MobiCS: An Environment for Prototyping and Simulating Distributed Protocols for Mobile Networks

1. MobiCS: An Environment for Prototyping and Simulating Distributed Protocols for Mobile Networks Ricardo C.A. da Rocha (IME/USP) rcarocha@ime.usp.br Markus Endler (PUC-Rio) endler@inf.puc-rio.br

2. Outline • Motivation and Related Works • System Model and Reference Architecture • MobiCS Overview • Deterministic simulation • Stochastic simulation • Example • Conclusions

3. Motivation  • Characteristics of Mobile Computing Environments • Dynamic Network Topology • Energy is scarce resource  Mobile Host may enter doze mode or be turned off • Wireless communication • unreliable connectivity (e.g. intermittent periods of disconnection) • QoS parameters change very fast • lower throughput

4. Motivation  • Distributed Protocols for Mobile Computing should... • handle variable number of interacting nodes • make efficient use of wireless communication • consider non-availability  failure • maintain consistent distributed state despite disconnections • be correct and efficient for any number of hosts (scalability) and mobility pattern (mobility robustness) Fact: Evaluating the protocol´s correctness and efficiency are difficult tasks

5. Motivation • Our goal: • Build a tool for rapid prototyping and evaluation of distributed protocols (e.g. multicast, reliable message delivery, notification protocols) • Approach: Protocol evaluation (correctness & efficiency) through simulation. • The tool should support: • definition of appropriate abstractions for programming the protocol (e.g. message, request-reply, transaction) • design of network elements with arbitrarybehaviors. • programming of appropriate simulation models, specially mobility models.

6. Other Simulators  Common Limitations • Protocol developer has also to deal with low-level details. • Form of simulation (e.g. parallel) is not fully transparent. • Limited extensibility. • Lack of integrated support for protocol validation and testing. • Limited programmabilty of mobility models.

7. System Model for Protocols in Mobile Computing • We assume a structured mobile network composed of Mobile Hosts (MHs), Mobility Support Stations (MSSs) • We adopt the Indirect Model [Badrinath94], where all communications are split into a wired and a wireless part • Basic unit of interaction in a protocol message • If mobile host is reachable, wireless message is delivered. But MH may be disconnected or migrating. • QoS of the wireless connection is modeled as its effective transmission rate. • Hand-Off is initiated by the MH • At any time, every MH is associated with exactly one MSS

8. Reference Architecture for Simulation • Application makes service requests (user or automatically generated) • Distributed Protocols are programmed and tested • Network Elements implement HW and basic SW functionality (OS, low-level Netw. Protocols) • Simulation Engine: • schedules event processing order • may implement several simulation modes. Application Distributed Protocols Network Elements Simulation Engine

9. MobiCSMobileComputingSimulator • MobiCS is a java class library implementing the Reference Architecture • Main Advantages: • Single tool for prototyping, validating and analysing distributed protocols. • A generic Simulation Engine API offers complete transparency of simulation modes. • Programmable and customizable simulation models (e.g. mobility, connectivity, etc.) • Supports the creation of abstractions for protocol implementation. • Comes with a deterministic and a stochasticsimulation mode (others may be added).

10. Protocol Wired Wireless Handoff MobiCS:Protocol Programming  • Object-oriented protocol design • Protocols are composed of micro-protocols, which interact through events (mainly, messages and timers) • Main Protocol Components: • Micro-protocols are Java interfaces whose methods are handlers for the events.

11. MobiCS:Deterministic Simulation  • Used for debugging/testing the correctness of the protocol. • A user creates a simulation script, which is executed by the simulator. • This script describes a specific scenario (i.e. pattern of protocol-external events) • Events may be application requests, MH migrations, MH disconnections, etc. • Global synchronization points end_step()in the script define the causal order relationship among the events. • Message acceptance can be toggled on/off to simulate message transmission delays: Accept(msgType) and AcceptTurnOn(bool).

12. MobiCS:Deterministic Simulation  • Example: • The simulation executes in steps (i.e. there is no notion of simulated time) • Scripts should reflect critical situations in which the protocol behaviour is to be tested. • Since only a minimal fraction of all possible situations can be described, this method gives no guarantee of the protocol´s correctness  testing Mh1.moveTo(cell1); // Mh1 at cell of Mss3Mh1.send(new Req);Mss3.accept(Req);end_step(); Mh2.unavailable();

13. C Independent events MobiCS:Deterministic Simulation  • Script {ha,MSSo,MSSn}.acceptOn() mh.send(new Req()); mh.moveTo(MSSn); end_step(); // cut C server.accept(Req); mh.accept(Res); server res Home agent (ha) req res MSSo req mh res MSSn

14. MobiCS:Deterministic Simulation  • Output • Programmer may add printout of messages in specific event handlers • User-configurable Event Log generated by MobiCS´ simulation engine. • Exceptions raised during execution of either the script or the protocol code.

15. MobiCS:Stochastic Simulation  • Allows “performance analysis” of a protocol (i.e. message complexity) • Conists of a continuous test with randomly generated events. • User creates a simulation model: Defines the behavior of all network elements concerning mobility and connectivity. • Simulation Model can be: • programmed (extending classes) or • configured (instantiation of pre-defined objects). • A simulationObject (for each network element) determines whether an event of certain type will be generated at each simulated time unit.

16. Using MobiCS • Protocol Implementation  extend basic classes Protocol and Message • Implement the Network Elements and configure the network to be simulated  extend basic classes Mss, Mh, ... • Build the simulation scenarios: • Choose the deterministic scenarios  program deterministic script  run simulation  compare expected and real result • Choose stochastic simulation model  create corresponding simulation objects  run simulations  analyse event log

17. server Res Req Ack proxy Proxy created MSSp Req Mh ForwardRes PList DeReg UpCurLoc ForwardRes ? Ack Greet MSSo UpCurLoc Hand-off PList DeReg Ack Greet MSSn FRes ExampleRDP 

18. Mss Mss wireless wireless wired wired Mh wireless handoff handoff RDP Structuring: Protocol Interactions  • Protocol structured as 3 micro-protocols • wired, wireless e handoff Req,Ack ForwardRes ForwardRes Ack RemPList ForwardRes PList UpdCurrLoc DeReg

19. RDP Structuring:Protocols  • Since there are 3 types of network elements, Server, Mh and Mss ... • we need to declare following Protocol interfaces: • Define 3 protocol instances (subclasses of Protocol): RDPServer, RDPMh, RDPMss,that implement the corresponding Protocols RDPHandOffModule RDPMssWired RDPMssWireless RDPMhWireless RDPServerWired

20. Example:Network Configuration  mh = new MyMh(“Mh 1",sim); cell1 = new Cell(); cell2 = new Cell(); cell3 = new Cell(); mss1 = new MyMss(“Mss 1",sim,cell1); mss2 = new MyMss(“Mss 2",sim,cell2); mss3 = new MyMss("Mss 3",sim,cell3); wr = new WiredLink(mss2.getAddress(), mss1.getAddress()); wr2 = new WiredLink(mss1.getAddress(), mss3.getAddress());

21. Res Req Ack Proxy created Req MSSo receives ForwardRes before handoff of Mh is completed ForwardRes PList DeReg UpCurLoc ForwardRes ? Ack Greet UpCurLoc PList DeReg Ack Greet FRes Example: Choosing a Deterministic Scenario  • Goal: Test protocol when ForwardRes arrives at a MSS while a Mh is migrating to another cell server proxy MSSp Mh MSSo MSSn

22. Res Req Ack server Proxy created proxy Req ForwardRes PList DeReg MSSp UpCurLoc ForwardRes Mh ? Ack Greet UpCurLoc MSSo PList DeReg Ack Greet FRes MSSn Example: Scripting the Scenario  Server.acceptTurnOn(false); MSSn.acceptTurnOn(false); Mh.send(new Req()); Mh.moveTo(MSSo); end_step(); Mh.moveTo(MSSn); end_step(); Server.acceptTurnOn(true); end_step(); MSSn.acceptTurnOn(true);

23. Example:Stochastic Simulation  • Example of a Simulation Model • MH Activity and Cell Attraction • Activity: probability that a MH is active (reachable) • Cell Atraction: probability that a migrating MH chooses the cell as its target cell Mobilidade • Migration Willingness: probability that a MH moves to another cell • Network Topology: neighbourhood relation among cells • Wireless QoS: Effective wireless transmission rate • Application requests: probability that a service is requested from the protocol (e.g. RDP request)

24. Stochastic Simulation: Some Results  • We measured how the number of re-transmissions (ForwardResult) per Requests is affected by the Mobility Factor • Mobility factor = probability that a migration event is generated every n simulated time units • Other tests: size of proxyList with growing Request/Migration Ratio • Conclusion: RDP´s message overhead grows quickly with increasing migration and request rates.

25. Conclusions • MobiCS Flexible simulation environment that integrates protocol testing (correctness) and performance analysis • Supports modular and extensible prototyping of distributed protocols  OO and micro-protocols • Provides deterministic and stochastic simulation modes, and allows for other modes (e.g. parallel) to be programmed. • Protocol implementation is totally independent of the chosen simulation mode.

26. Conclusions • Main Contributions: • Implementation of a tool for prototyping and analysis of distributed protocols  MobiCS • Proof of concept of: • Reference Architecture for flexible and extensible simulators for Mobile Computing. • Framework for the implementation of MC simulation models and integration in a simulator • Usability • MobiCS has been used in a graduate courses at IME/USP to implement a multicast protocol MCAST [Acharya93]

27. Conclusions  • Future Works: • Define “Network Emulation API”  MobiCS as a testbed for MC applications • Build library of mobility and wireless QoS models. • Implement parallel simulation mode. • Create Graphic User Interfaces  script creation, log-based animation, protocol debugging • MobiCS is freely available URL http://www.ime.usp.br/~rcarocha/mobics