AIT Chapter 5 Sensor Networks

1. Assign address from given pool of possible addresses

2. Not used addresses are put back into pool

3. Manage duplicate address detection

1. Choose address randomly

2. Avoid addresses used in neighborhood

3. Choose address randomly but check

4. Let a fix neighbor perform strategy 3. for you

1. ID-centric routing with tables how to reach destination

2. Forward given packet to next hop

3. Nodes might change while routing

1. Link state (OSPF) has to much OH

2. Distance vector (RIP) to inflexible

3. Flooding with no tables but prohibitive OH

1. Proactive or table-driven

2. Reactive or on-demand

3. Hybrid of 1. and 2.

1. Optimized link state routing (OLSR)

2. Destination sequence distance vector (DSDV)

3. Dynamic source routing (DSR)

1. Local link costs are broadcasted

2. BC only by multi-point relays (MPR)

3. MPR are neighbors which are one-hop accessible by any two-hop neighbor

4. Forward data via MPRs

1. Based on distributed Bellman Ford procedure

2. BC periodically full route updates

1. Reactive protocol

2. Discover route with small route request

3. Destination sends route reply with best path

4. If route has been established send data

1. Sources as sensors

2. Sinks as receiving data from WSN

3. Actuators as controlling devices based on data // Also sink

Addresses labeled with physical or virtual position

1. Point (x,y,z)

2. Circle or sphere

3. Rectangle

4. Polygon

5. From connectivity information

1. Basic idea of DSR for discovery procedure

2. Nodes maintain routing tables using sequence numbers and remembering origin of packet

3. Less overhead but higher delay than DSR

1. Minimize energy/bit

2. Maximize network lifetime

3. Maximize total available battery capacity

4. Minimize battery cost routing

5. Conditional max-min battery capacity routing

6. Minimize variance in power levels

7. Minimize total transmission power

1. Costly retransmission

2. Time-varying nature of wireless channel

3. Asymmetric

1. Expected transmission count (ETX) 2. RSSI 3. LQI 4. PRR and 5. energy consumption

1. Position-based 2. geo-casting and 3. virtual coordinate addressing based

Positions of nodes are known and packets sent to closer node

1. Most forward within range r strategy (MFRS)

2. Nearest node with forward progress

3. Directional routing considering connecting line

4. Face routing

5. Geometric perimeter state routing (GPSR)

1. Face is largest region not cut by any edge // Exterior or interior

2. Send packet around the face with right hand rule // Put right hand to the wall and follow

3. Prohibits dead ends

4. Needs additional rules for circles

1. Use MFRS routing till no progress possible

2. Use face routing

3. Use entering into face position for MFRS

Simple strategies might cause dead ends

Send to nodes in given area

Beacon vector routing (BVR)

1. Randomly select beacon nodes

2. Construct trees from beacons to other nodes

3. Every node knows distance to every beacon

4. Nodes neighbors are beacons 1 hop away

1. Greedy with geographic forwarding

2. Fallback mode

3. Scoped flooding with known distance but missing direction information

1. Minimize sum of differences to closer beacons d_k^+(p,d) = Sum_i\inC_k(d) max(p_i-d_i,0)

2. Minimize sum of distances to farther beacons d_k^-(p,d) = Sum_i\inC_k(d) max(d_i-p_i,0)

3. With C_k(d) k closest beacon nodes of d

4. Return neighbor N if distance between N and D is smaller than current min_distance of packet P

Route to fallback_bcn (Bcn closest to D)

Preprocessing data to reduce amount of transmitted bits

1. Adaptation of data to importance (High resolution temperature if passing limit)

2. Aggregation of data

1. Apply functions as min max ave sum on convergecast tree

2. Possible to save partial state records

1. Duplicate sensitive as sum, histograms OR insenstive as max or min

2. Summary or exemplary

3. Composable f if g exists with f(W) = g(f(W1),f(W2)) with W=W1\cupW2

4. Distributive, content sensitive or holistic

1. Accuracy with difference of aggregated and original

2. Completeness

3. Latency

4. OH

SELECT {agg(expr), attributes} FROM sensors

WHERE {selectionPredicates}

GROUP BY {attributes} HAVING {havingPredicates}

EPOCH DURATION i