On the Evaluation of Caching in
Vehicular Information Systems
N. Loulloudes, G. Pallis, M. D. Dikaiakos
Department of Computer Science,
University of Cyprus
9th Hellenic Data Management Symposium
July 2nd 2010
Introduction

Traffic Accidents (EU only)




Search for free parking place (EU only)



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39.200 deaths
3.3 million casualties
€180 billion in material losses (2x the total EU budget for all activity)
44% of entire traffic is searching for a free parking place
€3.5 million for gasoline and diesel are spend annually
150.000 hours of waiting time annually
Vehicular Information Systems can:
1.
2.
Provide traffic conditions monitoring and hazard warnings
Discover the availability of road-side facilities (parking, gas stations)
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Vehicular Ad Hoc Networks (VANETs)
Cellular Networks
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Vehicular Ad-Hoc Networks
Sub-class of MANETs
Characteristics
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
Very high mobility
Frequent topology changes and network fragmentation
Ample power, process and storage capabilities
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Vehicular Information Systems (VIS)
Impose a high network overhead in order to obtain and maintain global or partial view
of the vehicular environment conditions
Saturation of limited network resources
Low response times, Low information quality
Robust mechanisms for efficient information dissemination
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Research Motivation

Key Question
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
“Does the co-existence of a pro-active, location-aware, communication
protocol and caching maintain acceptable levels of information quality while
sustaining network performance? “
Vehicular Information Transfer Protocol (VITP)
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

A pro-active, location-aware, application layer communication protocol for
Vehicular Computing
VITP specifies the syntax and semantics of messages exchanged between VITP
peers. [Dikaiakos et al. JSAC’07]
VITP Transaction Phases:
1. Dispatch-Query Phase
2. VAHS-Computation Phase
3. Dispatch-Reply Phase
4. Reply-Delivery Phase
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Dispatch-Query Phase
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Dispatch Query Phase Modification
When a peer receives a query checks to see if it can be served from the cache.
 If there is a CACHE HIT  update cached object’s “last_accessed” parameter 
Generate reply containing the cached data and send to source node.
 Else if there is a CACHE MISS  forward query towards destination.

Incoming Query
HIT
Lookup
MISS
Reply
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Cache
Forward Incoming Query
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VAHS Computation Phase
S
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Dispatch-Reply Phase
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Dispatch-Reply Phase Modification
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When a peer receives a reply checks whether the message is already cached locally.
If there is a CACHE HIT  Update cached object with the new one
Else if there is a CACHE MISS  Cache new message
Forward Reply to Source
Incoming Reply
Lookup
Cache
Forward Incoming Reply
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Reply-Delivery Phase
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Enabling Caching Support in VIT

VITP message syntax extended to support cache-based
location aware service - Introduce Cache – Control
Headers
Directive
Cacheable

Value
Boolean
Description
The reply can be cached
Expires
Time-stamp
The time after the reply is considered expired (if cached)
Private
Boolean
The cached reply can be reused only from the original peer that requested it
Public
Boolean
The cached reply can be reused by any peer
Validate-after
Seconds
A peer must validate the cached reply with the target area after “n” seconds since the
reply generation time
P-validate-after
Boolean
A peer must validate the cached reply with the neighbour peers after “n” seconds
since the reply generation time
P-validate
Boolean
A peer must validate the cached reply with the neighbour before servicing a request
Retransmit
Boolean
Serve incoming request first from cache and retransmit it to target area also
Headers act as directives to VITP peer caching decisions.
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Information Systems
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Problem Statement
Can the cached enabled-VITP maintain acceptable
levels of information quality while sustaining
network performance?
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Simulation Test bed Setup
Vehicular Mobility Generation
TrafficModeller
SUMO
• Simulated traffic in two real cities with different topological layouts
• 970 and 875 mobility traces respectively for the above cities were
generated using TrafficModeller and SUMO
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Simulation Test bed Setup
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Network Simulation Setup
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Performed using ns-2.33
Vehicles are equipped with IEEE 802.11 communication hardware
(200m coverage) and are VITP enabled
Simulation duration set to 1000s
200s warm up phase to allow caches to reach a level of stability
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Evaluation Scenarios and Query Generation
Scenario 1:
Vehicles are aware of
the road topology.
Use a “forward scan”
query system to
Objective:
identify road
Can cached-based VITP maintain an acceptable level of traffic
information
conditions
from
quality and minimize network overhead caused by trafficcurrent
queries
? to
position
destination
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Evaluation Scenarios and Query Generation
Scenario 2:
Same as before.
Unscheduled events
(i.e. accidents) take
place in the candidate
Objective:
road-paths
to
Can cache-based VITP accurately capture the traffic conditions
and the
destination
existence of un-scheduled events?
July 2ndJuly
HDMS,
2010
2nd 2010
N. Loulloudes
On-the
On Evaluation
the Evaluation
of Caching
of Caching
in Vehicular
in Vehicular
Information
Information
Systems
Systems
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Metrics

Query Recall: the number of replies received while issuing queries
towards a specific location of interest over the number of replies that
should have been received

Response Time: average Round Trip Time in seconds of a successful VITP
transaction

Information Accuracy: how close the received value describing some
information at a location of interest is to the actual value

Number of Exchanged Messages: total number of exchanged messages,
including geographic routing message and VITP query resolution
messages.
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Evaluation – Querying Road Traffic Conditions
Round-Trip
Time
• Longer TTL  better information diffusion  increased probability that information is found from vehicle’s cache.
• Due to geographic routing, queries traverse a greater number of hops to overcome break-downs and reach target
location.
• RTT improves up to 31% for Region 1 and up to 27% for Region 2.
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Evaluation – Querying Road Traffic Conditions
Query Recall
• As TTL increases  replicated information in the network increases  queries are served from
information in vehicle’s cache.
• Increased probability that otherwise unresolved queries will be resolved from vehicle’s cache.
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Evaluation – Querying Road Traffic Conditions
Information
Accuracy
• As TTL increases  queries resolved from cache  accuracy drops  Cached items do not reflect accurately road
conditions
• Accuracy is heavily influenced by un-scheduled events and road topology.
• Cache-enabled VITP can maintain high level of accuracy: up to 83% for Region 1 and up to 33% for Region 2
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Evaluation – Querying Road Traffic Conditions
Exchanged
Messages
• Cached-based VITP reduces network overhead
• Up to 21% for Region 1
• Up to 27% for Region 2
• Fewer exchanged messages  fewer network failures  increased network reliability
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Evaluation – Querying Road Traffic Conditions
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Evaluation Scenarios and Query Generation
Scenario 3:
Vehicles issue queries
to discover road-side
facilities (RSUs) such
as gas-stations.
Objective:
RSUs broadcast
Can cached-based VITP locate and aid in the dissemination of
information
information
at fixed
time intervals
broadcasted by RSUs?
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2010
2nd 2010
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On Evaluation
the Evaluation
of Caching
of Caching
in Vehicular
in Vehicular
Information
Information
Systems
Systems
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Evaluation – Querying Road-Side Facilities
Query Recall
• Lack of a diffusion mechanism  very low probability to retrieved information broadcasted by RSU (i.e.. T=0s)
• As TTL increases  query recall increases  caching can diffuse RSU information.
• Increases probability that RSU related queries will be resolved.
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Evaluation – Querying Road-Side Facilities
RSU
Information
Accuracy
• Even for low TTL (50s), query recall up to 52% is achieved with information accuracy up to 74%
• Increasing TTL  decreases RSU information accuracy
• While TTL = 200s gives recall up to 72% for Scenario 2, it only manages to reflect 53% of the information accuracy
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Conclusions

With cache-based VITP:

Acceptable levels of information quality are maintained

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Network overhead is reduced
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Accuracy up to 65%.
Under normal traffic conditions where vehicle mobility presents periodicity
In the presence of un-scheduled traffic events (no periodicity)
Dissemination of RSU information without any diffusion
mechanism is infeasible.
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Cache-based VITP allows the diffusion of such information
Even for low TTL, it achieved a query recall up to 52% with information
accuracy of up to 74%.
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The Dynamics of Vehicular Networks in Urban
Environments
G(t) = undirected graph of VANET at time t
V = {Ui) - vehicles.
E = {Eij} – communication links among vehicles
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Data – Knowledge Perspective
•
Which effects does mobility and road topology impose on
the VANET ?
•
How can these be exploited to improve inter-vehicle
communication?
•
Study the spatio-temporal evolution of the VANET
communication graph
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Engineering Perspective

Routing Protocol Design
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Geo-casting (location multi-casting)

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“Which are the highest-quality vehicles to carry out the forwarding
process?”
“Which are the bridge nodes so as to deliver messages when the
network is fragmented?”
“How can we spread the message with the minimal number of
rebroadcasts so as to reduce collisions and latency?”
Road-Side Unit Placement

“What is the distribution of the position of vehicles?”
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Graph Metrics Examined
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Network Oriented metrics
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Centrality Metrics
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Betweeness Centrality, Lobby Index
Clustering Metrics
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Degree, Diameter, Graph Density
Clusters, Clustering Co-efficient, Communities, Conductance
Link-Level Metrics
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Link Duration, Connected Periods, Re-Healing Periods
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Traffic Data Studied
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Real GPS traces [CabSpotting Project]
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Realistic Vehicular Traces
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Use of tools that generate realistic traces from highly accepted mobility
models [VanetMobiSim]
Mobility traces on different road topologies
Simulation of different wireless communication standards
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IEEE 802.11a (75m) - 802.11p (300m)
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Market Penetration (20% - 100%)
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Presence of RSUs
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Recorded and studied 742000 snapshots of the VANET graph
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General Observations
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The VANET communication graph exhibits small world
properties
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At 300m  average degree of separation: ~8 hops
At 300m transmission ranges, the VANET includes a giant
cluster occupying a large portion of the geographic space
Existence of communities – “Data islands”
At 75m transmission ranges 3 or more RSUs per Km2 are
required to maintain stable cluster connectivity
Road topology affects the existence of “central” nodes
Lobby index can identify “central” nodes
Large link durations (~34s at 75m - ~117s at 300m)
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Thank You !!!
37
N. Loulloudes - On the Evaluation of Caching
in Vehicular Information Systems
July 2nd 2010