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Jun Suzuki and Tatsuya Suda

Bionet Project Overview: Applying Biological Concepts and Mechanisms for Designing Adaptable, Scalable and Survivable Communication Software. Jun Suzuki and Tatsuya Suda jsuzuki@ics.uci.edu Dept. of Information and Computer Science, University of California, Irvine. Agenda.

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Jun Suzuki and Tatsuya Suda

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  1. Bionet Project Overview:Applying Biological Concepts and Mechanisms for Designing Adaptable, Scalable and Survivable Communication Software Jun Suzuki and Tatsuya Suda jsuzuki@ics.uci.edu Dept. of Information and Computer Science,University of California, Irvine JWAITS 2001 @La Jolla, CA

  2. 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 Architecture Design • Current Project Status and Future Work • Conclusion JWAITS 2001 @La Jolla, CA

  3. Motivation: Bionet Project • 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 • They have to be able to scale to billions of nodes and users. • Adaptability • They have to be able to adapt to diverse and dynamic conditions in the network. JWAITS 2001 @La Jolla, CA

  4. Availability and Survivability • They have to be secure and highly available. • Autonomy • They have to require minimal human configuration and management. • Networks need to have built-in mechanisms to provide these features JWAITS 2001 @La Jolla, CA

  5. Bionet: Applying Biological Concepts and Mechanisms • Observation: large scale biological systems scale, adapt, and survive • e.g. bee colony • Bionet: applying biological concepts/mechanisms to network services and applications • A bee colony can scale to a large number of bees because all activities of the colony are carried out without centralized control. • decentralization JWAITS 2001 @La Jolla, CA

  6. Bees act autonomously, influenced by local conditions and local interactions with other bees. • The bee colony also adapts to dynamic conditions, often to optimize its food gain relative to energy expenditure. • The bee colony is survivable because it is not dependent on any single bee • Scalability, adaptability and survivability are not present in any single bee. Rather, they emerge from the collective actions and interactions of all the bees in the colony. JWAITS 2001 @La Jolla, CA

  7. Complex Adaptive System a super entity with emergent characteristics emergencethrough self-organization Feedback andreinforcementlearning individual entities (agents) JWAITS 2001 @La Jolla, CA

  8. 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 Architecture Design • Current Project Status and Future Work • Conclusion JWAITS 2001 @La Jolla, CA

  9. Emergent Behavior • Biological systems • consist of many autonomous entities • useful group behavior emerges from autonomous local interaction of individuals with simple behaviors JWAITS 2001 @La Jolla, CA

  10. Bio-Network • application constructed from a collection of cyber-entities (objects/agents) • cyber-entities have biological behaviors • e.g. migration, reproduction, death, energy exchange • each cyber-entity has basic functionality related to its application and service JWAITS 2001 @La Jolla, CA

  11. Food and Energy • Biological systems • biological entities naturally strive to gain energy by seeking and consuming food JWAITS 2001 @La Jolla, CA

  12. Bio-Network • 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 control mechanism (natural selection mechanism) • abundance induces replication or reproduction • scarcity induces death JWAITS 2001 @La Jolla, CA

  13. Evolution and Adaptation • Biological systems • the biological system specializes and optimizes itself for environmental changes. • key enablers: • diversity from mutations and crossovers during replication/reproduction • natural selection keeps entities with beneficial features alive and increase reproduction probability JWAITS 2001 @La Jolla, CA

  14. Bio-Network • 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 JWAITS 2001 @La Jolla, CA

  15. 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 Architecture Design • Current Project Status and Future Work • Conclusion JWAITS 2001 @La Jolla, CA

  16. Bionet Platform Architecture CE CE CE CE CE Context Bionet Services Bionet Container Bionet Platform Java VM JWAITS 2001 @La Jolla, CA

  17. Bionet Platform Components • Bionet Platform • is developed by Java and runs on a Java virtual machine. • Major components: • Cyber entity • runs and moves autonomously • Provides a simple service • is the smallest component in Bionet environment. • Cyber entity context • Bionet Services • Bionet Container JWAITS 2001 @La Jolla, CA

  18. A CE has a single method “service”, which accepts a message written in an Agent Communication Language (ACL). Each CE has an ACL interpretation engine. Ineter-CE Communication CE CE service(<ACL msg>) <request> <name>reserve</name> <arg>01</arg>… </request> JWAITS 2001 @La Jolla, CA

  19. The class CyberEntity extends CyberEntity HotelReservationAgent private float energy private int age private String name… private float rate private Vector reservations Body’s non-executable data attribute reserve()checkAvailability() cancelRerservation() Body’s executable code migrate() replicate() reproduce() … init(Object[]): void run(): void getCEContext(): AgentContextsetCEContext(CEContext): voidlog(): void …onCreated(): void onMove(): void onArrival(): void onActivated(): void onDeactivated(): void onDestroy(): void Behavior Auxiliary methods Callback operations JWAITS 2001 @La Jolla, CA

  20. Cyber Entity Context • CE Context • is an entry point for CE to access Bionet Services. • is created and associated with each CE implicitly by Bionet Lifecycle Service, when a CE is created, replicated, reproduced, or migrated from another host. • is called by only its associated cyber entity. CyberEntity CEContext 1 1 getCEContext(): CEContextsetCEContext(CEContext): void … find(String): ObjectgetBionetContainer(String): BionetContainergetReference(): CERreference JWAITS 2001 @La Jolla, CA

  21. Bionet Services Bionet Services Energy Management RelationshipManagement Cyber EntityMigration Pheromone Emission Social Networking ResourceAllocation CE Directory ResourceSensing Security Cyber-Entity Lifecycle Cyber-Entity Comm. JWAITS 2001 @La Jolla, CA

  22. Process 1 Process 2 Bionet Container Bionet Container Bionet Container • Bionet Container • is a sandbox in which CEs and Bionet Services run. • runs on per-process basis. • One or more Bionet containers can run on a single host. a host JWAITS 2001 @La Jolla, CA

  23. CE Bionet Services Bionet Services Bionet Services CE Bionet Container memory threads connection • Bionet Platform provides the bottom most operations to maintain Bionet Platform. • CE registration/unregistration • CE activation/deactivation • resource management • CE reference management • request/event parsing available resources JWAITS 2001 @La Jolla, CA

  24. 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 Architecture Design • Current Project Status and Future Work • Conclusion JWAITS 2001 @La Jolla, CA

  25. Current Project Status • Bionet Simulator • Adaptation/evolution simulation done. • See a technical paper for details: netresearch.ics.uci.edu/bionet/ • Results show Bio-Networking Architecture works well. • Bionet Platform is design/early implementation stages. • on top of CORBA and Enterprise Java Beans (EJB) JWAITS 2001 @La Jolla, CA

  26. 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. JWAITS 2001 @La Jolla, CA

  27. 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 JWAITS 2001 @La Jolla, CA

  28. 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. JWAITS 2001 @La Jolla, CA

  29. 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 JWAITS 2001 @La Jolla, CA

  30. 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/ • Bionet Platform will be available in the middle of this year. JWAITS 2001 @La Jolla, CA

  31. This work has been supported by the National Science Foundation through grants ANI-0083074 and ANI-9903427, DARPA through Grant MDA972-99-1-0007, AFOSR through Grant MURI F49620-00-1-0330, grants from the University of California MICRO Program, Hitachi, Hitachi America, Standard Microsystems Corporation, Canon, Canon USA, Novell, Tokyo Electric Power Company, Nippon Telegraph and Telephone Corporation (NTT), NTT Docomo, Fujitsu, Nippon Steel Information and Communication Systems Incorporated (ENICOM), Matsushita Electric Industrial company. Acknowledgements JWAITS 2001 @La Jolla, CA

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