Immune Based Bio-Network Architecture and its Simulation Platform for Future Internet

Immune Based Bio-Network Architecture and its Simulation Platform for Future Internet

Yong-Sheng Ding (Ministry of Education, China), Xiang-Feng Zhang (Ministry of Education, China & Shanghai Dianji University, China) and Li-Hong Ren (Ministry of Education, China)
DOI: 10.4018/978-1-60566-310-4.ch010
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Abstract

Future Internet should be capable of extensibility, survivability, mobility, and adaptability to the changes of different users and network environments, so it is necessary to optimize the current Internet architecture and its applications. Inspired by the resemble features between the immune systems and future Internet, the authors introduce some key principles and mechanisms of the immune systems to design a bio-network architecture to address the challenges of future Internet. In the bio-network architecture, network resources are represented by various bioentities, while complex services and application can be emerged from the interactions among bio-entities. Also, they develop a bio-network simulation platform which has the capability of service emergence, evolution, and so forth. The simulation platform can be used to simulate some complex services and applications for Internet or distributed network. The simulators with different functions can be embedded in the simulation platform. As a demonstration, this chapter provides two immune network computation models to generate the emergent services through computer simulation experiments on the platform. The experimental results show that the bio-entities on the platform provide quickly services to the users’ requests with short response time. The interactions among bio-entities maintain the load balance of the bio-network and make the resources be utilized reasonably. With the advantages of adaptability, extensibility, and survivability, the bio-network architecture provides a novel way to design new intelligent Internet information services and applications.
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Background

The Requirements of Future Internet

Future Internet should exhibit a strong sense of automation: 1) Support for survivability from massive failures and attacks; 2) Ability to configure and reconfigure system dynamically; 3) Awareness of Internet system environment; 4) Seeking of behavior optimization to achieve its goal; and 5) Requirement to detailed knowledge of system components and status.

The requirements of future Internet resemble the self-organizing and the self-healing properties of biological systems. There is a strong similarity between the complex interaction of organisms in biological systems and that of components in a networked system (Bhalla & Lyengar, 1999; Girvan & Newman, 2002). This makes us to study the relationships among components in the Internet environment by associating it with biological systems, especially with some key concepts and principles in biological immune systems. As such, we can introduce some immune mechanisms to study evolutionary Internet systems with those desirable properties.

Key Terms in this Chapter

Immune Symmetrical Network: The symmetrical network theory for the immune system is a tractable first approximation. The principle lymphocytes fall into just two specificity classes. The first class is the antigen-binding set, denoted T+ and B+ for T cells and B cells respectively. The second set is minus or anti-idiotypic set, T- and B-. There are three types of interaction between the plus and minus sets as follows: stimulation, inhibition, and killing. Stimulation can occur when two lymphocytes encounter each other. The receptors of one lymphocyte (‘+’) can cross-link the receptors of a second lymphocyte (‘-’), the converse is also true. So stimulation is assumed to be symmetrical in both directions between the two sets. Specific T cells factors could inhibit receptors. Finally, antibody molecules are assumed to be killed in a symmetrical fashion. According to the interaction among B cells and T cells, we can receive a set of four stable steady states for the system of T+, B+, T- and B- cells. The steady states are the initial state, the suppressed or unresponsive state, the immune state and the anti-immune state.

P2P Network: In P2P network, every node (peer) of the system acts as both client and server and provides part of the overall resources/information available from the system. In a pure P2P system, no central coordination or central database exists and no peer has a global view of the system. Participating peers are autonomous and self-organize the system’s structure, i.e., global behavior emerges from local interactions. P2P technologies have many applications, such as file sharing and exchanging, distributed computing, collaborative system, P2P computing, and enterprise applications.

Mutual-Coupled Immune Network: The mutual-coupled immune network hypothesis shows that the immune systems are constructed by forming large-scale immune networks with the interactions among small-scale networks. According to the hypothesis, we consider that each small-scale network has a specific task, and can be regarded as a local immune network (LIN). The interactions among the small-scale networks form a global network, and the global network has its remarkable ability to accomplish a complex task.

Biological Immune Systems: The biological immune system in our body is an efficient adaptive system. According to the immunologists, the components such as cells, molecules and organs in the biological immune system can prevent the body from being damaged by pathogens, known as antigens. The basic components of the immune system are lymphocytes that have two major types, B cells (B lymphocytes) and T cells (T lymphocytes). Biological immune systems are adaptive systems and their learning behaviors take place through evolutionary mechanisms similar to biological evolutions. They are distributed systems without central control. They can survive local failures and external attacks and maintain balance because of emergent behaviors of the interactions of many local elements, like immune cells. In the immune systems, the whole is more than the sum of the systems’ parts because of the interactions among the parts, just as emergent behaviors in other complex systems.

Bio-Network Platform: The bio-network simulation platform is a software framework fully implemented by Java language based on the bio-network architecture by utilizing multi-agent systems. The ideal model would place the bio-network platform on every device as a network node. The bio-network simulation platform has the capability of service emergence, evolution etc.. The platform can be used to simulate some complex services and applications for Internet or distributed systems.

Web Service: Web services are self-contained, modular applications that can be described, published, located, and accessed over network by using open standards. The functionality of the individual Web service is limited and cannot satisfy some practical requirements. The potential of Web services can only be achieved if they are used to dynamically compose some new Web services that provide more sophisticated functionalities compared to existing ones. The Web service composition is a highly complex task, and it is already beyond the human capability to deal with the whole process manually. Some methods for automatic composition and management of Web services have been proposed. They are conducted to fall into the realm of workflow composition or artificial intelligence planning methods.

Emergent Computation: Emergent computation is generally characterized by the interaction of relatively simple entities, forming a system to exhibit emergent properties. Emergent computation has three aspects: self-organization, aggregative behavior, and cooperative behavior.

Future Internet: The future Internet will be the core of the worldwide information infrastructure and the general service platform with computation, communication, entertainment, e-business, and so on. Future Internet should configure and reconfigure its network services dynamically to satisfy demanders and Internet application can adapt to the change of different network environments. Internet nodes also should be secure and can survive failures and attacks. Obviously, future Internet should be capable of extensibility, survivability, mobility, and adaptability to the changes of different users and network environments.

Bio-Network Architecture: We consider the biological immune system as a set of active computational components interacting in a dynamic and often unpredictable environment. Then, the behaviors of the biological immune systems can be modeled in terms of bio-entities and society-entities. Bio-entities in the bio-network architecture are regarded as autonomous agents and possess the characteristics such as interaction, no central control, diversity, mobility, and evolution. The bio-network architecture will make it possible to emerge the complexity of the biological immune systems from the interactions of bio-entities. We only need design simple behaviors of bio-entities, while complex biological behaviors are the emergence of bio-entities behaviors. The layered infrastructure of the bio-network architecture consists of bio-entities, bio-entity survivable environment, bio-network core services, bio-network low-level functional modules, and bio-network simulators.

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Editorial Advisory Board
Table of Contents
Foreword
Lipo Wang
Preface
Hongwei Mo
Chapter 1
Fabio Freschi, Carlos A. Coello Coello, Maurizio Repetto
This chapter aims to review the state of the art in algorithms of multiobjective optimization with artificial immune systems (MOAIS). As it will be... Sample PDF
Multiobjective Optimization and Artificial Immune Systems: A Review
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Chapter 2
Jun Chen, Mahdi Mahfouf
The primary objective of this chapter is to introduce Artificial Immune Systems (AIS) as a relatively new bio-inspired optimization technique and to... Sample PDF
Artificial Immune Systems as a Bio-Inspired Optimization Technique and Its Engineering Applications
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Chapter 3
Licheng Jiao, Maoguo Gong, Wenping Ma
Many immue-inspired algorithms are based on the abstractions of one or several immunology theories, such as clonal selection, negative selection... Sample PDF
An Artificial Immune Dynamical System for Optimization
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Chapter 4
Malgorzata Lucinska, Slawomir T. Wierzchon
Multi-agent systems (MAS), consist of a number of autonomous agents, which interact with one-another. To make such interactions successful, they... Sample PDF
An Immune Inspired Algorithm for Learning Strategies in a Pursuit-Evasion Game
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Chapter 5
Luis Fernando Niño Vasquez, Fredy Fernando Muñoz Mopan, Camilo Eduardo Prieto Salazar, José Guillermo Guarnizo Marín
Artificial Immune Systems (AIS) have been widely used in different fields such as robotics, computer science, and multi-agent systems with high... Sample PDF
Applications of Artificial Immune Systems in Agents
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Chapter 6
Xingquan Zuo
Inspired from the robust control principle, a robust scheduling method is proposed to solve uncertain scheduling problems. The uncertain scheduling... Sample PDF
An Immune Algorithm Based Robust Scheduling Methods
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Chapter 7
Fabio Freschi, Maurizio Repetto
The increasing cost of energy and the introduction of micro-generation facilities and the changes in energy production systems require new... Sample PDF
Artificial Immune System in the Management of Complex Small Scale Cogeneration Systems
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Chapter 8
Krzysztof Ciesielski, Mieczyslaw A. Klopotek, Slawomir T. Wierzchon
In this chapter the authors discuss an application of an immune-based algorithm for extraction and visualization of clusters structure in large... Sample PDF
Applying the Immunological Network Concept to Clustering Document Collections
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Chapter 9
Xiangrong Zhang, Fang Liu
The problem of feature selection is fundamental in various tasks like classification, data mining, image processing, conceptual learning, and so on.... Sample PDF
Feature Selection Based on Clonal Selection Algorithm: Evaluation and Application
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Chapter 10
Yong-Sheng Ding, Xiang-Feng Zhang, Li-Hong Ren
Future Internet should be capable of extensibility, survivability, mobility, and adaptability to the changes of different users and network... Sample PDF
Immune Based Bio-Network Architecture and its Simulation Platform for Future Internet
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Chapter 11
Tao Gong
Static Web immune system is an important applicatiion of artificial immune system, and it is also a good platform to develop new immune computing... Sample PDF
A Static Web Immune System and Its Robustness Analysis
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Chapter 12
Alexander O. Tarakanov
Based on mathematical models of immunocomputing, this chapter describes an approach to spatio-temporal forecast (STF) by intelligent signal... Sample PDF
Immunocomputing for Spatio-Temporal Forecast
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Chapter 13
Fu Dongmei
In engineering application, the characteristics of the control system are entirely determined by the system controller once the controlled object... Sample PDF
Research of Immune Controllers
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Chapter 14
Xiaojun Bi
In fact, image segmentation can be regarded as a constrained optimization problem, and a series of optimization strategies can be used to complete... Sample PDF
Immune Programming Applications in Image Segmentation
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Chapter 15
Xin Wang, Wenjian Luo, Zhifang Li, Xufa Wang
A hardware immune system for the error detection of MC8051 IP core is designed in this chapter. The binary string to be detected by the hardware... Sample PDF
A Hardware Immune System for MC8051 IP Core
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Chapter 16
Mark Burgin, Eugene Eberbach
There are different models of evolutionary computations: genetic algorithms, genetic programming, etc. This chapter presents mathematical... Sample PDF
On Foundations of Evolutionary Computation: An Evolutionary Automata Approach
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Chapter 17
Terrence P. Fries
Path planning is an essential component in the control software for an autonomous mobile robot. Evolutionary strategies are employed to determine... Sample PDF
Evolutionary Path Planning for Robot Navigation Under Varying Terrain Conditions
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Chapter 18
Konstantinos Konstantinidis, Georgios Ch. Sirakoulis, Ioannis Andreadis
The aim of this chapter is to provide the reader with a Content Based Image Retrieval (CBIR) system which incorporates AI through ant colony... Sample PDF
Ant Colony Optimization for Use in Content Based Image Retrieval
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Chapter 19
Miroslav Bursa, Lenka Lhotska
The chapter concentrates on the use of swarm intelligence in data mining. It focuses on the problem of medical data clustering. Clustering is a... Sample PDF
Ant Colonies and Data Mining
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Chapter 20
Bo-Suk Yang
This chapter describes a hybrid artificial life optimization algorithm (ALRT) based on emergent colonization to compute the solutions of global... Sample PDF
Artificial Life Optimization Algorithm and Applications
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Chapter 21
Martin Macaš, Lenka Lhotská
A novel binary optimization technique is introduced called Social Impact Theory based Optimizer (SITO), which is based on social psychology model of... Sample PDF
Optimizing Society: The Social Impact Theory Based Optimizer
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Chapter 22
James F. Peters, Shabnam Shahfar
The problem considered in this chapter is how to use the observed behavior of organisms as a basis for machine learning. The proposed approach for... Sample PDF
Ethology-Based Approximate Adaptive Learning: A Near Set Approach
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Chapter 23
Dingju Zhu
Parallel computing is more and more important for science and engineering, but it is not used so widely as serial computing. People are used to... Sample PDF
Nature Inspired Parallel Computing
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Chapter 24
Tang Mo, Wang Kejun, Zhang Jianmin, Zheng Liying
An understanding of the human brain’s local function has improved in recent years. But the cognition of human brain’s working process as a whole is... Sample PDF
Fuzzy Chaotic Neural Networks
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