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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
Outline
 Motivation and Related Works
 System Model and Reference Architecture
 MobiCS Overview
 Deterministic simulation
 Stochastic simulation
 Example
 Conclusions
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
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
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, requestreply, transaction)
design of network elements with arbitrary behaviors.
programming of appropriate simulation models,
specially mobility models.
Other Simulators 
Common Limitations
 Protocol developer has also to deal with lowlevel 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.
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
Reference Architecture for
Simulation 
Application
Distributed
Protocols
Network Elements
Simulation
Engine
 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.
MobiCS
Mobile Computing Simulator 
 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 stochastic
simulation mode (others may be added).
MobiCS:
Protocol Programming 
 Object-oriented protocol design
 Protocols are composed of micro-protocols, which
interact through events (mainly, messages and timers)
 Main Protocol Components:
Protocol
Wired
Wireless
Handoff
 Micro-protocols are Java interfaces whose methods are
handlers for the events.
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).
MobiCS:
Deterministic Simulation 
 Example:
Mh1.moveTo(cell1);
Mh1.send(new Req);
Mss3.accept(Req);
end_step();
// Mh1 at cell of Mss3
Mh2.unavailable();
 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
MobiCS:
Deterministic Simulation 
C
 Script
server
res
Home agent
(ha)
MSSo
mh
MSSn
req
req
{ha,MSSo,MSSn}.acceptOn()
mh.send(new Req());
mh.moveTo(MSSn);
end_step();
Independent // cut C
server.accept(Req);
res
events
mh.accept(Res);
res
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.
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.
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
Example
RDP 
server
Res
Req
proxy
Ack
Proxy created
MSSp
Mh
Req
ForwardRes
DeReg PList
UpCurLoc
MSSo
ForwardRes
?
Greet
Ack
UpCurLoc
Hand-off
DeReg
PList
Ack
MSSn
Greet
FRes
RDP Structuring:
Protocol Interactions 
Mh
• Protocol structured as 3 micro-protocols
wired, wireless e handoff
ForwardRes
Mss
Req,Ack
Mss
wireless
wired
handoff
wireless
ForwardRes
wireless
RemPList
PList
UpdCurrLoc
DeReg
wired
handoff
RDP Structuring:
Protocols 
 Since there are 3 types of network elements, Server, Mh
and Mss ...
 we need to declare following Protocol interfaces:
RDPHandOffModule
RDPMssWired
RDPMssWireless
RDPMhWireless
RDPServerWired
 Define 3 protocol instances (subclasses of Protocol):
RDPServer, RDPMh, RDPMss, that implement the
corresponding Protocols
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());
Example: Choosing a
Deterministic Scenario 
 Goal: Test protocol when ForwardRes arrives at
a MSS while a Mh is migrating to another cell
server
Res
MSSo receives ForwardRes before
proxy
Req
Proxy
created
handoff
of Mh
MSSp
Mh
MSSo
Ack
is completed
Req
ForwardRes
DeRegPList
UpCurLoc
?
Greet
ForwardRes
UpCurLoc
DeReg PList
MSSn
Ack
Greet
FRes
Ack
Example:
Scripting the Scenario 
server
Req
proxy
Res
Proxy created
MSSp
Mh
MSSo
Req
DeRegPList
UpCurLoc
Greet
Server.acceptTurnOn(false);
MSSn.acceptTurnOn(false);
Mh.send(new Req());
Mh.moveTo(MSSo);
end_step();
Ack
Mh.moveTo(MSSn);
end_step();
Server.acceptTurnOn(true);
ForwardRes
end_step();
MSSn.acceptTurnOn(true);
ForwardRes
?
Ack
UpCurLoc
DeReg PList
MSSn
Ack
Greet
FRes
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)
Stochastic Simulation:
Some Results 
ForwardResult /
Requests
 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
2
1.5
1
0.5
0
0
0.2
0.4
0.6
0.8
1
Migration Factor
 Other tests: size of proxyList with growing Request/Migration Ratio
 Conclusion: RDP´s message overhead grows quickly with increasing
migration and request rates.
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.
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]
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, logbased animation, protocol debugging
 MobiCS is freely available
URL http://www.ime.usp.br/~rcarocha/mobics