Routing, Resource Discovery and Hierarchical Architecture in Wireless Networks Ahmed Helmy Lecture 3 - A Spring 07.

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Presentation transcript:

Routing, Resource Discovery and Hierarchical Architecture in Wireless Networks Ahmed Helmy Lecture 3 - A Spring 07

Birds-Eye View: Research in Wireless UFL Architecture & Protocol Design Methodology & Tools Test Synthesis (STRESS) Mobility Modeling (IMPORTANT) Protocol Block Analysis (BRICS) Query Resolution in Wireless Networks (ACQUIRE & Contacts) Robust Geographic Wireless Services (Geo-Routing, Geocast, Rendezvous) Gradient Routing (RUGGED) Worms, Traceback in Mobile Networks Behavioral Analysis in Wireless Networks (MobiLib & IMPACT) Multicast-based Mobility (M&M) Mobility-Assisted Protocols (MAID) Context-Aware Networks

Road Map Unicast Routing with caching Resource Discovery issues Contact based architectures –CARD, TRANSFER Geographic routing issues

Related Reading list From book (C. Perkins): (one order of reading) –ch 3 DSDV, ch 5 DSR, ch 6 AODV, ch 8 TORA, ch 4 cluster-based, ch 7 ZRP From the paper reading lists –unicast routing list in syllabus (all papers, most overlap with book, read the book or papers) –broadcast: - broadcsat storm, - min dominating sets –Resource discovery: book chapter (on-line) TRANSFER, CARD, MARQ

Related Reading list (contd.) –Mobility Modeling IMPORTANT, PATHS, BRICS, Bk Chptr (posted) Partial reading list for geographic routing aspects –GPSR, - LAR, - Geocast, –From my web site Perfect Geocast Inaccuracy/inconsistency, Face routing with inaccuracy Mobility prediction Black listing Book chapter (posted)

Routing and Resource Discovery in Wireless Networks

Conventional Approaches Flooding: –Simple –Overhead: N-1 transmissions, g.(N-1) receptions (where g is average node degree)… expensive! Expanding Ring Search: –Repeated floods with expanding TTL –Terminates when target found –Initial TTL & increment have significant impact

Conventional Approaches (contd.) Reduced Broadcast heuristics (bcast storm ppr): Probabilistic rebroadcast with p Counter-based: suppress bcast if cnt rx > cnt thresh Distance-based: suppress if min(d) < D thresh, where min(d) is min dist to nbr bcast Location-based: supp if added coverage > Area thresh –Attempts delivery to all nodes –Does not guarantee delivery –Works well when density/redundant bcast is high

Cluster-based and Min. Dominating Set - Guarantees delivery - Optimum Dist Algo NP hard - Approximations reduce amount of redundant bcasts to cover all the nodes - re-configuration may be major with dynamics/mobility Example connected dominating set, black nodes belong to the backbone constituting a dominating set.

On-demand routing with caching

DSR-like routing model: –a querier node Q issues a request for a target resource T. –The request process progresses as follows: 1. Q performs local lookup, 2. If a cached route to T is not found then request a lookup from 1-hop neighbors (within transmission range), 3. If a cached route is not found (or is invalid) then flood a request throughout the network, 4.a. Intermediate nodes with cached route to T reply to Q, 4.b. The target T replies to requests returning multiple paths to Q.

State diagram for on-demand routing in DSR-like mechanisms. p:hit ratio q: validity ratio qr: obtained by flooding Overhead (number of transmitted messages) 1 - local cache lookup: no overhead 2 - Nbr Cache lookup: NC=1+ .g, where g av deg, and  fraction of nbrs responding 3 - Cost of Flood: CF~(N-1)+g.L+ .N. .L, where L is av. path length from Q to T, .N is fraction of intermediate nodes responding, and .L is av. path length for such responses Ov=(1-p1).NC+(1-(p1q1+p2q2-p1p2q2)).CF/qr

Define cache efficacy as p.q (hit a valid local or nbr cache)

For small transfers, in mobile, large-scale, wireless networks, cache efficacy is very low, - need new paradigms: - hierarchy, - hybrid/loose hier. Arch.s