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Download [IEEE 2009 8th IFIP Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net 2009) - Haifa, Israel (2009.06.29-2009.07.1)] 2009 8th IFIP Annual Mediterranean Ad Hoc Networking Workshop - Extrapolation-based and QoS-aware real-time communication in wireless mobile ad hoc networks

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  • Extrapolation-based and QoS-aware Real-TimeCommunication in Wireless Mobile Ad Hoc

    NetworksAdnan Agbaria, Gidon Gershinsky, Nir Naaman, and Konstantin Shagin

    IBM Haifa Research LaboratoryHaifa 31905, Israel

    AbstractIn mobile ad hoc networks (MANETs), it is increas-ingly important to devote attention to real-time and quality ofservice (QoS) issues. We present here a novel extrapolation-basedand QoS-aware technology for providing soft real-time servicesin MANETs. The proposed technology combines elements ofproactive and location-based techniques. Each node maintains aglobal view, which is periodically updated through state exchangeamong all the nodes. At any time, a node is able to extrapolatethe location of a given node based on its velocity vector. Resourcemanagement, dynamic scheduling, velocity-based extrapolation,and multipath search techniques are employed to meet the real-time and QoS requirements despite network contention andfrequent topology changes. We demonstrate this technology bypresenting a real-time and QoS routing protocol. We evaluate theperformance of the protocol and compare it to the performanceof other well-known routing protocols.


    Mobile wireless applications increasingly depend on com-munication technologies that provide QoS support, such asresource reservation, reliability, and security. For example, inthe transportation domain, police cars need to communicatecontinuously in a predictive real-time fashion to performcollaborative tasks such as vehicle pursuit. Regular vehiclesneed a reliable and fast communication channel to report adangerous road condition in real-time to the following vehi-cles, or to send an accident alert to a nearby ambulance. In themilitary domain, wireless real-time communication is requiredfor combat troops in the field. Supporting a real-time traffic inany network is a challenge. Obviously, this challenge becomesmore difficult in MANETs. Particularly, mobility, frequent out-of-range disconnects, high rate of errors in transmission, andpacket collisions are only some of the reasons that make real-time and QoS communication in MANETs a difficult goal toachieve.

    As mentioned in [1], the hard guarantee of real-time inMANETs is impossible. We focus on providing soft real-timeon data delivery, where some traffic may miss its deadline. Aservice model where no hard guarantees for data delivery ontime is provided in [1]. For example, the data delivery sessionscan be dropped and re-established due to disconnects causedby high mobility.

    In this paper we present a combination of state-of-the-art techniques for soft real-time and QoS communication inMANETs. Among those techniques are extrapolating the most

    efficient path between the source and destination, dynamicselection of the efficient routing path, scheduling the datatransmissions according to their real-time and QoS require-ments along this path, resource management.

    To demonstrate our innovative technology, we present areal-time and QoS unicast routing protocol, called RUMAN(Real-time Unicast Mobile Ad-hoc Network). In RUMAN,every mobile node broadcasts its state, periodically or upona significant change, to all the other nodes. The state messagehas a constant size and contains only location, velocity, and theamount of allocated resources of the sender node. As a result,each mobile node can extrapolate the connectivity graph of thesystem at any time. Upon a connection request between twonodes, RUMAN is responsible for creating and maintaining aQoS path for the connection so that every packet arrives at itsdestination within a specific time frame.

    Using the extrapolated connectivity graph, RUMAN findsall the candidate paths that fulfill the QoS requirementsbetween the two nodes. RUMAN immediately starts to sendthe data packets along the multiple paths until it detects themost effective path among them. RUMAN addresses the highmobility by extrapolating the candidate paths and choosing themost effective path(s) from the connectivity graph. To supportthe extrapolation real-time traffic, RUMAN reduces the col-lisions among the mobile nodes by limiting the transmittedpackets to a rate that does not exceed the maximum capacityof the shared medium among the mobile nodes within 2-hopneighbors. In addition, RUMAN manages the resources andschedules the message transmission at every node to supportthe desired traffic service.


    We assume a MANET system consisting of a set ofmobile nodes that may communicate with each other usingomni-directional antennas. We denote the mobile nodes byM1,M2, . We assume that all mobile nodes have the sametransmission range of r. Two nodes Mi and Mj can commu-nicate directly with each other if Mi is within the transmissionrange of Mj and vice versa. Let d() be the Euclidean distancefunction, we say that Mi is a neighbor of another node Mjif d(Mi,Mj) r. We denote by Ni all the neighbors of Mi,

    The 8th IFIP Annual Mediterranean Ad Hoc Networking Workshop 2009

    978-1-4244-4661-2/09/$25.00 2009 IEEE 21

  • i.e., Ni = {Mj | d(Mi,Mj) r}.1 We represent a MANETsystem with a corresponding graph. The nodes of the graphrepresents the mobile nodes. Two nodes are connected in thegraph only if they are neighbors.

    We impose no limit on the maximum number of mobilenodes in the system but we assume that the mobile nodesare scattered in a given finite size area. A node can physicallymove within this area. It may move at any time in any directionand at any speed. New nodes may join and existing nodes mayleave at any time. Therefore, the link connectivity and networktopology change with nodes movement.

    We assume that every node has access to a location servicesuch as Global Positioning System (GPS). Such a serviceprovides position, velocity, and time (PVT) information aboutthe node. In addition, we assume the standard communicationstack for the mobile nodes, where the MAC layer works withCSMA/CA transceiver. We assume that every mobile node hasa unique address for routing.

    If a mobile node Mi wants to send data to another nodeMj , we say that Mi wants to establish a session with Mj . Weassume that a session s is associated with three parameters:the latency deadline (denoted Ds), the required bandwidth ortransmission rate (denoted Bs), and the lifetime (denoted Ls).Ds specifies the real-time requirement where every packet Pof s should arrive at the destination node within Ds. Whena session s is established between two nodes Mi and Mj ,a corresponding path called the session path, denoted s, isdefined between Mi and Mj .


    We outline the main state-of-the-art techniques of our pro-posed technology.

    Extrapolation: By this technique, every mobile node canextrapolate the location of any other node in the system.It requires that every mobile node disseminates its locationand velocity periodically and whenever there are significantchanges in its velocity vector. The dissemination is done byan efficient broadcast routing protocol such as the multipointrelaying protocol [2]. Since we require that every node Midisseminates its state info only upon a significant changein its velocity vector, the period time between consecutivedisseminations at Mi could be quite long. As we see later,the overhead of those state info messages is small.

    Bandwidth Management: As mentioned in [3], [4], thebandwidth management in MANETs is a key issue for pro-viding QoS communication. Consider Figure 1, when node Miwants to transmit a packet P , its transmission might collidewith that of other nodes in Ni, which includes Mj and Ml.Moreover, due to the hidden terminal problem and contentionin the wireless shared media, Mi may contend also with Mk,

    1In practice, the transmission range does not behave exactly as a diskdue to various physical phenomena. However, for the description of theprotocol it does not matter, and on the other hand, a disk assumption greatlysimplifies the formal model. In any case, our simulation results are carriedon a simulator that simulates a real transmission range behavior includingdistortions, background noise, unidirectional links, etc.

    where the packet may collide at Mj . Therefore, Mi contendswith all the nodes in

    MjNi Nj . We define the contention

    region of Mi, denoted by Ci =

    MjNi Nj .

    Fig. 1. Several nodes may contend with Mi

    As mentioned in [3], the bandwidth for a QoS connectioncan be evaluated. Therefore, if we assume that the maximumbandwidth of a contention region Ci is B bps, then by limitingthe transmission rate to B we improve the QoS transmissionsin Ci, by keeping data contention low. We define B to bethe maximum transmission rate of a wireless channel in theMANET system.

    We say that a mobile node Mi participates in a particularsession s if a path of s includes Mi. Let Si be the setof all the sessions in which Mi participates. Let bi be thetransmission rate of the node Mi. The value of bi equalsthe sum of required bandwidth of all sessions in whichMi participates, i.e., bi =

    sSi Bs. To guarantee a QoS

    connection for every session s, therefore, we need to allocateat least Bs bandwidth in Ci at every node Mi in s. Theallocated bandwidth in Ci should not exceed the thresholdB. Hence, upon a new session s at Mi, Mi decides whetherto allocate a new bandwidth for s according to the availablebandwidth in Ci. We define the available bandwidth of Mi inCi, denoted by ABi, as ABi = B (

    MjCi bj). We need

    to ensure the condition that ABi 0 at every node Mi.Session Management: The available bandwidth condition

    ABi 0 should hold at every node. However, due to mobility,this condition may not hold. Once ABi becomes negative,we select one or more sessions in Mi to suspend until ABibecomes nonnegative. Notice that when a session be