A Multi-agent Ant-based System for Routing in Mobile Ad ... - CiteSeerX

MAntS-Hoc: A Multi-agent Ant-based System for Routing in Mobile Ad Hoc Networks Liliana CARRILLO *, José L. MARZO *, Pere VILÀ *, César MANTILLA * * Institut d’Informàtica i Aplicacions (IIiA), Universitat de Girona (UdG) Campus Montilivi, Av. Lluís Santaló s/n, Edifici P-IV, 17071 Girona, Spain {lilianac, marzo, perev, cmantill}@eia.udg.es http://bcds.udg.es

Abstract. A Mobile Ad hoc NETwork (MANET) is a local area network or other small network that does not require fixed infraestructure and consist of wireless or plug-in connections. In this kind of networks, mobility is a critical factor because mobile nodes need to communicate with other mobile nodes that are not in direct range, then these nodes must communicate via intermediary mobile nodes. Considering the high degree of mobility in these networks, the task of finding paths between the communication end points is really a challenge. In this paper, we propose a novel hybrid routing scheme which combines both Ant Colony Optimization (ACO) and Multi-Agent System (MAS) techniques in order to provide high connectivity of nodes and reduce route discovery latency and the end-to-end delay. Keywords. Ant Colony Optimization, Multi-Agent Systems, Ad Hoc Networks, Routing.

Introduction MANETs do not require fixed infrastructure, because they are self-configured wireless networks. Their nodes create connections with distant communication partners when is necessary. On the other hand, the radio transmission range is small, therefore, communication partners are often not within direct radio range and connections should be set-up over multiple nodes, being used these nodes as relays to forwarding data. Moreover, the network topology constantly changes because of node mobility. These changes cause frequent route breaks and force sources to re-establish or maintain connections to their distant communication partners. Numerous ad hoc routing algorithms exist to allow networking under various conditions. They can be traditionally separated into two groups, proactive and reactive algorithms. On the one side, proactive routing algorithms maintain continuously updated state of the network and the existing routes; however, in some cases it may generate an unnecessary overhead to maintain the routing tables and then may be better to create routes only on demand, the case of reactive routing algorithms. On the other hand, reactive routing algorithms require time-consuming route creations that may delay the actual transmission of the data when sources have no path towards their destination and then, in this case may be better to use a proactive routing algorithm.

Due to advantages and disadvantages of each kind of routing algorithm, we consider that the use of a hybrid routing algorithm may be suitable in different cases, having as big objective to route for real-time data and multimedia communication. This paper provides the description of a hybrid routing scheme based on both an Ant Colony Optimization (ACO) and a Multi-Agent System (MAS) that ‘pretends’ to profit the advantages of both reactive and proactive algorithms. This paper is organized as follows: In section 1, we present the idea of routing in MANETs and its difficulties. In section 2, we present a brief state-of-the-art of routing protocols. Then, in section 3 we focus on discussing ant inspired routing algorithms and mobile multi-agent systems to route in MANETs, advantages and disadvantages. In section 4, we propose a novel approach called MAntS-Hoc which combines Ant based routing and Multiagent System techniques to solve the problem of routing in these changing networks such as MANETs. And finally, in section 5, we provide some concluding remarks and describe future work. 1. Routing in Mobile Ad Hoc Networks: Concept Illustration MANETs consist of a collection of wireless nodes, all of which can be mobile, that dynamically create a wireless network between themselves without a fixed infrastructure or administrative support [1]. They can be created and used ‘anywhere, any time’ offering unique advantages and versatility for certain environments and certain applications, i.e. for rescue agencies, policies, transporting companies or merely for office use. In the case of rescue problems, for example in data analysis in scenes of natural disasters, an ad hoc network could be formed by communication devices in fire brigades, helicopters, ambulances, policies and also people with laptop computers or mobile phones in hospitals, pharmacies and so on, all together working in a collaborative way to provide effective solutions to the problem. In figure 1, we show an example of an ad hoc network which has different communication devices and some connections amongst themselves (it is when devices are in of range between each other). A

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Figure 1. Representation of a Mobile Ad Hoc Network, i.e. to solve recue problems

It is obvious that they need to communicate each other; however the high degree of mobility in this kind of network does networks change quickly. Some devices could be out of range with respect to others and therefore each device (node) must be able to act as a router to relay packets generated by other nodes.

In figure 1, when node G needs to communicate to node I, node H has to act as a router and transmit its information. But, what happen when node H is out of range with respect to node I? It can exist the possibility that node E is now in of range and the topology of the network has changed to one different as it is shown in Figure 2. In this new topology, node G can communicate to node I through node D, E acting as routers. A

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Figure 2. Representation of a new network topology in a case of rescue problems

Then, we can see what difficult the tasks of routing and maintaining paths in MANETs are and how much they are affected because of the node mobility, transmission signal, limitations on the battery power of mobile nodes, and moreover limitations on the resources in terms of bandwidth of the wireless medium and the fact of sharing this medium (most commonly controlled by the IEEE 802.11 Medium Access Control (MAC) protocol). In the next section we explain the traditional way of routing in MANETs, protocols that already exist, their advantages and disadvantages. 2. Routing in Mobile Ad Hoc Networks: Existing Protocols Routing in MANETs has traditionally used the knowledge of the instantaneous connectivity of the network with emphasis on the state of the links [2]. This is the so-called topologybased approach [3]. To overcome the problems associated with the link-state and distancevector algorithms, numerous routing protocols have been proposed. These protocols can be traditionally separated into two groups: periodic (also called proactive, global or

tabledriven), and on-demand (also called reactive) even though there is a new generation of hybrid protocols which are both proactive and reactive in nature [4]. Proactive protocols maintain a continuously updated state of the network and therewith nodes are able to create instant connections to other nodes. In case of frequent topology changes, the necessary overhead to maintain the necessary link tables often exceeds the advantage of quick route creations. Frequent routing packets overload the network and delay data packets or even cause packet drops. If nodes increase the period between consecutive topology updates, connectivity information in nodes possibly contains inaccuracies which can reduce network performance. Examples of proactive protocols are DSDV (Destination-Sequenced Distance-Vector Routing Protocol) [5], WRP (Wireless Routing Protocol) [6] and so on. The main differences among them are the number of used tables, the information that is kept and the forward packet police to maintain the tables updated. Reactive protocols create and maintain routes only on demand and do not try to maintain an overview over the network. This means that routes are determined and maintained for nodes that require sending data to a particular destination. This reduces the generated overhead (typical in proactive protocols), but requires time-consuming route creations, as sources do not have any path towards their destination. Route discovery usually occurs by flooding a route request packets through the network. Examples of reactive protocols are AODV (Ad Hoc On-Demand Distance Vector Routing) [7], DSR (Dynamic Source Routing) [8] and so on. Reactive protocols also can be classified into two categories, source routing where each data packet carries the complete source to destination address and hop-by-hop routing where each data packet only carries the destination address and the next hop address. Hybrid protocols try to profit the advantages of both reactive and proactive protocols and combine their basic properties into one. These protocols have the potential to provide higher scalability than pure reactive or proactive protocols thanks to the collaboration between nodes with close proximity to work together and therefore reduce the route discovery overhead. Examples of hybrid protocols are ZRP (Zone Routing Protocol) [9], DDR (Distributed Dynamic Routing) [10] and so on. Furthermore, each group of protocols has a number of different routing strategies, which employ a flat or a hierarchical routing structure. In the next section, we introduce related work in routing for MANETs that use the concept of stigmergy (first introduced by Grassé, 1959) that means the indirect communication among ‘biological networks or colonies of ants and bees’ made through modifications induced in the environment. 3. Ant-based Routing Algorithms for MANETs The already known ant-based routing has been the basis of different kinds of methods for distributed systems optimization, including tasks of routing. This kind of routing is derived from previous work with colonies of artificial ants, where the most important characteristic is the indirect communication among the ants, made through modifications induced in the environment. These algorithms are inspired in the behaviour of real ants and the only information used is the train of chemical substances (pheromones) placed by other ants in the environment. In a packet network context, such pheromones are simply probabilities derived from the number of visitations associated with route-finding packets or ants. There exist some successful ant-based algorithms to network control, being the most prominent AntNet [11], and Ant-based Control (ABC) [12], which have a number of properties desirable in MANETs. Their main properties are: the highly adaptive behaviour in dynamic networks, the constant use of sampling and discovering paths, and their scalable

nature. However, they can cause significant overhead if the fact of sampling is not dealt with carefully. There exist some attempts to design ant-based routing algorithms for MANETs. Examples of these algorithms are ARA (Ant-based Routing Algorithm for Mobile Ad-Hoc Networks) [13], PERA (Probabilistic Emergent Routing Algorithm) [14], and Ant-AODV hybrid algorithm [15]. These algorithms are a good attempt to explore the behaviour of antbased algorithms for routing in MANETs, however, we want to explore the ability of these algorithms to find paths enhanced by a multi-agent system. In the next section, we present the main ideas of our algorithm. 4. The Proposal Routing Scheme: MAntS-Hoc MAntS-Hoc is a hybrid multipath algorithm that combines both reactive and proactive features to route in MANETs. It is integrated by an ant-based routing algorithm (Ant Colony Optimization - ACO) enhanced by a Multi-Agent System (MAS). On the one hand, the MAS acts in the reactive route setup phase and offers to the ACO ‘a good base’ to its proactive work, and on the other hand the ACO acts in the proactive route probing and exploration to offer a path from source to destination to a data session and a group of possible backup paths. As it is shown in figure 3, the MAntS-Hoc is composed by three main data structures in each node: the Routing Table (RT), the Historical Path Table (HPT) and the Alliance Formation Table (AFT). The RTi in node i contains for each destination d and each possible next hop n a value Pdn (it is called pheromone) that represents the probability of choosing n as next hop to reach destination d when a data session in node source s needs it.

Figure 3. MAntS-Hoc routing scheme in each node

This pheromone tables in different nodes indicate multiple paths between s and d, and data packets can be sent from node to node until they reach their destination. To update the pheromone tables, initially, MAntS-Hoc (in fact, the MAS) has a reactive behavior when a data session is started at node s with destination d, and it does not find up-to-date routing information to reach d. The MAS acts sending agents (broadcasting) to the neighborhoods, and it waits for successful information represented by the initial AFT in node i. This AFT is inspired by previous works related to Alliance Formation for Agents

[16]. This AFTi represents node alliances for node i and contains information related to the degree of trust existing between node i and its neighbors to reach destination d. If the degree of trust related to node n (possible next hop) to reach destination d is high then the pheromone Pdn in RTi will be high, or viceversa. The MAS always acts when a reactive behavior is needed. As an Alliance Diameter Control (ADC), there is a hop-count field that would decide the number of hops to which the advertisement of trust may be propagated by receiving platforms. In a highly dynamic environment, such as MANETs, a small diameter of an alliance is more desirable. This is because, if the diameter is large, stability of a system in an alliance would be less. For implementation purposes, we will be limiting the hop-count to three. Hence, a system will only advertise its routing information to its threehop neighbors, and an ADC would be three. To maintain and explore routes in a proactive way, the MAntS-Hoc (in fact, the ACO) acts sending out routing packets (forward ants) according to the data sending rate while a data session is running. Ants follow and actualize the pheromone values in the routing table in order to maintain the existing routes, and they also have a small probability of being broadcasted, in order to have the possibility of finding new routes. Like in the traditional AntNet, when a forward ant finds a destination, a backward ant is generated to go back from the destination to the source with the goal of maintaining up-to-date the estimates of this path, and to update the pheromone values related to this path. If at any point the forward ant is broadcasted, it will explore new paths and leave a pheromone trail. In order to guide the forward ants a bit better, we use traditional hello messages for routing in MANETs. As it is shown in Figure 4, the ACO has two main aims, first to update the RT and second to maintain the HPT in order to have possible backup paths. The HPT contains information about the last five paths traversed, and their respective delay statistics. The MAS enhances the decisions of the ACO by using an AFT and updating the RT. Finally, when a data session arrives, it follows the Pdn pheromone to reach their destination d. Ants Agents

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Figure 4. MAntS-Hoc scheme which represents how it works

5. Conclusions and Future Work Routing in MANETs is ‘a hard work’ and actually it is an interesting research area that has been growing in recent years. Its difficulty is mainly generated because of the constant changes in the network. There exist some traditional solutions such as proactive protocols and reactive protocols, each one with their advantages and disadvantages. In spite of this, these solutions have to improve to offer better scalability and performance. In fact, there is a new generation of hybrid routing protocols that have ‘the potential’ to provide higher scalability than pure reactive or proactive protocols, and moreover to maintain routing information much longer because of the collaboration between nodes. In this paper, we have proposed MAntS-Hoc, a new Multi-agent Ant-based System for routing in mobile ad Hoc networks which is a hybrid algorithm that combines, in summary, a reactive behavior of a multi-agent system with a proactive behavior (route probing and exploration) of an ant-based routing algorithm. In order to evaluate our algorithm, and to obtain comparative results (with respect to AODV protocol), we plan to integrate the algorithm within the Omnet++ simulator [17]. We are interested in measures of performance such as scalability, delay, overhead, resource utilization and so on. We plan to have a base scenario of 50 wireless nodes randomly placed in a rectangular area of 1500 by 300 meters during 900 seconds of simulated time while moving according to the random waypoint model [8]. The maximum speed in the scenario could be 20 meters/sec and a pause time of 30 seconds, while the transmission range could be around 250 meters and the data rate of 2 Mbit/sec. We plan to consider data traffic generated by constant bit rate (CBR) sources. References [1]

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