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An agent-based approach for QoS provisioning to mobile users in the Internet Giuseppe Anastasi (1), Aurelio La Corte (2), Antonio Puliafito (3), Orazio Tomarchio (2) (1)

(2)

Dipartimento di Ingegneria dell'Informazione, Università di Pisa Via Diotisalvi 2, 56126 Pisa - Italy

Istituto di Informatica e Telecomunicazioni, Università di Catania} Viale A. Doria 6, 95025 Catania - Italy (3)

Dipartimento di Matematica, Università di Messina Salita Sperone - Contrada Papardo, 98166 Messina - Italy

ABSTRACT Although Internet implicitly assumed stationary users, nowadays user mobility represents a new variable to be taken into account when designing new services or defining new reference architectures. Mobile users wish to access all the services available in the Internet possibly with the same quality with which these services are accessed through a desktop computer. The provision of QoS guarantees, which is still an open issue even in networks with only stationary users, poses additional problems when mobile users are taken into account. Mobile software agents represent a possible solution to such kind of problems. In this paper we propose a reference scenario where mobile and static agents are used in order to provide QoS guarantees in the communication between a server and a mobile client. The main advantage of the proposed approach consists in its great flexibility and adaptability to different management, QoS negotiation, reservation and adaptation strategies, which may vary with the service and the network providers.

Keywords: User mobility, Mobile agents, Quality of Service.

1. INTRODUCTION The last years have been characterized by an explosive growth of the number of Internet users. The Internet was originally designed to support network applications like file transfer, electronic email, remote login, etc. which only required a reliable communication. To this end a transport protocol was used for handling occasional

losses and corruption of data packets. Furthermore, routing algorithms adaptive to node failures were applied. Other communication qualities and guarantees, like timeliness, were considered to be of less or negligible importance. Time, in particular, was assumed to be abundantly available so that a best-effort service quality resulted with respect to end-to-end delay. Recently, the development of multimedia application has asked for the provision of real-time services in the Internet. As a consequence, extensions to the Internet protocol stack such as the resource reservation protocol (RSVP) [1] have been proposed in order to provide guaranteed real-time services as well while relaxing the requirements with respect to reliability in communication. The designers of the Internet protocols implicitly assumed that users were stationary. However, in the last years, simultaneous to the explosion of the Internet, there has been a very large diffusion of cellular (and, more generally, of wireless) communications from one hand, and of portable computing devices (like mobile computers, laptop, Personal Digital Assistants, etc.) from the other hand, which have made mobile computing more and more important. Users whish to access the information they need at any moment, independently of the place where they are. Furthermore, people using mobile computer wish to access all the services available in the Internet and, possibly, with the same quality with which these services are accessed from a desktop computer. In particular, users would like to use their mobile computer, other than for sending/receiving email messages and/or faxes, also for browsing Web pages, receiving voice messages, asking for the transmission of video sequences, taking part to video-conference, etc., and, all that, while moving. So one of the most exciting challenges to face will be the provision of services with Quality of Service (QoS) guarantees to mobile users

connected to the Internet. The provision of QoS guarantees is still an open issue even in networks with only stationary users. Guaranteeing a specified QoS to mobile users poses additional problems. In fact, mobile users are usually connected to the Internet through a wireless link so that the connection between a sender (e.g., a fixed server) and a receiver (e.g., a mobile client) involves, at least, two network components, a wired one and a wireless one. As is well known, the wireless component is usually characterized by a lower bandwidth and a greater packet loss rate. In addition, the quality of service provided by the wireless network component, both in terms of throughput and packet loss rate, may change abruptly over time due to geographic impairments (e.g., physical obstructions), meteorological conditions, and so on. Furthermore, the mobile user may move between cells characterized by different number of served users and, hence, with different available bandwidth. Even if the mobile user remains temporarily static the bandwidth available to it may vary as a consequence of the mobility of other users. Furthermore, due to the user movements, the path between the sender and the receiver may change. A path variation causes the rerouting of data packets, and, consequently, a possible variation of resources even in the wired part of the connection. Another aspect to be considered is the strategy according to which a mobile host selects the connection to a base station (instead of a second one), if the host itself is covered by the signal of different cells in a specified interval. In such cases, the strategy is usually statically fixed in network devices, and the single service provider can do nothing for changing the selection. The use of approaches based on code mobility make possible the dynamic runtime variation of this strategy, without stopping the service. In this paper we propose an approach for managing the QoS of the communication between a (fixed) server and a mobile client based on (mobile) software agents. The same approach has been successfully experienced in the Internet when all the users are stationary [2,3]. Using software agents for the management of QoS in a mobile computing environment may be very effective thanks to the advanced schemes of cooperation and coordination they allow.

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Fig. 1: System model

The paper is organized as follows. Section 2 describes the system model we assume as the reference model. Section 3 describes the agent approach adopted, while in Section 4 some agent specific functionalities of the system will be given. Finally in Section 5 we conclude our work. 2. REFERENCE SCENARIO To gain a clearer understanding of the environment in which mobile agents can be used as a flexible tool for adapting and managing the QoS, we consider a multimedia service supported by the mobile communication system [4,5] shown in Fig. 1 The communication system is made up of a wired network interconnecting static hosts (SHs) and a wireless network with mobile hosts (MHs). Some of the static hosts (the Base Stations - BSs) act as radio access interfaces, thus allowing MHs located in a cell (the radio-electric coverage area of the BS) to access the wired network. Cells may partially overlap, or may be organized in multilayers, according to a microcell/ macrocell overlay system [6]. In any case we assume that, even if an MH can exchange control information with more than one BS, it only exchanges user information with one BS at a time. In particular, we assume that the MH is connected with the BS assuring the "best QoS". The QoS is specified by the user in terms of bandwidth necessary, maximum probability of loss admitted, or range of values of end-to-end delay, according to the service that has to be supported. In a mobile system like the one depicted in the figure, one of the main problems is handling mobility in a broad sense. It means dealing with location [7], rerouting [8], and signaling [9] at the same time. When, in fact, a generic MH moves within the area covered by the network, the first task is to identify his position, both when there is a connection in progress and when there is not. This is because the point of access to the network, i.e. the MH's location, can no longer be deduced by the terminal identifier alone (i.e. by the name with which the network identifies the terminal) as in a wired system: it is also necessary to have a position identifier, involving consequent modifications to the connection set-up process. At the same time, when a MH leaves an area controlled by one BS to move to one controlled by another BS, it is necessary to provide continuity of service, which means maintaining the communication, the sequential delivery of cells and meeting the QoS negotiated. All this also means re-routing, i.e. changing the original path connecting the terminal to the network. Moreover, for supporting the host mobility in the Internet, the extended IP protocol, called Mobile IP [10,11], is used. Note that Mobile IP can coexist with other solutions for mobility management like Wireless LANs (WLANs), cellular or pico-cellular networks, and so on. The model depicted in Fig. 1 is quite general and includes all the above solutions.

The mobile agent technology can also be useful for solving some issues concerning location tracking, rerouting (after handover), and for managing the signalling [12,13]. However, the analysis of these issues is not one of the purposes of this paper. Without losing in generality, in the following we will assume that the communication is between a (fixed) server and a mobile client. The client requires from the server a service with a specified QoS. The QoS parameters are negotiated by the client at the communication setup phase and may be renegotiated while the communication is in progress, e.g., due to variations in the network conditions. To make the model as general as possible it is also assumed that no mechanism for bandwidth reservation is used at the BSs. This means that the wireless bandwidth is provided by the BS to the user of its cell on a best effort basis. On the other hand, mechanism for bandwidth reservations may be present in the wired network. 3. AN AGENT-BASED APPROACH The use of an agent-based infrastructure for the management of QoS in a mobile computing environment is a good choice for implementing several adaptation strategies by which available resources need to be rearranged in such a way that the user is still satisfied. Particularly interesting for the implementation of adaptation strategies is the exploitation of agents' cooperation abilities for optimization purposes [14]. A general reference architecture has to be established in which agents are coordinated by communicating certain events and internal status information to each other. As a

result, each agent is influenced by and can influence the behavior of other agents. The reference architecture we refer to is depicted in Fig. 2.Software agents are classified in the architecture according to the specific functionalities they carry out. A user on the client system interacts with the QoS management component by means of an appropriate User Agent. This agent is specific for each service required by the user, and enables the user to specify and negotiate the desired QoS parameters. The System Agent provides all the information about the client's system state; relying on the services provided by the operating system of the host machine, it has the mechanisms to control the QoS on the client. Besides, the System Agent is responsible for communicating the characteristics of the user device to the other agents (mainly to Network Agents), in order to avoid spreading the user device with information that the user cannot appropriately view on a mobile device with limited capabilities. On each server node (in the wired network) a Service Agent is present which has to monitor whether the QoS parameters (for each service required by the clients) are respected. It keeps track of the users logged in and their occupied resources, in order to optimize the use of available resources. This agent also maintains the knowledge of the server's capabilities. Finally, on the BS a set of Mobile Support Agent are present. Their task is the management of MHs within the virtual cell, and allow customizing the different management policies concerning the processing of data flows (from a point of view of QoS) from and to MHs. Control functionalities are implemented by Network Agents. Network agents have the following

Fig. 2: Agents reference architecture

responsibilities: • reservation of suitable network resources; • monitoring of system parameters; • initiation of corrective QoS adaptation activities if QoS violations are detected; • interaction with the network management system in order to obtain additional resources and/or to optimize their use. The implementation of software agents is based on MAP [15], a mobile agent platform developed at University of Catania. MAP is entirely developed in Java, so it is platform independent and it can execute on heterogeneous hardware and software platforms. It provides basic mechanisms to create agents, to make them communicate each other, to migrate them on different nodes of the network.

4. FUNCTIONALITIES OF AGENTS In this section we point out some functionalities and scenarios where the agent approach proves flexible and convenient. If we look at the path between a (fixed) server and a client running on a MH, we can think as it is made up of a wired part and a wireless part. We can observe that, because of mobility, in the wireless part of the path the available bandwidth changes over time. In fact, in the scenario that we have previously described, when a MH moves from one cell to another, in general, the conditions in the new cell are different from those in the old cell. In particular the amount of bandwidth achieved by the MH in the new cell may be even much different. It could be noted that bandwidth variations also occur, because of congestions, in wired links where resource reservation is not possible and, hence, no guarantee is provided by the network. However, bandwidth variations at wireless links are, in general, much more frequent and, likely, of greater entity. This make the need for a management of the QoS more felt than in a completely wired networks. This management is provided by opportune agents whose tasks will be described in the following, where we have made a distinction between

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Fig. 3: Communication reference scenario

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the agents operating in the wireless (mobile) part of the network, and the ones operating in the wired (fixed) part of the network.

4.1 Agents in the mobile part The main use of mobile agents in the wireless part of the network concerns the opportunity (for service providers) of a flexible and easy introduction of new services, and the opportunity (for the managers of the network) of introducing new strategies of management "on demand". The example that we will examine in detail is that in which (unlike the scenario described in section 2, when each MH belongs to only one virtual cell) a MH is reached by the signal of different BSs, and might therefore belong to different virtual cells (i.e. the mobile host MH4 in Fig. 3. In the commonly used solutions, the cell from which the best signal is received is usually selected, by following a strategy that has statically been fixed within the MHs and the BS. In the situation shown in Fig. 3, the MH4 mobile user receives the best signal from BS1, but cell 1 is very crowded, and the QoS the MH4 user requires cannot be assured. However, the BS2 from which MH4 might receive (even if less effectively) is empty; thus the MH4 user, by means of an alternative strategy, is assigned to cell 2. A change of this strategy in a traditional environment would involve a change in the network devices belonging to the BS. By using an agent infrastructure for the management and the support of users' mobility, this strategy might be changed according to the needs of the network, of the service provider, or of the specific application being used by the user. In fact, the selection policy is included in an appropriate network agent, which is dynamically run on the BS involved: from now on, the registration policy of MHs in cells will take place according to what was scheduled in the corresponding network agent. The reason why the standard policy may not be adequate for some applications, depends on the type of application and on the quality support that has to be provided by the environment. These are some of the points where this approach proves convenient: • performing policies of balancing of the processing load among the different BS; • assuring a quality of service to specific classes of users; • for remarks concerning the availability of resources in the fixed network to which the MSS is connected; • as a tool of support for algorithms for the prediction of the movement within the different cells. In each case, we would like to outline how the agent approach provides high flexibility and adaptability for the implementation in the network of management policies customized according different ISP requirements.

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Fig. 4: Rerouting of packets due to the movement of MHs to a different cell

4.2 Agents in the fixed part In the wired part of the network, the agent system interacts with the existing mechanisms of resource reservation, in order to allow the user to obtain the quality required. This issue has already been dealt with in [3] (where agents have been used for implementing flexible strategies of QoS management in IP networks), and in [2] (where agents have been added to the existing mechanisms of resource reservation, in order to improve performances). In the case examined in this paper, as well as the issues present in a wired network, we add the ones deriving from the mobile environment considered. In the described scenario, good co-operation among the network agents of the wired network and the Mobile Support Agents in the BS is needed, in order to rearrange the resources needed for the different data flows. The agents of the wired network intervene in three situations: 1. when the setup of a connection is made; 2. due to the mobility of the user, and therefore to the change in the cell where the MH is; 3. due to a change (either negative or positive) in the quality parameters in the wireless part, if they are not due to the user's mobility, but to outside factors such as a change in the number of the MHs present in a cell. Actually, in the three cases listed before, the agents present in the wired part of the network will have the task of assuring the quality parameters required. The first case is a negotiation of parameters: network agents interact with the existing reservation mechanisms (for

example, RSVP [1]), in order to assure a fixed level of QoS. In the second case, the user's mobility may cause a rerouting of packets in the wired network and, hence, a variation in the resource availability also in the wired part of the path. As we show in Fig. 4, when the mobile user moves from cell 1 to 2, the path of the packets within the wired network changes: the router R1 is no longer interested in the connection between the MH and the SH, while now the router R2 is involved. In general, the negotiation of the QoS parameters, done when the user was in a cell (position), may no longer be valid when the user moves to another cell (position). Agents will therefore have to intervene, so to rearrange the resource reservations on the fixed part, and, if necessary, on the wireless part of the connection. In the third case, the change in the conditions of the cell where the mobile host operates can require some readaptation operations of the parameters negotiated before. As we have already said in [3], the agent system in the fixed part of the network allows a very flexible implementation of adaptation strategies needed for dealing with degradations in the quality of service. One of the advantages of an agent-based approach, is that policies can be implemented dynamically, allowing for a resource-state-based admission and reservation strategy. Agents are used to discover about resources available inside the network and claim resources on behalf of customers according to some ``figures of merit''. Figures of merit capture trade-offs between bandwidth claimed and loss risk incurred due to high utilization. Loss, although not being a monetary quantity, can be seen as a cost measure for claiming resources at a particular state of the network. Different customers may follow different figures of merit so that a negotiation becomes possible. Implicitly, of course, this concept is based on the assumption of customers' varying willingness to pay for resources under different circumstances. The willingness may vary from customer to customer but also with time from a single customer's perspective, resulting in a nonhomogeneous approach. Another advantage of agents is their capability to trigger adaptation of applications inside the network on behalf of customers. This allows for an immediate response to resource shortages, diminishes the amount of useless data transported, and reduces signaling overhead. The agents perform adaptation along the lines of figures of merit mentioned earlier, thus allowing again the incorporation of customer policies and preferences. This concept is combined with underreservation of resources [3], allowing for a minimum quality of service (which is related to customer requirements) to be guaranteed. Adaptation is performed based on sharing of excess (bandwidth) resources. 5. CONCLUSIONS In this paper static and mobile software agents have been

used in order to face the problem of QoS provisioning when mobile users wish to access distributed services. We have identified some circumstances where software agents can be successfully adopted when a mobile host has to select the more appropriate base station or when resources reservation in the wired part of the system has to be done. QoS adaptation can also be executed dynamically by modifying system parameters either in the wireless and/or in the wired part. The flexibility of the approach and the possibility to implement different strategies on the same hardware support are the principal advantages of using software agents (static and dynamic) in a networking environment. Some experiments have been carried on and the numerical results confirm how agent technology can be successful adopted for QoS purposes. Acknowledgements: This work has been partially supported by the European Community through the VESPER project (#IST-1999-10825) under the IST programme. 6. REFERENCES [1] L. Zhang, S. Deering, D. Estrin, S. Shenker, D. Zappala. RSVP: A New Resource Reservation Protocol. IEEE Network, 7(5), September 1993. [2] H. de Meer, A. Puliafito, J.P. Richter, O. Tomarchio. Tunnel Agents for Enhanced Internet QoS. IEEE Concurrency, 6(2), April-June 1998. [3] H. De Meer, A. La Corte, A. Puliafito, O. Tomarchio. Programmable Agents for Flexible QoS Management in IP Networks. IEEE Journal on Selected Areas in Communication.18(2), February 2000. [4] B.R. Badrinath, A. Acharya, T. Imielinski. Impact of mobility on distributed computation. Operating Systems Review}, 27(2):15--20, April 1993. [5] A. Acharya, B.R. Badrinath. A framework for delivering multicast messages in networks with mobile hosts. Mobile Networks and Applications, 1(2):199-219, October 1996. [6] J.H. Reed N.D. Tripathi, H. VanLandingham. Handoff in cellular systems. IEEE Personal Communications, 5:26--37, December 1998. [7] T.F. La Porta, K.K. Sabnani, R.D. Gitlin. Challenges for nomadic computing: Mobility management and wireless communications. Mobile Networks and Applications, 1(1):3--16, August 1996. [8] S. Ramanathan M. Steenstrup. A survey of routing techniques for mobile communications networks. Mobile Networks and Applications, 1(2):89--104, October 1996. [9] D. Raychaudhuri. Wireless ATM: An enabling technology for multimedia personal communications. Wireless Networks, 2(3):163--171, August 1996. [10] C.E Perkins. Mobile IP. IEEE Communication Magazine, 35(5):84--99, May 1997. [11] D.C. Lee and alii. The next generation of the

internet: aspects of the Internet Protocol version 6. IEEE Network, 4:28--33, January/February 1998. [12] T. Magedanz, K. Rothermel, S. Krause. Intelligent Agents: An Emerging Technology for Next Generation Telecommunications?. INFOCOM'96, San Francisco, CA, USA, March 1996. [13] M. Breugst, T. Magedanz. Mobile Agents Enabling Technology for Active Intelligent Network Implementation. IEEE Network, 53--60, May/June 1998. [14] P. Chandra et alii. Darwin: Resource Management for Value-Added Customizable Network Service. Sixth IEEE International Conference on Network Protocols (ICNP'98), Austin, October 1998. [15] A. Puliafito, O. Tomarchio, L. Vita. MAP: Design and Implementation of a Mobile Agent Platform. Journal of System Architecture, 46(2):145-162, January 2000.