Open and Flexible Control and Resource Management for ATM Networks using Intelligent Agents E. Vayias, J. Soldatos, N. Mitrou e-mail: {evayias;jsoldat}@telecom.ntua.gr,
[email protected] National Technical University of Athens 9, Heroon Polytechneiou Street, Zografou 15773, Greece tel: +30 1 772 1479, fax: +30 1 772 2534 Network Control in ATM, as it is currently carried out by means of standard signalling protocols, presents several drawbacks such as the inability of the Service Providers to adapt network resource control to the particular needs of their services, or the difficulty in deploying advanced schemes for CAC and traffic control in order to achieve increased utilisation. An open distributed software architecture based on the concept of Intelligent Agents may provide a solution. This paper highlights the major issues of this problem and presents the architecture of a system that enables open and flexible control and network resource management using intelligent agents. Keywords: ATM, Intelligent Agents, Java, Open Control
1. Introduction The need for open control interfaces and flexible and intelligent control architectures for ATM networks has now become evident [1], [2]. It is even argued that, without a control infrastructure which is more open and flexible than conventional signalling, the advantages of ATM technology for provision of broadband services will not materialise. New software paradigms such as Intelligent Software Agents and distributed object architectures may contribute towards more flexible network control and management [3]. This paper elaborates on the work performed in the IMPACT project1 regarding the implementation of a prototype system for ATM network control, where tasks such as admission control, routing, connection handling and Virtual Path management, will be performed by higher-intelligence, distributed software entities called “Intelligent Agents”. The advantages of performing network control by using Intelligent Agents can be basically summarised in two points: • Flexible management of resources according to the policy desired by the network operator or the service provider, rather than the policy embedded in the network elements by the equipment vendor (this can be achieved by customising agents’ behaviour and
overriding the internal control logic of the network elements). • Control functionality that is not feasible otherwise, such as reactivity to unexpected events of various forms (e.g. failures) or re-arrangement of resources allocated to existing connections in order to optimise utilisation (e.g. re-routing existing connections to accept a new one). Our objective is not simply to describe the system architecture, but also to illustrate how this agent-based system can provide solutions to the issues of network control in a multi-service, broadband environment. In this respect, we present, in the next section, some open issues in ATM control, as well as the future network environment that we envisage; we then present the approach adopted in the IMPACT system, showing how this approach fits in this environment and deals with these open issues; finally, we give some details about the implementation of the IMPACT system on an ATM testbed with heterogeneous equipment in order to assess and demonstrate the ability of agents to control ATM networks.
2. Network Control in ATM: Facts and Open Issues By the term “Network Control”, we usually refer to a set of mechanisms and procedures that should be performed in a short time scale (real-time), each time a new connection is requested (or new traffic is being injected into the network in the case of datagram networks). These procedures deal with the admission control, the routing, the resource allocation and the establishment, maintenance and release of connections. Since a network is a distributed system, network control involves an interaction protocol called the “signalling2” protocol for exchanging control information (connection requests, topology updates) among the network elements. It also involves certain algorithms for executing procedures such as connection admission, resource allocation and routing.
1
IMPACT (AC324) is a research project funded by the European Commission in the framework of the Advanced Communications Technologies and Services (ACTS) programme.
2
The term’s origin lies in the fact that older generation network elements were controlled by electrical signals.
The goal of network control is to decide whether the newly offered traffic can be admitted into the network and to configure the internal traffic control mechanisms of the network elements, so that the established connection gets the requested QoS while not affecting the QoS of other connections. Thus, the network control algorithms should take decisions that guarantee, on one hand, the QoS of connections and permit, on the other hand, an efficient utilisation of network resources. Another objective of network control is to achieve a specific connection-level performance, e.g. by trying to keep the ratio of blocked (rejected) connection requests or the connection set-up time under some predefined limits. In ATM networks, the principal control procedures are connection admission control (CAC), routing and connection establishment/release [4]. It is evident that procedures operating in such short time scales cannot easily achieve the - often conflicting - goals mentioned above (especially when trying to compromise between traffic-level and connection-level performance). For this reason, they are assisted by Network Resource Management (NRM) procedures which provide logical configurations based on the Virtual Path (VP) concept in order to facilitate and speed up admission control and routing. Provision and appropriate dynamic management of VPs can maintain a high level of utilisation, while at the same time reduces the steps to be taken by CAC and routing (see e.g. [5], [6], [7]). Moreover, Virtual Paths enable the provision of logically separated “Virtual Networks” on the same physical infrastructure. Different virtual networks may belong to different Service Providers, for example. Although NRM mechanisms reside in the management plane from a computational viewpoint ([8], [9]), the fact that they operate in considerably shorter time scales than network planning and provisioning tasks, makes them tightly coupled with network control (for an intuitive explanation of the time-scales of the various control functions in ATM see [10]). Therefore, in this paper, by the term Network Control Architecture, we will consider a set of network control algorithms and the associated information exchange protocol (signalling), as well as a set of NRM mechanisms. Network control in ATM has been based on standard signalling protocols such as ITU-T Q.2931 or ATM Forum UNI 3.1 and PNNI. Although, these protocols succeeded in providing a base for the rapid development and deployment of interoperable ATM equipment, their stem from the classical telephony model [11] (Q.2931 came as an extension to Q.931 ISDN signalling) burdens them with drawbacks which do not fit with ATM’s inherent flexibility. The incorporation of the traffic requirements of applications into the signalling protocol results in the loss of a key advantage of ATM which is
the ability to accommodate almost any network service, even ones that have not yet appeared (see [10] for a discussion on ATM traffic classes). This means that signalling will need modifications in case different service requirements arise. Moreover, the implementation of control logic into the switches in an immutable fashion inhibits service providers from specifying their own resource allocation policies for their specific services [12]. Both these facts are hindrances to the easy deployment of ATM services, since it is hard to adapt the network and service control logic to the differentiated and often conflicting needs of broadband services. Several proposals exist in the literature ([12], [13], [14], [15] to name a few) regarding open broadband control architectures, making apparent that ATM control is not a solved problem. The P1520 Working Group of IEEE has also specified a framework for programmability in the network element, network service and application service layers [1]. However, none of the above control architectures can cope with the entirety of services that may be offered over an ATM transport infrastructure; most of them are oriented to specific service needs (e.g. [13] considers mostly multimedia communications, [14] speeds up the set-up time for intra-network services and [15] deals with interworking of IP and ATM). Therefore, as is supported in [11], we should not expect to have a single ATM control architecture even on the same physical transport network. Rather, we anticipate a network environment where the transport network is provided and operated by a Network Provider (NP) and is open to various Service Providers (SPs). Each SP has its own virtual overlay network (VN) on the physical infrastructure and uses its custom control logic depending on the kind of services it offers (e.g. video conferencing, interactive TV, IP service, leased lines, etc.). In the sequel, we will show how a multi-agent system may enable the co-existence of different such control policies for various Service Providers.
3. Agents and Telecommunications Control and Management The term “Software Agent” is used to describe an autonomous software entity (e.g. a process) which possesses some internal logic that enables it to automate “tasks regarded as mundane or laborious to a human agent” [3]. An Agent also possesses asynchronous communication capabilities for interaction with other Agents or its operating environment. Multi-Agent Systems (MASs), in particular, consist of agents interacting with each other and with their environment in a co-ordinated manner in order to solve a particular problem. MASs have been considered for flexible, efficient and robust control of complex, distributed
systems, such as electrical power distribution systems, nuclear plants and telecommunication networks. Several applications of Agents in Telecommunications can be found in the literature (see [3] for an overview), but dealing mostly with specific tasks such as routing, CAC, VP management, delegation of management tasks and not considering control architectures as a whole, in a multi-provider environment.
4. The IMPACT Agent System Let us now present the basic components of our system and explain the network environment in which they function. We assume that each Service Provider “buys” a specific capacity of the physical transport network from the Network Provider. This capacity may be in terms of physical link bandwidth, VPI space in each link, VCI space within predefined VPs, buffers, etc. For instance, in this paper we will consider that each SP is allocated a fixed, guaranteed bandwidth portion of each link and some predetermined VPIs. Another scenario could be to allocate the SPs a fixed bandwidth per source-destination pair [16]. In a more advanced scenario, SPs could buy bandwidth with statistical guarantees or bandwidth could be re-allocated among SPs depending on the actual traffic demand. The NP will also probably be a service provider itself and will manage a large portion of the network resources. Each SP has a logical VP network overlaid on the physical network using the resources allocated to it. Provision of the VP network of the SPs is performed by the Network Provider Agent (NPA). Bandwidth is allocated to the VPs and it can be managed dynamically by a Service Provider Agent (SPA). The SPA is responsible for creating, maintaining and managing the logical configuration of the SP. It does so by collecting data for current and anticipated traffic demand and using a VP management algorithm to periodically adjust the VP capacities. In a first phase, routes will consist of end-to-end VPs as this speeds up connection set-up and simplifies routing. However, in a second stage multi-VP routes will be considered, since they yield much better utilisation in larger networks. For each source-destination pair (sd-pair) there exists a Resource Agent (RA); different SPs have different RAs for the same sd-pair. Each RA controls some preassigned routes (actually VPs in this phase) allocated by the SPA. When a new connection request arises, the appropriate RAs (depending on the sd-pair of the connection) receive a call for proposals indicating the connection requirements, issued by a Proxy User Agent (explained below). The RAs are responsible for selecting the most appropriate route and ensuring that it has sufficient resources for the connection (by performing a CAC check). A RA may reply to the call
for proposals by issuing one of the following proposals, depending on resource availability [17]: • the RA has routes (VPs) with sufficient resources for the connection, so the connection is routed along one of these routes. • the RA has no routes with sufficient resources, but if some connections are re-routed from one route to another of the same sd-pair, some route will acquire enough resources for the new connection. • available resources in this sd-pair are not sufficient, but if the user may tolerate a slow setup time, it may be possible to negotiate bandwidth with other RAs (sd-pairs) of the same SP. The negotiation is coordinated by the SPA with some sort of Contract Net Protocol [18]. At the access network nodes, there are Proxy User Agents (PUAs), one per UNI port. PUAs intercept the connection requirements from the end-systems/users (probably sent in the form of signalling messages) and translate them to agent language by issuing a call for proposals to the appropriate RAs. They are actually user delegates, since they may also select among the proposals returned by the RAs, based on criteria such as cost, set-up delay, offered QoS, etc. In general, they deal with the interworking between the protocols used at the user-network interface (e.g. ATM signalling, RSVP or some meta-signalling language) and the agent-based control system. Mobile agents, delegated by the user and containing the user’s custom logic, can be an interesting alternative in this role. Each switching node has a Switch Wrapper Agent (SwWA) which provides a generic, vendor-independent abstraction of the physical switch’s resources and exports a generic switch control interface for connection control, configuration management and performance monitoring. Through this interface, RAs and SPAs interact with the switch so as to establish and release connections and VPs, as well as to measure utilisation and availability of switch resources in order to perform CAC checks or predict traffic demand. The SwWA is capable of receiving messages from several Ras concurrently and of processing them in a serialised way. The SwWA is a very practical and re-usable component for agent-based ATM network management systems; it has the ability to understand FIPA agent language semantics which embed, in their “content” field (see [19]), switch control commands defined in a generic manner, independent of the switch’s model. The SwWA then transforms the agent language commands into switch-specific commands to be carried out on the physical switch by using a protocol such as GSMP or SNMP. Its modular design enables easy adaptation to different switch models [20]. The supported commands
facilitate the development of a great variety of management and control applications that may make use of the SwWA3.
portability and simplicity, which enables fast development and maintenance of experimental prototype systems, especially when dealing with heterogeneous equipment. The agent communication language (ACL) used in the platform is aligned with FIPA recommendations [19] with regard to the language semantics. However, the content is encoded as Java objects instead of strings to take advantage of RMI’s features. The receiving agent interprets the message depending on the object class-type and the values of certain attributes.
The following figure depicts the architecture of the system showing the basic agent types and illustrating their role. Due to the use of distributed object techniques, the physical location of the agents is not important. The exact interaction diagrams indicating the semantics and content of the messages exchanged between the agents can be found in [17]. The system has been implemented on an ATM testbed with commercial, multi-vendor ATM equipment, in Basel, Switzerland. Furthermore, since the overall architecture is largely vendor-independent, apart from
Since the BAT provides a very convenient framework for the implementation of multi-agent systems, different alternative approaches for CAC and Network Resource Management have been tried. The approaches were
Net. Provisioning Layer
NPA
SPA-A
Net. Resource Management Layer
SPA-B
Reactive Layer
RA1
Connection Request
RA2
cfp
RA3 PUA
PUA SwWA
SwWA
Core Network
Access Node
Access Node
Routes managed by RA3 in the core network Figure 1 - Basic agent types in the system and their role
“thin” adaptation layers (wrappers) between the physical devices and the agents, the has also been ported to other sites, such as the ATM testbed of Tele-Danmark (Aarhus, Denmark) and the Telecommunications Laboratory of NTUA. The agent platform (called the Basic Agent Template – BAT [17]) is based on the Java Remote Method Invocation (RMI) distributed object architecture. RMI has been chosen instead of CORBA because of Java’s
3
We are currently implementing such a Web-based Management application for the ATM switches of the Telecommunications Laboratory of NTUA.
based on the same basic agent types presented above, but differed in terms of agent interactions and algorithms used internally in the agents. Apart from the approach presented here (depicted in the above figure), the reader may refer to [16] for another approach based on the same architecture.
5. Conclusions This paper addressed the problem of ATM network control. It has been argued that, although current control protocols have enabled rapid deployment of interoperable ATM networks, they present some drawbacks when it comes to customising control of network and services. Moreover, with the increase in
traffic demand in ATM networks, advanced CAC and network resource management schemes will be needed in order to maximise utilisation. The network control mechanisms currently built into ATM equipment do not facilitate such objectives, thus the assistance of distributed computing architectures should be considered. Such an architecture, based on the concept of Intelligent Agents, has been presented; it provides an open framework for the deployment of network control schemes. Different service providers are even free to use different control algorithms on the same (logically partitioned) physical infrastructure. The performance of the system has been demonstrated and assessed in experiments under different policies for CAC, VP management and bandwidth negotiation and using devices from various manufacturers. Although the system lacks in call-setup speed with respect to conventional signalling systems, the major strength and contribution of agent control is the ability to specify different control policies, operating together on the same physical infrastructure, with the inherent ability for negotiation, resource re-allocation and adaptation to changes in traffic demand. ACKNOWLEDGEMENTS The authors gratefully acknowledge support from the European Commission under the ACTS Project AC324 “Implementation of Agents for CAC on an ATM Testbed”. The authors also acknowledge valuable help and contributions from its partners Queen Mary and Westfield College, Swisscom, Tele-Danmark, Flextel, Teltec, and ASPA.
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[18] R. Smith and R. Davis, “Frameworks for Cooperation in Distributed Problem Solving”, IEEE Trans. on Systems, Man & Cybernetics, vol. 11, no. 1, pp. 61-70, 1981. [19] Foundation for Intelligent Physical Agents, FIPA 97 Specification Part 2, “Agent Communication Language”, http://www.fipa.org. [20] IMPACT AC324 Project Deliverable 04 “Specification of Signalling Implementation”, November 1998, available from http://www.actsimpact.org.
