ad hoc and sensor networks routing protocols (part ii)
TRANSCRIPT
Ad hoc and Sensor NetworksRouting protocols
(Part II)
Outline
4.1 Routing Challenges and Design Issues in WSNs 4.2 Flat Routing 4.3 Hierarchical Routing 4.4 Location Based Routing 4.5 QoS Based Routing 4.6 Data Aggregation and Convergecast 4.7 Data Centric Networking 4.8 ZigBee 4.9 Conclusions
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Chapter 4.6 Data Aggregation and
Convergecast
Aggregation in Sensor Networks
Traditional Address-Centric routing IP address routing Not suitable in large scale sensor networks
Data-Centric Routing Content-based routing Enhance the data aggregation opportunity
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Source 1 Source 2
A B
Sink
Source 1 Source 2
A B
Sink
a) Address-Centric (AC) Routing b) Data-Centric (DC) Routing
1
1
2
2
21
1+2
DataAggregation
Theoretical Results on Aggregation
Let there be k sources located within a diameter X, each a distance di from the sink. Let NA and ND be the number of transmissions required with AC and optimal DC protocols, respectively.
1. The following are bounds on ND:
2. Asymptotically, for fixed k, X, as d = min(di) is increased,
3. Although the problem is NP-hard in general, the optimal data aggregation tree can be formed in polynomial time when the sources induce a connected sub-graph on the communication graph.
( 1) min( )
min( ) ( 1)D i
D i
N k X d
N d k
1lim D
dA
N
N k
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Aggregation Techniques
In general the formation of the optimal aggregation tree is NP-hard. Some suboptimal DC routing heuristics as follows: Center at Nearest Source (CNSDC)
All sources send the information first to the source nearest to the sink, which acts as the aggregator.
Shortest Path Tree (SPTDC) Opportunistically merge the shortest paths from each source
wherever they overlap.
Greedy Incremental Tree (GITDC) Start with path from sink to nearest source. Successively add next
nearest source to the existing tree.
Address Centric (AC) No aggregation, distinct shortest paths from each source to sink.
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Performance Study
Event-Radius model Random Sources model
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Performance Study (cont.)
Energy Costs
Event-Radius model
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Performance Study (cont.)
Energy Costs
Random Sources model9
Conclusions
Data aggregation can result in significant energy savings for a wide range of operational scenarios.
The gains from aggregation are paid for with potentially higher delay. It should be possible to design routing algorithms for sensor networks in which this tradeoff is made explicitly.
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Reference
B. Krishnamachari, D. Estrin, and S. B. Wicker, "The impact of data aggregation in wireless sensor networks," In Proceedings of the 22nd International Conference on Distributed Computing Systems Workshops (ICDCSW'02), pp. 575-578, Vienna, Austria, July 02-05 2002.
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Chapter 4.7 Data centric networking
4.7.2 Data-centric Storage
Data centric storage Data is stored inside the network. All data with the same name (or data range) will be
stored at the same sensor network location Why data centric storage?
Energy efficiency Robustness against mobility and node failures Scalability
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One-dimensional Data Storage
Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table (GHT [Ratnasamy et al. 2003]) Data Storage and Retrieval Perimeter Refresh Protocol Structured Replication
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One-dimensional Data Storage GHT
Put(k, v)- stores v (observed data) according to the key k
Get(k)- retrieve whatever value is associated with key k
Hash function Hash the key into the
geographic coordinates Put() and Get()
operations on the same key “k” hash k to the same location
(12,24)
user
queryresponse
data
Hash (‘elephant’)=(12,24)
Put (“elephant”, data)Get (“elephant”)
Hash (‘elephant’)=(12,24)
Elephant Data
An example for GHT
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Perimeter Refresh Protocol
Assume key k hashes at location L
A is closest to L so it becomes the home node
E
F
B
D
A
C
L
home
Replica
Replica
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Structured Replication
Augment event name with hierarchy depth
Given root r and given hierarchy depth d Compute 4d – 1 mirror
images of r
(0, 0) (100, 0)
(100, 100)(0, 100)
root point
level 1 mirror points
level 2 mirror points
Example of structured replication with a 2-level decomposition
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Conclusions Data centric storage entails naming of data and
storing data at nodes within the sensor network GHT uses Perimeter Refresh Protocol and
structured replication to enhance robustness and scalability
DCS is useful in large sensor networks and there are many detected events but not all event types are Queried
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Multi-dimensional Data Storage
Multi-Dimensional Range Queries in Sensor Networks (DIM [Li et al. 2003]) Building Zones Data Insertion Query Propagation
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Building Zones
Divide network into zones.
Each node mapped to one zone.
Encode zones based on division.
Each zone has a unique code.
Map m-d space to zones.
Zones organized into a virtual binary tree.
6
5
1110
1111
43
21
78
10
9
1100111
0110
010
0001
0000 001 10
L[1/2, 1)L[0, 1/2)
T[
1/2,
1)
T[
0, 1
/2)
L[0, 1/4) L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)
T[3/4, 1)T[1/2, 3/4)
T[1/4, 1/2)T[0, 1/4)
L: Light, T: Temperature
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Data Insertion
Encode events Compute
geographic destination
Hand to GPSR
Intermediate nodes can refine the destination estimation
1110
1111
L[1/2, 1)
L[0, 1/4)
1
110
L[0, 1/2)
0111
0110
010
T[
1/2,
1)
0001
0000 001 10
T[
0, 1
/2)
L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)
T[3/4, 1)T[1/2, 3/4)
T[1/4, 1/2)T[0, 1/4)
2
34
5
6
987
10
E1= <0.8, 0.7>
Store E1
L: Light, T: Temperature
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Query Propagation
Split a large query into smaller sub-queries.
Encode each sub-query.
Process sub-queries separately, resolving locally or forwarding to other nodes based on their codes.
1110
1111
L[1/2, 1)
L[0, 1/4)
1
110
L[0, 1/2)
0111
0110
010
T[
1/2,
1)
0001
0000 001 10
T[
0, 1
/2)
L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)
T[3/4, 1)T[1/2, 3/4)
T[1/4, 1/2)T[0, 1/4)
2
34
5
6
987
10
Q10= <.75-1, .5-.75>
Q1= <0.5-1, 0.5-1>
Q12= <.75-1, .75-1>Q11= <.5-.75, . 5-1>
L: Light, T: Temperature
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Conclusions DIM resolves multi-dimensional range queries
efficiently. Work that still needs to be done
Skewed data distribution These can cause storage and transmission hotspots.
Existential queries Whether there exists an event matching a multi-
dimensional range. Node heterogeneity
Nodes with larger storage space assert larger-sized zones for themselves.
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Chapter 4.8ZigBee
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The ZigBee Standard
ZigBee is a low cost, low power, low complexity, and low data rate wireless communication technology at short range. Based on IEEE 802.15.4, it is mainly used as a low data rate monitoring and controlling sensor network
802.15.4
ZigbeeSpecification
Applications
Application Framework
Network & Security
Medium Access Control (MAC) Layer
Physical (PHY) Layer
Application
Zigbee stack
Hardware
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The Network Layer
ZigBee identifies three device types The ZigBee coordinator (one in the network) is an FFD
managing the whole network A ZigBee router is an FFD with routing capabilities A ZigBee end-device corresponds to a RFD or FFD acting
as a simple device
The ZigBee network layer supports three types of network configurations: Star topology Tree topology Mesh topology
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The Network Layer (cont.)
ZigBee coordinator ZigBee router ZigBee end device
(a) Star network (b) Tree network (c) Mesh network
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Network Formation and Address Assignment (Tree Network)
Before forming a network, the coordinator determines Maximum number of children of a router (Cm)
Maximum number of child routers of a router (Rm)
Depth of the network (Lm)
Note that a child of a router can be a router or an end
device, so Cm ≥ Rm
The coordinator and routers can each have at most Rm
child routers and at most Cm − Rm child end devices
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Network Formation and Address Assignment (cont.)
For the coordinator, the whole address space is logically partitioned into Rm + 1 blocks
The first Rm blocks are to be assigned to the coordinator’s child routers and the last block is reserved for the coordinator’s own child end devices
From Cm, Rm, and Lm, each router computes a parameter called Cskip to derive the starting addresses of its children’s address pools
1
1 1 ,if 1
1 Otherwise,1
Lm d
Cm Lm dRm
Cskip d Cm Rm Cm Rm
Rm
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Network Formation and Address Assignment (cont.)
The coordinator is said to be at depth d = 0, and d is increased by one after each level
Address assignment begins from the ZigBee coordinator by assigning address 0 to itself
If a parent node at depth d has an address Aparent :
the n-th child router is assigned to address:
Aparent + (n − 1) × Cskip(d) + 1
the n-th child end device is assigned to address:
Aparent + Rm × Cskip(d) + n
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Network Formation and Address Assignment (cont.)
ZigBee coordinator ZigBee router ZigBee end device
Addr = 12
Addr = 8
Addr = 9
Addr = 10
Addr = 25
Addr = 0Cskip = 6
A4
Addr = 19Cskip = 1
A3
Addr = 13Cskip = 1
Addr = 24
A1
Addr = 1Cskip = 1
Addr = 6
Addr = 3
Addr = 2
Cm = 5: Maximum number of children of a router Rm = 4: Maximum number of child routers of a router Lm = 2: Depth of the network A2
Addr = 7 Cskip = 1 the n-th child router:
Aparent + (n − 1) × Cskip(d) + 1
the n-th child end device: Aparent + Rm × Cskip(d) + n
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ZigBee Routing Protocol
In a ZigBee network, the coordinator and routers can directly transmit packets along the tree
When a device receives a packet, it first checks if it is the destination or one of its child end devices is the destination
If so, this device will accept the packet or forward this packet to the designated child. Otherwise, it forwards the packet to its parent
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ZigBee Routing Protocol (cont.)
If a device n receives a packet with destination Adest . Assume that the depth of the device n is d and its address is A. This packet is for one of its descendants if the destination address Adest satisfies A < Adest < A+ Cskip(d − 1), and this packet will be relayed to the child router with address
If the destination is not a descendant of this device, this packet will be forwarded to its parent
1
1dest
rA A
A A Cskip dCskip d
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ZigBee Routing Protocol (cont.)
ZigBee coordinator ZigBee router ZigBee end device
Cm = 6Rm = 4Lm = 3
1
1dest
rA A
A A Cskip dCskip d
A < Adest < A + Cskip(d − 1)
Addr = 125
Addr = 30
Addr = 31
Addr = 38
Addr = 126
Addr = 92
Addr = 63Cskip = 7
Addr = 64Cskip = 1
Addr = 1Cskip = 7
Addr = 32Cskip = 7
Addr = 33Cskip = 1
Addr = 40Cskip = 1
Z
? ?
BC
A
Addr = 0Cskip = 31
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Route Discovery (Mesh Network)
Field Name Description
Destination Address
16-bit network address of the destination
Next-hop Address
16-bit network address of next hop towards destination
Entry Status One of Active, Discovery or Inactive
Routing Table in ZigBee
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Route Discovery (cont.)
Field Name Description
RREQ ID(route request)
Unique ID (sequence number) given to every RREQ message being broadcasted
Source Address
Network address of the initiator of the route request
Sender Address
Network address of the device that sent the most recent lowest cost RREQ
Forward Cost The accumulated path cost from the RREQ originator to the current device
Residual Cost The accumulated path cost from the current device to the RREQ destination
Route Discovery Table
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Route Discovery (cont.)RREQ message
Create RDT entry and record fwd path
cost
Update RDT entry with better fwd path
cost
DoesRREQ report
A better fwd path
cost ?
Send RREPDrop RREQ
No
Yes
No
Yes
No
Yes
The RREQ processing
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RDT entry exists for this RREQ ?
IsRREQ for local node or one of end-device children ?
Create RT entry(Discovery under way)And rebroadcast RREQ
Route Discovery (cont.)
S
D
A
C
T
B
Discard route request
route
req.
route req.
route req.
route req.
route req.
route reply
UnicastBroadcastWithout routing capacity
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References
P. Baronti, P. Pillai, V. Chook, S. Chessa, and F. Gotta, A. andFun Hu. Wireless sensor networks: a survey on the state of the art and the 802.15.4 and zigbee standards. Communication Research Centre, UK, May 2006.
J. Bruck, J. Gao and A. A. Jiang, “MAP: Medial Axis Based Geometric Routing in Sensor Network,” in Proceedings of ACM MobiCom, 2005.
Q. Fang, J. Gao, L. Guibas, V. de Silva, and L. Zhang. GLIDER: Gradient landmark-based distributed routing for sensor networks. In Proc. of the 24th Conference of the IEEE Communication Society (INFOCOM’05), March 2005.
B. Chen, K. Jamieson, H. Balakrishnan, and R. Morris. Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. In International Conference on Mobile Computing and Networking (MobiCom 2001), pages 85–96, Rome, Italy, July 2001.
Y. Xu, J. Heidemann, and D. Estrin. Geography-informed energy conservation for ad hoc routing. In Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking, pages 70–84, Rome, Italy, July 2001.
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Conclusions
Routing in sensor networks is a new area of research, with a limited but rapidly growing set of research results
We highlight the design trade-offs between energy and communication overhead savings in some of the routing paradigm, as well as the advantages and disadvantages of each routing technique
Overall, the routing techniques are classified based on the network structure into four categories: flat, hierarchical, and location-based routing, and QoS based routing protocols.
Although many of these routing techniques look promising, there are still many challenges that need to be solved in sensor networks