QoS Topology Control and Energy Efficient Routing in Ad hoc Wireless Networks

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QoS Topology Control and Energy Efficient
Routing in Ad hoc Wireless Networks

• Prof. Xiaohua Jia
• Dept of Computer Science,
• City Univ of Hong Kong

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Mobile Ad Hoc (Wireless) Networks

• Whats a mobile ad hoc network?
• Mobility
• No wired infrastructure

S
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Energy-efficiency in ad hoc networks

• Power function
• p(u,v) da(u,v), 2 a 4
• Two special features of radio transmission
• Broadcast in nature.
• p(u,w) p(w,v) lt p(u,v),
• relaying messages by a third node may result in
  a smaller energy cost.

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Topology Control Problem
Given a set of wireless nodes V in a plane, for
each node u, adjust its transmission power to
p(u), such that the network is fully connected
and is minimized.
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R. Ramanathan, R. Rosales-Hain, Topology control
of multihop wireless networks using transmit
power adjustment, INFOCOM00.
Greedy algorithm (based on Kruskals MST
algorithm)
C
D
A
B
Side-effect edge problem Distributed algorithms
LINT and LILT
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R. Wattenhofer, L. Li, P. Bahl and Y.M. Wang,
Distributed topology control for power efficient
operation in multihop wireless ad hoc networks,
INFOCOM01.

• G topology by max power G topology by min
  power.
• Algorithm
• Divide uniformly a nodes region into cones with
  angle a
• Increase a node-power until there is a neighbor
  in each cone, or it reaches max power of the node.

• Theorem. Let a 2p/3. G is connected if G is
  connected.

a
u
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N. Li, J. Hou and Lui Sha, Design and Analysis
of an MST-based Topology Control Algorithm, IEEE
INFOCOM03.N. Li and J. Hou, Topology control
in heterogeneous wireless networks problems and
solutions, IEEE INFOCOM04.

• Algorithm
• Collect information about maximally reachable
  neighbors
• Construct a local MST (in terms of transmission
  power) among neighbors by each node
• Determine the actual power of each node (the
  neighbors of u in G are 1-hop nodes in us local
  MST).
• Theorem 1. G is connected if G is connected.
• Theorem 2. The degree of any node in G is
  bounded by 6.

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QoS topology control
Given a set of nodes in a plane B, max
bandwidth capacity at a node. ?s,d, end-end
traffic demand between s, d. ?s,d, maximal
hop-count allowed between s, d. Problem. Find
transmission power p(i) for 0 ? i ? n, such that
?s,d, for all pairs (s,d), can be routed within
?s,d, and Pmax is minimized, where Pmax
maxp(i) 0 ? i ? n.
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Traffic Non-splittable Formulations
Variables xi,j - boolean, xi,j 1 if there is a
link from node i to node j otherwise, xi,j 0.
- boolean, 1 if the route from s to d
goes through the link (i,j) otherwise
0. Pmax - the maximum transmitting power of nodes.
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Traffic non-splittable

• Objective Min Pmax

• Topology constraints

• Transmission power constraint

• Delay constraint

i
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Traffic non-splittable

• Bandwidth constraint

• Flow constraints

• Binary constraint

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Traffic non-splittable
Topology of six nodes and six requests
Non-splittable case
Splittable case
Tab. 2. The QoS requests and their routes for
Fig. 2
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Trarffic Splittable Formulation
Variables
and Pmax remain the same.
- amount of (s, d)s traffics going through link
(i, j).
Objective Min Pmax

• Topology constraints

• Transmission power constraint

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Formulation (contd)

• Bandwidth constraint

• Flow constraints

• Variable constraints

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Two steps of solution Step 1. QoS load-balanced
routing
Lmax maximal node-load Problem. Given a network
graph G and traffic demands between node pairs,
route these traffics in this graph, such that
Lmax minimized.
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Formulation of QoS routing problem
Objective Min Lmax
Constraints
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Step 2. QoS topology control

• Algorithm
• sort all node-pairs (i,j) in ascending order
  according to their distance d(i,j).
• pick up the node-pair with closest distance but
  not yet connected and increase the power to make
  them connected.
• run the QoS routing algorithm on G to obtain
  Lmax. If Lmax B, then stop otherwise repeat
  (b) and (c).

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Experimental results
(a) ? 0.02B (b) 0.1B
(c) ? 0.2B (d) ? 0.32B
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Experimental results
Node-degrees versus ?m
X. Jia, D. Li, and D. Du, QoS topology control
in ad hoc wireless networks , INFOCOM04.
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Routing Protocols in Ad Hoc Networks

• Proactive protocols (routing table based), such
  as DSDV (Destination Sequenced Distance Vector),
  OLSR (Optimized Link State Routing), etc.
• On-demand protocols (reactive protocols), such as
  DSR (Dynamic Source Routing), AODV (Ad-hoc
  On-demand Distance Vector), etc.
• Virtual backbone based protocols, such as
  Spine-based method, clustering method,
  hierarchical protocols, etc.

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D. B. Johnson, D. A. Maltz, Y.C. Hu, and J. G.
Jetcheva, The Dynamic Source Routing Protocol for
Mobile Ad Hoc Networks, http//www.ietf.org,
draft-ietf-manet-dsr-05.txt, Mar 01.

• Dynamic Source Routing (DSR)
• Source s finds a route to destination d by
  flooding a Rreq packet.
• d replies a Rrep packet to s by reversing the
  route appended to the Rreq.
• s includes the route to d in each data packet to
  d (called source routing).

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Route Caching in DSR

• Each node learns routing information from both
  Rreq and Rrep packets and caches the routes.
• When a node receives a Rreq to d and it has a
  valid route in its cache, it replies the route to
  s.

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Charles E. Perkins, E. M. Royer and Samir R. Das,
Ad-hoc On-Demand Distance Vector (AODV)
Routing, draft-ietf-manet-aodv-08.txt,
http//www.ietf.org, Mar 2001.

• AODV (Ad-hoc On-demand Distance Vector)
• It is similar to DSR in route discovery, but
  improves DSR by keeping routing tables (next-hop)
  at nodes (no route info in data packets).
• When a node receives a Rreq, it sets up a reverse
  path to the source in its routing table.
• Rrep travels along the reverse set-up path to s
  and the forward-path (i.e., the route from s to
  d) is set up as the Rrep travels to s.
• Entries in routing table are purged after a
  timeout.

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C. E. Perkins and Pravin Bhagwat, Highly Dynamic
Destination-Sequenced Distance-Vector Routing
(DSDV) for Mobile Computers, ACM SIGCOMM, Oct
1994, pp.234-244.

• Destination Sequence Distance Vector Routing
• It mimics the Distance Vector Routing.
• Each node keeps a routing table next-hop and
  distance to each destination, and
  dest-sequnce-no.
• Each node periodically exchange the routing table
  with neighbors.
• Data packets are forwarded towards destinations
  by using the next-hop info in routing tables on
  the way.

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Power-Aware Routing

• Define optimization goals on energy cost for
  routing, e.g., minimum energy cost per packet,
  maximum network lifetime, maximum minimum
  residual energy.
• Assign a weight to each link according to
  optimization goal, e.g., energy cost over a link,
  residual energy at nodes.
• Perform routing with minimum weight.

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Energy Efficient Broadcasting
Ts broadcast tree rooted from source s NL(Ts)
set of non-leaf nodes of Ts. Problem. Given a set
of nodes in a plane, for each node u, adjust its
transmission power p(u), to form a Ts, such that
S
To determine, for each node u 1) Transmission
power of u, and 2) The children of u.
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J. Cartigny, D.Simplot, and I. Stojmenovic,
Localized minimum-energy broadcast in ad-hoc
networks, IEEE INFOCOM03.

• Algorithm
• Construct a connected topology that has min total
  energy.
• Derive the broadcast tree from the min-energy
  topology using neighbor elimination scheme.

S
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J.E. Wieselthier, G. D. Nguyen, and A.
Ephremides, On the Construction of
Energy-Efficient Broadcast and Multicast Trees in
Wireless Networks, IEEE Infocom00.

• BIP (broadcast incremental power)
• It is based on Prims MST algorithm.
• Starting from s, each time a new node that can be
  connected by a tree-node with least incremental
  power is added to the tree, until all nodes are
  in the tree.

s
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Energy Efficient Broadcast with Given
Transmission Power

• p(v) transmission power of node v
• Ts broadcast tree rooted from source s
• NL(Ts) set of non-leaf nodes of Ts.
• Problem. Given a set of nodes in a plane and p(v)
  for each node v, find a Ts that

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Transforming the problem to the Steiner tree
problem

• The broadcast routing problem is transformed to
  finding a directed tree Ts in G that spans all
  nodes in V and the total weights of Ts is
  minimized.

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A Greedy Heuristic

• U uncovered set D covered set
• Vi set of outgoing neighbors of node i
• 1) D ?Vs U ? V Vs
• 2) Pick from D a node i that has the largest
  value of VinU/p(i)
• D ? D Vi U ? U - Vi
• 3) Repeat step 2 until D V.

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A Node-weighted Steiner Tree Based Heuristic

• Theorem 1. Given G(V, E) and s, this heuristic
  can output a broadcast tree in time O(n4).
• Theorem 2. The approximation ratio is at most
  2ln(n-1)1.

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Experimental Results

• D. Li , Xiaohua Jia and H. Liu, "Energy efficient
  broadcast routing in ad hoc wireless networks",
  IEEE Trans on Mobile Computing, Vol. 3, No. 2,
  Apr - Jun, 2004, pp.144-151.

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Energy-Balanced Multicast Routing
Given a wireless network G(V,E) Ei initial
energy at node i. wi,j power cost per time-unit
on link li,j, wi,j dai,j.
Problem. For a multicast request (s, D, t), find
a routing tree, such that the minimal remaining
energy of nodes is maximized after the multicast
session.
S. Cheng, X. Jia, F. Hung, and Y. Wang, Energy
efficient broadcasting and multicasting in static
wireless ad hoc networks, IEEE Trans on Wireless
Communications.
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Maximizing broadcast/multicast duration routing
Given a wireless network G(V,E) Ei initial
energy at node i wi,j power cost per time-unit
on link li,j.

• Problem. Find a set of broadcast / multicast
  trees, such that the duration of the broadcast /
  multicast session is maximized.

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The End