ANSI: A swarm intelligence-based unicast routing protocol for hybrid ad hoc networks☆,☆☆
Introduction
Hybrid ad hoc networks consist of a mixture of mobile, ad hoc network (MANET) nodes and nodes which belong to highly capable infrastructure such as mesh networks or cellular networks. The problem of hybrid ad hoc networks is to make these networks work efficiently without relying on pre-configured network topologies or centralized control. Hybrid ad hoc networks are useful in many situations where impromptu communication facilities are required such as battlefield communications, and disaster relief missions.
Since the problem of hybrid ad hoc networking shares a lot of problems with typical MANET problems, typical routing solutions for hybrid networks start with a MANET routing solution and then apply some optimizations to work for specific scenarios. A number of ad hoc routing protocols have been proposed, for example [1], [2], [3], [4], [5], of which some of them, like AODV [1] work on hybrid ad hoc networks. In proactive protocols such as [5], nodes in the network maintain routing information to all other nodes in the network by periodically exchanging routing information. Nodes using reactive protocols, such as [1], [2], delay the route acquisition until a demand for a route is made. Hybrid protocols, like [4], [6], use a combination of both proactive and reactive activities to gather routes to the destinations in a network—nodes using ZRP, for example, proactively collect routes in their zone, and other routes are collected reactively. In [6], on the other hand, the level of proactive activity and reactive activity are chosen autonomously by the nodes in the network, and proactive activity is only seen around favorite destination nodes. In most traditional reactive protocols, like [1], [2], only when a route breaks irreparably does the protocol mechanisms repair the damage. In reality, route deterioration in mobile networks is most often not sudden but gradual,1 and most often available routes get better/deteriorate gradually and not suddenly. So the routing protocol should continuously maintain information about the nodes in the local area to perform effectively and avoid too may link breakages.
In this paper, we present a hybrid routing suite (with both proactive and reactive components) for hybrid ad hoc networks which uses the mechanisms of swarm intelligence [7] to select good routes to destinations. We use Swarm Intelligence (SI) because SI mechanisms allow for self-organizing systems [8] and maintain state information about the neighboring network better than traditional MANET routing mechanisms. Self-organizing systems are robust environments where erroneous system behavior is corrected autonomously by the coordinated working of lower-level components. The combination/interaction of lower-level components in SI such as positive/negative feedback and amplification of fluctuations along with multiple interactions are the mechanisms which allow a node to change routing information quickly and efficiently to adjust to an ever-changing local topology and route deterioration, thus initiating fewer link breakages.
Our protocol, ANSI, uses a highly flexible cost function which allows it to use the information collected from the local ant activity, such as the congestion status of the neighboring nodes, in useful ways. In addition, the ant-like working of our protocol allows for the maintenance of multiple routes to a destination. In nodes which use proactive routing in ANSI, this fact is used to perform stochastic routing, and in nodes that use perform reactive routing (pure MANET nodes), when one route fails, others may be used. Our motivation comes from the fact that different networks face different conditions, and thus a protocol suite should allow for various configurations as the network conditions dictate. Furthermore, supporting multiple routes simultaneously is essential to ensure survivability of the network [9]. ANSI facilitates ad hoc unicast routing by exploiting route finding behaviors that are emergent from ant packets working collectively, rather than explicitly coding them to cope with the problem. We formulate the routing problem at node i as a set of “food foraging” problems from nest i, where each “food source” is a destination d in the network. In this formulation, next hops are evaluated on the basis of the strength of the pheromone trail2 on the link connecting a node and a next hop.
The remainder of this paper is organized as follows: In the next section, we discuss a number of approaches and protocols which are related to our research. In Section 3, we describe in detail the components of ANSI unicast routing protocol, and follow it with Section 4 where we discuss the results of the comparison of simulated models of ANSI with a popular routing protocol, AODV [1]. We conclude in Section 5 with a brief note on future research effort.
Section snippets
Related work
The main ingredients of SI, positive/negative reinforcement, and amplification of fluctuations are achieved in an environment with multiple interactions among nodes [7]. Because the above components of SI are the lower-level components required for self-organizing behavior, the benefits of using SI-based algorithms are not fully accrued if the any of the above lower-level components are not present in a swarm intelligence-based protocol. This is because in any SI-based system, these aspects
Protocol overview
ANSI is a hybrid routing protocol for hybrid ad hoc networks comprising of both proactive and reactive routing components. Pure MANET (mobile) nodes in ANSI use only reactive routing, and choose routes deterministically, while nodes belonging to more capable, infrastructured (immobile) networks use a combination of both proactive and reactive routing and perform stochastic routing when multiple paths are available. The outline of the process of ANSI routing is as follows:
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When a route to a
Simulation results
ANSI was simulated in QualNet (Version 3.7), and the performance of ANSI was compared with a popular routing protocol, AODV [1], for the same network and load characteristics. We chose to compare ANSI with AODV because AODV has been shown to perform well in a vast majority of ad hoc network scenarios. In addition, AODV also works on hybrid ad hoc networks. Our work here is an extension of our earlier work [19] which only tested ANSI under UDP loads over a pure MANET. As we mentioned earlier,
Conclusions and future work
This paper describes the design, implementation, and performance of a swarm intelligence-based hybrid routing protocol, ANSI, for hybrid ad hoc networks. We simulated ANSI and carried out a performance comparison with AODV, and the results show that ANSI performs better than AODV for both UDP and TCP flows in both pure MANET and hybrid ad hoc networks with respect to packet delivery, number of packets delivered, end-to-end delay, and delay jitter. We also see ANSI affects the upper layer
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A section of this work was presented at ICAI 2005, June 2005, Las Vegas, NV, USA.
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This work is supported in part by National Science Foundation under grant ANI-0240398.