On the Evaluation of Caching in Vehicular Information Systems

On the Evaluation of Caching in Vehicular Information Systems

N. Loulloudes, G. Pallis, M. D. DikaiakosDepartment of Computer Science,

University of Cyprus

July 2nd 20109th Hellenic Data Management Symposium

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Introduction

July 2nd 2010 N. Loulloudes - On the Evaluation of Caching in Vehicular Information Systems

Traffic Accidents (EU only) 39.200 deaths 3.3 million casualties €180 billion in material losses (2x the total EU budget for all activity)

Search for free parking place (EU only) 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. Provide traffic conditions monitoring and hazard warnings2. Discover the availability of road-side facilities (parking, gas stations)

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Cellular Networks

Vehicular Ad Hoc Networks (VANETs)

Sub-class of MANETs Characteristics

Very high mobility Frequent topology changes and network fragmentation Ample power, process and storage capabilities


Vehicular Ad-Hoc Networks

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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

“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) 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 Phase3. Dispatch-Reply Phase4. Reply-Delivery Phase


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Dispatch-Query Phase


7July 2nd 2010 N. Loulloudes - On the Evaluation of Caching in Vehicular Information Systems

Dispatch Query Phase ModificationWhen 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

Reply Forward Incoming Query

HIT

MISS

Lookup

Cache

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VAHS Computation Phase


S

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Dispatch-Reply Phase


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Dispatch-Reply Phase Modification


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 oneElse if there is a CACHE MISS Cache new messageForward Reply to Source

Incoming Reply

Forward Incoming Reply

Lookup

Cache

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Reply-Delivery Phase


Enabling Caching Support in VIT VITP message syntax extended to support cache-based location aware

service - Introduce Cache – Control Headers

Headers act as directives to VITP peer caching decisions.

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Directive Value Description

Cacheable Boolean 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

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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


• 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

TrafficModeller SUMO

Vehicular Mobility Generation

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Simulation Test bed Setup Network Simulation Setup

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 identify road conditions from current position to destination

Objective: Can cached-based VITP maintain an acceptable level of traffic information

quality and minimize network overhead caused by traffic queries ?



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Scenario 2:Same as before.

Unscheduled events (i.e. accidents) take place in the candidate road-paths to destination

Objective: Can cache-based VITP accurately capture the traffic conditions and the

existence of un-scheduled events?

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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


• 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.

Round-TripTime

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• 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.

Query Recall

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• 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

Information Accuracy

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• 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

ExchangedMessages

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Scenario 3:Vehicles issue queries to discover road-side facilities (RSUs) such as gas-stations.

RSUs broadcast information at fixed time intervals

Objective: Can cached-based VITP locate and aid in the dissemination of information

broadcasted by RSUs?

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Evaluation – Querying Road-Side Facilities


• 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.

Query Recall

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Evaluation – Querying Road-Side Facilities


• 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

RSUInformationAccuracy

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Conclusions With cache-based VITP:

Acceptable levels of information quality are maintained Accuracy up to 65%.

Network overhead is reduced 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. 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

“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?”

Geo-casting (location multi-casting) “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 Network Oriented metrics

Degree, Diameter, Graph Density

Centrality Metrics Betweeness Centrality, Lobby Index

Clustering Metrics Clusters, Clustering Co-efficient, Communities, Conductance

Link-Level Metrics Link Duration, Connected Periods, Re-Healing Periods


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Traffic Data Studied Real GPS traces [CabSpotting Project]

Realistic Vehicular Traces 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 IEEE 802.11a (75m) - 802.11p (300m)

Market Penetration (20% - 100%)

Presence of RSUs

Recorded and studied 742000 snapshots of the VANET graph


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General Observations The VANET communication graph exhibits small world

properties 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)


Thank You !!!


On the Evaluation of Caching in Vehicular Information Systems

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