HoWL: An Efficient Route Discovery Scheme Using Routing History in Mobile Ad Hoc Networks Faculty of Environmental Information Mika Minematsu 親 : masato, haru

Outline Problem Definition HoWL CEI Performance Evaluation of HoWL Conclusion and Future Work

Outline Problem Definition HoWL CEI Performance Evaluation of HoWL Conclusion and Future Work

No need of a pre-existing infrastructure Formed dynamically by mobile nodes Nodes may communicate via multihop Adapt to topology changes Conduct route discovery when needed Use Flooding （ e.g. DSR, AODV) Mobile Ad Hoc Networks (MANET) multihop src dst

High overhead imposed on network! Reduces overhead! DST SRC DST SRC Limited Broadcast Flooding (Maximum hop)

Outline Problem Definition HoWL Design Implementation CEI Performance Evaluation of HoWL Conclusion and Future Work

Design of Hop-Wise Limited broadcast (HoWL) 1. When a link failure occurs and a new route is searched, search area is limited based on the history of hop counts of previously used routes. 2. When the HoWL failure detect timer expires, route request messages are repropagated for a wider search area.

Implementation of HoWL Implemented as an extension to Dynamic Source Routing (DSR). Two versions of HoWL: 1. Utilizing the previously used route. 2. Utilizing history of previously used routes.

Hop Count of Limited Search Area 1. TTL = hop_old + α 2. TTL = β*hop_old + (1-β)*history TTL: hop count of limited search area hop_old: hop count of previously used route α: constant added to hop_old β: proportional relevance of each component (In this implementation, 0.8) history: other valid hop counts Each HoWL represented as H(α) and H(ave).

Contains hop counts of previously used routes arriveTime hopCount next head tail destAddr next Hop Table Entries Hop History Entries Hop Table

Common Parameters Rate limiting the limited route search first failure: doubles the search area second failure: conducts flooding HoWL failure detect timer: 30 ms * ttl ttl: hop count of limited search area Preserved duration of the history: 600 seconds

Effect of HoWL 1. Reduces the overhead of route request phase by limiting the area which receives route request messages. 2. Reduces the overhead of route reply phase by eliminating route reply messages for long, detouring routes. 3. Shortens latency by limiting the area where routes are searched.

Outline Problem Definition HoWL CEI Performance Evaluation of HoWL Conclusion and Future Work

Where does HoWL function? Example of real world scenario:

Variable parameters: Number of nodes Speed of nodes Transmission range Area of the network Traffic rate Variable parameters for the scenario More parameters mean longer time is needed for evaluation and analysis!

Goal of Characterized Environmental Indicators (CEI) To characterize “ uniform ” real world environments with fewer parameters. CEI former

CEI Node Density(ND): an indicator for node density. Average Hop count of route(AH): an indicator for scale of network. frequency of Link Failure(LF): an indicator for characteristics of node movement and traffic pattern.

CEI applied to simulation environment The expressions of the three indicators: where number of nodes, maximum speed of nodes, size of simulation field, and radius of transmission range are n (nodes), s (m/s), x * y (m^2), and r (m), respectively. Note: CEI is only a characterization. ex. traffic rate and pause time are related to LF.

Advantages of CEI when Applied to Simulation Environments 1. CEI simplifies evaluation and analysis by reducing the amount of simulations to be conducted. 2. CEI facilitates stating the advantageous and disadvantageous conditions for a simulation target. 3. CEI absorbs various scaled environments.

Outline Problem Definition HoWL CEI Performance Evaluation of HoWL Conclusion and Future Work

Performance comparison with related work Quantitative Evaluation through simulation 1. Overhead imposed on the network 2. Latency of route discovery Qualitative Evaluation 1. Cost 2. Simplicity 3. Generality Evaluation of HoWL

Expanding Ring Search (RING) Gradually expands search area from 1, 2, 4, 8, to 16 hops. Comparative Target (1)

LAR : [Vaidya98] Limits geographical region Requires GPS Requires to know average moving speed Comparative Target (2)

Problem on implementing LAR No information on specifications. ex: What ’ s the size of a route request packet? Source routing/hop-by-hop routing? However, LAR is implemented on GloMoSim.

GloMoSim vs. ns-2 SimulatorGloMoSimns-2 Radio Modelstandardabstract Signal reception SNRT based, BER based SNRT based Radio frequency 2.4GHz914 MHz The physical layer and radio model are more realistic in GloMoSim than ns-2.

GloMoSim Code for LAR and DSR is provided. We implemented HoWL and RING as an extension to DSR.

SRC LAR DST Similar to HoWL, LAR conducts flooding for the first route discovery.

SRC LAR DST´ Expected location of the destination is calculated. expected zone radius = velocity * time_elapsed radius radius: radius of the expected zone centered at DST ’ velocity: moving speed of the destination time_elapsed: time elapsed since last time route was found DST ’ : previous location of the dest

SRC LAR DST´ Calculate Request zone based on Expected zone and location of SRC. Request Zone

Quantitative Evaluation of HoWL 1. Overhead The total number of bytes of control packets (route request and reply messages). 2. Latency The time route request messages are propagated to the time the last route reply message is received at the source node.

Simulation Environment GloMoSim Random way point mobility model Pause time: 0 second Simulation time: 15 minutes Traffic: 1 CBR (Constant Bit Rate) Sending interval: 5 seconds

Simulation Scenarios 1. ND = 1, AH = 10, LF = 1/ ND = 3, AH = 10, LF = 1/ ND = 1, AH = 5, LF = 1/ ND = 1, AH = 10, LF = 3/ simulations were conducted for each of the scenarios.

Overhead in Ratio (LF=3/100) When network topology changes frequently, overhead of RING and LAR is high.

Overhead in Ratio (ND=3) When more nodes exist, it is more likely that a cache reply succeeds.

Summary for Overhead HoWL is effective under high node mobility. RING is effective under high node density. Efficiency of HoWL is higher than LAR for all cases.

Latency in Ratio (LF=3/100) When network topology changes frequently, overhead of RING and LAR is high.

Latency in Ratio (ND=3) When more nodes exist, it is more likely that a cache reply succeeds.

Summary for Latency HoWL is effective under high node mobility. RING is effective under high node density. Efficiency of HoWL is higher than LAR for all cases. The results accord with the analysis in overhead aspect.

Qualitative Evaluation H(α), H(ave) RINGLAR Cost ○ ○ × Simplicity ○ ○ × Generarity ○ ○ × LAR requires GPS and moving speed of other nodes. HoWL is generally considerably more effective than LAR.

Discussion HoWL is more effective than LAR both in quantitative and qualitative aspects. Performance of HoWL probably enhances by implementing nonpropagating search.

Outline Problem Definition HoWL CEI Performance Evaluation of HoWL Conclusion and Future Work

Conclusion We have proposed HoWL, a route discovery scheme using routing history. We have introduced CEI that characterizes real world environments. We have evaluated performance of HoWL over related work, and showed that HoWL is effective under high node mobility.

Future Direction Additional performance evaluation under different traffic patterns and mobility models. Algorithm that acquires the optimized search area. Relative speed of a src-dest pair Dynamic refining Further analysis of CEI. Compare with other related work. (ex. OLSR)

Published Papers Related to this Thesis M. Minematsu, M. Saito, H. Aida, and H. Tokuda “ Hop-Wise Limited broadcast (HoWL) for Mobile Ad hoc Networks ”, DICOMO2002, Jul Winner of the Best Paper Award Minematsu, Saito, Aida, Tobe, and Tokuda “ HoWL: An Efficient Route Discovery Scheme Using Routing History in Ad Hoc Networks ”, IEEE Conference on Local Computer Networks (LCN), Nov. 2002

Thank you.