Active Dynamic Routing (ADR)

Transcription

1 Active Dynamic Routing (ADR) Louise Crawford and Alan Marshall School of Electrical and Electronic engineering, The Queens University of Belfast Ashby Building, Stranmillis Road, BT9 5AH Belfast. Northern Ireland, U.K. Abstract The advent of high-speed networking has introduced opportunities for applications such as video conferencing and medical imaging. These applications have stringent performance requirements in terms of delay, delay jitter and loss rate. Subsequently a central issue in the design of modern communication networks is the provision of performance guarantees. To facilitate the use of real-time communications in the Internet new characteristics and services must be added. In traditional routing, packets are delivered using a route based on their source and destination addresses, while in Quality of Service (QOS) based routing the traffic requirements are also taken into account. The paper describes a novel approach, termed Active Dynamic Routing (ADR) that allows routes to be selected based on a range of criteria. Furthermore these criteria (bandwidth, delay, jitter, cost etc) can dynamically vary over the lifetime of a connection, subsequently changing the optimal route. Often the number of hops is the metric used to make the routing decisions but with ADR, customers can use different criteria, and different rules to effectively select an optimal path to their destinations. ADR is based on the concepts of programmable and active networks, whereby the functionality of network elements can be changed or modified by end users or third parties. The ADR approach aims to provide a preventative measure against congestion, and is achieved by using agents placed at chosen routers through the network. Selecting a path that provides QoS, requires additional information. In operation, this information, including the traffic profile, can be held and exchanged by the communicating agents. Each agent will have access to read and update a multi-dimensional matrix that identifies the individual weighted costs to move between different specified routers for each class/ type of traffic. A novel aspect of this approach is that the agents take account of the packet scheduling used, along with current status of the queues in each router, in order to derive an optimal route. The matrix is then used to determine the most appropriate path for a given packet or a stream of packets given its/their specific needs 1 Introduction The phenomenal expansion in the World Wide Web in recent years exemplifies the explosion of growth in demand for multimedia applications delivered over networks. Distance learning, e-commerce, digital libraries, video conferencing, and telemedicine all offer access wherever we desire at home or on the move or in the office [1], [2] and are all having significant effects on the network technology. Such multi media applications (e.g. Digital video and audio) often have stringent quality of service (QoS) requirements. To meet these performance guarantees; networks exercise control and reserve resources. Subsequently much research has been dedicated to resource reservation, packet scheduling and admission control [3], [4]. Essentially the term resource reservation refers to the network finding resources and making reservations, and can only be done after a path with adequate resources has been found i.e. routing has to take into consideration a wide range of QoS requirements. In traditional data networks routing is focused on connectivity [1] and typically supports only one type of datagram service called Best Effort Routing. Current Internet routing protocols such as OSPF use shortest path routing in which routing is optimised for a single arbitrary metric (such as hop count or delay) without considering the resources availability and other requirements [5]. Routing protocols now need a more complex model whereby a route through the network is characterised by multiple metrics such a bandwidth, delay and loss probability. The basic problem of QoS routing is then twofold: (i) to satisfy the QoS requirements for every admitted connection, and (ii) to achieve global efficiency in resource utilization [2]. However before this can be done state information must be collected and the search for a feasible path performed.

2 QoS routing involves the network routing elements gaining a full or partial state representation of the network, or their section of it, and routing algorithms then aim to identify the best feasible route from a given source to a destination that satisfies QoS constraints. A major problem with multimedia services is that their traffic demands are highly variable [7] and modern high speed communication networks are rapidly becoming more dynamic and complex (changing the global state representation).this along with the increasing range of QoS requirements highlights the need for routing to be able to dynamically adapt to changing demands. 2. Active Networks and ADR 2.1 Active Networks Active and programmable networks increase the flexibility of the network infrastructure by giving users and service providers the opportunity to customise network elements to meet their own specific needs. The behaviour of the previously static switches and routers can now be modified by the injection of customised codes into the network. Currently there are two favoured approaches for introducing programmability into the network; OPENSIG and Active Packets [9]. The new approach to dynamic routing based on active networking technologies, allows route allocation to respond to current factors in the network and subsequently ensures that network resources are used efficiently whilst also meeting QoS demands of the traffic. 2.2 Using the Agents Active Dynamic Routing (ADR) proposes to place agents (active packets) at chosen routers through the network. Basically the agent is an independent executing program that can autonomously choose and perform actions in response to events. To make QoS guarantees for a connection, a route through the network must be found which supports the specified level of service requested. Finding such a route requires a large amount of information about the network state that is both distributed throughout the network and rapidly changing. At the very least a router must know or be able to discover the connectivity of the network in order to select a path. Selecting a path that provides QoS requires additional information. With ADR, each link in the network has associated multiple QoS parameters (metrics). These include residual bandwidth, loss probability, delay (It should be noted that delay is composed of both the propagation and queuing time), delay jitter, security status, cost (monetary), and hop count. In operation this information including the traffic profile, can be held and exchanged by the communicating agents. Data regarding the traffic load at their respective routers can then be incorporated into the delay cost to produce a more realistic delay cost value. Additionally the agents can take account of the packet scheduling technique used, along with the current status of the queues in each router, in order to derive an optimal route. The arriving traffic is identified as belonging to one of a number of categories such as video conferencing, ftp, , streaming audio and video and voice. In order to differentiate or categorise these different types of traffic flows, we can label or tag the packets so that when these packets arrive at a node which hosts an agent, the label will be read and the packet/stream type identified. If the agent knows the type of traffic it can then assign the relevant specific metric bounds for that particular case. Also for every traffic type each metric is weighed since it will hold differing levels of importance to each traffic type. Bandwidth however is the exception, since in all cases if the level of residual bandwidth if not sufficient to meet QoS requirements then that link is not feasible. Wang and Crowcroft have argued that using bandwidth as the first discriminating characteristic is often efficient since bandwidth affects many of the remaining QoS parameters [1]. For example increases in delay would result from there being insufficient bandwidth since packets would have to queue in the routers. Each agent will have access to read and update a multidimensional matrix that identifies the individual weighted costs to move between different specified routers for each class/type of traffic. 2.3 The ADR Routing Matrix Updates Until recently routing tables were generated in a centralised (and often human mediated) manner. However centralised management tools depend by definition on restricting important decisions to one or a few nodes,

3 consequently these nodes become overworked and points of congestion as they are required to relay more and more topological information to other nodes. Resultantly large networks need to be broken up into smaller more manageable subnetworkswhilst still supporting interactions between these subnetworks. Subsequently ADR uses a decentralised approach whereby the agent in each sub network cooperates with their neighbours to accumulate and distribute connectivity information. The subnetworks overlap at points allowing those agents at the edges to obtain information about their neighbours in the next subnetwork. The overalltopology is determined and stored by the agents at nodes along a route. In the OSPF (Open shortest Path First) protocol, metric values are updated every 30 minutes, in contrast a QoS router would require more frequent updates to track rapidly changing link parameters to avoid incorrect routing decisions. There is an obvious trade off between protocol overhead and accuracy of the network state information. With OSPF, link state advertisements are triggered only when there is a significant change in the value of metrics since the last advertisement, while at the same time a periodic trigger can be implemented to ensure small interval updates [10]. This update can be shortened from 30 mins to several seconds. Therefore it can be deduced that with ADR the metric updates will be dramatically increased in comparison to the current OSPF link state advertisements, since an update should occur whenever the cost metric for a specific type of traffic has increased/decreased enough to move outside its pre-specified range. This range is determined by the traffics performance parameter bound for that particular metric. Fortunately, it is shown that OSPF update traffic is only a small fraction of a links capacity [11]. 3 ADR And Current Routing Architectures As the dynamic within a network s traffic increases so the optimal routes through it will change more frequently thus the pre-allocation of routes will rapidly result in inefficient use of the networks resources.. Since route demands need to share resources, and a certain level of service has been guaranteed to each route, new requests can only be accommodated with some reference to the current network state. The need for this information means that the routes can only be allocated on demand. Hop-by hop routing and Source routing are the two basic routing architectures for data networks. Source routing is mainly used for special policy routes while the hop-by- hop strategy is implemented for the general purpose routing in our current networks. On hop-by-hop routing, each node has a routing table with next hops for all destinations, so when a packet arrives at a node a simple look-up is performed to find the next hop. Conversely with source routing a forwarding path is computed on demand at the source and listed in the packet header and packets are forwarded according to this path. To do this the source must have access to full routing information for each link for path computation and packets must have a larger header in comparison to that of hop-by-hop routing. This is because with hop-by-hop routing packets do not have to carry a full forwarding path. Each type of routing is relevant to providing QoS. General purpose routing could be performed using hop-by-hop and those cases needing a special mechanism to override general routing can use source routing. With ADR and source routing the agent, will be aware of the pre-computed routes by reading the packet header, and use this knowledge to partly predict future traffic conditions at specific nodes, subsequently the agent can now make an more educated route allocation. Also, to aid the resource reservation process, an agent can readily communicate to other agents the pre-computed route to be used for a packet/stream of packets. The agents can update their routing tables and anticipate which routers will have more traffic load in the future. Depending on whether hop-by-hop or source routing is being used the format of the search matrix needed to determine a suitable route willdiffer (i.e. on the search information needed). For example, given a specific service (e.g. video), which is the best route through the network or given a particular route or set of routes (i.e. VPNs), which is the best to connect each service through to their destination?

4 4 Two Alternative Matrix Designs Figure1 (a) and Figure1 (b) illustrate the search matrix form needed to choose the best route for each service, given a particular set of VPNs. Consider Figure1 (a), the entry R 01 refers to the costs incurred by traffic moving between two routers in the subnetwork labelled R0 and R1. The router labelled in the top line gives the router which the packet/packet stream is moving to and the routers labelled down the left side of the matrix indicates the router which the packet/stream of packets are moving from. Figure1 (b) illustrates an entry that would be found in the upper matrix i.e. it would be a nested matrix within Figure1 (a) that declares each individual cost of moving between those two routers, for each type of traffic. Every connection will not be concerned with every cost (This depends on the grade of service it requests) and so the volume of data will be substantially reduced. R0 R1 R2 R3 R4 R0 X R 01 R 02 R 03 R 04 R1 R 10 X R 12 R 13 R 14 R2 R 20 R 21 X R 23 R 24 R3 R 30 R 31 R 32 X R 34 R4 R 40 R 41 R 42 R 43 X Figure 1(a)- Upper level of ADR-VPN Search Matrix Bandwidth Cost Delay Jitter Loss-prob Path-length Reliability Hop-Count Video-conf M 00 M 01 M 02 M 03 M 04 M 05 M 06 M 07 FTP M 10 M 11 M 12 M 13 M 14 M 15 M 16 M 17 M 20 M 21 M 22 M 23 M 24 M 25 M 26 M 27 Audiovideo M 30 M 31 M 32 M 33 M 34 M 35 M 36 M 37 Voice M 40 M 41 M 42 M 43 M 44 M 45 M 46 M 47 Figure 1(b)- An element of ADR-VPN Search Matrix Figure2 (a) and Figure2 (b) show the matrix form adopted to analyse the best route through the network for a specific service. The first column from the left of the matrix in Figure2 (a) are the routers from which the packet/packet stream start their journey and the upper row identifies which category the traffic belongs to. The matrix depicted in Figure2 (b) relates the form of an individual element of Figure2(a). In Figure2 (b) the first column on the left labels the router to which the packet is moving next and the top row identifies each of the metric columns.. Video-conf FTP Audio-video Voice R0 C 00 C 01 C 02 C 03 C 04 R1 C 10 C 11 C 12 C 13 C 14 R2 C 20 C 21 C 22 C 23 C 24 R3 C 30 C 31 C 32 C 33 C 34 R4 C 40 C 41 C 42 C 43 C 44 Figure 2(a)- Upper level of ADR-Traffic Search Matrix

5 Bandwidth Cost Delay Jitter Loss-prob Path-length Reliability Hop-Count R0 M 00 M 01 M 02 M 03 M 04 M 05 M 06 M 07 R1 M 10 M 11 M 12 M 13 M 14 M 15 M 16 M 17 R2 M 20 M 21 M 22 M 23 M 24 M 25 M 26 M 27 R3 M 30 M 31 M 32 M 33 M 34 M 35 M 36 M 37 R4 M 40 M 41 M 42 M 43 M 44 M 45 M 46 M 47 Figure 2(b)- An element of ADR-Traffic Search Matrix 5 Obtaining The Optimal Route. Different costs hold different levels of priority to different types of traffic, in fact some of the costs may not be of any relevance to a given service level at all. Subsequently in the instance whereby only a small number of different costs are applicable (i.e. 1 to 3 costs) to the traffic type to be routed, a minimal spanning tree between the source and destination router could be obtained for each of the individual costs and these trees could then be overlapped to obtain a common overall spanning tree. If a common tree cannot be directly obtained then it can be derived by compromising a cost of lower/lowest priority (whilst ensuring it still remains on or within its required bounds). In the instances when service requests have a larger variety of metrics, dynamic programming techniques, in particular variations of the Simplex Method can be employed. Conclusion This paper presents a new approach to dynamic routing in the Internet called ADR. ADR developes the new approach to dynamic routing based on active networking technologies that will encourage fluidity in route allocation and offers realtime resource utilization. This will help ensure that the network resources are used efficiently and in a way that maintains QoS guarantees. The approach is based on the premise that knowledge exists regarding the overall network topology and the current utilisation of all subnetworks. With this knowledge at hand it is possible to make routing decisions that not only take advantage of lightly loaded routes but also allow traffic to be rerouted to make generally better use of a network s resources. ADR is primarily geared towards providing QoS for any routing system, to perform well in the face of changing conditions it must be pro-active rather than reactive, ie problems need to be avoided before they occur. If congestion is developing in the forwarding route the agent will pick up a message from another agent and the necessary adjustments will be made to the corresponding routing matrix. An acceptable route may be considerably longer than the shortest path in previous terms(i.e. the number of hops). The agents have an embedded learning algorithm either individually or as an agency (i.e. all agents in a subnetwork), allowing them to demonstrate their adaptive behaviour and to alter their future action sequences and behaviour such that future mistakes can be alleviated. In future work I aim to utilise this attribute and incorporate SOM (Self Oragnising Maps) theory, namely Kohonen Networks. Acknowledgements I gratefully acknowledge the financial support provided to me by Nortel Networks and DHFETE (Department Of Higher and Further Education, Training and Employment). References [1] Z.Whang and J Crowcroft Quality-of-Service Routing for Supporting Multi-media Applications IEEE Journal on selected Areas in Communications vol.14, no.7, pp [2] S.Chen and K.Nahrsted An Overview of Quality of Service Routing For Next Generation High Speed Networks IEEE Networks, vol.12, no.6, pp 64-79, [3] L.Zhang, S.Deering, D.Estrin, S.Shenker, and D Zappala, RSVP : Anew Resouorce Reservation Protocol IEEENetwork, Sept 1993.

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