Bjarne E. Helvik

Using the Cross-Entropy Method to Guide/Govern Mobile Agent's Path Finding in Networks

The problem of finding paths in networks is general and many faceted with a wide range of engineering applications in communication networks. Finding the optimal path or combination of paths usually leads to NP-hard combinatorial optimization problems. A recent and promising method, the cross-entropy method proposed by Rubinstein, manages to produce optimal solutions to such problems in polynomial time. However this algorithm is centralized and batch oriented. In this paper we show how the cross-entropy method can be reformulated to govern the behaviour of multiple mobile agents which act independently and asynchronously of each other. The new algorithm is evaluate on a set of well known Travelling Salesman Problems. A simulator, based on the Network Simulator package, has been implemented which provide realistic simulation environments. Results show good performance and stable convergence towards near optimal solution of the problems tested.

Using Stochastic Game Theory to Compute the Expected Behavior of Attackers

This paper presents ongoing work on using stochastic game theory as a mathematical tool for computing the expected behavior of attackers. The possible use of the Nash Equilibrium as a part of the transition probabilities in state transition models is defined and motivated. To demonstrate the approach, a simple example of an attack against a computer network is modelled and analyzed.

Distributed soft policy enforcement by swarm intelligence; application to loadsharing and protection

Managing complex heterogeneous computer and telecommunication systems is challenging. One promising management concept for such systems is policy based management. However, it is common to interpret policies strictly and resort to centralized decisions to resolve policy conflicts. Centralization is undesirable from a dependability point of view. Swarm intelligence based on sets of autonomous “ant-like” mobile agents, where control is distribute among the agents, has been applied to several challenging optimization and tradeoff problems with great success. This paper introduces and demonstrates how a set of such ant-like mobile agents can be designed to find near optimal solutions for the implementation of a set of potentially conflicting policies. Solutions are found in a truly distributed manner, hence an overall more dependable/robust system is obtained. The enforcement of the policies is soft in the sense that it is probabilistic and yields a kind of “best effort” implementation. To demonstrate the feasibility of the overall concept, a case study is presented where ant-like mobile agents are designed to implement load distribution and conflict free back-up policies.RésuméGérer des systèmes complexes et hétérogènes est un véritable défi auquel tente de répondre la gestion par règles. Il est courant d’interpréter strictement les règles et de s’en remettre à un système de décision centralisé pour résoudre les conflits. Mais cette centralisation n’est pas toujours désirable. Pour résoudre certains problèmes difficiles d’optimisation on a été amené à utiliser une forme d’intelligence collective répartie entre des agents mobiles autonomes. Cet article montre la façon dont on peut utiliser un tel ensemble d’agents pour implémenter une des règles éventuellement conflictuelles. Les solutions étant trouvées de façon réellement distribuée, il en résulte un système plus robuste. La mise en œuvre des règles est flexible au sens où elle est probabiliste et conduit à une implémentation du type «au mieux» (best effort). Pour démontrer la faisabilité de ce type d’approche, on présente une étude de cas dans laquelle les agents mobiles sont conçus pour traiter les politiques de distribution de charge et de protection.

Towards a stochastic model for integrated security and dependability evaluation

We present a new approach to integrated security and dependability evaluation, which is based on stochastic modelling techniques. Our proposal aims to provide operational measures of the trustworthiness of a system, regardless if the underlying failure cause is intentional or not. By viewing system states as elements in a stochastic game, we can compute the probabilities of expected attacker behavior, and thereby be able to model attacks as transitions between system states. The proposed game model is based on a reward-and cost concept. A section of the paper is devoted to the demonstration of how the expected attacker behavior is affected by the parameters of the game. Our model opens up for use traditional Markov analysis to make new types of probabilistic predictions for a system, such as its expected time to security failure.

Cross entropy guided ant-like agents finding dependable primary/backup path patterns in networks

Telecommunication network owners and operators have for half a century been well aware of the potential loss of revenue if a major trunk is damaged, thus dependability at high cost has been implemented. A simple, effective and common dependability scheme is 1:1 protection with 100% capacity redundancy in the network. A growing number of applications in need of dependable connections with specific requirements to bandwidth and delay have started using the internet (which only provides best effort transport) as their base communication service. In this paper we adopt the 1:1 protection scheme and incorporate it as part of a routing system applicable for internet infrastructures. 100% capacity redundancy is no longer required. A distributed stochastic path finding (routing) algorithm based on Rubinsteins Cross Entropy method for combinatorial optimisation is presented. Early results from Monte Carlo simulations indeed indicate that the algorithm is capable of finding pairs of independent primary and backup paths satisfying specific bandwidth constraints.

A module-based wireless node for NS-2

Over the last decade an extraordinary amount of research work at all layers of the network stack has focused on wireless and mobile networks, e.g. wireless local area networks (WLAN), in parallel with their wide acceptance as access technologies. Simulation has been used massively to develop, test and compare new ideas and protocols tailored for such networks and ns-2 has been the most used network simulator for these studies. However, the support for wireless and mobile networking in ns-2 is monolithic and not entirely consistent with basic design principles so that it becomes now a burden for making the simulator evolve. It makes it tedious, if not impossible, to support new features such as multiple wireless interfaces. To overcome the current limitations, the MobileNode object itself is questioned and a new, more flexible and better integrated layout of existing components to support wireless and mobile networking using modules (MW-Node) is presented.

Analysis of Dependencies between Failures in the UNINETT IP Backbone Network

Dependencies between failures in operational networks may have a huge impact on their reliability and availability. In this paper we analyze failure logs to identify simultaneous and potentially correlated failures in routers and links of an IP backbone network. We show that the actual behavior of failure processes does not support the independence assumption commonly used in theoretical studies. Scatter plots are presented to visualize the failure processes, and it is seen that geographical adjacency has a pronounced effect. The existence of high correlation coefficients and high autocorrelation in some failure processes was observed. A formal analysis confirms this. The consequences of these dependencies on the provisioning of guaranteed availability are briefly discussed.

Towards a Plug and Play Architecture for Telecommunications

This paper presents an architecture specified within the project “Plug-and-play for Network and Teleservice Components” supported by The Norwegian Research Council. The hardware and software parts, as well as complete network elements that constitute a communication system, shall have the ability to configure themselves when installed into a network and then to provide services according to their own capabilities, the service repertoire and the operating policies of the system.

Dependability modelling and analysis of networks as taking routing and traffic into account

The existing work on dependability modelling and analysis of networks have main focuses on the, structural properties. However, the communication networks also have dynamic characteristics and behavioral properties, such as changes of topology, routes, and traffic loads, which should necessarily be reflected in the modelling. We regard the dependability modelling and analysis of IP networks with an intra-domain routing and traffic handling. This yields to an increased complexity in the modelling and analysis, due to the increase of the state space. Several techniques have been proposed to deal with the growth of the state space. To an analyst, an interesting point is, whether he/she can make a trade-off to the factors under consideration, i.e. the model representativeness vs. modelling complexity, and computation efforts vs. result accuracy. To meet these requirements, we propose a modelling approach where failures and repairs of network components as well as routing and traffic handling are described by a set of stochastic activity networks (SAN). The SANs are designed to restrict the generation of the state space to the most probable states, which enables an analysis without creation of an excessively large state space and achieving a sufficient accuracy of the result. A case study based on the Norwegian university IP backbone network demonstrates the applicability of this approach

Analysis of Failures Characteristics in the UNINETT IP Backbone Network

Core backbone networks must be designed to guarantee high levels of availability. Any interruption in the services that they provide may have massive consequences. For this reason there is a huge interest in developing methods able to keep the network robustness in the desired level. For the design of these methods are used models that need input information such as the operational state of network components which are stochastic variables. The aim of this paper is to provide an insight into the core networks behavior based on real operational data in order to help future related works to take more realistic assumptions. Based on failure logs provided by UNINETT we analyze availability levels and failure intensities in routers and links. We show that links may be classified in three groups with different properties. Additionally we observe that some links have similar dependability features than routers, making the perfect node assumption used on many related studies not correct. Finally, there were used parametrization techniques in order to fit the empirical processes with well-known distributions. We observe that the Weibull assumption that is traditionally used to model link failures processes fits properly the behavior of routers and short distance links but for the case of long distance fibers the gamma distribution seems to fit better.