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Network Layer Support for Service Discovery in MANETs

Network Layer Support for Service Discovery in MANETs. Ulas Kozat and Leandros Tassiulas University of Maryland, College Park Presented by Wei Gao. Background. Service discovery Users search for their desired network services

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Network Layer Support for Service Discovery in MANETs

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  1. Network Layer Support for Service Discovery in MANETs Ulas Kozat and Leandros Tassiulas University of Maryland, College Park Presented by Wei Gao

  2. Background • Service discovery • Users search for their desired network services • Examples of network services: remote printers, scanners, data sources, and webpages……

  3. Background • Components of a service discovery system: • Service requesters • Service providers • Service repositories • A service discovery process include: • Dissemination of service discovery messages • Matchmaking between the services requested and provided

  4. Background • Service discovery in MANETs • MANETs are highly dynamic • Prevalent node mobility • Adverse channel conditions • Unpredictable node failures • Requirements for service discovery • Scalable to search for matching services quickly and efficiently • Robust against unpredictable network topology changes

  5. Overall approach • Efficient dissemination of service discovery messages among service providers and repositories • Backbone management phase: Formulation of 1-hop clusters and a virtual backbone • Distributed service discovery phase: Distribution of service discovery messages

  6. Backbone Management (BBM) Phase • Some notations regarding the virtual backbone • Service Broker Node (SBN): the clusterheads connecting other non-backbone nodes • Virtual Access Point (VAP): the non-backbone node acting as the access point for another node to the backbone • Directory Agent (DA): software agent that store service registrations

  7. Backbone Management (BBM) Phase • Construct a virtual backbone for dissemination of service discovery messages • Essentially, a clustering process • Clusterheads consists of a dominating set • Criterion of clusterhead selection • Normalized link failure frequency (NLFF) • Properties: • Convergence of cluster formation: a dominating set can always be constructed (Lemma 1) • Cluster completeness: every node has an associated VAP (Lemma 2)

  8. Backbone Management (BBM) Phase • An example

  9. Distributed Service Discovery (DSD) Phase • Service registration • A node registers its service to the DA located on its VAP • For a backbone node, just register at itself • Multicast dissemination to other DAs located on other VAPs • A multicast tree is rooted at every DA consisting all the other VAPs in the network • Construction of multicast tree: broadcast + self-pruning

  10. Distributed Service Discovery (DSD) Phase • Example of multicast tree construction

  11. Distributed Service Discovery (DSD) Phase • An example of resource discovery

  12. Simulation results • Successful ratio • Advantage is shown compared to plain network architecture • Slightly affected by node mobility

  13. Simulation results • Service discovery delay • Improved over anycast-DSR • Slower response than DSDP and AODV

  14. Simulation results • Constructions of backbone and multicast trees cost extra communication overhead

  15. Summary • Pros: • Propose an approach to constructing a clustered network architecture for service discovery • The clustered network architecture is able to achieve high successful ratio of service discovery • Distributed service discovery provides sound robustness against link failures

  16. Summary • Cons: • The proposed approach leads to extra communication overhead, and thus may not be suitable for large-scale networks • This is mainly because the 1-hop clustered architecture. There will be too many backbone nodes and VAPs in the network

  17. Relation to course project • Multi-hop extension based on the approach in this paper • Service discovery on multi-hop clusters • Clusterhead selection considering both efficiency and stability • Solving possible inconsistency • Distributed storage of service registrations • Deployment of local DHTs on multi-hop clusters • Local searching based on Hash results

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