SGER: Exploratory Research on A New Survivable, Scalable, and Self-Adapting Network Architecture Based on Biological Concepts

PI在这个项目中提出的生物网络架构的灵感来自于观察到生物世界已经开发出必要的机制来实现下一代互联网（NGI）的关键要求，如可扩展性，异构性和动态性，安全性，生存性和简单性。 在生物世界中，每个个体实体（例如，蜂群中的蜜蜂）遵循一组简单的行为规则（例如，迁移、繁殖、能量交换、突变和死亡），而一组实体（例如蜂群）表现出复杂的、涌现的行为（例如，因此，如果服务和应用程序采用生物概念和机制，他们也可能能够实现NGI的关键要求。研究人员建议应用生物世界的关键概念和机制来设计，实现和经验评估一个新的网络架构，称为生物网络架构。 在生物网络架构中，服务和应用程序是由多个实体的集合实现的，称为网络实体（如蜂群由多只蜜蜂组成）。 这些网络实体具有与其服务或应用相关的功能，并遵循简单的行为规则（例如，迁移，繁殖，能量交换，突变，死亡）类似于生物实体。在生物网络架构中，有用的涌现行为（例如，适应性、进化性、安全性和生存性）是个体网络实体相互作用时产生的结果。 生物网络架构可应用于各种NGI应用和服务，包括信息发布、数据存储、资源发现或公钥基础设施。拟议项目的创新主张是： 拟议的生物网络架构是第一次尝试应用 涌现行为、自主控制和适应的生物学概念 和演进到广泛和通用的网络服务类别， 应用. 以前对生物结构的研究是为了 理解生物过程的目的，模拟生命或紧急 行为、分布式计算或机器人。 生物网络架构使服务和 满足NGI关键要求的应用。 可扩展性是 实现，因为网络实体自主行动，并在本地基础上使用 只有本地信息。 服务或应用程序的构造是 简化，因为只有相对简单的行为在网络层面 需要设计。 适应性、安全性和 生存能力仅仅是网络实体的涌现行为 作为一个整体互动。 使用生物网络架构设计的服务和应用程序 适应异构和动态变化的网络条件， 他们的网络实体的自主行动，每个都表现出简单的 行为。 它们也会通过进化， 生物网络的突变和自然选择机制 架构 当前的网络服务必须手动配置， 优化网络条件。 生物网络架构具有可用作 额外的攻击防御层。 服务和应用程序可以 除了使用传统的安全技术（如身份验证）之外， 和加密，生物网络体系结构的功能，如入侵 检测，自主复制，算法多样性，以及 网络实体作为附加层 这些特点增加了 服务或应用程序能够检测、存活和恢复的概率 免受内部人员、恐怖分子或国家的协同攻击。 电流 网络服务和应用程序只有一层防御， 不太可能在协同攻击中幸存

The Bio-Networking Architecture that the PI proposes in this project is inspired by the observation that the biological world has already developed the mechanisms necessary to achieve such key requirements for the Next Generation Internet (NGI) as scalability, heterogeneity and dynamicity, security, survivability, and simplicity. In the biological world, each individual entity (e.g., a bee in a bee colony) follows a simple set ofbehavior rules (e.g., migration, reproduction, energy exchange, mutation, and death), yet a group of entities (e.g. a bee colony) exhibits complex, emergent behavior (e.g., adaptation, evolution, security, urvivability).Therefore, if services and applications adopt biological concepts and mechanisms, they too may be able to achieve the key requirements of NGI.The researcher proposes to apply key concepts and mechanisms from the biological world to design, implement, and empirically evaluate a new network architecture called the Bio-Networking Architecture. In the Bio-Networking Architecture, services and applications are implemented by a collection of multiple entities called cyberentities (as a bee colony consists of multiple bees). These cyberentities have functionality related to their service or application and follow simple behavior rules (e.g., migration, reproduction, energy exchange, mutation, death) similar to biological entities. In the Bio-Networking Architecture, useful emergent behaviors (e.g., adaptation, evolution, security, and survivability) result when individual cyberentities interact. The Bio-Networking Architecture can be applied to a variety ofNGI applications and services, including information dissemination, data storage, resource discovery, or public key infrastructure.The innovative claims of the proposed project are: The proposed Bio-Networking Architecture is the first attempt to apply the biological concepts of emergent behavior, autonomous control, and adaptation and evolution to a broad and general class of network services and applications. Previous studies of biological architectures were for the purpose of understanding biological processes, simulating life or emergent behavior, distributed computation, or robotics. The Bio-Networking Architecture enables the construction of services and applications which meet the key requirements of NGI. Scalability is achieved because cyberentities act autonomously, and on a local basis using only local information. Construction of the service or application is simplified because only relatively simple behaviors at the cyberentity level need to be designed. The other requirements of adaptation, security, and survivability are simply the emergent behavior of the cyberentities interacting as a whole. Services and applications designed using the Bio-Networking Architecture adapt to heterogeneous and dynamically changing network conditions through the autonomous actions of their cyberentities, each exhibiting simple behaviors. They also evolve to more desirable behaviors through the mutation and natural selection mechanisms of the Bio-Networking Architecture. Current network services must be manually configured and optimized to network conditions. The Bio-Networking Architecture has features which can be used as additional layers of defense against attacks. Services and applications can use, in addition to traditional security techniques such as authentication and encryption, features of Bio-Networking Architecture such as intrusion detection, autonomous replication, algorithmic diversity, and dispersion of the cyberentities, as additional layers. These features increase the probability that the service or application can detect, survive, and recover from coordinated attacks by insiders, terrorists, or nations. Current network services and applications have only one layer of defense, so they are unlikely to survive a coordinated attack.