UAV ASSISTED DISRUPTION TOLERANT ROUTING

Transcription

1 UAV ASSISTED DISRUPTION TOLERANT ROUTING Michael Le, Joon-Sang Park, and Mario Gerla Computer Science Department University of California, Los Angeles Los Angeles, CA proposed DTN UAV Assisted routing protocol will make it possible for far flung mobile nodes to communicate in environments where they normally would not be able to due to practical constraints such as the lack of energy and the lack of long range high capacity network interfaces. This paper is structured as follows. Section 2 describes the scenario that we envision in more detail, Section 3 describes the DTN UAV Assisted routing protocol, Section 4 discusses the simulation results, and Section 5 concludes this paper. Abstract In order to provide network connectivity in highly partitioned ad-hoc networks, we propose a routing strategy that incorporates an existing ad-hoc routing protocol, Ad hoc On Demand Distance Vector (AODV), with Disruption Tolerant Networking (DTN) a la storecarry-forward mechanisms using Unmanned Aerial Vehicles (UA Vs) as carriers. This paper focuses on the design, implementation, and evaluation of the routing strategy. The major contribution of this work is the implementation of our DTN aware routing protocol on top of existing and mostly unmodified AODV We show the advantage of the DTN protocol through simulation using ns-2. II. Environment Description The environment that we envision consists of islands of mobile ground nodes that are spread wide apart with practically no network connection between any two islands. Between these islands of mobile ground nodes are the UAVs. These UAVs do not exist for the sole purpose of carrying messages as in [5] but are there for a different and possibly independent reason. We do not assume that we have control over the motion of the UAVs. Our routing protocol makes use of these UAVs for communication and to create network connections between disjoint islands of mobile ground nodes. The mobile ground nodes are equipped with short range high bandwidth air interfaces and the UAVs have both short range high bandwidth as well as long range, low bandwidth interfaces. We assume that the UAV long range air interfaces are mainly for UAV motion control and management; but, can also carry a small amount of data traffic. Geo location is available (using GPS or other localization means) on UAVs but not in the ground nodes. The network is assumed to be always connected via a combination of long and short range links (with aggregate low rate); it is only intermittently I. Introduction This paper focuses on the design and evaluation of a routing strategy for highly partitioned ad-hoc networks. These networks have the characteristics of being sparse with intermittent end to end connectivity due to mobility and limited range of the communication hardware [1,2,5]. The routing strategy that we are proposing uses Ad hoc On Demand Distance Vector (AODV) [4] as the underlying routing protocol with very minor augmentation for Disruption Tolerant Networking (DTN) support. The DTN part of our protocol basically uses UAVs as message ferries to store, carry, and forward messages to the destination when it is impossible and or impractical to directly transmit the messages through intermediate nodes [5]. The * This work was supported in part by the National Science Foundation under Grant No and the US Army under MURI award W91 1NF Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies. 1

2 connected by short range links (and high data rate). Not all the ground nodes are directly connected to a UAV, thus several hops may be needed for a ground node to reach a UAV. A diagram of our scenario can be seen in Figure. 1. Adt tro ieintaifto SUASV Sde y Cact I1~LoW. b>andodth F-1 Desiinabon Side Sky Cartac., Aj r t1o OiwUhdX lntftfe -Short rhe -High Sndh * A X. irt * ai Oud X Air irte - ru N3dleI The source-side-sky-contact performs the store-carryforwarding. While the source-side-sky-contact is ferrying the data, it probes the destination at very low rate. This is done by conventional RREQ/RREP handshaking. When a UAV ferrying data receives a RREP through the high bandwidth interface, it hands data over to the node transmitted the RREP using the high bandwidth interface and the data will be delivered to the destination through the path found by the last RREQ/RREP handshaking. There can be various store-carry-forward policies that can be implemented in the UAV. This store-carry-forward policy deals with the issues of when and where to forward a message once a message arrives at a UAV. For instance, if a UAV carrying the data flies by another UAV which is expected to meet the data destination in the near future, it might be better to hand over the data. Here, we implement the simplest policy, no hand-over of data between UAVs, and leave different store-carry-forward policy as future work. All messages flowing through the UAVs are first examined by the DTN routing agent to determine if the message is a control or data message. Control messages, such as AODV's RREQ/RREP, are forwarded immediately by the UAV by passing it down to the AODV layer after inserting additional information for forwarding decision. We assume that we know if a data packet is received through the long range low bandwidth interface or short range high bandwidth interface. Otherwise, the DTN routing agent indicates in the packet before sending. Data packets are passed down to the AODV layer for forwarding if the next hop can be reached with a short range high bandwidth interface. hrt range g1h bahnd h Figure 1. Network environment III. Routing Protocol Description Our routing strategy has two main parts: conventional reactive/proactive ad-hoc routing on the ground and DTN routing in the sky. Although our proposed routing strategy does not warrant a specific routing protocol on the ground, in this paper we use AODV to describe how to combine the reactive ad-hoc routing on the ground with DTN routing in the sky to create one cohesive routing protocol for the networking scenario. Detail of the AODV routing protocol can be gleaned from [4]. Our proposal requires no modification of AODV running on ground nodes. When a node tries to find a path to another node, it floods the network with RREQ; RREQ packets propagate through the low bandwidth, long range links as well as radio and high bandwidth, short range links. The destination replies with RREP which will follow the reverse path. We call the ground node that transmits the RREP to the UAV the destination-sideground-contact and the UAV that the RREP first encounter the destination-side-sky-contact. The RREP packet flows through the UAV network and it is transmitted to the island of ground nodes in which the source resides. We call the UAV transmitting the RREP to the ground the source-side-sky-contact. Once the source gets the RREP, it starts sending out data. IV. Simulation Results We implemented the protocol in ns-2 [3] and conducted a set of experiments. We used without RTS/CTS as the MAC Layer. The rate for the carrier sense and capture threshold of the MAC is set to the default values in ns-2. The bandwidth for the control packet is also set to the default value, which is 1Mbps. We used the free space propagation model in ns-2. The first two simulation scenarios have a topology of 500m x 500m while the rest have a topology of 700m x 700m all mapped on a 2-D grid. 2

3 Our simulation consists of mobile UAVs and ground nodes. The UAV nodes have two network interfaces: one interface is a long range narrow band with a transmission range of 250 meters and a bandwidth of 10Kbps while the second interface is a short range wide band with a transmission range of 60 meters and a bandwidth of 11Mbps. The above numbers are purely hypothetical, as no experimental data on UAV to UAV range and bandwidth was available at the time of this writing. Most of the time, the long range interface is only used to transmit control packets to set up a path. Each UAV also has buffer that can contain up to 500 packets. As we discussed above, the UAV performs the carry aspect of transmission and has a large buffer to accommodate the throughput demand. As mentioned earlier, the ground nodes contain one short range wide band interface with the same configuration as its counterpart in the UAV. We used a CBR traffic generator with the data rate of 10Kbps. Each of our simulation run is 1 hour long. Each results graph compares the sender throughput versus the actual throughput in each scenario. The sender throughput is measured by counting the number of packets being sent by the application. Since we used a constant bit rate traffic model, the sender is constantly sending, and so the number of packets sent is linearly increasing with time. We do not take into account packets being dropped at the source interface due to buffer overflow. The receiver throughput is measured by counting the number of packets actually received at the application layer. We consider a set of rather simple scenarios focusing on showing the basic DTN function of our protocol. The first scenario is the UAV shuttling scenario where two ground nodes are separated by more than the range of their network interface and two UAVs (triangles) are flying back and forth between the two ground nodes as illustrated in Figure 2.(b). The result of the UAV shuttling experiment in Figure 2 shows that the receiver throughput almost matches the sender throughput which is possible since the two UAVs are constantly taking turn shuttling messages from source to destination. However, there is a chance of the sender being disconnected from both UAVs and data is lost when this happens and thus there is discrepancy between the sender throughput and the receiver throughput. Also since the size of the UAV's buffer is limited, some messages that cannot be buffered at the UAV are dropped, thus further decreasing the receiver throughput. Shuttling: AJVas Carry -9 rc, a. I.- W.0 E z :DOO :OO 25DO Time (sec) Figure 2.(a). : Sender vs. Receiver s d Figure 2.(b). Scenario: Two ground nodes (circles) are separated by more than the range of their network interface. There are two UAVs (triangles) that start at opposite side of each other and fly back and forth between the two ground nodes. Figure 2. UAV Shuttling Scenario To measure the benefits of our store-carryforward policy versus the forward-only policy using long range radios, we ran the third simulation experiment using the scenario shown in Figure 2.(b) and the results are shown in Figure 3. The graph shows the actual throughput of using our store-carry-forward policy versus the forward-only policy. Our store-carryforward policy is to hold a message unless the next hop is a short range hop with high bandwidth interface. As can be seen from Figure 3, our store-carry-forward policy clearly out performs the forward-only policy despite the carry and forward delay. Since the long range interface has an extremely small bandwidth, it is 3

4 more beneficial to just hold on to the packets and deliver everything at once rather than try to forward "at all cost" using long range radios. Shutding: Carr Vs. Forward Through put is shared by two senders. In Figure 5, the second sender has lower throughput than the first sender and this is due to the second UAV's buffer being full after carrying messages from the first sender leaving no room for the second source. Multple Islands E t 000 Sende w Time (secj Figure 3. : Carry Vs. Forward Figure 4 shows our protocol in action when there is an intermediate island of ground nodes that separate the source ground node from the destination ground node. The transmitted message must traverse multiple UAVs (with an intermediate island of ground nodes) before reaching the destination. To transmit a message in this scenario, first the UAV has to carry and hand off the message to the middle island and have the ground nodes in that island forward the message up to the UAVs that can reach the final destination. The low receiver throughput is mainly attributed to the disconnection of the sender from UAVs. Since there is only one UAV flying between the leftmost island and the island in the middle, the sender (and also all other nodes in the same island) is disconnected from the UAV from time to time. The throughput is further decreased due to the limited amount of UAVs to do the actual shuttling. Figure 5 shows the results of the same scenario as in Figure 4 but with multiple sources at the first and second island while the destinations are at the third island. In this multiple source and destination scenario, the reasons for the discrepancy between the sender throughput and receiver throughput again are disconnection of the source from UAVs and limited buffer space. The receiver throughput in this multiple source and destination cases is lower than the one sender and receiver case since the limited UAV storage z 5000 IN Trime (sec) Figure 4.a. : Sender vs. Receiver Figure 4.b. Multiple Islands Scenario: Three islands of ground nodes (circles) with multiple ground nodes per island. The distance between the first and second island is 120m and between the second and third island is 300m. 3 UAVs (triangles) total, with one UAV hovering at the first island. The second UAV is shuttling between the second and third island. The third UAV is hovering at the third island. Figure 4. Transmitting Across Multiple Islands Throughout these simulation experiments we have made some observations regarding the interaction of AODV and our DTN routing protocol. As mentioned above, the UAV requires the ability to send out RREQ using the AODV agent during the flight to route and keep track of the destination's location. The rate of this request cannot be determined independently by the UAV since the AODV protocol has its own policy of when and how often these RREQ can be sent out into the network. Even if there is a better route to the destination using only short range high bandwidth links, if there is no provision in the AODV to 4

5 constantly update the paths and there are no path failures, no new path will ever be constructed and the UAV will miss the chance of discovering more optimum paths to the destination. In addition, AODV picks a path based on hop count and not channel bandwidth as would be desired, so the notion of optimum path for DTN and AODV is not the same. Since the UAV forwarding policy is greatly affected by what route is available to destination, the rate of sending out RREQ will greatly affect the overall performance of the protocol. Currently there is no provision to allow a node to forward messages to a UAV despite no path being discovered. This is not a problem given our connectivity assumption mentioned above, but might be an area where further improvements may be necessary. order to prevent this type of message loss. Another problem related to AODV's caching behavior is how to make sure AODV does not send out messages it has cached when a new route has been constructed. This new route might not be desirable according to the DTN policy and so the UAV must be able to control the caching behavior of the AODV layer and prevent cached messages from being automatically sent. It is clear that better interaction between AODV and UAV DTN policy is necessary for improved performance. V. Conclusions In this paper we have presented a routing strategy for highly partitioned mobile ad hoc networks. The routing strategy uses AODV as the underlying routing protocol with very minor augmentation for DTN support. One immediate future work is to use GPS information and trajectory calculation of UAVs during route discovery and data forwarding. This would require a more elaborate geo-information exchange scheme to support mobility and latency. Additionally, different forwarding policies mentioned in Section 3 can be simulated to provide a clearer picture of the drawbacks and benefits of each policy. Multiple Source and Destination.4.. Qfi ru + 15 Sendler I eg F eiw 1 Sender2 Reeiver 2 _ 10 :z References 40 Time (sec) [1] K. Fall. A Delay-Tolerant Network Architecture for Challenged Internets. In Proceedings of ACM Figure 5. Multiple Islands with Multiple Source and Destination. Same scenario as in Figure 4.b but with one source is at the first island and second source is at the island in the middle. Two destination ground nodes are at the third island. SIGCOMM [2] S. Jain, K. Fall, R. Patra. Routing in a Delay Tolerant Network. In Proceedings ofacm SIGCOMM [3] ns-2. [4] C. E. Perkins, E. M. Royer. Ad hoc On-Demand Distance Vector Routing. In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, [5] W. Zhao, M. Ammar, E. Zegura. A Message Ferrying Approach for Data Delivery in Sparse Mobile Ad Hoc Networks. In Proceedings ofacm MobiHoc A potential problem that may lead to messages being lost is the AODV's caching behavior. Some packets might be caught in AODV's cache (instead of DTN storage) but AODV will discard any messages that it had cached due to a route failure after some time period. The UAV has knowledge of DTN policy and can thus decide the optimum time to keep the buffered messages in AODV's cache before sending them back to DTN storage. There must be some cross layer interaction between the UAV DTN middleware and the lower layers, such as the AODV or even the MAC, in 5