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  1. 1. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 259 Efficient Broadcasting with Guaranteed Coverage in Mobile Ad Hoc Networks Jie Wu, Senior Member, IEEE, and Fei Dai, Student Member, IEEE Abstract—We study an efficient broadcast scheme in mobile ad hoc networks (MANETs). The objective is to determine a small set of forward nodes to ensure full coverage. We first study several methods that guarantee coverage when the local view of each node on its neighborhood information is updated in a timely manner. Then we consider a general case where nodes move even during the broadcast process, making it impractical to maintain up-to-date and consistent local views. A formal framework is used to model inaccurate local views in MANETs, where full coverage is guaranteed if three sufficient conditions, connectivity, link availability, and consistency, are met. Three solutions are proposed to satisfy those conditions. First, we give a minimal transmission range that maintains the connectivity of the virtual network constructed from local views. Then, we use two transmission ranges, one for neighborhood information collection and the other for actual data transmission, to form a buffer zone that guarantees the availability of logical links in the physical network. Finally, we propose a mechanism called aggregated local view to ensure consistent local views. By these, we extend Wu and Dai’s coverage condition for broadcasting in a network with mobile nodes. The effectiveness of the proposed scheme is confirmed via both performance analysis and simulation study. Index Terms—Broadcasting, localized algorithms, mobile ad hoc networks (MANETs), mobility, simulation. æ1 INTRODUCTIONB ROADCASTING a packet to the entire network is a basic operation and has extensive applications in mobile adhoc networks (MANETs). For example, broadcasting is information requires additional hardware, such as GPS. Other types of information can also be used which fall in between the above two models: directional information,used in the route discovery process in several routing where messages arrive from a certain angle-of-arrivalprotocols, when advising an error message to erase invalid (AOA), and distance information based on the signalroutes from the routing table, or as an efficient mechanism strength received. All these models assume some sort offor reliable multicast in a fast-moving MANET. In MANETs special hardware. In addition, location/direction/distancewith the promiscuous receiving mode, the traditional blind information may not be accurate. In this paper, we limit ourflooding incurs significant redundancy, collision, and consideration to deterministic broadcast protocols that usecontention, which is known as the broadcast storm problem neighbor set information only, which corresponds to the[23]. Efficient broadcasting in a MANET focuses on weakest assumption on neighborhood information used.selecting a small forward node set while ensuring broadcast In a broadcast process, each node decides its forwardingcoverage. status based on given neighborhood information (such Broadcast protocols can be classified into deterministic information is constructed from the neighbor set of eachand probabilistic approaches. The probabilistic approach node), and the corresponding broadcast protocol is called[11], [23] usually offers a simple solution in which each self-pruning. In Fig. 1, black (white) nodes are forwardnode, upon receiving a broadcast packet, forwards the (nonforward) nodes. Each circle corresponds to a one-hopbroadcast message with probability p. However, the neighborhood. Any source node is a black node by default.probabilistic approach cannot guarantee full coverage. The Basically, forward nodes form a connected dominating setdeterministic approach guarantees full coverage and can be (CDS), where each node in the system is either in the set orfurther classified based on the type of neighborhood the neighbor of a node in the set. That is, each white nodeinformation used: location-information-based and neighbor- has at least one black neighbor. However, most existingset-based. In location-information-based broadcast protocols, broadcast schemes assume either the underlying networklocation information of neighbors is available, whereas in topology is static or quasi-static during the broadcastneighbor-set-based broadcast protocols, only neighbor set process such that the neighborhood information can beinformation is available. Location information facilitates updated in a timely manner. The results in [7] show thatefficient broadcasting in terms of generating a small existing static network broadcast schemes perform poorlyforward node set; however, it comes with a cost—location in terms of delivery ratio when nodes are mobile. There are two sources that cause the failure of message delivery:. The authors are with the Department of Computer Science and Collision. The message intended for a destination collides Engineering, Florida Atlantic University, 777 Glades Rd., Boca Raton, with another message. In Fig. 1, if messages from nodes FL 33431. E-mail:, w and x collide at node y, node y does not receive anyManuscript received 16 June 2004; revised 25 Aug. 2004; accepted 4 Oct. message.2004; published online 29 Mar. 2005.For information on obtaining reprints of this article, please send e-mail to: Mobile nodes. A former neighbor moves out of, and reference IEEECS Log Number TMC-0199-0604. transmission range of the current node (i.e., it is no 1536-1233/05/$20.00 ß 2005 IEEE Published by the IEEE CS, CASS, ComSoc, IES, & SPS
  2. 2. 260 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 probabilistic broadcasting [23] is also a controllable para- meter. However, it is difficult to establish a direct connection between parameter selection and node mobility. Finally, we propose a new mechanism called aggregated local view to ensure consistency of the global view. The conservative approach aggregates past k local views in a special way to eliminate potential view inconsistency caused by asynchro- nous “Hello” intervals and collection process delay for k-hop information at each node. The main contributions of this paper are as follows: 1. Propose the first localized broadcast protocol thatFig. 1. Forward node set in a MANET. can handle node mobility while ensuring broadcast coverage. longer a neighbor). In Fig. 1, when node w moves out of 2. Systematically address the issue of inconsistent local the transmission range of u, the nodes along the branch view caused by neighborhood information delay, rooted at w of the broadcast tree will miss the message.1 asynchronous “Hello” intervals, and node mobility. 3. Introduce a new controllable parameter to balance Results in [7] show that the effect of collision can be broadcast efficiency and broadcast delivery ratio.relieved by a very short (1ms) forward jitter delay, where a 4. Conduct a simulation study to verify the effective-very high (! 99 percent) delivery ratio is achieved in static ness of the new approach.networks. The majority of delivery failures are caused by The remainder of the paper is organized as follows:mobile nodes. Therefore, in this paper, we focus on delivery Section 2 provides some preliminaries, especially Wu andfailures caused by mobility only. The major challenges in Dai’s coverage condition, and motivations. Section 3 pro-designing a localized broadcast protocol while ensuring poses the mobility control method based on two transmissionbroadcast coverage are as follows: 1) The network topology ranges, presents the consistent global view constructionchanges over time, even during the broadcast process. through aggregation of local views, and gives some2) The local (1-hop) information is constructed based on analytical study and optimization techniques. Simulation“Hello” intervals. To avoid serious collision among “Hello” results are presented in Section 4. The paper concludes inmessages, nodes start their intervals asynchronously, Section 5.making it difficult to ensure consistent local/global viewsamong nodes. 3) The collection process for k-hop informa-tion incurs delay which may not reflect the current network 2 PRELIMINARIES AND MOTIVATIONStopology when there are mobile nodes, even for a small k in This section starts with some related work on mobilitylocalized solutions. management and, in particular, neighbor set management As a consequence, the virtual network constructed from in a mobile environment. Then, an overview of broadcastlocal views of nodes may not be connected (connectivity issue), protocols in MANETs based on self-pruning is given. Theits links may not exist in the physical network (link availability focus is on Wu and Dai’s coverage condition and six existingissue), and the global view constructed from the collection of protocols as its special cases. Finally, we focus on thelocal views may not be consistent (consistency issue). limitation of Wu and Dai’s coverage condition in dynamic In this paper, we first give a sufficient condition for networks to motivate this study.connectivity at the physical network to ensure the con- 2.1 Mobility Managementnectivity at the virtual network. We then propose a solutionusing two transmission ranges to address the link avail- The capacity of MANETs is constrained by the mutualability issue. The neighborhood information, as well as the interference of concurrent transmissions between nodes.forward node set, are determined based on a short The mobility of nodes adds another dimension of complex-transmission range, whereas the broadcast process is done ity in the mutual interference. Camp et al. [4] gave aon a long transmission range. The difference between these comprehensive survey on mobility models for MANETs.two ranges is based on the update frequency and the speed Several studies [10] focused the effect of mobility on theof node movement. The difference is also used as a new network capacity. The impact of mobility on performance ofcontrollable parameter to balance broadcast redundancy and routing protocols is discussed in [2]. Very little work has been done in maintaining accuratebroadcast delivery ratio. Although many deterministic neighborhood information in a mobile environment with-broadcast protocols have been proposed with different out increasing the frequency of “Hello” messages. Onebroadcast redundancies (and collated broadcast delivery exception is [12], where a stable zone and a caution zone ofratios), each broadcast protocol has only its “fixed” broad- each node have been defined based on a node’s position,cast redundancy (and broadcast delivery ratio). It is, in speed, and direction information obtained from GPS.general, hard to control redundancy and delivery for a given Specifically, stable zone is the area in which a mobile nodebroadcast protocol. Note that the forwarding probability in can maintain a relatively stable link with its neighbor nodes 1. Nodes in the branch may still receive the message if some adjacent since they are located close to each other. Caution zone isnodes of the branch forward the message. the area in which a node can maintain an unstable link with
  3. 3. WU AND DAI: EFFICIENT BROADCASTING WITH GUARANTEED COVERAGE IN MOBILE AD HOC NETWORKS 261Fig. 2. (a) Forward node set without history information (static).(b) Forward node set with upstream history information (dynamic) withnode v being the source (visited node).its neighbor nodes since they are relatively far from eachother. The drawback of this approach is that it is GPS-based,which comes with a cost. In addition, there is no rigorousanalysis on the impact of mobility on the selection of thesetwo zones. Several papers [3] address the time period that two nodeswill remain close enough in proximity for a link betweenthem to remain active. Several routing protocols, associa- Fig. 3. A sample broadcast process. Gray nodes are forward nodes andtivity-based routing (ABR) [22] and signal stability-based white nodes are nonforward nodes. Arrows represent receptions of the broadcast packet.adaptive routing (SSA) [8], have been proposed that selectstable links to construct a route. In [20], GPS information is the accumulative neighbor set between neighbors areused to estimate the expiration time of the link between needed to collect k-hop information at each node.two adjacent hosts. Recently, several studies have been The “Hello” messages also propagate the priority of eachdone on the effect of mobility on routing path duration [17]. node, which could be a static property (e.g., node id) or aHowever, no broadcast protocol uses the notion of stable dynamic one (e.g., node degree). During a broadcastlink to evaluate the stability of a neighbor set in order to process, each node may also extract from the incomingbetter decide the forwarding status of each node. Although broadcast packets a list of visited nodes that have forwardedseveral probabilistic broadcast protocols [11], [23] have been the broadcast packet. Using k-hop information, priority, andproposed by trading between efficiency (simple design) and visited node information, each node decides its own status,coverage (delivery ratio), it is difficult to establish a direct forwarding/nonforwarding, based on the following cover-connection between forwarding probability and node age condition:mobility. Coverage Condition [24]. Node v has a nonforward node status2.2 Broadcast Protocols Based on Self-Pruning if for any two neighbors u and w, a replacement path existsA MANET is usually modeled as an undirected graph that connects u and w via several intermediate nodes (if any)G ¼ ðV ; EÞ, where V is a set of mobile nodes and E is a set with either higher priority values than the priority value of v orof wireless links. A link exists between two nodes u and v with visited node status.if and only if their physical distance is less than atransmission range r. Wu and Dai [24] proposed a generic Assume node id is used as priority. Node x in Fig. 2a is aefficient broadcast protocol based on self-pruning. In a nonforward node based on the coverage condition becauseself-pruning protocol, each node determines its forwarding its neighbors, v and w, are connected via a replacement pathstatus based on its local k-hop information, where k ¼ 2 or 3. that contains only intermediate nodes (in this case, y) withEvery node is a forward node by default and becomes a higher node id than x. Node y is a forward node because nononforward node (pruned) when a sufficient coverage such replacement path exists. It was proved in [24] that thecondition holds, as will be discussed later. For a node coverage condition ensures the coverage; that is, thev 2 V , its exact k-hop neighbor set, Hk ðvÞ, is the set of forward nodes, including the source, form a connectednodes that is exactly k-hops away from v, and its k-hop dominating set (CDS) of G, if G is connected. Therefore, theneighbor set, Nk ðvÞ ¼ fvg [ H1 ðvÞ [ H2 ðvÞ [ . . . [ Hk ðvÞ, is broadcast packet is delivered to all nodes in V if no packetthe set of nodes that is at most k hops away from v. The is lost due to node mobility or MAC layer collision.k-hop information of v, Gk ðvÞ, is the induced graph of Six existing algorithms were shown in [24] to be specialNk ðvÞ, excluding links among nodes in Hk ðvÞ. For example, cases of the coverage condition. They are Wu and Li’slinks between two nodes exactly 2 hops away are included marking process with Rules 1 and 2 [26], Dai and Wu’sin 3-hop information, but not in 2-hop information. Each Rule k [6], Chen et al.’s Span [5], Sucec and Marsic’snode builds its k-hop information by exchanging ðk À LENWB) [21], Peng and Lu’s SBA [15], and Stojmenovic’s1Þ-hop information with its neighbors via periodical algorithm [19]. Fig. 3 shows a sample broadcasting based on“Hello” messages. Therefore, k rounds of exchanges of self-pruning.
  4. 4. 262 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 A self-pruning protocol is static if it does not use visitednode information in the coverage condition; otherwise, it isdynamic. In a static protocol, forward nodes are predeter-mined before any broadcast process and are sourceindependent. For example, node w in Fig. 2a is a forwardnode in a static protocol because there is no replacementpath to connect neighbors x and y. When node v is thesource, there are actually three forward nodes v, w, and y. Ina dynamic protocol, the forward status is determinedduring the broadcast process. Each node usually determinesits status after a short backoff delay when the node receivesthe packet for the first time. During the backoff delay, moreneighbors may forward the same broadcast packet andthose neighbors become visited nodes. Each broadcastpacket carries a list of recently visited nodes and each nodeuses the visited node information to enhance the chance ofbeing pruned. The number of forward nodes is usuallysmaller than in a static protocol, but the selection of forwardnodes is usually source dependent. Fig. 2b shows thebroadcast process in the same network and with the samesource node as in Fig. 2a. This time, node w is a nonforwardnode because nodes x and y are connected via node v, Fig. 4. The mapping from the logical network and broadcast state to thewhich is known by w as a visited node (such information is physical network.piggybacked with the broadcast packet). There are onlytwo forward nodes v and y. unchanged until the broadcast process completes. For the In [24], it is assumed that local views of the broadcast sake of clarity, we assume node id is used as priority.specific information (i.e., visited node information) are Two Levels of Abstraction. The correctness of thedynamic but safe, i.e., an unvisited node will not be coverage condition is based on the assumption that themislabeled as visited and those of the broadcast indepen- local view is an accurate and immediate reflection of thedent information (i.e., k-hop information and priority) are physical topology. In MANETs, however, this assumption“static” and accurate during a broadcast process. However, can be easily invalidated due to the continuous nodein mobile networks, such “static” information usually mobility. In fact, in order to apply the coverage condition onchanges and causes inaccurate local views. Based on these MANETs with potentially outdated local views, we intro-inaccurate views, full coverage (i.e., 100 percent delivery duce the concepts of logical network, a dynamic virtualratio) is not guaranteed. Recently, we conducted a simula- network constructed from all local views, broadcast state, ation study on the performance of the coverage condition snapshot of local views during a broadcast process, and twoand its special cases [7]. Simulation results show that most levels of abstraction, as shown in Fig. 4:efficient broadcast protocols suffer from a low delivery ratioin highly mobile networks. 1. Level-1 abstraction: from physical network (time- space view) to logical network (time-space view). 2. Level-2 abstraction: from logical network (time-3 PROPOSED METHOD space view) to broadcast state (space view).This section proposes a mobility control method that A logical network is the collection of all local views, i.e., aaddresses connectivity, link availability, and consistency supergraph containing all the nodes and links in localissues. Three sufficient conditions are given: the first one on views.the connectivity of the physical network to ensure con- Definition 1. The local view, G0k ðv; tÞ ¼ ðNk ðv; tÞ; Ek ðv; tÞÞ, of 0 0nectivity of the virtual network, the second one on the node v is its k-hop information collected at time t. The logicalbound of the range difference to ensure link availability, network, G0 ðtÞ ¼ ðV ; S0 ðtÞÞ, is the union of all local views at Eand the third one on the consistent local views to ensure time t, where E 0 ðtÞ ¼ v2V Ek ðv; tÞ. 0correct decision made at each node. Two mechanisms,called buffer zone and aggregated local view, are proposed Both local view and logical network are time satisfy the latter two conditions. Finally, we introduce When the physical topology changes, the change is detectedmethods to relax these stringent sufficient conditions based by “Hello” messages and reflected in the logical network.on probabilistic analysis and optimization techniques. Consider the MANET in Fig. 5a. We assume that each node3.1 Logical Network and Broadcast State has the same “Hello” interval f,2 but each node starts its period asynchronously. Fig. 5b shows the update of localIn [24], the coverage condition was applied on a static or views. We label the time each node sends its last “Hello”quasi-static physical network. In a quasi-static physicalnetwork, the physical topology stops to change several 2. The condition can also be be relaxed in a controllable way, such as“Hello” intervals before a broadcast process and stays ð1 Æ 0:25Þf in AODV.
  5. 5. WU AND DAI: EFFICIENT BROADCASTING WITH GUARANTEED COVERAGE IN MOBILE AD HOC NETWORKS 263 and ti . On receiving the broadcast packet from v, both nodes x and y wait for a random backoff delay and determine their forwarding status. Node x becomes a nonforward node and node y becomes a forward node. Nevertheless, both nodes sample their local state at the time the decision is made. Subsequently, nodes w and u receive the broadcast packet and make their decision based on their local state. The global state is the union of all local states, which are sampled at different physical times during the broadcast process. Next, we examine the “gap” at each level of abstraction. The gap is caused by various synchronization delays and protocol handshakes at each level of abstraction. We will look at potential problems caused by the gap and, in the next section, we will present solutions to these problems. Gap in level 1 abstraction. In order to build k-hop information, each node advertises its ðk À 1Þ-hop informa- tion via “Hello” messages. Each node updates its local view based on received “Hello” messages. Because of asynchronous periodic exchanges among neighboring nodes, the 1-hop neighbor set in a local view at a particular time t does not reflect the actual neighbor set at time t, but the offset is bounded by the “Hello” interval f. In fact, k-hop information is a set that consists of neighborhood information sampled at different times. In general, Hiþ1 ðuÞ was sampled one interval after Hi ðuÞ for i ¼ 1; 2; :::; k À 1.Fig. 5. (a) A physical network and (b) the corresponding time-space view Clearly, the k-hop information at time t does not reflect theduring two broadcast processes. The first broadcast process starts after actual neighborhood topology at time t and the offset istime tiÀ1 and succeeds. The second one starts after time ti and fails due bounded by kf. Suppose the speed of node movement isto inconsistent local views. upper bounded by s. Then, sf is the maximum distance a node can move around during a “Hello” interval. Themessage before the broadcasting as ti , the time for previous maximum relative distance between two nodes in such an“Hello” messages as tiÀ1 ; tiÀ2 , and so on. Note that ti at each interval is Á ¼ 2sf.node may refer to different physical time. Here each node Gap in level 2 abstraction. In a broadcast process basedbuilds 2-hop information. If node y0 “Hello” message is first on self-pruning, each node follows three steps: 1) firstreceived by node v between tiÀ2 and tiÀ1 (the “Hello” receipt of broadcast message, 2) backoff delay, andmessage propagation is shown in a dotted arrow line), it is 3) forward/nonforward status decision and transmissionadded to v0s 1-hop neighbor set, which is advertised in v0 s (if needed). A broadcast period starts from the source sendingnext “Hello” message at tiÀ1 . That is, link ðv; yÞ is added to out the message and ends with the last node deciding itslocal views of nodes v and x. Similarly, link ðw; yÞ is also forwarding status. Like [24], it is assumed that the broadcastdetected and added to local views of nodes u, w, and x. message propagates quickly and its delay can be ignored. Broadcast state is a snapshot of local views of the logical Backoff at intermediate nodes is allowed, but accumulativenetwork. For a specific broadcast process, broadcast state backoff along each path of the broadcast tree is bounded byforms a virtual static network, upon which the coverage b, called broadcast delay, for each broadcast. Note that b maycondition is applied. also include broadcast message propagation delay if suchDefinition 2. A local broadcast state G00 ðvÞ ¼ ðNk ðv; tv Þ; 0 delay cannot be neglected. k 0 Ek ðv; tv ÞÞ of node v for a broadcast is its local view at the time 3.2 Mobility-Sensitive Broadcasting tv , when it makes its forwarding/nonforwarding decision. A Wu and Dai’s coverage conditions can be applied to the global state G00 ¼ ðV ; E 00 Þ, is the union of all local broadcast S global broadcast state and ensures coverage, given that the states, where E 00 ¼ v2V Ek ðv; tv Þ. 0 following three conditions are met: connectivity, link availability, and consistency. The first two conditions In Fig. 5b, the time that each individual node makes its resolve the gaps at level 1 and level 2 abstractions,decision is marked with a black dot. Note that local respectively. The third condition ensures the consistentbroadcast states are taken at the times marked by these use of local dots and the global broadcast state is the collection Connectivity. The virtual network that corresponds toof local broadcast states (marked by the dashed line the global broadcast state should be connected in order toconnecting all black dots). Suppose node v in Fig. 5a apply Wu and Dai’s coverage condition. The followingissues a broadcasting, where nodes y and w become theorem shows the density requirement at the physicalforward nodes. The corresponding broadcast state is network for ensuring a connected virtual network:shown in Fig. 5b. The source node v samples its local Theorem 1. If the physical network with transmission rangestate at the beginning of the broadcasting, between tiÀ1 r1 À Á0 is connected under all time, where Á0 ¼ 2sðf þ bÞ,
  6. 6. 264 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 Fig. 7. The physical network (a) before and (b) after the movement, and (c) the aggregated local view of node y.Fig. 6. Forward node selection and forwarding process based The above theorem provides some theoretical founda-on two different transmission ranges: r1 and r2 . tions for ensuring full coverage. However, the analysis shows only the worst case situation, which rarely occurs. then every virtual network induced from a global broadcast Later we will show that even when r2 À r1 is much smaller state is connected. than Á00 , the probability of an undetected link failure is veryProof. Assume the global broadcast state is taken in a low. Since most self-pruning protocols have certain degrees broadcast process started at time t. Since the maximum of redundancy, it usually takes several link failures to cause broadcast delay is b, all local states are taken within time a global delivery failure. Therefore, the probability can still period ½t; t þ bŠ. If the distance of two nodes u and v, be high that a high delivery ratio can be achieved with a dðu; vÞ r1 À 2sðf þ bÞ at time t À f, then dðu; vÞ r1 relatively small buffer zone width. There is a wide range of during ½t À f; t þ bŠ. Suppose u takes its local broadcast potential tradeoffs between broadcast efficiency and broad- state at tu 2 ½t; t þ bŠ, it must have received v0 s last cast delivery ratio. “Hello” message in ½t À f; tu Š. Therefore, link ðu; vÞ exists The idea of two transmission ranges is to use the “ring,” in u0 s local broadcast state. Since the global broadcast the area bounded by two circles with transmission ranges r1 state consists of all links from local broadcast state and and r2 , as a buffer zone to nullify the various bad effects the network is connected at time t À f in the range of r1 À Á0 , the corresponding virtual network induced from caused by node mobility and transmission delay. However, the global broadcast state is also connected. u t one bad effect, called inconsistent local views, cannot be nullified no matter how wide the buffer zone is. Incon- Theorem 1 poses a rather strict connectivity requirement sistent local views ultimately result in a bad decision from aon the physical network. That is, if the physical network node. A decision is bad if a node that should forward thecannot meet the connectivity requirement, the virtual message decides on a nonforwarding is not guaranteed to be connected and Wu and Consistency. Two local views (or states for a specificDai’s approach will fail. We will discuss later an approach broadcasting) of nodes u and v are inconsistent, if a linkthat relaxes the connectivity requirement under the cost of ðv; wÞ exists in u0 s local view (state), but v does not view w aspruning efficiency. a 1-hop neighbor. For example, assume the physical Link availability. Any link in the global broadcast state topology in Fig. 2 changes shortly before the broadcast.should still exist in the physical network during thebroadcast period. We propose to use two transmission The broadcast may fail due to inconsistent views. Fig. 7aranges, r1 and r2 , with r1 < r2 . r1 is used to collect neighbor shows the physical network before the change, whereset and k-hop information through “Hello” messages, node x is a nonforward node because its neighbors v and wwhereas r2 is used to perform actual transmission. A node are connected via a replacement path ðv; y; wÞ. Fig. 7b showsthat is within the range of r1 of node u is called a neighbor the physical network before the broadcast, where y is aof u and the collection of such nodes is the neighbor set of u. nonforward node because w is no longer a neighbor. Node yThe set of nodes that are reachable based on r2 is called detects the broken link ðy; wÞ before node x, since y iseffective neighbor set. Fig. 6 shows the relationship between adjacent to the link, whereas x is 2-hop away from the link.these two transmission ranges. In this example, v is in u0 s Both nodes may take a nonforwarding status in theneighbor set (also in u0 s effective neighbor set), whereas w is broadcast, x0 s decision based on the outdated view and y0 sin u0 s effective neighbor set (but not in u0 s neighbor set). based on the updated view. Therefore, node w may neverTheorem 2. To ensure the link availability requirement, r2 receive the broadcast packet. should be set so that Á00 r2 À r1 , where Á00 ¼ kÁ þ Á0 and We say node v0 s local view (state) is consistent with the k for k-hop information. logical network (global state) (or simply consistent), if its local view (state) contains all its adjacent links in the logicalProof. (sketch) We need to show that any neighbor under network (global state). Formally speaking, let H1 ðvÞ denote the transmission range r1 when its state is sampled is still an effective neighbor under the transmission range r2 v0 s exact 1-hop neighbor set in its local view (state), and à when the message is sent out. The total delay includes H1 ðvÞ its exact 1-hop neighbor set in the logical network k-hop neighbor set collection that takes k intervals and (global state). The local view (state) is consistent if ðf þ bÞ for broadcast and synchronization delay. The à H1 ðvÞ ¼ H1 ðvÞ. The following lemma and theorem show former contributes a distance of kÁ and the latter Á0 . t u that this definition of consistency, together with the
  7. 7. WU AND DAI: EFFICIENT BROADCASTING WITH GUARANTEED COVERAGE IN MOBILE AD HOC NETWORKS 265Fig. 8. Life spans of a single link in local views of neighboring nodes. (a) Inconsistent local states may be sampled due to inconsistent local viewsand/or the broadcast delay. (b) Local states sampled from aggregation local views enhanced by delayed advertisement and delayed removal.connectivity and link availability conditions, are sufficient view and uses the aggregation of those local views to makeconditions to ensure full delivery in a self-pruning protocol. the forwarding/nonforwarding decision. More formally, let G0 ðvÞ ¼ ðNk ðvÞ; Ek ðvÞÞ be the currentLemma 1. If the global state G00 is connected and local states k local view of v and GÀi ðvÞ be the local view that is i “Hello” G00 ðvÞ of all nodes v are consistent, then the forward node set k intervals before the current one (or simply called view Ài). determined by applying Wu and Dai’s coverage condition on Let Lj ðvÞ ¼ ðHjÀ1 ðvÞ Â Hj ðvÞÞ Ek ðvÞ contain links between each node’s local states form a CDS of G00 . v0 s ðj À 1Þ-hop and j-hop neighbors. Links in Lj ðvÞ have anProof. Suppose F is the forward node set derived using Wu “age” of j; i.e., this information takes j rounds of “Hello” and Dai’s coverage condition on G00 , F is a CDS of G00 exchanges to build up. Also, LÀi ðvÞ corresponds to the Lj ðvÞ j (connectivity condition). Let F 0 be the forward node set in view Ài, which has an age of i þ j. The aggregated local derived using Wu and Dai’s condition on local state G00 ðvÞ view of v, G0k ðvÞ, is defined as follows: of each node v. Consider each nonforward node v 62 F 0 . In v0 s local state, any two neighbors in H1 ðvÞ are connected G0k ðvÞ ¼ ðNk ðvÞ; L01 ðvÞ [ L02 ðvÞ [ . . . [ L0k ðvÞÞ; via a replacement path in G00 ðvÞ. Since G00 ðvÞ is a subgraph where of G00 and H1 ðvÞ ¼ H1 ðvÞ (consistency condition), any à à ÀðkÀjÞ two neighbors in H1 ðvÞ are also connected by a replace- L0j ðvÞ ¼ Lj ðvÞ [ LÀ1 ðvÞ [ . . . [ Lj j ðvÞ ment path in G00 . Therefore, v 62 F . That is, F 0 is a superset of F and a CDS of G00 . u t for 1 j k. Note that the maximal age of L0j ðvÞ is k. In aggregated local views, the life span of each link isTheorem 3. If the connectivity, link availability, and consistency extended to compensate for the propagation delay of the conditions are all satisfied, then Wu and Dai’s generic self- link failure information. Aggregated local views are con- pruning protocol ensures full coverage. sistent; that is, local broadcast states sampled at the sameProof. Based on the connectivity and consistency condi- physical time would be consistent (e.g., when the broadcast tions, the global state is connected and consistent. From process completes instantly). Fig. 7c shows the aggregated Lemma 1, the corresponding forward node set F 0 is a local view of node y. Based on this local view, node y will CDS of the global broadcast state. Based on the link still forward. Intuitively, once a node v appears as a availability condition, each link in the global broadcast neighbor of u (in the range of r1 ) during the recent k intervals, it still has to be treated as a neighbor even if it state corresponds to a valid link in the physical network. currently moves out of u0 s visible range but is still in u0 s Therefore, all nodes in the physical network finally effective neighbor set (as shown in Theorem 2). receive the broadcast. u t Another cause of inconsistency is the backoff delay, where a new link is detected during a broadcast process. As Next, we propose to use the aggregated local view to shown in Fig. 5, node u is initially a neighbor of w and lateraddress the inconsistency problem. The inconsistency in the moves to x as its neighbor. If a “Hello” message is sent fromabove example occurs when node y removes link ðy; wÞ in x to w after x has made its decision, but before w0 s decisionits local view before node x does so. As shown by the is made, then w0 s decision is made based upon informationbroadcast state 1 in Fig. 8a, a broken link is first detected by that is not available to x. Consider the following sequence ofthe end nodes (1-hop neighbors). This link is not removed events as shown in Fig. 5:from local views of other nodes until the link failure isadvertised via “Hello” messages. When k-hop information 1. x decides its nonforwarding status,is used, it takes up to k “Hello” intervals for all affected 2. u is detected by x as a new neighbor,nodes to update their local views. The solution is that once a 3. x advertises its new neighbor set, andnode advertises its 1-hop neighbor set, it cannot back away from it 4. w believes that u is covered by x and becomes aimmediately. Each node v keeps k recent versions of its local nonforward node.
  8. 8. 266 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005In this case, u will never receive the broadcast packet. Thissituation is illustrated in Fig. 8a as broadcast state 2, wherelife spans of a single link in local views of neighboringnodes (1; 2; . . . ; k hops away from the link) are shown. Thenew link is detected after a 1-hop neighbor has made itsdecision, and is propagated to a 2-hop neighbor before adecision is made there. One solution is the delayedadvertisement. As shown in Fig. 8b, a 1-hop neighbor will Fig. 9. A network with one mobile node w (a) before the movement andhold the advertisement of a new link if its age is younger (b) after the movement. Dotted lines represent undetected physicalthan b, the maximal time period of a broadcast process. links. The dashed line represents an undetected broken link. (a) “Hello”Thus a new link detected during a broadcast process will range r1 causes partition. (b) “Hello” range r2 causes link failure.not affect the decision of other nodes. Two other problems may cause inconsistency in aggre- Node u is a nonforward node and node v is supposed togated local views. The first one is illustrated by the forward the broadcast packet to node w. However, node wbroadcast state 1 in Fig. 8a. When the broadcast process moves out of the transmission range of v and never receivesbegins at a k-hop neighbor and ends at a 1-hop neighbor of a this packet.broken link, this link may be removed from the 1-hop Our solution is based on maintaining two neighbor sets.neighbor’s local view before the local state is sampled. The effective neighbor set consists of all nodes within theAnother problem is that a link failure may be detected by actual transmission r2 and the advertised neighbor set consiststwo end nodes in different times, a time skew bounded by of only nodes with distance less than r1 . If v is a nonforwardthe “Hello” interval f. Both problems can be solved by the node, every pair of nodes in v0 s effective neighbor set mustdelayed removal of a link from local views of its end nodes be connected via a replacement path. In this case, node v inwith a delay of f þ b. Fig. 8b shows the effect of delayed Fig. 9a views w as a neighbor and becomes a forward node.advertisement, aggregated view, and delayed removal. On the other hand, only the advertised neighbor set isAfter using delayed advertisement, if a link does not propagated to its k-hop neighbors. Because link ðv; wÞ inappear in the local view of a 1-hop neighbor, it will not Fig. 9b is invisible to node u, node u also forwards theappear in a i-hop (i ! 2) neighbor’s local state either. After broadcast packet and ensures the coverage. Note that this method is conservative. If link ðv; wÞ is still available,using the aggregated view and delayed removal, the making node u a forward node causes extra redundancy.removal of a link from the local views of its 1-hop neighbors Using the dual neighbor set mechanism, the connectivityis extended by kf þ f þ b. Because this link will be removed condition in Theorem 1 is relaxed without violating the linkfrom local views of all i-hop neighbors within k “Hello” availability condition. It is sufficient that the physicalintervals, the local views are always consistent. In addition, network is connected with transmission range r2 À Á0 .the time skew between two 1-hop nodes and the broadcast If the physical distance between two neighbors can bedelay are compensated by the additional delay of f þ b. estimated based on the signal strength of a receivedTherefore, if a link appears in the local state of an i-hop message, the dual neighbor sets can be implemented vianeighbor, it will also appear in both 1-hop neighbors’ local sending “Hello” messages with transmission range r2 . Eachviews. The following theorem can be easily proven based on node classifies its neighbors into effective and advertisedthe above reasoning: neighbors based on their estimated distances. When theTheorem 4. If each node maintains its aggregated local view with signal strength is unavailable or inaccurate, each node will delayed advertisement and delayed removal, then all local send two types of “Hello” messages. The first type of broadcast states sampled from these local views are consistent. “Hello” messages, sent via transmission range r2 , are used to detect effective neighbors. The second, sent via transmis-3.3 Implementation Details sion range r1 , are used to identify advertised neighbors.According to Theorem 1, full coverage is guaranteed only 3.4 Analytical Studywhen the network is sufficiently dense (i.e., connected withtransmission range r1 À Á0 ). In the following, we propose a Based on Theorem 2, in order to guarantee that a neighbormechanism, called dual neighbor sets, to relax the connectivity (within r1 ) at t0 is an effective neighbor (within r2 ) at a time t1 ¼ t0 þ f, r1 must be smaller than r2 À 2sf for a givenrequirement under the cost of pruning efficiency. In sparse maximal node speed s and time period f. In this section, wenetworks, using a small “Hello” transmission range may show that the probability, p, that a node within r1 at t0 movescause partition in the logical network. As shown in Fig. 9a, out of range r2 at t1 is reasonably small with a much larger r1 .when the “Hello” transmission range is r1 ¼ r2 À Á00 , neither We assume a mobility model similar to the random directionu nor v views w as a neighbor because they cannot receive model [16], where each node is moving at a random speed in“Hello” messages from node w. Therefore, both nodes u and ½0; sŠ to a random direction in ½0; 2Š. This is a simplifiedv are nonforward nodes and no one will forward the model for ease of probabilistic analysis. In addition, thisbroadcast packet to node w. On the other hand, using a model usually represents the worst case in terms of relativelarger r1 violates the link availability condition in Theorem 2. distance between two nodes in a given interval.The broadcast process may fail due to the lack of a buffer Consider two neighboring nodes u and v as shown inzone. Fig. 9b shows the situation when r1 ¼ r2 is used. Fig. 10. Node v is within u0 s “Hello” transmission range (the
  9. 9. WU AND DAI: EFFICIENT BROADCASTING WITH GUARANTEED COVERAGE IN MOBILE AD HOC NETWORKS 267 ~ ~ ~ ~ between 0 and 2s: jV j ¼ 0 when Vu ¼ Vv , jV j ¼ 2s when Vu ~ ~ ~ ~ ¼ ÀVv , and jVu j ¼ jVv j ¼ s. However, its probability function, fjV j ðtÞ, is unknown. McDonald and Znati [14] ~ conducted a probabilistic analysis on the joint mobility of two nodes, but their analysis is based on the random walk mobility model [4], where the mobility vector of each node is the sum of several epochs and each epoch has different speed, direction, and duration. Li et al.’s analysis [13] is based on the same mobility model as ours, but their analysisFig. 10. Calculation of the probability that a neighbor within the “Hello” is simplified by the implicit assumption that node u is fixedtransmission range (r1 ) moves out of the normal transmission range (r2 ). ~ and jV j is uniformly distributed in ½0; sŠ. Here we calculate fjV j ðtÞ at a given t as ~shadowed area) at time t0 and moves to position v0 at t1 .Assume that their distance at t0 is d and v moves a distance FjV j ðt þ tÞ À FjV j ðtÞ ~ ~of x with respect to u at t1 . The probability that v moves out fjV j ðtÞ % ~ tof the actual transmission range of u is P ðt ~ jV j t þ tÞ 8 ¼ ð4Þ 0 : x r2 À d t I ð2;sÞ I ð2;sÞ ~ ~ pðx; dÞ ¼ 1 À : r2 À d x r2 þ d ð1Þ RðVu ; Vv ; t; t þ tÞ ~ ~ : ¼ dVu dVv ; 1 : x r2 þ d; ð0;0Þ ð0;0Þ ð2sÞ2 t 2 2 2 where FjV j ðtÞ is the distribution function, t is a small ~ x þd Àr2where ¼ cosÀ1 2dx is the largest value of ffuvv0 that positive value, and 0 satisfies dðu; v Þ r2 . The probability that any node within ~ ~ 1 : ~ ~ a jVv À Vu j bthe “Hello” transmission range of u moves out of its actual RðVu ; Vv ; a; bÞ ¼ 0 : otherwise:transmission range at t1 is Z r1 Z r1 ~ Fig. 11a shows the distribution of jV j calculated from (4), 2d 2d when s ¼ 1m=s and t ¼ 0:001m=s. Note that the probability pðxÞ ¼ pðx; dÞ dd ¼ 2 pðx; dÞ dd; ð2Þ ~ 0 S1 0 r1 that jV j 1:5s is small ( 5 percent). Based on this distribution, we calculate the probability p that any nodewhere S1 ¼ r2 is the area within the “Hello” transmission 1 within the “Hello” transmission range (r1 ¼ 100, 150, 200,range. The probability that a node with any constant relative and 250) of u moves out of its actual transmission rangespeed t with respect to u moves out of the actual (r2 ¼ 250m) during a “Hello” interval (f ¼ 1s) when thetransmission range is maximal single node speed s varies from 0 to 160m=s. As shown in Fig. 11b, we can use an r1 that is much larger than Z 2s r2 À 2sf and still expect a low probability that an effective p¼ fjV j ðtÞ pðftÞ dt: ~ ð3Þ neighbor moves out of the actual transmission range. For 0 example, when r1 ¼ 200m and s ¼ 80m=s, the probability of ~ ~ ~ Here, V ¼ Vv À Vu is the random joint mobility vector losing an effective neighbor is less than 5 percent. Note that ~ ~between any two mobile nodes u and v, where Vu (Vv ) is the the corresponding r1 that guarantees the availability of link ðu; vÞ at time t1 is r2 À 2sf ¼ 90m. When r1 ¼ 100m andrandom mobility vector of node u (v). Note that (1) still holds, s ¼ 160m=s, the probability of losing an effective neighbor is ~as the direction of V is also uniformly distributed in ½0; 2Š about the same. On the other hand, there is no r1 that can ~ ~ ~and is independent of the speed of V , jV j. We know that jV j is guarantee the link availability, as 2sf ¼ 320m r2 .Fig. 11. (a) The probability function fjV j ðtÞ of the random joint mobility vector and (b) the probability that a neighbor within a given “Hello” transmission ~range r1 moves out of the actual transmission range r2 .
  10. 10. 268 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 TABLE 1 existence of wireless links due to the irregular variation of Simulation Parameters transmission range. It was shown in [7] that the contribu- tion of a backoff delay to the protocol efficiency is trivial except for SBA. Therefore, our implementation of the proposed method does not use a backoff delay. The mobility model used in the simulation is the random direction model [16]. In this model, each node moves towards a random direction at a random speed until it reaches the boundary of the area, where it selects new direction and speed and repeats the same process. Our mobility pattern generator is from [4], which has a parameter called average moving speed (Vavg ). For a given Vavg , the speed of each node is randomly selected from the range ½0; 2Vavg Š. Note that the random direction model4 SIMULATION usually yields sparser networks and higher mobility thanSimulations are conducted to evaluate the proposed the commonly used random waypoint model [4]. Therefore,method and explore appropriate “Hello” transmission a reliable protocol in this simulation study is a reliableranges that achieve high delivery ratio with low broadcast protocol under the random waypoint model, but not viceredundancy under various mobility levels. We also evaluate versa. Other simulation parameters are listed in Table 1.the effectiveness of two implementation options that use 4.2 Simulation Resultsdual neighbor sets to improve the delivery ratio under Fig. 12 shows simulation results in relatively dense net-various environments. works (100 nodes), with buffer zone width (i.e., r2 À r1 )4.1 Simulation Environment varying from 0m to 100m. As expected, high delivery ratioThe proposed mobility management method is simulated (! 98 percent) can be achieved with large buffer zone widthon ns-2(1b7a) [9] and its CMU wireless extension. We extend (100m) in highly mobile networks (with average speed 160m=s). Note that this buffer zone width is much smallerWu and Dai’s coverage condition by using two transmis- than that required by Theorem 2, which should be at leastsion ranges r1 (for “Hello” messages) and r2 (for actual 2  2Vavg ¼ 640m. This also confirms our prediction intransmission). When r1 ¼ r2 , the new algorithm is equiva- Section 3.4 that high delivery ratio can be achieved usinglent to the original generic self-pruning protocol. We also a small buffer zone. The only problem is the high broadcastsimulate the dual neighbor sets enhancement for sparse cost (! 60 percent forward nodes). If the network mobilitynetworks. The consistency enforcement mechanisms (i.e., level is known, we can select the buffer zone width basedaggregated local views, delayed advertisement, and de- on the mobility level to balance the delivery ratio andlayed removal) are not implemented. redundancy. For example, at average speed 120m=s, we can The broadcast traffic rate is 10 packets per second with use a buffer zone width of 50m, which achieves 95 percent64 bytes per packet. Each packet is issued from a randomly delivery ratio with 40 percent forward nodes. At averageselected node. Since our purpose is to observe the behavior speed 40m=s, a 10m buffer zone achieves the same deliveryof self-pruning protocols under mobile environments, all ratio with only 30 percent forward nodes.simulations use an ideal MAC layer without contention or Fig. 13 shows the performance of the proposed methodcollision. If a node sends a packet, all neighbors within its in relatively sparse networks (50 nodes). When a 0m buffertransmission range will receive this packet after a short zone is used, the delivery ratio drops rapidly as the averagepropagation delay. We assume that accurate location speed increases. Using a larger buffer zone width (! 50m)information is either unavailable or unable to predict the improves the delivery ratio under high mobility level, butFig. 12. Performance of the original single neighbor set method in relatively dense (100 nodes) networks. (a) Delivery ratio. (b) Broadcast cost.
  11. 11. WU AND DAI: EFFICIENT BROADCASTING WITH GUARANTEED COVERAGE IN MOBILE AD HOC NETWORKS 269Fig. 13. Performance of the original single neighbor set method in relatively sparse (50 nodes) networks. (a) Delivery ratio. (b) Broadcast cost.Fig. 14. Performance of the dual neighbor set enhancement in relatively sparse (50 nodes) networks. (a) Delivery ratio. (b) Broadcast cost.performs poorly under low mobility level. The delivery for each mobility level, high delivery ratio can be achievedratio is low ( 85 percent), even with trivial mobility with a buffer zone much thinner than required by(1m=s). One reason for the low delivery ratio in sparse Theorem 2. The dual neighbor set enhancement is provednetworks is the relatively low redundancy. The broadcast successful in relaxing the connectivity requirement incost is low (40 percent) under different buffer zone widths. Theorem 1 and achieves high delivery ratio in sparseThis is because the broadcast process fails in most cases, networks.where only a few nodes receive and forward the packet. Simulation results in [7] showed that all self-pruningprotocols have lower delivery ratio in sparse networks than 5 CONCLUSIONSin dense networks under the same mobility level. Another In this paper, we have proposed a mobility managementreason is that when the network is not sufficiently dense, method based on the use of two transmission ranges. Usingthe connectivity requirement in Theorem 1 is not satisfied this mechanism, we have also extended Wu and Dai’sand, therefore, cannot guarantee the coverage. This problem coverage condition to a dynamic environment wherecan be solved with the dual neighbor set enhancement network topology is allowed to change, even during theintroduced in Section 3.3. Fig. 14 shows the performance of broadcast process. In addition, connectivity, link availabil-the enhanced scheme, where all neighbors within the actual ity, and consistency issues related to neighborhood infor-transmission range r2 are put into the effective neighbor set mation of different nodes have also been addressed. Theand only neighbors within transmission range r1 are put proposed scheme can also be extended to provide mobilityinto the advertised neighbor set. With this enhancement, management for other activities, such as topology control inhigh delivery ratio (! 90 percent) can still be achieved MANETs [25].under the highest mobility level. However, the correspond- The constraint used on r2 À r1 in this paper is conserva-ing broadcast cost is also higher (80 percent). Under low tive. Our probabilistic analysis suggests that high deliveryand median mobility (Vavg 40), a smaller buffer zone ratio can still be achieved with a larger r1 . Simulation resultswidth (50m) can be used to reduce the broadcast cost to show that the proposed method and the dual neighbor set60 percent. enhancement achieve good balance between delivery ratio Overall, simulation results show that balance between and broadcast redundancy by adjusting the value of r1delivery ratio and broadcast redundancy can be achieved based on the network mobility level. A future extensionby adjusting the buffer zone width based on the network would be automatic buffer zone width adjustment thatmobility level. As predicted by our probabilistic analysis, adapts to the neighborhood mobility level.
  12. 12. 270 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 3, MAY/JUNE 2005 In Wu and Dai’s coverage condition, node id is used to [17] N. Sadagopan, F. Bai, B. Krishnamachari, and A. Helmy, “Paths: Analysis of Path Duration Statistics and their Impact on Reactivebreak a tie. We could also use the notion of relative mobility MANET Routing Protocols,” Proc. MobiHoc, June 2003.[1], defined as absolute relative speed averaged over time, [18] M. Singhal and N.G. Shivaratri, Advanced Concepts in Operatingfor tie breaking. In general, a node with high relative Systems: Distributed, Database, and Multiprocessors Operating Sys-mobility is more prone to unstable behavior than a node tems. McGraw-Hill, Inc., 1994.with less relative mobility and therefore should be pruned [19] I. Stojmenovic, M. Seddigh, and J. Zunic, “Dominating Sets and Neighbor Elimination Based Broadcasting Algorithms in Wireless(from being a forward node) when possible. In this case, Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 13,relative mobility is calculated locally through some form of no. 1, pp. 14-25, Jan. 2002.approximation and distributed through piggybacking with [20] W. Su, S.-J. Lee, and M. Gerla, “Mobility Prediction and Routing inregular “Hello” messages. Our future work also includes Ad Hoc Wireless Networks,” Int’l J. Network Management, vol. 11, no. 1, pp. 3-30, Jan.-Feb. 2001.the adoption of vast results from the distributed system [21] J. Sucec and I. Marsic, “An Efficient Distributed Network-Widecommunity with regards to global/local states and view Broadcast Algorithm for Mobile Ad Hoc Networks,” CAIPconsistency [18]. Technical Report 248, Rutgers Univ., Sept. 2000. [22] C.-K. Toh, “Associativity-Based Routing for Ad-Hoc Mobile Networks,” IEEE Personal Comm., vol. , 4, no. 2, pp. 36-45, Mar.ACKNOWLEDGMENTS 1997. [23] Y.-C. Tseng, S.-Y. Ni, and E.-Y. Shih, “Adaptive Approaches toThis work was supported in part by US National Science Relieving Broadcast Storms in a Wireless Multihop Mobile AdFoundation grants ANI 0073736, CCR 0329741, CNS Hoc Network,” IEEE Trans. Computers, vol. 52, no. 5, pp. 545-557,0434533, CNS 0422762, and EIA 0130806. May 2003. [24] J. Wu and F. Dai, “Broadcasting in Ad Hoc Networks Based on Self-Pruning,” Proc. IEEE Infocom, Mar./Apr. 2003. [25] J. Wu and F. Dai, “Mobility-Sensitive Topology Control in MobileREFERENCES Ad Hoc Networks,” Proc. IEEE Int’l Parallel and Distributed[1] B. An and S. Papavassiliou, “A Mobility-Based Clustering Processing Symp., May 2004. Approach to Support Mobility Management and Multicast [26] J. Wu and H. Li, “On Calculating Connected Dominating Set for Routing in Mobile Ad-Hoc Wireless Networks,” Int’l J. Network Efficient Routing in Ad Hoc Wireless Networks,” Proc. DiaLM, Management, vol. 11, no. 6, pp. 387-395, Nov./Dec. 2001. pp. 7-14, 1999.[2] F. Bai, N. Sadagopan, and A. Helmy, “IMPORTANT: A Frame- work to Systematically Analyze the Impact of Mobility on Jie Wu is a professor in the Department of Performance of Routing Protocols for Ad-Hoc Networks,” Proc. Computer Science, Florida Atlantic University. IEEE Infocom, Mar./Apr. 2003. He has published more than 250 papers in[3] S. Basagni, I. Chlamtac, A. Farago, V.R. Syrotiuk, and R. Talebi, various journals and conference proceedings “Route Selection in Mobile Multimedia Ad Hoc Networks,” Proc. and has served on many conference organiza- IEEE MOMUC, Nov. 1999. tion committees. He presently serves on the[4] T. Camp, J. Boleng, and V. Davies, “A Survey of Mobility Models editorial board of IEEE Transactions on Parallel for Ad Hoc Network Research,” Wireless Comm. Mobile and Distributed Systems and was recently a co- Computing (WCMC), special issue on mobile ad hoc networking: guest-editor of IEEE Computer and the Journal research, trends and applications, vol. 2, no. 5, pp. 483-502, 2002. of Parallel and Distributing Computing. He[5] B. Chen, K. Jamieson, H. Balakrishnan, and R. Morris, “Span: An served as the program cochair for IEEE MASS 2004 and is the author Energy-Efficient Coordination Algorithm for Topology Mainte- of the text Distributed System Design, published by the CRC press. He nance in Ad Hoc Wireless Networks,” Proc. MobiCom, pp. 85-96, was the recipient of the 1996-97 and 2001-2002 Researcher of the Year July 2001. Award at Florida Atlantic University and served as an IEEE Computer[6] F. Dai and J. Wu, “An Extended Localized Algorithm for Society Distinguished Visitor. His research interests are in the areas of Connected Dominating Set Formation in Ad Hoc Wireless mobile computing, routing protocols, fault-tolerant computing, and Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 15, interconnection networks. He is a member of the ACM and a senior no. 10, pp. 908-920, Oct. 2004. member of the IEEE.[7] F. Dai and J. Wu, “Performance Comparison of Broadcast Protocols for Ad Hoc Networks Based on Self-Pruning,” IEEE Fei Dai received the BS and MS degrees in Trans. Parallel and Distributed Systems, vol. 15, no. 11, pp. 1027- computer science from Nanjing University, 1040, Nov. 2004. Nanjing, China. He is currently a PhD candi-[8] R. Dube, C. Rais, K. Wang, and S. Tripathi, “Signal Stability Based date in the Department of Computer Science Adaptive Routing (SSA) for Ad Hoc Mobile Networks,” IEEE and Engineering, Florida Atlantic University. His Personal Comm., vol. 4, no. 1, pp. 36-45, Feb. 1997. recent research has focused on localized and[9] K. Fall and K. Varadhan, “The ns Manual,” The VINT Project, self-organizing algorithms for wireless ad hoc UCB, LBL, USC/ISI and Xerox PARC, and sensor networks. He has also conducted nsnam/ns/doc/, Apr. 2002. research study in the broad areas of network-[10] M. Grossglauser and D. Tse, “Mobility Increases the Capacity of ing, mobile computing, parallel and distributed Ad-Hoc Wireless Networks,” Proc. IEEE Infocom, Apr. 2001. computing, artificial intelligence, and software engineering. He has[11] Z.J. Haas, J.Y. Halpern, and L. Li, “Gossip-Based Ad Hoc been a senior programmer in Greatwall Computer, China, for three Routing,” Proc. IEEE Infocom, June 2002. years and a software architect and team leader in JA Securities,[12] W.-I. Kim, D.-H. Kwon, and Y.-J. Suh, “A Reliable Route Selection China, for four years. He is a student member of the IEEE. Algorithm Using Global Positioning Systems in Mobile Ad-Hoc Networks,” Proc. ICC, June 2001.[13] N. Li, J.C. Hou, and L. Sha, “Design and Analysis of an MST- Based Topology Control Algorithm,” Proc. IEEE Infocom, Mar./ . For more information on this or any other computing topic, Apr. 2003. please visit our Digital Library at[14] A.B. McDonald and T.F. Znati, “A Mobility-Based Framework for Adaptive Clustering in Wireless Ad Hoc Networks,” IEEE JSAC, Special Issue on Ad-Hoc Networks, Aug. 1999.[15] W. Peng and X. Lu, “On the Reduction of Broadcast Redundancy in Mobile Ad Hoc Networks,” Proc. MobiHoc, pp. 129-130, 2000.[16] E. Royer, P. Melliar-Smith, and L. Moser, “An Analysis of the Optimum Node Density for Ad Hoc Mobile Networks,” Proc. ICC, 2001.