ARE LARGE-SCALE AUTONOMOUS NETWORKS UNMANAGEABLE?

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1 ARE LARGE-SCALE AUTONOMOUS NETWORKS UNMANAGEABLE? Motivation, Approach, and Research Agenda Rolf Stadler and Gunnar Karlsson KTH, Royal Institute of Technology Stockholm-Kista, Sweden May 3, 2002 Abstract Future large-scale networks need the capability of autonomous self- and re-configuration, because of their sheer size and the (probably) frequent changes in state and topology. Our interest is focused not only on the questions of how autonomous networks can be engineered, but, specifically, on how if at all they can be managed. By management we understand the capability to compute state abstractions of the system in a short time and to perform control operations that influence the network state in a desired way. We require that such a management operation can be started from any node in the system. While recent research in the field of complex systems seems to suggest that the most promising approach to controlling a very large system is bottom-up, i.e., identifying and possibly controlling the emerging global properties of well-defined system components, we believe, based on our recent results, that a top-down approach can succeed as well. Introduction There is no contradiction between the concept of an autonomous, self-organizing system and the idea of ensuring the controllability of such a system by an external entity. In this context, controllability relates to setting and modifying the constraints under which the system is operating. In other words: We understand the capability of managing an autonomous system as being able to define, adapt and enforce a set of policies under which the system operates. The system is controllable, if management goals can be reached by the definition of policies. Today s management architectures, and the programming principles developed for them, are no longer adequate for future large-scale networks with frequent changes in state and topology. Current solutions, created for telecom systems, can be characterized by applying centralized control, using hierarchical structures, having a management system that is separate from the service delivery system, and being based on a programming paradigm that is defined by the MIB concept. We believe that a management paradigm for future large and dynamic networks must be founded on decentralized control, adaptable organizational structures, integration of the management system with the communication system, and a programming paradigm that supports these properties. R. Stadler, G. Karlsson Page 1

2 Reaching globally optimal goals by means of simple local mechanisms is known to be very hard in most settings. For instance, routing in the Internet based on the distancevector protocol is an example of a self-organizing system, where each router only acts on neighborhood information, and yet the distributed decisions lead to globally optimal routes. However, as the rate of changes in the network increases, the self-organization never reaches a new equilibrium and the network state becomes uncertain. This cautions us not to approach the problem bottom up, even when the goal in principle can be reached in an entirely decentralized manner. Thus, we will be working at it also topdown. Our primary objective is to understand and eventually engineer management capabilities in large-scale autonomous systems. This includes the task of finding a small (or better a minimal ) set of functions present in every node within the system, which allow the system to organize itself, such that global policies can be executed and enforced. The management system is closely connected to the control functions in the network, where the controls actuate directives that are set by management-level policies. This means, first, that the controls must be able to fulfill the policy, and, second, it should be backward verifiable that the intended goal of the policy is being met. Policies, which lead to conflicting control actions or which are impossible for the control system to achieve, must be identified and returned to the issuer or resolved by the management system. It is therefore clear that we need to consider management and control jointly with respect to policies. By doing that, we see the management system as an autonomous, self-organizing system in itself, which, on the one hand, offers external interfaces for managing policies, and, on the other hand, performs global control operations (i.e., management operations) on the service delivery system. Current Work Our work in this problem domain started some two years ago. Since then, we have developed a methodical approach to realizing management functions that are based on distributed control. Our work can be understood as applying the mobile agent paradigm to network control, whereas a management operation is executed generating a swarm of light-weight mobile agents. Contrary to most mobile agent applications to date, the agents in our approach are very simple, they exploit the parallel processing capability of the network, and, although, they always carry state, they carry code only when necessary. The key concept in our approach is the navigation pattern, which separates the semantics of the management operation from the details of the underlying distributed control scheme. A navigation pattern includes a (distributed) graph traversal algorithm, which defines the control scheme that characterizes the particular pattern. R. Stadler, G. Karlsson Page 2

3 A management operation is executed as a diffusing operation, i.e., it is initiated by a single node and joined by others after receiving a control message. One pattern we have discovered to be particularly useful is the echo pattern. It relies on a class of PIF (propagation with information feedback) algorithms, which flood (parts of) the network with commands in a first phase and aggregate results of the local operations in a second phase. Based on this pattern, a variety of abstractions of the global state can be computed, such as the distribution of the link loads or the average degree of the network nodes, and other characteristics can be identified, such as highly loaded sub networks. Pattern-based management operations can be very efficient. For a network with the characteristics of the Internet (topology, size, delays, etc.), we have estimated that echobased operations could be performed within some 18 seconds [1]. (The reason for this result lies in the parallelism with which the operation is conducted, as well as in the fact that the diameter of the Internet is small compared to the number of nodes.) We have demonstrated advantages of the pattern concept. These include (a) the possibility to study the performance characteristics of management operations through the analysis of the underlying traversal algorithms; (b) the re-usability of patterns in the sense that the same pattern can be used for a class of different operations; (c) the fact that the degree of code mobility can be controlled in a fine-grained way. We have developed robust versions of patterns, which ensure that operations execute and terminate in a well-defined way in case of node or link failures. Also, for a robust pattern, we can control to a certain extent the tradeoff between a large coverage of the operation and a fast execution time. For experimentation, we have developed a simulator that allows us to run pattern-based management operations for networks of up to 100,000 nodes [4]. Our plans The current goal of the above research is to develop an inventory of navigation patterns that are applicable to key management tasks, analyze them regarding performance, scalability, and survivability, and implement them as software components that can be embedded in management and service platforms. Our approach to make a system manageable is to enable it to run navigation patterns. This functionality is similar to making all network nodes part of a lightweight mobile agent system. Therefore, our next task will be to design a system that configures itself into a thin functional layer, which supports navigation patterns. The basic functions that realize such a system need to be present on every network node. We believe that the emerging field of complex systems provides us with useful concepts and a terminology to formulate the problems we are facing and to state our overall approach. A complex system is composed of many parts, which interact with each other. R. Stadler, G. Karlsson Page 3

4 Generally, complex systems require an enormous amount of data be described on the level of the parts and their interactions, i.e., the micro level. Therefore, a description of the system on a higher level, the so-called macro level, is sought, which can be expressed with a different model and less parameters than that on the micro-level. In our problem domain, the macro model serves as the abstraction, on which management policies are formulated. The enforcement of the policies must take place in the real network, i.e., on the micro level. The results of enforcing a policy can then be observed on the macro level. The challenge here is to come up with mechanisms that map global policies into operations on local nodes. In this context, we will collaborate with control theory experts to come up with an approach that will help us understand and realize some of these mappings. The concepts and functions developed in this project will be tested on service and network functionality developed by others. For instance, we plan to implement a subsystem that performs autonomous address management, dynamically controllable by management policies. Second, we plan to experiment with different robustness policies for network services and study the trade-offs of these policies for very large networks. On the control side we are studying simple, local control rules for traffic smoothing on a short timescale, which are supplemented by controls on longer timescales that operate end-to-end across the network [5]. In addition we will consider spatial distribution of network load in a similar manner. A key consideration is the assessment of feedback information in terms of performance gain. For instance, is the control performance obtainable from incomplete but local and thereby current state information better or worse than the performance achievable with more global information, which only is available with delay? Herein lies a fundamental question for network control, whether it is more efficient to reach a management goal by self-organization through local controls, or by centralized controls. By considering also the top-down view, we hope to decompose the control functions so that actions reaching over long distances are actuated on a long time scale and vice versa in order to find practicable methods for management and control of autonomous networks. The effort we are forming at KTH includes researchers in distributed systems, algorithms, and automatic control, in addition to networking specialists. Our research group is therefore prepared to work on the aspects sketched above, for instance, on the convergence properties of self-organizing systems, the stability of distributed controls, the specification and enforcement of policies, as well as on a new networking paradigm that stresses self-configuration, de-centralized operation, and external controllability. References [1] K.S. Lim and R. Stadler: "A navigation pattern for scalable Internet management," IFIP/IEEE International Symposium on Integrated Network Management (IM'01), Seattle, Washington, May 14-18, R. Stadler, G. Karlsson Page 4

5 [2] K.S. Lim and R. Stadler: "Developing pattern-based management programs," IFIP/IEEE International Conference on Management of Multimedia Networks and Services (MMNS 2001), Chicago, IL, Oct 29 Nov 1, [4] K.S. Lim and R. Stadler: SIMPSON A SIMple Pattern Simulator for large Networks, Vers. 1.5, May 2002, [5] K. H. Johansson, H. Hjalmarsson, M. Auvert and G. Karlsson, On Router Control for Congestion Avoidance, to appear in Proc. RVK, Kista, Sweden, June R. Stadler, G. Karlsson Page 5