Routing, Resource Discovery and Hierarchical Architecture in Wireless Networks

Ahmed Helmy

Lecture 4 - A

Spring 08

Birds-Eye View: Research in Wireless Networks @ 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

1

2

3

Q

T

T

4.b

4.a

Cache table

T: target nodeQ: queriertr: transmission range request reply

tr2

2

2

3

3

3

4.b

• 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.

Localcachelookup

Flood request

Valid route

Neighborcachelookup

Foundlocalcache

Foundneighborcache

p1 q1

1-p1

1-q1

p2

1-p2 q2 1-q2

qr1- qr

DiscoveryRequest

State diagram for on-demand routing in DSR-like mechanisms.

p:hit ratioq: validity ratioqr: obtained by flooding

Overhead (number of transmitted messages)1 - local cache lookup: no overhead2 - Nbr Cache lookup: NC=1+.g, where g av deg, and fraction of nbrs responding3 - 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+(1-p1)p2q2)).CF/qr

Define cache efficacy as p.q (hit a valid local or nbr cache)[Recall: Overhead p.q ]

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