Long lived path routing with received signal strength for ad hoc networks

Long-lived Path Routing With Received Signal Strength for Ad Hoc Networks Ruay-Shiung Chang+ and Shing-Jiuan Leu++ +Department of Computer Science and Information Engineering National Dong Hwa University, Shoufeng, Hualien, Taiwan, ROC email: rschanggmail.ndhu.edu.tw 'Department of Information Management Tung Nan Institute of Technology, Taipei, Taiwan, ROC Abstract-Routing paths in mobile ad hoc networks are easily disrupted due to the mobility of nodes Therefore, it is desirable to find a routing path such that all edges in the path are long-lived, Based on the Ad hoc On-demand Distance Vector Routing (AODV) 15, 251 protocol, we propose an AODV-RSS (AODV with Received Signal Strength) routing protocol such that connectivities of links in the route found can sustain longer The AODV-RSS algorithm uses the received signal strength, RSS, and the received signal strength changing rate, ARSS, to predict the link available time, LAT Using the LAT as a constraint, our method will find out a satisfying routing path Simulation results show that our routing algorithm can greatly improve the quality of the routing path in route connection time, and route reestablishment frequency Keywords: Ad Hoc Networks, Received Signal Strength, Ad hoc On-demand Distance Vector routing I INTRODUCTION Wireless networks provide mobile users with ubiquitous communication and information access capabilities regardless of their locations There are currently two variations of mobile wireless networks The first is known as infrastructured networks, i.e., networks with fixed and wired gateways A typical network is the cellular personal wireless communication system The second type of mobile wireless network is the infrastructureless mobile networks, commonly known as a Mobile Ad Hoc NETwork, or MANET [1] The infrastructureless network has no fixed routers Each mobile node operates not only as a host but also as a router, which discovers and maintains routes to other nodes in this network Example applications of ad hoc networks are emergency search-and-rescue operations and data acquisition operations im inhospitable terrains The mobility and limited computing capability of mobile hosts make the design of routing protocols challenging Many protocols have been proposed, such as DSDV [2], CGRS [3], WRP [4], AODV [5, 25], DSR [6], TORA [7], ZRP [8], etc Among them, AODV (Ad hoc On-demand Distance Vector) routing protocol is one of the most frequently mentioned It chooses a minimal hop-count path to be the routing path However, a path having the minimal hop-count does not always mean that it is the optimal routing path in various respects Even the smallest hop-count path may be longer than O-7803-9410-O/06/$20.OO ©2006 IEEE other paths in real distance It is highly probable that the spatial distance between intermediate nodes on the route is larger than another path The actually longer distance between neighboring nodes may give rise to path maintenance cost, reduce the * quait * * *' ch low packett mio rate,bhigh cof su ras power consuming rate [22, 23]) and suffer more path broken frequency The whole system performance will be affected by the inferior routing path In this paper we propose a routing scheme to improve the quality of edge connection time in the routing path found for mobile ad hoc networks This protocol is called AODV-RSS (AODV with Received Signal Strength) Our method is based on the received signal strength, RSS, and the received signal strength changing rate, zIRSS We use these parameters to forecast the link available time (LAD between two mobile nodes Then we can find a minimum hop count routing path that satisfies a minimum LAT constraint This method is very useful in the multimedia communication environment where there are real time flows and best effort flows A real time flow needs QoS guarantees, such as packet delay bound, delay jitter, bandwidth, etc Though a larger LAT does not necessarily translate into better QoS guarantees, it is a good start for finding such a path Using the LAT constraint, at least our routing protocol will produce a more long-lived and stable routing path for the real time flows The remainder of this paper is organized as follows Section describes some of the routing protocols for ad hoc networks Section describes the AODV-RSS routing protocol In Section 4, the simulation environment and the results of comparing the performance of our method and related work are presented Section concludes this paper II RELATED WORK In an ad hoc network environment, the routing protocol must keep up with the changing topology So, the routing algorithm is more complex then the other network environment Various routing schemes have been proposed in resent years In this section, we review some ad hoc routing protocols and categorize these researches into four types 1) Table-driven protocols 2) On-demand driven protocols 3) Location aided protocols 4) QoS supported routing protocols The table driven routing protocols (also known as proactive protocols) attempt to maintain consistent, up-to-date routing information from each node to every other node in the network These protocols require every node to maintain one or more routing tables and have to propagate its routing table contents throughout the network in order to have a consistent network view for every node In Destination-Sequenced Distance-Vector Routing (DSDV) [2] routing protocol, every mobile node maintains a routing table in which all the possible destinations in the network and the number of hops to each destination are recorded The contents of routing table are exchanged periodically The Clusterhead Gateway Switch Routing (CGSR) [3] is a cluster based DSDV routing protocol A cluster head controls a set of mobile nodes In a cluster, the DSDV routing protocol is used to maintain the routing path A gateway is the bridge of two or more cluster heads In the Wireless Routing Protocol (WRP) [4], each node in the network is responsible for maintaining four tables: (a) distance table, (b) routing table, (c) link-cost table, and (d) message retransmission list (MRL) table Mobile nodes send update messages after processing updates from neighbors or detecting a change in a link to a neighbor The neighbors then update their distance table entries and check for new possible paths through other nodes Any new paths are relayed back to the original nodes, so they can update their tables accordingly The on-demand routing protocols (also known as reactive protocols) create routes only when desired by the source node When a node requires a route to a destination, it initiates a route discovery process within the network Ad-hoc On-demand Distance Vector Routing (AODV) [5, 25] protocol builds on the DSDV algorithm It is a pure on-demand protocol, as nodes that are not on a selected path not maintain routing information or perform routing table exchanges When a source node wants to send a message to some destination node and does not have a valid route to that destination, it broadcasts route request (RREQ) packets to its neighbors The intermediate nodes re-broadcast the RREQ packet until the destination node receives the RREQ Upon receiving the RREQ packet, the destination node sends the route reply (RREP) packet back to the neighbor from which it first received the RREQ Except carry a series of node IDs, the Dynamic Source Routing (DSR) [6] routing procedure is very similar to AODV DSR allows nodes to keep multiple routes to a destination in their cache If a link on route is broken, the source node can select another valid route to the destination without re-start route discovery procedure Base on the link reversal concept, Temporally-Ordered Routing Algorithm (TORA) [7] uses a "height" metric to establish a directed acyclic graph (DAG) rooted at the destination A routing path from source to destination is found by DAG The Zone Routing Protocol (ZRP) [8] is for the re-configurable, large scale, and highly mobile ad hoc networking environment Through the use of the zone radius parameter, the scheme exhibits adjustable hybrid behavior of proactive and reactive routing schemes The location aided protocols are base on the knowledge of mobile host's location by using the global position system (GPS) Most related researches of location aided routing are focus on reducing the complexity of routing procedure and saving the routing message The most famous and original scheme is the Location Aided Routing (LAR) [9] According to the destination mobile host's location and moving speed, LAR computes the destination's excepted zone (a circle at destination's now location with radios speed multiply excepted time) A routing request zone is drawn as a rectangle from source's location to the excepted zone Only these nodes in the routing request zone can forward the routing request message, so the routing message is restricted in the routing request zone The routing message is saved Location Aided Knowledge Extraction Routing (LAKER) [10] uses guiding-route to reduce the complexity of ad hoc routing LAKER inherits the route strategy from DSR A forwarding-route in DSR is a series of node IDs from source to destination A guiding-route is a series of locations of the forwarding-route Using the guiding-route message, LAKER attempts to learn the information about the network topology and forward the routing request to the right way to be near to the destination A Location-Aided Power-Aware Routing (LAPAR) [11] protocol is proposed by Xue and Li This method used location aided to reduce the routing message overhead In order to save power consuming, power aware try to select a route with distance of any two mobile nodes is shorter Generally speaking, the topics of Quality of Service (QoS) may be related to bandwidth, throughput, packet delay, delay jitter, etc Having no fixed network infrastructure, QoS support in ad hoc network reveals more difficulties in many manners In order to discover a more stable path, the degree of association stability opinion is used in Associativity-Based Routing (ABR) protocol [12] The essence of ABR lies on the fact that a mobile host's association with its neighbor changes as it is migrating Its transiting period can be identified by the associativity "ticks" There are stable and unstable ticks The Signal Stability Routing (SSR) protocol [13], which selects routes based on the signal strength between nodes and on a node's location stability This method maintains a routing tables and the signal stability table The signal strength recorded in the signal stability table is characterized as strong or weak by the average received signal strength in the past few beacons A Core-Extraction Distributed Ad Hoc Routing Algorithm (CEDAR) [14] uses three key components: a) the establishment and maintenance of a self-organizing routing infrastructure; b) the propagation of the link state of high bandwidth and stable links; and c) a QoS-route computation algorithm to support the QoS routing in ad hoc networks The Flow Oriented Routing Protocol (FORP) [15] uses the mobile's moving direction, speed, and transmission range to predict the link expiration time, and then find out a route path according to this link expiration time Depending on the link expiration time concept, QoS support by bandwidth reservation is proposed in [16] If the available bandwidth on the path can't fit the bandwidth requirement, the connection request will be rejected Using the Global Positioning System (GSM), AODV Reliable Route Selection (AODV-RRS) [17] introduces the concept of stable zone and caution zone to discover a more stable routing path in ad hoc networks For improving network stability and total throughput, multiple paths routing protocols are proposed [18, 19] The total bandwidth of those paths cannot just be sum up because of "interference" The paper [20] discussed the "available bandwith" network capacity and "interference" according to different Media Access Control (MAC) protocols The Race-Free Bandwidth Reservation Protocol [21] is proposed for parallel bandwidth reservation in ad hoc networks For high-throughput and low power consuming, the excepted transmission count (ETC) [22] and medium time metric (MTM) [23] were proposed The ETX is defined as the inverse of packet forward probability (df) multiply ack reverse probability (dr) The MTM value was assigned by packet transmission rate A path has a high packet transmission rate will assign low MTM value A routing path with low ETX value or low MTM value will have a high-throughput III RECEIVED SIGNAL STRENGTH ROUTING ALGORITHM between node B and node A So the received signal at time t1, RSSBc(t]), is greater than RSSA,B(tl) at first But node B is moving toward node A, and node C is leaving from node B The received signal strength between B and C is decreasing over the time On the contrary, the received signal strength between A and B is increasing After a few minutes, the received signal strength of RSSA,B(t2) is larger than RSSB,C(t2) In our research, we are interest in using the received signal strength, RSS, and the received signal strength changing rate, ARSS, to calculate the LAT (Link Available Time) between two mobile nodes RS ti t2 sTime Fig Moving direction and RSS Let t1 be the time when node i and node j first detect the presence of each other With this understanding, we can simplify ARSS, j(t1,t2) to ARSS,J (t2) Therefore, without loss of generality, we use ARSS (t) to denote the RSS ij changing rate between time t and the time node i and node j first met To calculate the link available time, let D,j (t) denote the distance between node i and node j at time t and Sj j(t) denote the relative speed Assume TR is the radio transmission Minimum-hop count routing is the spirit of most routing algorithms But some researches [15, 16, 17, 22, 23] showed the minimum-hop count routing path will be an unstable, power waste, low packet deliver rate path In this section, we present a routing scheme to find out a stable routing path in ad hoc network Based on the Ad hoc On-demand Distance Vector (AODV) routing protocol, our scheme will try to find a route such that links in the route are long-lived This new routing protocol is called AODV-RSS (Ad hoc On-demand Distance Vector with Received Signal Strength) routing protocol , j a I The received signal strength will be larger when the distance ir of two mobile nodes is closer Our long-lived path routing node i and node j are moving toward each other, as shown in algorithm uses the Received Signal Strength, RSS, and Fig 2(a) The time needed before they are at their closest Received Signal Strength changing rate, ARSS to predict the points (Fig 2(b)) can be approximated by D,(t) After the link available time between two mobile nodes Let RSSij(t) S1 (t) denote the received signal strength seen by nodej with respect closest points, they will leave away from each other Their to node i at time t Assume a symmetric wireless network connection will be broken when each is at the border of the Then Define transmission range of the other (Fig 2(c)) The time for them RSSi,j(t)=RSSj,i(t) ARSS (t1,t2) = RSSJJ(t2)- RSSj (tl) , t2 >tl ARSSj ,t2) to move from the position in Fig 2(b) to that of Fig 2(c) can t2 -t be approximated by TR Therefore, the total time for the can be seen as the RSS changing rate from time t, to t2 Since Sj (t) If RSS1J(t)=~RSSi(t), we have ARSSJ(ti ~2) =ARSSji link between node i and node j to be effective is D, (t) + TR ARSSI j (tl, t2 ) > 0, it means that node i and nodej are closer at Sjj(t) time t2 than they were at time t, On the contrary, a negative Similarly, if ARSSij (t) is negative, node i and node j are ARSSij (tl, t2) means that node i and nodej are leaving away leaving away from each other The time needed for them to from each other Usually, RSS1,1(t) depends on the distance lose contact can be approximated by TR-D,(t) Combining between node l and node] at time t ARSS1j (t, (t2) depends on Si (t) how fast node i and nodej are moving relatively Therefore, we the above results, the link available time between node i and can use xRSSJ J(t,I,t2) as an indication of the relative speed nodej, LATj (t), can be defined as: between nodeiland node A large (t, ,t2) meansnode (1) if AIRSSJ (t) is positive, L ( Di.j(t)+TR ; else i and node]j are moving toward or leaving away from each l, S17(t)l other quickly Its concept is illustrated in Fig The distance (2)if tRS (t) is negative,= TR-DQj().between node B and node C is shorter than the distancel LA;jt= J(t, (t, t2), D:l ft) ^ v J * J ~ k(b) (a) ;"' TR (c) Fig The relative position of two approaching nodes However, from the point of view of node j (or node i), it does not have the values of Di,j (t) and Sj (t)9 From [24], Then assume RSS1j (t) is proportional to [Dj (t)]2 dRSS dD2 -2DdD dt dt dt S(t)oc D3ARSS 3ARS tRSS =-2D3S(t) Therefore ARSS Using the above reasoning, LAT j(t) can be redefined as: (1)if ARSS1j (t) () LATj (t)= (2) if LAT, (t)= is positive, is negative, ; else (RSS/ ,(t)) +TR (RSSj (t)) *ARSSj( ARSSi j (t) TR-(RSS 1(t))~ TR-(RSS,j (t)) (RSS (t))-3*ARSS, (t) 1l,1 Since RSS,j (t) and ARSSij (t) can be estimated in each node without extra information, the link available time can thus be computed The calculated LAT represents a measurement of how long two nodes can keep connected Assume a connection wants to transmit M bytes and a link's data transmission rate is N bits per second, the whole data transmission time for this connection will be M*81N seconds The AODV-RSS algorithm can use the data transmission time in the routing path discovery procedure as an LAT constraint Intuitively, if we set the LMT constraint to the data transmission time, it means that AODV-RSS algorithm can find out a routing path that can transmit the entire data without suffering any broken routing path That is, a connection using data transmission time as the LAT constraint will have a good service quality However, a higher LAT constraint will suffer from a higher connection rejection probability This is because a higher LAT constraint needs a longer link available time between any two mobiles The number of available paths for a higher LAT constraint will be less than others To decrease the route discovery time and increase the route discovery probability, less rigid LMT constraints may be used Using the above LAT constraint, our long-lived path routing algorithm will find out a minimum hop-count routing path that satisfies the LAT constraint In Fig 3, the number above the link between two mobiles means the link available time Assume, the LAT constraint is 14 Because the LAT of B-C does not satisfy the LAT constraint, the RREQ (Route Request) packet will not be sent to node C in AODV-RSS algorithm So, our algorithm will select A-B-D-E-F as the routing path Every link of this routing path satisfies the LAT constraint On the other hand, the routing path discovered by AODV will be A-B-C-E-F or A-B-D-E-F, depending on which path's RREQ packet is received first by F If the routing path discovered by AODV is A-B-C-E-F, it will suffer from more frequent path broken than the path found byAODV-RSS C D 15 Fig Routing path discovery example The routing path and maintenance procedure of AODV-RSS is establishment In the routing similar to AODV path discovery procedure, AODV-RSS algorithm just sends the RREQ packet to the nodes, whose link available time satisfies the LAT constraints If a RREP (Route Reply) packet is not received within the path discovery time, this connection request is rejected On the contrary, the packet is sent through the routing path until the path is broken due to the mobile node's moving If the source node receives a RERR (Route Error) packet or an ACK message is not heard from the receiver within a time period, the source node will re-send the RREQ packet to re-establish a new path In order to assess the performance of our algorithm, simulations are done to compare with AODV algorithm The simulation environments and results are described in the following section IV PERFORMANCE EVALUATIONS 4.1 Simulation Environments We evaluate the proposed AODV-RSS protocol by simulation and compare the performance with that of AODV protocol The link breakage is detected by the feedback of MAC layer in both protocols No additional network layer mechanism is used And the bandwidth limitation of each mobile node is not taken into consideration to simplify the simulation model In our simulation model, we generate 100 mobile nodes in a 1500*1500 square meters area The sides of the square are wrapped around The moving direction of each mobile node is a random variable of degree to 360 degree The mobile node's transmission range is 240 meters [17] The data transmission time of each connection is an exponential distribution with mean 50 seconds The mobility patterns are 12 different speeds (1, 2, 3, 4, 9, 10, 11, 12 meters per second) The node traversal time is a conservative estimate of the time that a packet spent before being retransmitted It should include queuing delays, interrupt processing times and transfer times The same as [25], the node traversal time is set to 40 milliseconds in our simulations The following characteristics are taken into consideration to measure the AODV and AODV-RSS routing protocols' perormance Thesecharacteristicsaredepictedas follows * Average Route Discovery Time: The time period from RREQ packet is sent from source node to the RREP packet is received by source Its value means the latency of connection established A lower value is better * Path Discovery Failure Probability: The path discovery 025 failure probability is the probability that the routing path for a new connection is not established in the first connection request A lower value is desired * Average Route Connection Time: The average time of a routing path from established to broken due to the node mobility A larger value is better, which means the path can delivery packet for a long time, not suffer any breach * Average Route Discovery Frequency: The moving of mobile node will lead to a broken routing path So a routing path will be re-established Its value indicates how many times the route discovery procedure is required for a packet transmitting connection is best, which means the network system find out a routing path and whole the packets are transmitted by this path without suffer any breach, but its value is always larger than However, a value closing to is better * Connection Broken Probability: When the routing path is broken, we find a new routing path for this connection The connection broken probability is the probability where the new path is not established in the first re-routing discovery time A lower value is desired The simulation program is written in SimScript Each simulation is executed for two hours The simulation results are the average of runs and these results are shown as follows 02U *AODV °/AODV-PSSJ l1 -005 p() 10 11 12 Fig Average path discovery failure probability vs mobility 0.n6 o0 o AOD V -X 003 002 e VMlR Q:)sS FAOD AODV-RSSC02) AODV-RSS(O6) Speed2 m79ec) Fig Connection broken probability vs mobility Increase the path discovery latency and path discovery failure probability, the goal of our method is to will find out a more stable path with long route connection time Fig shows the average route continuing connected time for AODV-RSS with different LAT constraint versus AODV routing protocol When moving speed is lower, our AODV-RSS algorithm is doing a good job in maintaining the connection For example, 4.2 Simulation Results in moving speed 1, AODV-RSS with 0.6 and 0.8 LAT Fig shows the average route discovery time per connection constraint will increase route connection time about seconds as a function of mobility (speed) for the proposed AODV-RSS, But from this Fig 7's tendency, we can see the routing with 0.2, 0.4, 0.6 and 0.8 LAT constraint, and AODV The connected time is shorter when the moving speed is higher In average route discovery time for AODV is about 0.28 second moving speed 12, AODV-RSS increases the routing connected According the trend of lines in Fig 4, we see the route time about 1.5 seconds for all LAT constraints That is because discovery time is increased by the higher moving speed and when the moving speed is high the LAT of any two nodes is higher LAT constraint At 12 moving speed of 0.8 LAT short in the whole network So, no matter how high the LAT constraint, the results show our protocol will increase the route constraint is, the route connection time will not increase discovery time about 0.05 second Fig shows the path substantially The average frequency of route discoveries for discovery failure probability As all we know, a higher LAT each connection is shown in Fig In moving speed 1, the constraint will suffer a higher failure probability But it is frequency of AODV is about 2, and the AODV-RSS is about gratified, that the path discovery failure probability of 0.2 LMT 1.8, 1.7, 1.6, 1.6 in 0.2, 0.4, 0.6, 0.8 LAT constraint, constraint is almost the same as AODV Fig shows the respectively For moving speed 12, the frequency of AODV is connection broken probability The broken probability about 6.4, and the AODV-RSS is about 5.1, 4.6, 4.1, 3.8 in 0.2, increases by the moving speed and LAT constraint In the 0.4, 0.6, 0.8 LAT constraint, respectively Due to the moving moving speed the AODV-RSS with 0.8 LAT constraint will speed increasing, the route discovery frequency of AODV increase the broken probability about 1.8% than the AODV increasing too, the moving speed 12 is about 3.2 (6.4 divides 2) routing protocol In the worst case, the increasing broken times of the moving speed I's The frequency increasing rate of probability iS near 40O AODV-RSS is about 2.8, 2.7, 2.5, 2.4 for 0.2, 0.4, 0.6, 0.8 L4T 035' constraint The AODV-RSS can control the route discovery frequency increasing rate - AODV AODV-RSSQ12 80.3 |DW =~~~ ~~ + RSS(0 8) 0.25 1-:, l2AODV - itAODV-RSS ~ 30 ~AODV-R,-SQfJ.4)5 10 ~ 11 ~~ 20 ~ ~ O~~~~~~~~~~~~25 ~ 12 ~ ~~ ~ -AODV-RSS(02 ~AODV-RSS(H) AODV-PSSWp 10 Speed (M/sec) Fig Average route discovery time vs mobility o Xi Speed (nJsec) 10 11 12 Fig Average route connected time vs mobility distance-vector routing (DSDV) for mobile computers," Proceedings of the SIGCOMM '94, August 1994, pp 234-244 C.-C Chiang, H.K Wu, W Liu, and M Gerla, "Routing in clustered multihop, mobile wireless networks with fading channel," IEEE SICON '97, April 1997, pp 197-211 S Murthy and J J Garcia-Luna_Aceves, "An efficient routing protocol W lfor wireless networks," ACMMobile Networks and Applications Journal, Special Issue on Routing in Mobile Communication Networks, October 1996, pp 183-197 C E Perkins and E M Royer, "Ad-hoc on-demand distance vector routing," 2nd IEEE Workshop on Mobile Computing Systems and Applications, February 1999, pp 90-100 D B Johnson and D A Maltz, "Dynamic source routing in ad-hoc X _ A0DV 4