In this project, the PI explores an innovative idea of applying key concepts and mechanisms from the biological world onto network application designs to enable construction of large scale network applications. The Bio-Networking Architecture that the PI proposes is inspired by the observation that the biological world has already developed the mechanisms necessary to achieve the key requirements for the Next Generation Internet (NGI), such as scalability, adaptability to heterogeneous and dynamic conditions, security, survivability, and simplicity. In the biological world, each individual entity (e.g., a bee in a bee colony) follows a simple set of behavior 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, survivability/availability). Therefore, if services and applications adopt biological concepts and mechanisms, they too may be able to achieve the key requirements of NGI.

The PI is currently investigating the feasibility of the Bio-Networking Architecture through simulation and empirical design/implementation.

The goal of the project is to apply key concepts and mechanisms from the biological world to design and empirically evaluate the new network architecture called the Bio-Networking Architecture. The innovative claims of the proposed project include:

• 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.
• The Bio-Networking Architecture enables the construction of services and applications that meet the key requirements of NGI. Scalability is achieved because cyber-entities 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 cyber-entity level need to be designed. The other requirements of adaptation, security, and survivability/availability are simply the emergent behavior of the cyber-entities acting collectively.

• Services and applications designed using the Bio-Networking Architecture adapt to heterogeneous and dynamically changing network conditions through the autonomous actions of their cyber-entities, each exhibiting simple behaviors. They also evolve to more desirable behaviors through the mutation and natural selection mechanisms of the Bio-Networking Architecture.

The PI’s approaches to the Bio-Networking Architecture are to investigate the feasibility through simulations and to empirically evaluate the Bio-Networking Architecture through prototype design and implementation. Both approaches are briefly summarized below.

The PI has developed a simulator for the Bio-Networking Architecture in Java. The simulator can simulate a wide variety of network topologies and user demand workloads. It can also simulate cyber-entities with different behavior policies.

Design for the Bio-Networking Architecture is described in the technical report submitted in December 1999, and it is summarized below. In the Bio-Networking Architecture, services and applications are implemented by super-entity, i.e., a collection of multiple entities called cyber-entities (as a bee colony consists of multiple bees). (See Fig.1 at http://netresearch.ics.uci.edu/bionet/darpa-report/tech/figure1.gif ). These cyber-entities 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. (See Fig.2 at http://netresearch.ics.uci.edu/bionet/darpa-report/tech/figure2.gif) The Bio-Networking platform software on each node in the Bio-Networking Architecture provides an execution environment and supporting facilities for cyber-entities. (See Fig.3 at http://netresearch.ics.uci.edu/bionet/darpa-report/tech/figure3.gif.) A specialized cyber-entity, the resource cyber-entity, manages and allocates resources to the other cyber-entities on the network node. In the Bio-Networking Architecture, useful emergent behaviors (e.g., adaptation, evolution, security, and survivability) result when individual cyber-entities interact.

With the funding from DARPA, the PI has initiated feasibility study of the proposed Bio-Networking Architecture through simulations and implementations of a small scale web application using the Bio-Networking Architecture. The PI has also initiated investigation of various techniques to provide secure communication on the Bio-Networking Architecture. In addition, the PI has taken steps to gain support from the research community for the Bio-Networking Architecture. Since the proposed Bio-Networking Architecture is innovative and new, it is important that the research community recognizes the advantages of the proposed architecture.

In the following sections, the preliminary results obtained to date, as well as various PI’s activities to gain research community’s support, are summarized. As for the implementation activities, please refer to the technical report submitted in December, 1999. Initial results show that the proposed architecture exhibits such key features as adaptability, survivability and availability.

To demonstrate the key features of the Bio-Networking Architecture (such as adaptability and scalability), as well as to obtain a better understanding of the Bio-Networking Architecture, we have simulated an adaptive and scalable web content distribution application called Aphid. (Aphid is only one of many possible applications that can be constructed using the Bio-Networking Architecture.)

Aphid cyber-entities are constructed according to the design described in the Approach section. The attributes section of the Aphid cyber-entity contains information about itself, including a unique ID, which web site (super-entity) the cyber-entity belongs to, what web pages are in its body, and what system resources are required by the cyber-entity. The body section of the Aphid cyber-entity contains the web pages that they disseminate. The behavior section of the Aphid cyber-entity contains behaviors that control the autonomous actions of the cyber-entity. They include but are not limited to:

• A service behavior that accepts HTTP requests for web pages and delivers them to the requester.
• A resource buying behavior that uses the cyber-entity’s energy units to buy resources, such as CPU time, memory space, and network bandwidth, from the Bio-Networking platform software.

• A migration behavior which causes migration towards users.
• A reproduction behavior which causes reproduction during periods of high user demand.
• A death behavior which causes the cyber-entity to die during periods of low user demand.

Cyber-entities execute on network nodes running the Bio-Networking platform software (see Figure 2) hereafter simply referred to as Bio-net nodes. Cyber-entities pay the resource cyber-entity energy units for the use of resources on the network node. Cyber-entities also pay energy units for migration and reproduction since these actions requires extra node resources. To receive a web page held by an Aphid cyber-entity, users must first locate a nearby cyber-entity containing the desired web page. When a user receives a web page from an Aphid cyber-entity, the user pays the cyber-entity with energy units.

The detailed simulation models and results are reported in the paper at http://netresearch.ics.uci.edu/bionet/publications/publications.html. The following summarizes the initial findings.

The simulation results are based on a simplified network topology of the existing Internet and the user workload that follows an estimated weekly usage patterns. Simulations were conducted to test the following capabilities of the Bio-Networking Architecture: adaptation to changing user demand, survivability, adaptation to the location of users in the network, scalability. In order to test the Bio-Networking Architecture’s ability to adapt to changing user demand, the number of users in the network was changed in the simulation. The simulation results showed that the number of cyber-entities adapted to the user demand and provided a small response time to user requests. In order to test the survivability of the Bio-Networking Architecture, some cyber-entities were killed in simulations, representing failure of the node that they resided on. The simulation results showed that the cyber-entities regained its original population size and provided service without interruption. To test the Bio-Networking Architecture’s ability to adapt to the location of users, various cyber-entities with different migration behaviors were simulated. The simulation results showed a reduction in the average number of network hops between users and their closest cyber-entities, showing that cyber-entities adapt to the user location. To test the scalability, the number of users was increased to 1500 in the simulation. The simulation results shows that the number of cyber-entities increased according to the increase in the user population and still provided service with small delays.

Due to limited space, we only presented a limited set of simulation results. However, we believe the simulation results show that the Bio-Networking Architecture is promising.

The PI has started investigating how the energy is securely communicated between cyber-entities. Since the energy level controls cyber-entity behaviors, it is critical to provide secure energy communication mechanisms.

The possible security attacks to the energy level communication include (1) malicious cyber-entities modifying their own energy levels, (2) malicious cyber-entities modifying the energy level of other cyber-entities on the same node, and (3) malicious platform software modifying the energy level of cyber-entities being supported on the platform software. The solutions that the PI is currently investigating include (1) use of a trusted node for energy level modifications, (2) use of secure platform software for energy level modifications, and (3) use of public key approaches to secure the energy level in cyber-entities.

We are at the early stages of the research, and various security techniques will be investigated in this project.

In order to gain support from the research community on the new Bio-Networking Architecture, the PI has taken the following steps.

• The PI has contacted one of the NTT research laboratories. It agreed to dedicate a small group of researchers (3 full time researchers) to investigate the Bio-Networking Architecture with the PI. The PI and the NTT lab are in the process of asking NTT Docomo, other NTT laboratories and a number of university professors (including those at Tokyo Univ. and Osaka Univ.) to join the team to investigate the Bio-Networking Architecture.
• The PI has contacted the super distributed system working group of OMG to seek for the possibility of using the Bio-Networking Architecture as one of its reference architectures.
• The PI is organizing a workshop on "scalable and evoluvable distributed systems" at the IEEE SAINT conference to be held in January, 2001. The workshop topic is closely related to the Bio-Networking Architecture, and the Bio-Networking Architecture is one of the topics to be discussed at this workshop.
• The PI has agreed to write an invited paper to one of the IEICEJ (Japanese equivalent to IEEE) transactions on the topic of the Bio-Networking Architecture.
• The PI has agreed to give a keynote speech for the IEICEJ (Japanese equivalent to IEEE) meeting in December, 2000, regarding the future direction of networking research, and one of the emphasis of the talk is the Bio-Networking Architecture.

As described in Research Accomplishment section, the PI has initiated feasibility study of the proposed Bio-Networking Architecture through simulation and design/implementation of an example application, Aphid. Initial results show that the proposed architecture exhibits such key features as adaptability, survivability and availability. The PI has also started investigating secure energy exchange mechanisms for the Bio-Networking Architecture. The proposed research will follow the following major phases described below.

Large-scale simulation of the Bio-Networking Architecture will be conducted. Various biological concepts and mechanisms will be simulated, and their benefits and overheads empirically evaluated. Major tasks in this phase include design and implementation of a simulation environment for the Bio-Networking Architecture, and empirical evaluation of the benefits and overheads of various biological mechanisms in the simulation environment.

Components of the Bio-Networking Architecture will be designed and implemented. The major tasks in this phase include design of both the Bio-Networking platform software and cyber-entities and development of prototype implementation of various components. The major tasks also include design of secure energy communication mechanisms. Through the prototype deployment, the Bio-Networking Architecture will be empirically evaluated.

When the prototype deployment successfully shows the advantages of the Bio-Networking Architecture, it will be widely deployed over the Internet. Major tasks in this phase include identifying academic and industrial partners, as well as gaining support from the standard community for the Bio-Networking Architecture.

As described earlier, the PI has taken steps to gain research community’s support for the Bio-Networking Architecture. NTT and a few companies have already expressed interests and are dedicating significant resources to support the Bio-Networking Architecture. In addition, the OMG, a major standard making body, is interested in the Bio-Networking Architecture as one of its reference models. These activities will make the technology transition smooth.