Wireless Machine-to- Machine Routing Protocol with Unidirectional Links

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1 Smart Computing Review, vol. 1, no. 1, October Smart Computing Review Wireless Machine-to- Machine Routing Protocol with Unidirectional Links Megat Zuhairi 1, Haseeb Zafar 2 and David Harle 1 1 Department of Electronic and Electrical Engineering at the University of Strathclyde, Glasgow, UK / {megatfarez, d.harle}@eee.strath.ac.uk 2 Department of Computer Systems Engineering at the University of Engineering and Technology, Peshawar, Pakistan / haseeb@eee.strath.ac.uk Received June 19, 2011; Revised August ; Accepted September 6, 2011; Published October 31, 2011 Abstract: Wireless Machine-to-Machine (M2M) technology is a new approach to network communication that covers a wide area of applications. In this paper, we propose a reliable ondemand routing protocol for wireless M2M in Mobile Ad Hoc Network (MANET) applications such as telematics, healthcare devices, remote sensing for data mining, and building security monitoring systems. Generally, devices in such networks are typically battery powered and have wireless interfaces that could be connected to existing wireless infrastructures (e.g., IEEE ) wireless networks. Devices on the network have different properties (i.e., transmission power) and thus communication may follow a sub-optimal path (i.e., asymmetrical path). We propose a reliable routing protocol that efficiently constructs a routing path in M2M with minimal route acquisition time and is capable of utilizing all possible link connectivity (i.e., unidirectional and bidirectional links). The performance differentials are investigated using NS-2. Our simulation results show that the proposed scheme achieves minimal end-to-end delay connection, higher goodput, and maximum reduction of normalized routing loads when compared with the competing Ad Hoc Ondemand Distance Vector (AODV) routing protocol. Keywords: Machine-to-Machine (M2M), Mobile Ad Hoc Network (MANET), IEEE , Ad Hoc On-demand Distance Vector (AODV) Introduction T he M2M [1] communication in MANETs is more than a peer-to-peer communication between devices. In a complex network, data can be transmitted and relayed from client to server through the existing wireless infrastructure or via a series of relay client devices. The key mechanism to a successful end-to-end connection is route construction between a pair of source and destination machines. Generally, route establishment techniques can be classified DOI: /smartcr

2 Smart Computing Review, vol. 1, no. 1, October into proactive and reactive techniques. In MANET M2M communication, devices in effect transmit short bursts of data only when requested by the receiver. In such cases, compared to the proactive method, on-demand routing is more feasible since it invokes lower operating overheads. In general, excessive routing overhead is typically caused by multiple rounds of broadcast (i.e., route discovery packets) to discover the complete network topology. Therefore, it is essential that broadcasting in M2M is reduced as far as possible and to allow a maximum length message to be transmitted to the receiver. To facilitate data distribution in M2M applications, such as digital information boards, on-demand routing protocol may employ a controlled broadcasting technique to discover routes; for example, probability-based flooding or expansion-ring. Routes obtained using broadcasting methods could follow links that are not symmetrical. This asymmetry is due to the nature of wireless medium, where radio signal propagation between two wireless devices is not identical and has different characteristics leading to unidirectional links. The fact that MANET links can be unidirectional is incompatible with the operation of many routing protocols. As a result, forming symmetrical and bidirectional routes can fail and communication could be routed via paths that are detrimental to M2M system performance. Unidirectional links result from various combinatorial factors affecting the transmission range of wireless devices. Since links are radio signals, connectivity is heavily influenced by the external noise source that impacts the wireless signal strength. Such properties vary from one wireless device to another. A typical example is unequal signal to interference and noise ratio (SINR) experienced by adjacent wireless devices. For example, in Figure 1, nodes X and Y, set with equal transmission power level, are attempting to communicate with each other. SINR at node X, for instance, is lower than that measured at node Y. This is because of the severe interference caused by external noise generated by neighboring nodes W and Z. Due to the high background noise and accumulated interference (i.e., due to packet interference from nodes W and Z), nodes X and Y will experience two different levels of SINR. Therefore, in extreme cases, node Y will not be able to correctly receive packets from node X which, from node Y s perspective, presents a unidirectional link. Unidirectional links may also be caused by unequal transmitting power (P t ) configured at each device. For instance, a network that employs a power-aware routing protocol [2] will attempt to control the awake and/or sleep scheduling of a node to conserve energy. Consequently, the power link budget in the forward direction may not be equal to that in the opposite direction, resulting in a unidirectional link. Other factors may also affect link directionality; for instance, directional antennas, network policy, and fading. Throughout this paper, the term unidirectional links will refer to links with asymmetrical properties caused by irregular P t. Routing with Unidirectional Links A wide variety of routing protocols have been proposed for MANETs [3 5]. However, many of the protocols simply ignore the presence of unidirectional links in the network. As such, the implementation of these schemes often exhibits

3 60 Zuhairi et al.: Wireless Machine-to-Machine Routing Protocol with Unidirectional Links connectivity issues, affecting the overall network performance. Next, a typical on-demand routing protocol (i.e., AODV) operation is discussed in a network scenario where the routing protocol is severely affected by the presence of unidirectional links. The fundamental property that ensures correct operation of the on-demand routing protocol depends in bidirectional link availability between nodes. Unless at least one single bidirectional path between the source and the destination exists, the routing protocol will not function properly and connections will not be made between node pairs. Other routing protocols that share a similar property may have similar constraints. If all links in the network are bidirectional, then AODV guarantees that, based on the algorithm, the routing path created between the source and the destination will be the shortest hop with the lowest delay. However, depending on the network condition, constructing routes solely via bidirectional links may not be possible. As such, if nodes are unable to find at least a single bidirectional link between the source and destination pair, then the AODV scheme will fail to function. In the presence of unidirectional links, AODV routing path construction may cause sub-optimal network performance. For example, a network with low node density and a large number of unidirectional links may have higher chances of setting a forward route (i.e., from source to destination) through unidirectional links. As a result, a destination node may not be able to reach the source using the reverse of the forward route created. Figure 2 shows that node A is the source and node G is the destination. The routing packet from A is assumed to reach G through path A-B-E-G. The link (B-E) is unidirectional, pointing to node E. Assuming that nodes are moving at a relatively low speed, route discovery will fail to construct a reverse route from G to A. This is because node E is able to receive packets from B, but not vice versa, even though E has established a reverse route with B as the next hop candidate to reach A. Further attempts of a route request broadcast by the source node will likely produce a similar result, hence increasing the overall routing overhead. To counter the inherently unreliable effect of unidirectional links, several schemes have been proposed. The current Ad Hoc On-demand Distance Vector (AODV) routing protocol implements a Blacklist technique [3]. Nodes that are not reachable due to unidirectional links are temporarily stored in a set of blacklist nodes. This is to ensure that all routes discovered will be completely bidirectional between source and destination nodes. Ko et al. [6] introduce Early Unidirectional Link Detection and Avoidance (EUDA), a proactive method to detect unidirectional links. An estimated distance towards the sender is computed using information carried within the route request (RREQ) packets, i.e., P t of the sender, SINR threshold, receive threshold (RXThresh), and total noise (P n ). Based on the estimated distance, the receiver node may be able to determine if the link facing the sender is unidirectional. Although the simulation results show improved performance, the overall routing load is increased due to the introduction of additional fields in the control packet, where P t and P n values are required to be piggybacked on RREQ. Nonetheless, this scheme is only suitable for networks characterized by low nodal mobility and high SINR. In addition, the computation of estimated link distance is resource exhaustive and may affect nodes battery lifetime.

4 Smart Computing Review, vol. 1, no. 1, October Loop-Based Source Routing (LBSR) [7], an on-demand routing protocol based on Dynamic Source Routing (DSR) [8], suggests that unidirectional links can be utilized using the loop detection method. The protocol is based on the combination of single flooding and multiple unicast message transmission. A Loop Request (LREQ) packet, similar to RREQ in DSR is flooded into the network and all nodes including destination append their identification (ID) into this packet. A Loop Confirmation (LCONF) packet containing a list of nodes ID is then unicast to every node on the network. Again, routing protocols such as LBSR and DSR rely heavily on flooding to discover the routing paths; therefore, they may have issues with inefficient routing overhead management. In [9], an ad hoc routing protocol with flooding control that takes advantage of unidirectional link is proposed. The objective is to limit the flooding range of a route reply (RREP) in the reverse path discovery. In this scheme, each node records the number of hops away from the source based on time-to-live (TTL) value in RREQ. Bounded by this value, the backward flooding search can be controlled effectively. The simulation results have shown that the messaging overhead in the proposed protocol is lower than those of DSR and AODV. Venugopalan et al. [10] introduce a framework called Bidirectional Routing Abstraction (BRA) that provides a bidirectional abstraction of an asymmetric network to the routing protocol. In this technique, the scheme actively discovers and maintains reverse paths for unidirectional links. The core is an algorithm called Reverse Distributed Bellman-Ford Algorithm (RDBFA) that searches for reverse routes in a bounded area around each node. The proposed scheme is able to offer improved connections between nodes and provides reverse route forwarding for unidirectional links. The Proposed Scheme We propose a scheme that supports unidirectional links for routing construction in wireless M2M. The scheme is based on AODV, but the core mechanism is protocol independent and as such, it may be incorporated into other routing protocols that share similar properties with AODV. Routing Operation The current AODV routing protocol defines an avoidance technique using a blacklist set to detect and avoid unidirectional links. By way of a contrast, the proposed scheme utilizes such links to its advantage in routing path construction. In the event of acknowledgement (ACK) packet absence, the identified unidirectional links will not be blacklisted. Instead, the routing packet is simply redirected to an alternative path that may have access to the sender. In order to find potential routes, nodes that are subject to unidirectional links will store the current RREP routing packet information and promptly invoke a one-hop local reply broadcast [11] mechanism. This technique benefits from the route entries recorded by intermediate nodes during the route discovery phase while maintaining the bidirectional link operation. To illustrate this idea, consider the scenario in Figure 2, and the corresponding routing entry recorded just after the first route discovery, as shown in Table 1. The following steps illustrate the routing path construction of the proposed scheme: 1) Initially, the scheme sets up a forward route through links A-B-E-G, assuming this link is a path with the lowest delay (i.e., shortest path). 2) Nodes C, D and F record the route entries received during the RREQ discovery phase. Although these nodes are not considered for routing path set up, they have a routing entry pointing towards the source (i.e., node A), shown in Table 1, and therefore could provide alternative routes if the reverse route is blocked by unidirectional links. 3) Upon the completion of RREQ discovery, the destination node (i.e., node G) then responds to the RREQ packet received by unicasts a RREP packet via the reverse route along with RREP_NO_FLAG bit set. 4) If the destination node receives multiple copies of a route request, then it will respond (by returning RREP) only to the first RREQ packet received or a packet with most updated entries. This effectively reduces the routing load incurred in the system. 5) A copy of RREP packet must be recorded prior to each transmission, which will be used for local reply broadcast retransmission if the preceding RREP forwarding fails. 6) At the intermediate node (e.g., node E), the received RREP content is checked against its routing table. An RREP packet with fresh information is forwarded to the immediate next hop node and waits for an ACK packet. Non-fresh packets will be dropped.

5 62 Zuhairi et al.: Wireless Machine-to-Machine Routing Protocol with Unidirectional Links 7) If ACK is not received within the time defined by ACK_WAIT_TIME in Table 2, then it caches B as an unreachable node. Node E then immediately invokes the one-hop local reply broadcast mechanism, where similar RREP copy is broadcast to the adjacent neighbors with TTL set to 1, effectively preventing a multi-hop packet propagation. 8) Any node (except packet originator), which is within node s E P t (i.e. node D), captures the broadcast RREP and subsequently forwards them to their corresponding next hop node. 9) Each node along the RREP propagation will indicate in their record (i.e., cache memory) that the packet has been recovered by inserting the source address, destination address, and sequence number <Src ID, Dest ID, seq_num> pair combination. Thus, any subsequent RREP packet received with a similar combination that matches the record will be dropped and propagated no further to reduce congestion. In the proposed scheme, a path between the source and the destination may be created on the first route discovery attempt if there are sufficient alternative routes to complete the route construction. In the worst case scenario, where a forward route could not be established by the first RREQ discovery attempt, a subsequent RREQ broadcast will be made by the source node until the maximum RREQ_RETRIES shown in Table 2 is reached. In addition, the RREP packet from the destination node must follow in reverse, as far as possible, the forward route created, and diverted to alternative route only when the primary forward path is blocked. Such requirement is important in order to preserve the bidirectional properties of the routing protocol. Network Layer Feedback As noted in [12], utilizing unidirectional links could increase the unnecessary routing overhead. Therefore, in this scheme, a countermeasure is implemented to minimize the unidirectional links. The introduction of ACK packet in the proposed scheme has slightly increases the overall routing overhead incurred. However, ACK packet exchange can be significantly reduced if nodes are correctly set to respond to different types of RREP packets. The protocol will ensures that ACK should only be returned for RREP packet, in which the RREP_NO_FLAG bit is set. On the other hand, nodes are not required to return ACK for RREP with the flag bit set to one-hop-broadcast (OHR). As a result, control message exchange can be reduced leading to the efficient use of bandwidth resource. Also, an important ACK timeout threshold is reset after every RREP delivery (i.e., RREP with flag RREP_NO_FLAG). The timeout parameter value is set by ACK_WAIT_TIME given by Table 2, where it should not exceed the maximum RREP_WAIT_TIME set by default AODV parameter specification. In addition to the ACK message exchange reduction, the proposed scheme can substantially reduce the number of RREQ in the system. The simulation results show that the RREQs packet generated by source account for the majority (more than 90%) of control packets in the network. For example, the Blacklist method requires multiple RREQ flooding by source to attempt to re-establish a broken routing path due to unidirectional links. In contrast, the proposed scheme

6 Smart Computing Review, vol. 1, no. 1, October effectively avoids such problem by attempting to locally restore the routing path. Therefore, a failure of ACK reception by any node will not cause subsequent RREQ flooding by the source. Reverse Path and Local Reply Broadcast As previously discussed, the scheme allows a node to seek multiple reverse routes if the primary path towards the source is blocked by unidirectional links. As such, multiple copies of RREP packet will be forwarded through different paths and may reach the source node on several paths. To ensure routing efficiency, each time a node generates or receives a RREP packet, it records the details in its cache, uniquely identified by the source ID, destination ID, and unique sequence number <Src ID, Dest ID, seq_num>. Assumes that node F is able to receive the signal (i.e., routing packet) from E. A recovered RREP packet from E will propagate via two reverse paths towards node A (i.e., E-D-B-A and E-F-C-A) after node E invokes the local reply broadcast mechanism. Upon reception of the first RREP (e.g., from path E-D-B-A), node A will record the RREP details in its cache (i.e., <node A, Node G, seq_num>). The subsequent RREP packet received (i.e., via path E-F-C-A) is then compared against this cache, and if a match is found, then the RREP is discarded. The RREP details are cached for a time period invoked by RCAST_WAIT_TIME shown in Table 2. The value of this timer must not exceed the time difference between a node propagating a RREQ and receiving the RREP back. Equation (1) computes the time difference (i.e., the roundtrip time of RREQ-RREP packet). 3 NetworkDia meter NodeTraversalTime (1) The Network Diameter is set to 30, based on the maximum allowed hop count in AODV. The Node Traversal Time is set to 0.03 seconds, which is based on a conservative estimate of the average one-hop traversal time, which includes queue, transmission, propagation, and all other delays. Simulation Setup and Routing Performance Analysis The proposed scheme is evaluated and compared to basic AODV and the AODV with Blacklist technique, which employs the unidirectional link avoidance technique through a blacklist database. The performance of each scheme is observed in terms of several performance metrics [13]. The routing protocols are simulated using NS-2.33 [14], a discrete event simulation tool that allows experiments to be replicated with controlled parameters. In this simulation, nodes P t are randomly varied with two different power levels. First, a radio transmitting power of 13dBm (20mW) is used; second, an approximately 50% power reduction to 7dBm (5mW). Thus, two adjacent nodes, each assigned with different P t, will presumably generate a unidirectional link. Simulation Setup Table 3 lists the protocol parameters used for the simulation. The number of source-destination pairs is set to 25 in order to simulate a highly congested network. In addition, the numbers of nodes assigned with P t values are varied gradually as shown in Table 4. The signal propagation model is set as a two-ray ground model, in which the shadowing and fading effect is not considered. The link layer for all schemes follows the MAC protocol. We have created 50 different unique network topologies generated using BonnMotion [16] tool. The same set of scenarios is then repeated for every scheme. In other words, each point plotted on the graph corresponds to an average of 50 experiment repetitions. All the nodes are restricted to a maximum speed of 10 m/s in a Gauss Markov mobility model. This model typically represents a more realistic node movement with speed and direction bounded in a square area. Result Analysis The proposed scheme is compared against AODV and Blacklist in terms of four performance metrics, packet delivery ratio, normalized routing load, average path length, and average end-to-end delay. In this simulation experiment, two different levels P t are assigned to 6 sets of nodes. To ensure that this setup will correctly produce a certain amount of unidirectional links in the network, we compute the number of RREQ packets generated by all source nodes. Figure 3 shows the average number of RREQ sent by the sources in each scheme. We

7 64 Zuhairi et al.: Wireless Machine-to-Machine Routing Protocol with Unidirectional Links observed that the average number of generated RREQ significantly increases with the increase of unidirectional links. In general, the source nodes are required to transmit four times as many RREQ packets when 50% of the links are set to 7dBm P t, as compared to when all nodes are set with 13dBm P t. In general, the simulation results obtained are consistent with our expectations, where unidirectional links can be generated by varying the nodes P t. Table 3. Parameters of Simulation Scenario MAC layer settings are configured based on Cisco Aironet 350 specification.[15] Packet Delivery Ratio First, we quantify the routing protocol s packet delivery ratio (PDR) based on the average ratio of accumulated data packets delivered to destinations compared to those generated by data sources. In line with our expectation, the resultant PDR of the proposed scheme in Figure 4 shows a significant difference compared to AODV and Blacklist. This effect is the result of the local reply broadcast, which more rapidly detects broken paths caused by the unidirectional links or nodes moving away from the established route. Also with the proposed scheme, the sources received significantly more RREP packets compared to those with the other competing protocols. As shown in Figure 5, the normalized number of unidirectional links (i.e., the number of unidirectional links per RREP) is reduced by as much as 90% compared to AODV. The high number of RREP received at the sources increases the chances of route being established, which leads to a better routing performance. Although the Blacklist scheme is able to setup more routes compared to AODV, shown by the high number of normalized unidirectional links, it fails to improve the PDR performance. This is caused by blocked links that result from the failure of transmitting RREP packets via the unidirectional links, therefore reducing the number of RREQ packets received by the nodes. Consequently, link connectivity is severely affected. On the other hand, instead of blocking the links that are found to be unidirectional, our proposed scheme redirects the packets around them by taking advantage of all available links associated with the neighbor nodes.

8 Smart Computing Review, vol. 1, no. 1, October Normalized Routing Load Next, we present the normalized routing load (NRL) performance metric. This value is based on the number of routing packets sent and forwarded by each node over the entire simulation time to the number of data packets received by the sink nodes (i.e., destination nodes). Essentially, a lower NRL value indicates an efficient network, where the number of data packets received is higher than the number of routing packets generated for that particular connection. In addition, NRL is also affected by the number of nodes participating in the routing packet exchange, where a low number of nodes propagating the RREQ may decrease the NRL value. As shown in Figure 6, at any intensity of unidirectional links, the Blacklist scheme always offers a lower NRL compared to AODV and the proposed scheme. The small increase in NRL by the proposed scheme is caused by ACK packet delivery and RREP retransmission after the detection of unidirectional links. Nevertheless, the additional overhead of these control packets is clearly compensated for by the higher PDR achieved by using the proposed scheme.

9 66 Zuhairi et al.: Wireless Machine-to-Machine Routing Protocol with Unidirectional Links Average Path Length Figure 7 shows the average path length (APL) found by each routing protocol. The average path length is quantified by the number of hops computed along each routing path found, averaged over the total number of routing path established throughout the simulation. The AODV and Blacklist schemes have been shown to compute a shorter path between source and destination pairs compared to that by the proposed scheme. On the contrary, the proposed scheme incurs a higher APL, which is the result of the local reply broadcast technique. The technique rediscovers an alternative path around the unidirectional links, resulting in a slight increase in the number of hop count. Since APL is directly proportional to the number of routing paths found, a high APL value may indicate better performance, where more routes are found using the proposed scheme compared to the other competing protocols. Average End-To-End Delay Figure 8 shows the average end-to-end delay in network scenarios by varying the number of unidirectional links. The proposed scheme and Blacklist show significant decrease in end-to-end delay compared to AODV. It is because the ACK packets are lost during transmission, thus causing forward routes to be detected as unidirectional. In addition, the absence of ACK packet invokes the local broadcast mechanism that finds alternative routes through a longer path; hence, a higher delay is incurred. It is also observed that the average end-to-end delay of AODV and the Blacklist scheme remain at a level consistently higher than the proposed scheme throughout the entire experiment. This is expected since both schemes constrain routing by using only bidirectional links. Therefore, such requirement avoids forward route construction over unidirectional links, which most often have longer paths and higher delays. In contrast, the proposed scheme takes a different approach; it utilizes the unidirectional links for route computation by compromising a slightly higher hop count (thus higher delay); therefore, an improved overall routing performance can be achieved. The effect of unidirectional links on end-to-end delay is clearly shown in Figure 8. With the presence of a high number of unidirectional links (i.e., Set 5), the average end-to-end delay of the proposed scheme is almost half as less, compared to AODV. Summary This paper presents the M2M routing protocol analyzed with non-homogeneous network consisting of various intensities of unidirectional links. The presence of unidirectional links may frequently arise; a consequence of irregular wireless properties in the network. Links that are unidirectional affect the routing path construction leading to a lower probability of connectivity. For example, the AODV routing protocol, which is designed to avoid routing packets through such links, may incur higher cost (i.e., routing overhead). In addition, node connectivity is not fully utilized. The Blacklist mechanism may offer just a slight improvement to the original scheme (i.e., AODV). Even though the detection mechanism is sufficient to identify and isolate unidirectional links, avoiding them is not the best approach. In fact, the resulting normalized routing load is higher, reducing the overall scheme s efficiency. In contrast to AODV and Blacklist, the proposed scheme utilizes all possible link connectivity (i.e., bidirectional and unidirectional link) to achieve an advantage. These links are not avoided; instead, they are temporarily allowed to forward the routing packets to the destination. On reverse route, nodes that are affected by unidirectional link promptly invoke a local reply broadcast to discover an alternative path towards the source. This method is effective, where the route may be quickly constructed without waiting for a subsequent route discovery request by the source. However, the benefit of rerouting through a different path comes with a tradeoff. The proposed scheme incurs a slight increase in hop count, but this drawback is generally insignificant compared to the overall performance. Conclusion We have proposed a scheme to improve the performance of wireless M2M communication in MANET with nonhomogeneous devices transmission power. The performance of the proposed scheme is evaluated and compared against that of the AODV and Blacklist schemes. The proposed scheme achieves higher packet delivery by more rapidly discovering alternative routes around the unidirectional link, thus avoiding the need for multiple RREQ discoveries. In network scenarios with a higher number of unidirectional links, the proposed scheme is able to minimize routing overhead, but with a slight increase in route length. The overall routing performance is analyzed with respect to realistic mobility models (i.e., Gauss Markov), and the results have shown that the proposed scheme improves M2M communication to

10 Smart Computing Review, vol. 1, no. 1, October operate in a network with high presence of unidirectional links. In future work, we will improve the scheme by adding detection using the receive signal strength index (RSSI). References [1] G. Lawton, Machine-to-machine technology gears up for growth, Computer, vol. 9, no. 37, pp , Sep Article (CrossRef Link) [2] J. Gomez, A. Campbell, Variable-range transmission power control in wireless ad hoc networks, IEEE Transactions on Mobile Computing, vol. 6, pp , Jan Article (CrossRef Link) [3] C.E. Perkins, E.M. Royer, S. Das, Ad hoc on-demand distance vector (AODV) routing, RFC 3561, July [4] C.E. Perkins, P. Bhagwat, Highly dynamic destination sequenced distance vector routing (DSDV) for mobile computers, in Proc. of ACM SIGCOMM, pp , Article (CrossRef Link) [5] V. Park, S. Corson, Temporally ordered routing algorithm (TORA), IETF Internet Draft, [6] J. Lee, EUDA: detecting and avoiding unidirectional links in ad hoc networks, ACM SIGMOBILE Mobile Computing and Communications Review, vol. 1, no. 2, pp. 1-4, Oct Article (CrossRef Link) [7] T. Asano, H. Unoki, H. Higaki, LBSR: routing protocol for MANETs with unidirectional links, in Proc. 3rd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, USA, pp. 84, Oct Article (CrossRef Link) [8] D.D.B. Johnson, Y. Hu, D.A. Maltz, Dynamic source routing in ad hoc wireless networks, RFC 4728, Feb [9] S. Terada, T. Miyoshi, H. Morino, Ad-hoc routing protocols with flooding control using unidirectional links, in Proc. of the International Symposium on Personal Indoor and Mobile Radio Communication, Greece, pp. 1-5, Sept Article (CrossRef Link) [10] V. Ramasubramanian, D. Mosse, BRA: a bidirectional routing abstraction for asymmetric mobile ad hoc networks, IEEE/ACM Transaction on Networking, vol. 16, no. 1, pp , Feb Article (CrossRef Link) [11] M. Zuhairi, Dynamic reverse route in ad hoc on demand distance vector routing protocol, in Proc. of 6 th International Conference on Wireless and Mobile Communications, pp , June Article (CrossRef Link) [12] M. Marina, Routing performance in the presence of unidirectional links in multihop wireless networks, in Proc. of 3rd ACM International Symposium on Mobihoc, Switzerland, Jun Article (CrossRef Link) [13] H. Zafar, D. Harle, I. Andonovic, Y. Khawaja, Performance evaluation of shortest multipath source routing scheme, IET Communications in Special Issue on Wireless Ad hoc Networks, vol. 3, no. 5, pp , May Article (CrossRef Link) [14] The Network Simulator NS-2, [15] Cisco Aironet 350 Series Client Adaptor specification, [16] BonnMotion: A mobility scenario generation and analysis tool, Megat Zuhairi is a PhD student within the Department of Electronic and Electrical Engineering at the University of Strathclyde, Glasgow, UK. He received his M.S in Communication Networks and Software from the University of Surrey, UK in 2002 and B.Eng. degree in Electronic and Electrical Engineering from Universiti Tenaga Nasional, Malaysia in He is a lecturer and a certified Cisco Network Academy Instructor in the System and Networking Section at Universiti Kuala Lumpur, Malaysia. His research interests include computer data networking, and wireless mobile ad-hoc communications. Haseeb Zafar received the Ph.D. degree in Wireless Mobile Ad-hoc Networks from the University of Strathclyde, Glasgow, UK in 2009, the M.S. degree in Telecommunications and Computers from the George Washington University, Washington DC, USA in 2003 and the B.Sc. degree (with Honors) in Electrical Engineering from the University of Engineering and Technology, Peshawar, Pakistan in He is a Visiting Researcher in the Department of Electronic & Electrical Engineering at the University of Strathclyde, Glasgow, UK and an Assistant Professor in the Department of Computer Systems Engineering at the University of Engineering and Technology, Peshawar, Pakistan. His research interests include data communications, computer networks, wireless communications and mobile ad-hoc, sensor and

11 68 Zuhairi et al.: Wireless Machine-to-Machine Routing Protocol with Unidirectional Links mesh networks. He has authored and co-authored many research papers in journals of international repute including the IET Communications. He has presented his research work in various international conferences. He is an active reviewer of many international journals including the IEEE Communication Letters and the IET Communications. Moreover, he has served as the TPC member of several international conferences including IEEE GLOBECOM, IEEE ICC, IEEE VTC, IEEE CCNC and IEEE WCNC. David Harle is currently a senior lecturer within the Broadband and Optical Networks Group within the Department of Electronic and Electrical Engineering at the University of Strathclyde, Glasgow. He received his Ph.D. in Integrated Telecommunications from the University of Strathclyde in 1990, having previously been a Research Assistant in the same department. His current research interests within the Broadband and Optical Networks group focus upon performance evaluation, design and management issues associated with current and future broadband and optical communication systems. The author of over 100 research papers and undergraduate texts, he is also a member of the IET and IEEE. Copyrights 2011 KAIS

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