Jun Suzuki and Tatsuya Suda

1. Bio-Networking Architecture:An Approach to Leverage Super DistributedObject Environment using Biological Concepts and Mechanism Jun Suzuki and Tatsuya Suda jsuzuki@ics.uci.edu Dept. of Information and Computer Science,University of California, Irvine OMG TC meeting at Irvine Feb. 2001

2. Agenda • Motivation to the Bio-Networking Architecture • Bio-Networking Platform Design • Current Project Status and Future Work • Conclusion OMG TC meeting at Irvine Feb. 2001

3. Motivation: Bio-Networking Architecture • The explosive growth of the net places larger and more challenging demands on underlying communication software. • Future network services and applications have to satisfy: • Scalability • Adaptability • Availability and Survivability • Autonomy, with minimum human configuration • Networks need to have built-in mechanisms to provide these features • large nets: beyond one’s capability to design OMG TC meeting at Irvine Feb. 2001

4. Observation • Observation: • large scale biological systems scale, adapt, and survive • e.g. bee colony OMG TC meeting at Irvine Feb. 2001

5. Our Approach • Our approach: Bio-Networking Architecture • apply biological concepts/mechanisms to future network services and applications • emergent behavior out of simple behaviors • life cycle • energy gain/consumption/exchange replication (with mutation), reproduction (with cross over) • adaptation and evolution through species diversity and natural selection • decentralized discovery through social networking and pheromone emission. OMG TC meeting at Irvine Feb. 2001

6. Emergent Behavior • Biological systems • consist of many autonomous entities • Useful group behavior emerges from autonomous local interaction of individuals with simple behaviors. OMG TC meeting at Irvine Feb. 2001

7. Bio-Networking Architecture • individuals = cyber-entities (objects/agents) • abstractions of various system components (users, resources and service components) • An application is constructed from a collection of cyber-entities. • Cyber-entities • is autonomous with simple biological behaviors • e.g. migration, replication, reproduction, death, energy exchange, relationship establishment, pheromone emission • makes its own decision according to its own behavioral policy. OMG TC meeting at Irvine Feb. 2001

8. Cyber-entity Example Behaviors • Energy exchange • biological entities naturally strive to gain energy by seeking and consuming food • cyber-entity stores/expends energy (food/money) • Energy is the unit of exchange for service or resource usages. • energy exchange • CE gains energy from a user/another CE in exchange for performing a service • CE expend energy to use network/computing resources • energy used as a natural selection mechanism • abundance induces replication or reproduction • scarcity induces death OMG TC meeting at Irvine Feb. 2001

9. Cyber-entity Example Behaviors (cont’d) • relationship establishment • a cyber-entity knows something (e.g., name, address, service type) about another cyber-entity • relationship can be used to group cyber-entities collectively providing a service • application constructed from a collection of cyber-entities • e.g., a web server (application) from a collection of web pages (cyber-entities OMG TC meeting at Irvine Feb. 2001

10. Evolution and Adaptation • Biological systems • the biological system adjusts itself for environmental changes of long-term and short-term. • key enablers: • species diversity from mutations and crossovers during replication/reproduction • natural selection keeps entities with beneficial features alive and increase reproduction probability OMG TC meeting at Irvine Feb. 2001

11. Bio-Networking Architecture • cyber-entities (CEs) evolve, adapt, and localize through diversity and natural selection • diversity • A CE behavior can be implemented by a number of algorithms/policies • human designers can introduce diversity in CEs • CEs replicate/reproduce with mutation/crossover • natural selection • death from energy starvation • replication/reproduction from energy abundance OMG TC meeting at Irvine Feb. 2001

12. Research Vision • No central or coordinating entity exists. • Autonomous decentralized system in mind • A large number of CEs created by billions of Internet users, autonomously behaving • CEs contacting other CEs providing related services, making relationship, • diverse behavior policies getting created, good behaviors survive, bad ones die, making system flexible, adaptable and evolvable OMG TC meeting at Irvine Feb. 2001

13. Agenda • Bio-Networking Architecture Overview • Motivation to Bionet Project • Observations of large scale biological systems that scale, adapt, and survive in dynamic environment • How bio concepts are used in the Bionet project • Bio-Networking Platform Design • Current Project Status and Future Work • Conclusion OMG TC meeting at Irvine Feb. 2001

14. Bio-Networking Platform(Bionet Platform) CE CE CE CE CE Context Bionet Services Bionet Container Bionet Platform Java VM OMG TC meeting at Irvine Feb. 2001

15. Bio-NetworkingArchitecture Components • Bio-Networking Architecture consists of • Cyber entity • Cyber entity context • Bionet platform OMG TC meeting at Irvine Feb. 2001

16. Cyber-entity • A cyber entity (CE) • is the smallest component to create an application (network service). • provides a simple service, replicates, reproduces, moves and dies autonomously. • communicates with each other using FIPA ACL. • in both synchronous and asynchronous manner • is a CORBA object with mobility. • IIOP is a message transport for ACL. OMG TC meeting at Irvine Feb. 2001

17. Cyber-entity Context • CE Context • is used to find available Bionet services. • is created and associated with each CE implicitly by Bionet platform (Bionet Lifecycle service), when a CE is created, replicated, reproduced, or migrated from another host. OMG TC meeting at Irvine Feb. 2001

18. Bionet Platform • Bionet Platform • runs on a Java virtual machine. • Bionet Platform consists of 2 components: • Bionet Services • provides a set of general-purpose runtime services that are frequently used for deploying and running CEs. • Bionet Container • provides the bottom most operations to maintain Bionet platform. OMG TC meeting at Irvine Feb. 2001

19. Bionet Services Bionet Services Energy Management RelationshipManagement Cyber EntityMigration Pheromone Emission Social Networking ResourceAllocation Directory ResourceSensing Security Lifecycle Communication OMG TC meeting at Irvine Feb. 2001

20. Bionet Life Cycle Service • Life Cycle service • manages life cycle of cyber-entities. • provides the operations of • initialization • activation • deactivation • destroy • replication • Mutation might occur • reproduction • with crossover OMG TC meeting at Irvine Feb. 2001

21. Bionet Energy Mgt. Service • Energy is a unit of exchange for a service provided by another CE and for the resources the CE uses. • Bionet Energy Management service • manages the energy level of CEs. • checks if a CE has enough energy when it migrates, replicates and reproduces. OMG TC meeting at Irvine Feb. 2001

22. Bionet Resource Sensing Service • Resource Sensing Service senses • Types, amount and costs of resources available on a local Bionet platform • neighboring Bionet platforms reachable with n hops • Types, amounts and costs of resources available on neighboring platforms • Supported types of resource • Physical resources: CPU time and memory space • Logical resources: threads and transport connections OMG TC meeting at Irvine Feb. 2001

23. Bionet Resource Allocation Service • Resource allocation service allocates physical/logical resources to a CE. • It requires a CE to pay energy for allocated resources. OMG TC meeting at Irvine Feb. 2001

24. Bionet Relationship Mgt. Service • Relationship is used to • Find other cyber-entities. • Bionet platform does not assume any centralized directory that knows all the CEs. • Group cyber-entities collectively providing a service. • An application is constructed from a collection of CEs. • Every CE finds others via its relationships. • Each cyber-entity has zero or more relationships. OMG TC meeting at Irvine Feb. 2001

25. Relationship Management service • establishes, inspects, update, and destroys relationships between CEs. • Updates relationship strength. customer Hotel reservation CE A CE arranging a travel plan CE CE consumer maven service provider partner service provider CE Flight reservation CE CE CE acquaintance A CE arranging a travel plan partner Hotel room whole seller CE OMG TC meeting at Irvine Feb. 2001

26. The relationship strength is not fixed but changed dynamically. • The decreases by a certain amount in every certain period. • When the strength of a relationship becomes 0, Relationship Management service destroys the relationship. • Relationship Management service provides the policies on how strength is increased. • how many messages are exchanged between two CEs • how much data is transferred between two CEs • how much energy gets exchanged • CE selects which policy to use. OMG TC meeting at Irvine Feb. 2001

27. Bionet Social Networking Service • Human society: “six degrees of separation” concept • network of family and friend relationships results in any two humans being separated by at most six relationships • A asks his friends to find B; friends of A ask their friends to find B; etc. OMG TC meeting at Irvine Feb. 2001

28. Social Networking service allows cyber-entities to discover another cyber-entity on remote platform. • Discovery is through relationships between cyber-entities. OMG TC meeting at Irvine Feb. 2001

29. Bionet Container • Bionet Container • provides the bottom most operations to maintain Bionet Platform. • CE registration/unregistration • CE activation/deactivation • resource management • CE reference management • request/event parsing OMG TC meeting at Irvine Feb. 2001

30. Agenda • Motivation to Bio-Networking Architecture • Bio-Networking Platform Design • Current Project Status and Future Work • Conclusion OMG TC meeting at Irvine Feb. 2001

31. Current Project Status • Development of Bionet Simulator • Simulation study of adaptation to changes of network environment • Simulation study of evolution of cyber-entities • Development of Bionet platform OMG TC meeting at Irvine Feb. 2001

32. An Ongoing project:Self-Organizing Agents • It has been one of the biggest problem in traditional distributed object computing environments to decide and optimize object locations. • Static and manual configuration in the environment without object mobility • e.g. Many objects on a powerful machine • Frequently interacting objects on the same host/process • Tedious and time-consuming • The system/object should be stopped; availability decreased. • The decision is ad-hoc or static even in mobile agent environments. • e.g. Developers define an agent itinerary that describes when and where to move at development time. OMG TC meeting at Irvine Feb. 2001

33. We need more dynamic and autonomous mechanism of deciding agent location. • Bionet facilitates this by using self-organizing cyber entities • A CE organization is emerged from autonomous local interactions. • Energy exchange between CEs • Energy exchange between an CE and its platform OMG TC meeting at Irvine Feb. 2001

34. Agent-agent/agent-platform interactions • Energy in Bionet • Unit of exchange for service or resource usages • Agent-agent interaction • Each agent gains energy from another agent (or user) in exchange for performing a service. • abundance induces replication or reproduction • scarcity induces death • Agent-platform interaction • Each agent expends energy to use network/computing resources. • e.g. thread, transport connection, memory space and CPU cycle • Agent platform knows the types, amount and cost of available resources. OMG TC meeting at Irvine Feb. 2001

35. An Example Scenario • Each agent asks its underlying platform to assign a thread, and pays its energy. • The unit cost of a thread utilization may vary with the number of available threads. • More idle threads exist in a pool, cheaper the unit cost is. • Each agent behaves autonomously with its policies. • e.g. An agent migrates to another host when migration cost is cheaper than thread utilization cost. • e.g. An agent deactivates itself when its thread utilization cost is too expensive to pay. • The concept of energy allows agents to consume available resources in a distributed environment effectively. CE (2) assigns an idle thread(3) requires the cost (1) registers agent registration table Thread pool Bionet Container OMG TC meeting at Irvine Feb. 2001

36. Wrap up • Bionet provides a new paradigm to build network services and applications. • Inspired by biology • Bionet Platform is in design/early implementation stages • Most of the elements are in place • Several simulation results have supported our direction. • Bionet Simulator is available at • http://netresearch.ics.uci.edu/bionet/ OMG TC meeting at Irvine Feb. 2001