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6.964 Pervasive Computing Grid: Scalable Ad Hoc Networking 1 November 2001 Douglas S. J. De Couto Parallel and Distributed Operating Systems Group MIT Laboratory For Computer Science http://www.pdos.lcs.mit.edu/grid Who are we? • Grid project in PDOS • Professor: Robert Morris • Students: – – – – – Douglas De Couto Dan Aguayo Jinyang Li Ben Chambers Hu Imm Lee Outline • • • • • • Motivation “Classic” ad hoc protocol Geographic forwarding Grid location service (GLS) Location proxies The Grid network So you want to build a pervasive network? • Assumptions – Wireless, packet-based, mobile – Bigger than just your living room (multihop) • Today’s approach: IEEE 802.11 base stations – – – – Site survey, measure radio performance Channel Allocation Inter-base-station network (wiring?) … Base-station example Wired network B1 B2 3 1 2 4 Ad hoc: a better way • “Ad hoc” means no infrastructure, no planning – Normally implies wireless, mobile, multihop • Place devices (nodes) anywhere • Constraint: devices should form connected network – If not, add “relay nodes” • Costs less! Ad hoc example 3 1 r 2 4 Ad hoc scenarios • Temporary, fast setup – Emergencies – Social events • Rooftop networks – Connect neighborhoods – No wires, trenches, etc. • Developing communities – Ad hoc is cheaper, more incremental – Automatic protocols no technicians needed Other ad hoc benefits • Better spectrum reuse (spatial) • Better scalability • Possibly better power Ad hoc challenges • How do we find multihop routes? • Is there enough network capacity? • Does it use too much device power? – Span: Chen et al., Mobicom 2001 “Classic” protocol • Dynamic Source Routing (DSR) – Flooding route discovery finds source routes as needed – Aggressive caching helps performance Why not use DSR? • Protocol works well with about a hundred nodes – Simulation results; vary with movement, data traffic • Protocols scales poorly – Propagates topology information throughout network – Overhead grows too fast with network size, especially with mobility DSR overhead Number of nodes Geographic forwarding (GF) C’s radio range A C B D F G E • Packets addressed to id,location • Next hop is chosen from neighbors to move packet geographically closer to destination location • Routing overhead constant as network size (nodes, area) grows GF With a Local Protocol D C A A’s nbrs: B, 1 hop (nh: B) C, 2 hops (nh: B) B E B’s nbrs: A, 1 hop (nh: A) C, 1 hop (nh: C) D, 22 hops hops (nh: (nh: C) C) D, F • Local protocol is 2-hop distance vector • A sends packets to F • dcf > dbf but… • ddf < dbf and • C is B’s next hop to D Geo. forwarding challenges • How do we find destination locations? • How do nodes find their own locations? – Location sensors not always practical • Topology problems (“holes”) • General ad hoc problems – Power, capacity Grid Location Service (GLS) overview E B H L D J G A F “D?” I K C Each node has a few servers that know its location. 1. Node D sends location updates to its servers (B, H, K). 2. Node J sends a query for D to one of D’s close servers. Grid Node Identifiers • Each Grid node has a unique identifier. – Identifiers are numbers. – Perhaps a hash of the node’s IP address. • Identifier X is the “successor” of Y if X is the smallest identifier greater than Y. GLS’s Spatial Hierarchy level-0 level-1 level-2 level-3 All nodes agree on the global origin of the grid hierarchy 3 servers per node per level sibling level-0 squares sibling level-1 squares sibling level-2 squares s n s s s s s s s s • s is n’s successor in that square. (Successor is the node with “least ID greater than” n ) Queries search for destination’s successors s n s s s Each query step: visit n’s successor at increasing level. s s s s1 s2 s s3 location query path x GF + GLS performs well Grid DSR Biggest network simulated: 600 nodes, 2900x2900m (4-level grid hierarchy) Number of nodes • Geographic forwarding is less fragile than source routing. • DSR queries use too much b/w with > 300 nodes. GLS properties • • • • Spreads load evenly over all nodes Degrades gracefully as nodes fail Queries for nearby nodes stay local Per-node storage and communication costs grow slowly as the network size grows: O(log n), n nodes • More details: Li et al, Mobicom 2000 Geo. forwarding challenges • How do we find destination locations? • How do nodes find their own locations? – Location sensors not always practical Location Proxies • Nodes that know their location can act as location proxies • Location proxies can communicate with each other using geographic forwarding and the local routing protocol • Nodes without location select proxies, and communicate through them using the local protocol • Nodes advertise proxy locations as their own • Proxies not special besides knowing locations Proxies Increase Delivery Rate The Grid network • • • • Red: 5th floor Blue: 6th floor > 20 “relay” nodes About 2 to 4 hops across each floor Current Grid services • IP routing, including Internet gateway – E.g. supports traceroute • Grid specific information – Who can my radio talk to? – Who do I have routes to? Grid services “in progress” • Location service – Where is node X? • Geocast – Send message m to every node in region R • Position estimation protocol – I don’t have a position sensor – Where am I? Grid Applications • What is a “Grid application” – Uses unique Grid services • Under development: Grid chat – Regular text + voice chat – Who’s nearby? (ask Grid) – Who’s at the student center? (ask Grid) Grid details • Protocol software implemented in the Click modular router – Runs at userlevel, easy to interface to applications – Very portable • Nodes: – Mobile: iPaqs + 802.11 PCMCIA + Linux – “Relay” : small PCs + 802.11 PCI cards + OpenBSD • Global distance vector (DV), or k-hop DV + GF Grid Summary • Grid routing protocols are: – Self-configuring – Easy to deploy – Scalable http://www.pdos.lcs.mit.edu/grid ipkg: http://www.pdos.lcs.mit.edu/~decouto/grid-feed ipkg install grid