PhD-TW-Colloquium, October 09, 2008Polling systems as performance models for mobile ad hoc networking Ahmad Al Hanbali, Richard Boucherie, Jan-Kees van

PhD-TW-Colloquium, October 09, 2008 Polling systems as performance models for mobile ad hoc networking

Polling systems as performance models for mobile ad hoc networkingAhmad Al Hanbali, Richard Boucherie, Jan-Kees van Ommeren and Roland de Haan


Mobile ad hoc networks (i)

• Static and mobile hosts (e.g., laptops, cellular phones, PDAs)

• Wireless communications

• No infrastructure, self-organizing


Application (i)• Wild-life monitoring

– Wild species equipped with radios form mobile ad-hoc network– Monitoring system for interactions of individuals and groups


Application (ii)

• Vehicular networks

– Vehicles and road signs/structures form mobile ad-hoc network

– E.g., distribution of traffic information, internet access in cars


Application (iii)• Disaster relief networks

– Existing communication means may fail– Rescue workers and equipment form an ad hoc network to

smoothen the rescue operation by allowing for voice/data-communication


Mobile ad hoc networks (ii)

• Main (functional) characteristics:

– Wireless communication(dynamic channel conditions, interference, collisions)

– Intermittent connectivity due to mobility(routing is an issue)

– Distributed network control(no central entity)


Research questions

• Transfer delays and buffer levels in such networks (QoS guarantees)

• (Optimal) routing protocols

• Network design (include extra stations?)


Related literature

• Experimental studies(mobility process)

• Simulations

• Analytical models(infinite populations, single packet)


Our contribution

• Practice:– Analytical modelling framework for mobile ad hoc

networks

• Theory:– Extension of the literature on polling systems


Research method

• Original situation:

• Modelling: create analytical queueing model containing key characteristic:

• Intermittent connectivity due to mobility


Queueing model

• Key ingredients:– (Random) Arrival process of customers– Service requirements– Single server

• Simplest model: M/M/1 queue

• Performance measures:– Queue length– Sojourn time


Intermittent connectivity

• Assumption:– mobile stations move in local neighborhood

• Modelling: – discrete set of locations for each station– stations remain a random time at a location

– given the specific locations of the stations, data transmissions may occur


Toy example - model

• Network: 1 fixed source S, and1 mobile destination D

Depending on the location of destination D, there exists either a link (state {0}) between S and D (i.e., S can transmit data to D) or no link (state {1})

S D?

0

1


Toy example - analysis• Let packets generated at S correspond to customer arrivals;• Let a link correspond to a server being available in a queueing model;

Link: No link:

=> Specific queueing model: Unreliable-server model [Gaver, 1962]

S D?


Towards more general networks:a polling system

• Single-server multi-queue model

• Key characteristics:– Multiple queues– Random arrival of customers– Service requirements– Server “visits” queues in some order– Service discipline

• Performance measures:– queue-length distribution and delay measures


Polling system - refined• Specific details to study MANETs:

– Autonomous service discipline

Random visit times of server (~ exponential time-limited discipline)

– Probabilistic routing of the server– Customer routing– Preemptive service

(acc. to preemptive-repeat-random policy)

S


Solution approach (i)• Construct relations for p.g.f.’s of queue-length distribution

at specific instants, viz.:– Server arrival instants to Qi and server departure instants from Qi:

– Server departure instants from Qi and server arrival instants to Qj

Qi Qj

ai bi

t

aj bj

Qi Qj

bi

t

aj bj ak


Solution approach (ii):

• System of equations (in terms of p.g.f.’s)

• Numerical iterative solution method:

• Joint queue-length distribution


Applications of polling systems (i)

• Queue-length and delay measures for, e.g.,:

– Multi-hop tandem networks,

– General single-channel networks (IEEE 802.11):

S R D? ?

S

T

V

?

?

U

?

??

?


Applications of polling systems (ii)

• Optimization:– Optimal delay via power control by adjusting visit time

parameter,

– Optimal delay via channel time assignment by adjusting visit time parameter

S

T

V

?

?

U

?

??

?

S R D? ?

?


Results

• Modelling framework for evaluation of emerging communication paradigms (Delay-Tolerant Networking, opportunistic networking)

• Exact analysis of polling systems operating under a novel service discipline


Concluding remarks

• Numerical solution approach creates need for (mean value) approximations

• Extend framework to:

– Multi-server polling models

– More general server visit times


Thanks for your attention

Documents

PhD-TW-Colloquium, October 09, 2008Polling systems as performance models for mobile ad hoc networking Ahmad Al Hanbali, Richard Boucherie, Jan-Kees van