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This paper describes the design of a scalable bio-mimetic framework in the management domain of complex Ubiquitous Service-Oriented Networks. An autonomous network service management platform - SwarmingNet is proposed. In this SwarmingNet architecture, the required network service processes are implemented by a group of highly diverse and autonomic objects. These objects are called Tele-Service Solons as elements of TeleService Holons, analogue to individual insects as particles of the whole colony. A group of TSSs have the capabilities of fulfilling the complex tasks relating to service discovery and service activation. We simulate a service configuration process for Multimedia Messaging Service, and a performance comparison is made between the bio-agents scheme and normal multi-agents scheme. ©IFIP International Federation for Information Processing 2009.

This paper presents a new paradigm for viewing the work of Wireless Sensor Networks. The Observed Field (OF) is described as a multi-dimensional Information Space (ISp). The Wireless Sensor Network is described as a Transformation Space (TS), while the information collector is a single point consumer of information, described as an Information Sink (ISi). Formal mathematical descriptions are suggested for the OF and the ISp. Mathematical descriptions for the TS and the ISi, based on the notion of Path Mutual Information, are proposed. Information flows from ISp to ISi via TS. TS can be formally thought of as a multi-dimensional transform function between ISp and ISi. It can be aggregated into a notional multidimensional value. This formal mathematical description can be used to create numerical optimization routines for generating TSs, against cost functions such as power consumption, and constraints such as maximum distance between sensors.

Risk and Vulnerability Analysis (RVA) plays an important role in selfprotecting and self-healing of Autonomic Communication Networks (ACNs). RVA aims at identifying the weaknesses of the networks that may be exploited to compromise the normal functions, such as service deployment, file system access permissions, applications activations and so on. ACNs are recently proposed as business-objective driven high-level self-managed telecommunication networks with the adaptation capability to cope with increasing dynamics as well as widely distributed network demands. Adaptation capability termed as adaptability becomes the premise of realizing thorough autonomy. However, statistical observations reveal that adaptability vs. autonomy and adaptability vs. vulnerability have strong similarity with respect to quantitative results of trends, while autonomy vs. vulnerability are a pair of contradicting factors in practice. In this paper, we make a delicate information-theoretic analysis on the relationship between adaptability, autonomy, and vulnerability, and propose a solution to breaking down these coherent links by maximizing systemsâ adaptability and reducing systemsâ vulnerability simultaneously.

Autonomic Communications have attracted huge attention recently for telecommunication network management in the European Network Research Community. The aim of this research is to propose an Object- oriented hybrid O:MIB structure to replace current MIB architecture and establish a way of enabling O:XML technology into autonomic communications more efficiently with such abilities as autonomy, scalability, adaptation as well as simplicity for autonomic management application in complex networks. This paper presents an experiment that evaluates the performances of O:MIBs in terms of the loss rate, link utilization, management polling with regards to the congestion avoidance process. Simulation results show that O:MIBs provide compatibility with existing MIBs and proved to be an efficient extension over traditional SNMP MIB approach in a view that the workload of manager is greatly reduced. Ve conclude this end- to- end approach maintains self- managing capability, easy- to- implement scalability involving heterogeneous smart algorithms for variant tasks. © 2007 IEEE.

There is a list of very much needed object-oriented and autonomous paradigms that are currently absent from traditional implementations of MIBs in telecommunication systems. We argue that some of autonomous features can be inherent in an application otf an Active MIB mechanism itself, and thus this type of application would be a more appropriate substrate in which to model, develop and integrate the benefits brought by the object-oriented approach. In our work, we claim that active networks are such an application area, in which the object-oriented and autonomous system ideas can be successfully applied. The objective of this research paper is to demonstrate applicability and compatibility of the AMIB concept with functional and architectural requirements of wireless mesh networks. This paper introduces new approaches for using AMIB-based mechanisms in telecommunication networks as well as discusses autonomic processes and algorithms that can be used to manage such networks. © Springer-Verlag Berlin Heidelberg 2007.

This paper describes the design of a scalable bio-mimetic framework that addresses several key issues of autonomous agents in the functional management domain of complex Ubiquitous Service-Oriented Networks.We propose an autonomous network service management platform - SwarmingNet, which is motivated by observations of the swarm intelligence in biological systems (e.g., Termite, Ant/Bees colonies, or Locusts). In this SwarmingNet architecture, the required network service processes are implemented by a group of highly diverse and autonomic objects. These objects are called TeleService Solons (TSSs) as elements of TeleService Holons (TSHs), analoguous to individual insects as members of the whole colony. A single TSS is only able to pursue simple behaviors and interactions with local neighbors, on the contrary, a group of TSSs have the capabilities of fulfilling the complex tasks relating to service discovery and service activation.We simulate a service configuration process for a Multimedia Messaging Service, and a performance comparison between the bio-agents and normal agents is analyzed. Finally, we conclude that through bio-swarming intelligence behaviors, this infrastructure develops the enhanced self-X capabilities which give IP networks advantages of instinctive compatibility, efficiency and scalability. © Troubador Publishing Ltd.

This paper introduces danger theory in Artificial Immune System as a method of responding to danger in wireless mesh networks. It identifies the challenges in deploying Wireless Mesh Networks (WMNs) and focus on secure routing as one of the key challenges in deploying WMNs. In order to implement a secure routing system, various Artificial Immune System (AIS) models were analysed. These models have been used in Intrusion Detection System (IDS) and computer security in the literature. In this paper, the authors propose to use Danger models to secure routing in WMNs. The first step in secure routing process is to identify and classify the network dangers and take necessary actions to overcome those dangers. For the classification task, we apply Self-organizing Maps (SOMs) as the classifier to classify the danger levels in WMNs. These identified danger conditions are further deployed as the warning signals for the design of secure routing protocol. The experimental results validate the proposal of applying the Danger Theory (DT) into security area and good performance is also reported by the use of Artificial Neural Network (ANN) classifier.

Risk and Vulnerability Analysis (RVA) aims at identifying the weaknesses of the networks that may be exploited to compromise the normal functions, such as service deployment, file system access permissions, applications activations and so on. Autonomic Communication Networks (ACNs) are recently proposed as business-objective driven high-level self-managed telecommunication networks with the adaptation capability to cope with increasing dynamics. Adaptation capability termed as adaptability becomes the premise of realizing thorough autonomy. As a theoretic foundation, we firstly propose an innovative Object-oriented Management Information Base (O:MIB). Secondly, a new information-theoretic security awareness strategy inspired from human immune system is proposed to reconfigure file access right, which has a direct relation with adaptability. The experimental results validate this methodology and find out a statistical bound for operators to set a vulnerability level of warning in practice. © 2007 IEEE.

Risk and Vulnerability Analysis (RVA) aims at identifying the weaknesses of the networks that may be exploited to compromise the normal functions, such as service deployment, file system access permissions, applications activations and so on. Autonomic Communication Networks (ACNs) are recently proposed as business-objective driven high-level self-managed telecommunication networks with the adaptation capability to cope with increasing dynamics. Adaptation capability termed as adaptability becomes the premise of realizing thorough autonomy. As a theoretic foundation, we firstly propose an innovative Object-oriented Management Information Base (O:MIB). Secondly, a new information-theoretic security awareness strategy inspired from human immune system is proposed to reconfigure file access right, which has a direct relation with adaptability. The experimental results validate this methodology and find out a statistical bound for operators to set a vulnerability level of warning in practice. © Springer-Verlag Berlin Heidelberg 2007.

Frequent changes caused by IP-connectivity and user-oriented services in Inter-Vehicular Communication Networks (VCNs) set great challenges to construct reliable, secure and fast converged topology formed by trusted mobile nodes and links. In this paper, based on a new metric for network performance called topology convergence and a new Object-Oriented Management Information Base - active MIB (O:MIB), we propose an ant-based topology convergence algorithm that applies the swarm intelligence metaphor to find the near-optimal converged topology in VCNs which maximizes system performance and guarantee a further sustainable and maintainable system topology to achieve Quality of Service (QoS) and system throughput. This algorithm is essentially a distributed approach in that each node collects information from local neighbor nodes by invoking the methods from each localized O:MIB, through the sending and receiving of ant packets from each active node, to find the appropriate nodes to construct a routing path. Simulation results show this approach can lead to a fast converged topology with regards to multiple optimization objectives, as well as scale to network sizes and service demands. © Springer-Verlag Berlin Heidelberg 2007.

This paper proposes a self-organizing scheme based on ant metaheuristics to optimize the operation of multiple classes of managed elements on an Operations Support Systems (OSSs) for mobile pervasive communications. Ant metaheuristics are characterized by learning and adaptation capabilities against dynamic environment changes and uncertainties. As an important division of swarm agent intelligence, it distinguishes itself from centralized management schemes due to its features of robustness and scalability. We have successfully applied ant metaheuristics to the network service configuration process, which is simply redefined as: the managed elements represented as graphic nodes, and ants traverse by selecting nodes with the minimum cost constraints until the eligible network elements are located along near-optimal paths-the located elements are those needed for the configuration or activation of a particular product and service. Although the configuration process is non-transparent to end users, the negotiated SLAs between users and providers affect the overall process. This proposed self-organized learning and adaptation scheme using Ant Colony Optimization (ACO) is evaluated by simulation in Java. A performance comparison is also made with a class of Genetic Algorithm known as PBIL. Finally, the simulation results show the scalability and robustness capability of autonomous ant-like agents able to adapt to dynamic networks. © Springer Science+Business Media, LLC 2007.

This paper describes a management paradigm to give effect to autonomic activation, monitoring and control of services or products in the future converged telecommunications networks. It suggests an architecture that places the various management functions into a structure that can then be used to select those functions which may yield to autonomic management, as well as guiding the design of the algorithms. The validation of this architecture, with particular focus on service configuration, is done via a genetic algorithm -- Population Based Incremental Learning (PBIL). Even with this centralized adaptation strategy, the simulation results show that the proposed architecture and benchmark can be applied to this constrained benchmark, produces effective convergence performance in terms of finding nearly optimal configurations under multiple constraints.

Autonomie Communications have attracted huge attention recently for the management of telecommunication networks in the European Network Research Community. The purpose of this research is to offer the abilities such as autonomy, scalability, adaptation as well as simplicity for management application in complex networks. The accomplished networks inspired by biological mechanisms or market-based concepts could enable agents to be of intelligence, scalablility, and interoperabliliry in the management functional domains with regards to the large volume requirements from services' fulfillment perspective in decentralized Multi-Agent Systems. In accordance with TMF and FIPA specifications and requirements, the autonomy attributes self-configuring, self-adapting, self-limiting, self-preserving, and self-optimizing are involved into our simulation. Resource allocation requests are bidded for a long session in the multi-unit Vickrey-Clarke-Groves auction. This design adopts the software development methodology-GAIA and the framework-JADEx. We have shown multiple service configuration in dynamic network can be nearly optimized by autonomie behaviors via bidding according to business objectives for getting maximum revenues. We conclude this end-to-end approach maintains self-managing capability, easy-to-implement scalability, and more incentively compatible and efficient over other common implementation so that it could achieve the optimal solution to the flexible requirements for the Service Fulfillment for advanced IP networks. © 2005 IEEE.

This paper describes the design of a scalable biomimetic framework that addresses several key issues of autonomous agents in the management domain of complex Ubiquitous Service-Oriented Networks. We propose an autonomous network service management platform - SwarmingNet, which is motivated by observations of the swarm intelligence in biological systems (e.g., Termite, Ant/Bees colonies, or Locusts). In this SwarmingNet architecture, the required network service processes are implemented by a group of highly diverse and autonomie objects. These objects are called TeleService Solons (TSSs) as elements of TeleService Holons (TSHs), analogue to individual insects as particles of the whole colony. A single TSS is only able to pursue simple behaviors and interactions with local neighbors, however, a group of TSSs have the capabilities of fulfilling the complex tasks relating to service discovery and service activation. We simulate a service configuration process for Multimedia Messaging Service, and a performance comparison between the bio-agents and normal agents is analyzed. Finally, we conclude that through bio-swarming intelligence behaviors, this infrastructure develops the enhanced self-X capabilities which give IP networks advantages of instinctive compatibility, efficiency and scalability.