftware Technologies, KTU, Kaunas, Lithuania, 2009, pages [9] Dube R., Rais C. D., Wang K., Tripathi. K., ignal tability based adaptive routing (A) for ad hoc mobile networks, IEEE Personal Communication, Feb. 997 [0] Chen G., Itoh K., ato T., Beaconless Location-Based Routing with ignal trength Assisted for Ad-Hoc Network, IEEE VTC 2007 fall, Baltimore. UA, Oct