1	Extending Network Knowledge: Making OLSR a Quality of Service Conducive Protocol Pedro Villanueva pvillanu@site.uottawa.ca Thomas Kunz tkunz@sce.carleton.ca Pramod Dhakal pdhakal@eion.com
2	Outline Introduction OLSR Protocol Extended Topology Knowledge (TK) Methodology Results Conclusions Future Work
3	Introduction MANETS require robust and efficient routing protocols. Proactive protocols are preferred over reactive protocols to support critical systems and QoS. OLSR reduces overhead. But, its partial topology view constrains path computation. We gradually extend the partial network view of OLSR.
4	OLSR Protocol OLSR (Optimized Link State Routing) allows manipulating the amount of advertised topology information. OLSR reduces the amount of advertised links, advertising nodes and forwarding nodes; by using the MPR mechanism. Periodic Hello and Topology Control messages advertise the known topology.
5	MPR Mechanism
6	Extended Topology Knowledge The partial view of the network topology represents a severe shortcoming when constructing routing paths. Lack of network (i.e. load), node (i.e. battery) and link (i.e. quality) status information acts against robustness and reliability Multiple paths could be provided.
7	Extended Topology Knowledge
8	Redundant Topology Information Five strategies defining the links to be advertised (TC_Redundancy). TC=0. Links to its MPR Selectors (MPRS). TC=1. Every node, links to MPRs and MPRSs TC=2. Every node, links to every one-hop neighbour. TC=3. Selected MPRs advertise links to MPRs and MPRSs TC=4. Selected MPRs advertise every link to every one-hop neighbour.
9	MPR Redundancy Defines the desired number of one-hop neighbours to reach every two-hop neighbour (MPR Coverage). Analyzed values: MPR =1,2,3. Effect: Increases the number of advertising nodes, advertised links and forwarders.
10	Methodology NS-2 simulation using the OOLSR implementation of OLSR (Hipercom project). Three different sets of scenarios Static scenarios without data traffic. Static scenarios with data traffic. Mobile scenarios with data traffic. Same scenarios were used for each strategy.
11	Simulation parameters for static scenarios
12	Generated TC Messages
13	Overhead vs TK
14	Simulation parameters for data traffic
15	MPRs vs TK
16	Delivery rate on static networks
17	Simulation parameters for mobile scenarios
18	Accuracy of TK
19	Per Packet Delay
20	NS-2 Bug Generated outliers on packet delay Statistical analysis was used to remove them
21	Conclusions High levels of TK can be achieved at different costs without impacting delivery rate TC=2 maximizes TK. TC=0 minimizes overhead. TC=4 offers a fair trade-off With data traffic no strategy keeps large TK
22	Conclusions Extended TK may support construction of better paths and QoS Higher reliability and robustness may be achieved if new metrics are applied Results can be used as a guideline to tune up OLSR
23	Future Work Advertise additional node and link status information to apply more powerful metrics Use alternative metrics for path computation Design new criteria to select the links to be advertised (i.e. quality of links, node’s resources and network load)
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25	Extending Network Knowledge: Making OLSR a Quality of Service Conducive Protocol Pedro Villanueva pvillanu@site.uottawa.ca Thomas Kunz tkunz@sce.carleton.ca Pramod Dhakal pdhakal@eion.com