Cluster construction research in mobile ad

hoc network

NTUIM92 R92725034

資管所研二 林明源IM Graduate Lin Ming Yuan

Outline

Problem statement

Previous work Cluster construction Mobility research Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

Problem statement (1/2) For specific applications like military missions, emergency response

operations, electronic community communication etc, we desire to construct a cluster topology in mobile ad hoc network including following considerations： Wireless communication advantage Individual/Group-based mobility pattern Cluster coordinator/manager selection (clusterhead) Resource management and allocation in clusters Connectivity Stability Reliability Efficient routing through clusterhead

Problem statement (2/2)

Cluster member

Clusterhead

Gateway node

Intra-Cluster link

Cross-cluster link

In the remaining slides, I will describe the issues mentioned above in detail, summary of the previous related works and methodologies and my work.

Outline

Problem statement

Previous work Cluster construction Mobility research Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

Cluster construction(1/10)

A mobility-based clustering approach to support mobility management and multicast routing in mobile ad-hoc networks [international journal of network management 2001;11:387-395][Author:Beongku An, Symeon Papavassiliou ]

MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network [wireless communication and mobile computing2003;3:255-270][Author:Beongku An, Symeon Papavassiliou ]

Geomulticast: architecture and protocols for mobile ad hoc wireless networks [www.ComputerScience Web.com received 17 October 2002][Author:Beongku An, Symeon Papavassiliou ]

Cluster construction(2/10) For some location-based reasons like regional network

management and resource allocation and scalability etc., we desire to partition nodes to subsets. And clustering is the method to organizes unlabeled nodes into groups by using feature vectors (such as similar mobility pattern). High cost to reconstruct the topology and election when clusterhead move out the

coverage of the cluster. Reconstruction causes the variation of the scheduling and allocation and

downsize the performance and utilization. Stability in location and less mobility are more important.

In MHMR, the author proposed MBC approach that use a combination of both physical and logical partitions of network (ex. geographic proximity and functional relation between nodes, such as mobility pattern, etc.)

Cluster construction(3/10)

From observations of the group mobile behavior, the author want to propose a Mobility-based Hybrid Multicast Routing (MHMR) which has the following three features and considerations: Mobility-based clustering and group-based hierarchical structure Group-based (limited) mesh structure and forwarding tree concept Combination of proactive and reactive concepts providing low acquisition delay

and low overhead Channel access and code separation Power control and bandwidth allocation Mobility management

MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (mobility pattern)(4/10)

Relative velocity V(m,n,t) between the node m and n is defined as :

Average relative mobility M m,n,T between any pair (m,n) of nodes during time period T is defined as:

Average motion behavior of a cluster Ci is defined as:

Average relative mobility within the cluster Ci is defined as:

N

in iYnm tnmVN

M ),,(1

,,

),(),(),,( tnVtmVtnmV

iCnm Tmmi MN

CM),( ,,

12

iCK ki TnVM

CM ),(1

1

MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (heuristic)(5/10)

Step1.Mobility Information DisseminationStep1.Mobility Information Dissemination Each node n periodically disseminate its velocity information Each node n periodically disseminate its velocity information

(V(n,ti),i=1,2…) to its neighboring nodes.(V(n,ti),i=1,2…) to its neighboring nodes.

Step2.Calculating Mobility MetricsStep2.Calculating Mobility Metrics Upon reception of neighboring nodes’ velocity information, each node Upon reception of neighboring nodes’ velocity information, each node

calculate the relative velocity V(m,n,T) of each pair nodes and exchange calculate the relative velocity V(m,n,T) of each pair nodes and exchange periodically.periodically.

Step3.Initial Cluster ConstructionStep3.Initial Cluster Construction Construct the set Sm Construct the set Sm includes node includes node m m and all the nodes from which and all the nodes from which

node node m m receives mobility information. receives mobility information. Among the nodes of Among the nodes of Sm Sm the node-the node-i i with the lowest ID that satisfies the with the lowest ID that satisfies the

following condition:following condition: Mm Mm,,ii,,T T < < ThmobThmob . .Node i €Node i € Sm Sm is selected as a is selected as a tentative clusterhead. That is tentative clusterhead. That is

MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (heuristic)(6/10)

Thmod is the mobility threshold parameter for the Thmod is the mobility threshold parameter for the network stability. (random node’s mobility or group network stability. (random node’s mobility or group mobility)mobility)

Step4.Clustering mergingStep4.Clustering merging According to the step 3, a parent clusterhead can include the other child According to the step 3, a parent clusterhead can include the other child

clusterheads as long as satisfying the TCH criteria and under the upper clusterheads as long as satisfying the TCH criteria and under the upper bound of the number of hops (L).bound of the number of hops (L).

Step5.Cluster Maintenance and Reconstruction Step5.Cluster Maintenance and Reconstruction When a node m moves into the cluster Cj and the clusterhead node n in When a node m moves into the cluster Cj and the clusterhead node n in

cluster Cj still satisfies the condition : cluster Cj still satisfies the condition : MmMm,,ii,,T T < < ThmobThmob , it’s not , it’s not necessary to reconstruct the cluster and elect new clusterhead. Then the necessary to reconstruct the cluster and elect new clusterhead. Then the node m request to clustering to node n. Otherwise node m repeats step node m request to clustering to node n. Otherwise node m repeats step 5 during this motion, elect new clusterhead among these nodes and 5 during this motion, elect new clusterhead among these nodes and reconstruct the cluster reconstruct the cluster

MBC approach (reference)(7/10)

Cluster construction- other proposed approach(8/10)

Max-min D-cluster formation in wireless ad hoc networks [inforcom 2000] [Author:Alan D. Amis Ravi Prakash Thai, H.P.Vuong Dung T. Huynh Department of Computer Science University of Texas at Dallas]

A multicast routing protocol for ad hoc network [processing of inforcom99 784-792 March 99] [J.J. Garcai-Luna-Aceves and Ewerton L. Madruga]

Max-min D-cluster formation in wireless ad hoc networks(9/10)

The heuristic runs for 2d rounds of information exchange. Each node maintains two arrays, WINNER and SENDER, each of size 2d node ids: one id per round of information exchange.

First round to select maximum ID as clsusterhead and second round to adjust the selected CH by minimum ID for load balance consideration.

A multicast routing protocol for ad hoc network(10/10)

Shared core-based multicast tree for each group and construct a mesh from different group trees.

The source node transmits the traffic to the core node and downstream multicast to the tree members.

New members join via group tree members or trace the neighbor to the core node (tree manager).

Outline

Problem statement

Previous work Cluster construction Mobility research Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

Mobility research(1/8)

A survey of mobility model for ad hoc network research [wireless communication and mobile computing 2002;2:483-502][author: Tracy camp, Jeff Boleng, and Vanessa Davies]

ODMRP On-demand multicast Routing Protocol in Multihop Wireless Mobile Networks [Mobile Network and Application; Dec 2002;7,6;ABI/INFORM Global][Authors: Sung-Ju Lee, William Su, Mario Gerla]

A survey of mobility model for ad hoc network research(2/8) Two type of the mobility models

Independent (entity mobility model)- Entity mobility models : mobility models that represent mobile nodes whose movements are independent of each other. Random walk mobility model (the most common) Random waypoint mobility model (the most common) Random direction mobility model A boundless simulation mobility model Gauss-Markov mobility model A probabilistic mobility model City section mobility model

Dependent (group-based mobility model)- In an ad hoc network, however, there are many situations where it is necessary to model the behavior of MNs as they move together. So the movement of MNs may depend on other’s (reference point) behavior. Exponential correlated random mobility model Column mobility model Nomadic community mobility model Pursue mobility model Reference point group mobility model

Random walk mobility model(3/8) The random walk mobility model was first described mathematically by Einstein

in 1926 in order to mimic erratic motion such as Brown Motion.

In this mobility model, a MN moves from its current location to a new location by randomly choosing a direction and speed in which to travel at a predefined step number or time slots. After choosing a new speed and direction, the new path is decided.

The new speed and direction are both chosen from [speedmin, speedmax] and [0, 2π]

The model is a memoryless mobility pattern because it retains no knowledge concerning its past locations and speed values when deciding the next speed and direction. (The defectives can be modified by the Guass-Markov model.)

If the specified time (or specified time) a MN moves in the model is short, then the movement pattern is a random roaming pattern restricted to a small portion of the simulation area.

Random walk mobility model(4/8)

Start point: (150, 300)

Speed range: o~10 m/s-1

Direction:0~2π

Time slot: 60s

Gauss-Markov mobility model(5/8)

The Gauss-Markov Mobility Model was designed to adapt to different levels of randomness via one tuning parameter. At fixed intervals of time, n, movement occurs by updating the speed and direction of each MN. Specifically, the value of speed and direction at the n-th instance is calculated based upon the value of speed and direction at the (n-1)-st instance and a random variable using the following equations.

n-1th instance: n-th instance:

select n-1th Gauss r.v.: n-1 n-1x and dxS

1 n-1 and dnS 1 n-1 and dnS

Gauss-Markov mobility model(6/8)

Start point: (150, 300)

Simulation time: 1000s α=0.75

Speed is fixed at 10 m/s-1 Mean direction is initial 90 degrees.

Eliminate the sudden stops and sharp turns. The Markov process can be applied to the x and y equation directly instead of through speed and direction variables.

Change direction mean

d

ODMRP on-demand multicast t Routing Protocol in Multi-hop Wireless Mobile Networks(7/8)

Adapting the Refresh Interval via Mobility Prediction Suppose 2 nodes i and j are within the transmission range r of each other. (xi, yi) : co-ordinates of mobile host I (xj, yj): co-ordinates of mobile host j vi and vj: speeds of i and j respectively oi and oj: moving directions of I and j respectively

Amount of time i and j will stay connected is predicted by:

a= vi cos oi - vj cos oj vj b= xi – xj c= vi sin oi - vi sin oj and d= yi - yi

Vi

Vj

i

j

r

b

dθi

θj 2 2 2at b ct d r

2 2( ) ( )at b ct d r 2 2 2 2

2 2

( ) ( ) ( )t

ab cd a c r ad bcD

a c

ODMRP on-demand multicast t Routing Protocol in Multi-hop Wireless Mobile Networks-prediction(8/8)

Due to the mobility effect, it’s necessary to predict the mobility information at t0+t1+t2+t3 first to make the decision more suitable for the scenario at t0+t1+t2+t3. Then we use the predicted mean value and ODMRP formula to compute the link duration (or reliability of the consecutive path).

t1 蒐集位置資訊與 mobility 資訊，包括速度與方向

t0 t0+t1 t0+t1+t2

t2 optimal algorithm computation time

t3 routing decision distribution time

t0+t1+t2+t3

T 是此次決策使用的時間

t0+t1+t2+t3+T

在 T 快結束之前，保留的時段 t1+t2+t3 作下一次 cluster 的決策

Outline

Problem statement

Previous work Mobility research Cluster construction Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

Integer formulation for clustering(1/7)

Minimum power broadcast trees for wirelessnetworks: Integer programming formulations [INFOCOM 2003, 30 March-3 April 2003, p1001- 1010 vol.2][auhtor: Das, A.K. Marks, R.J.   El-Sharkawi, M.   Arabshahi, P.   Gray, A. Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA]

Clique and clustering: A combinatorial approach [Mathematical Programming, 62, 133-151][author: E. L. JOHNSON, A. MEHROTRA, and G. L. NEMHAUSER,

1993. Min-cut clustering ]

Load-balance clusters in wireless ad hoc networks [Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology 2000, P.25][author: alan D. Amis, Ravi Prakash]

On the optimal clustering in mobile ad hoc networks [Proceedings of IEEE Consumer Communications and Networking, Las Vegas, Nevada USA/ January 5-8, 2004 ][author: Jamal N. Al-Karaki Ahmed E. Kamal Raza Ul-Mustafa Laboratory for Advanced Networks Dept. of Electrical and Computer Engineering]

Clique and clustering: A combinatorial approach- basic model for clustering(2/7)

e E

e eMin w y (E: the link set, we: the link weight; ye: the link decision variable for

cluster) (objective to minimize the total weights of clusters)

1

1 i VK

ki

k

z

Subject to:

(K: no. of clusters, zie: the belongness decision variable for node i

and cluster k; V: the node set)

k=1,......Kki i

i V

f z F

(F: maximum cluster capacity; maximum flow constraint for the cluster k)

1 1

1 K {1,......K},(i,j) Ek ki j ii

k K k K

z z y

(the flow balance constraint for the multicast tree of the cluster k)

ki,z {0,1} i V, k=1,......Kiiy Integer constraint

On the optimal clustering in mobile ad hoc networks(3/7) A Mobile Ad hoc Network (MANET) can be represented by a set of

logical clusters with clusterheads (CHs) acting like virtual base-stations, hence forming a wireless virtual backbone. The role of clusterhead is a temporary role, which changes dynamically as the topology or other factors affecting it change. The proposes includes: Reduce protocol overhead Minimize storage requirement

Trade-off of the network performance due to the large No. of CHs Hop count Communication overhead Extra energy consumption

In this paper, the author proposed a heuristic approach VGA (virtual grid architecture) and ILP formulation for clustering.

On the optimal clustering in mobile ad hoc networks-heuristic(4/7)

In VGA clustering, the network area is divided into fixed, disjoint, and regular shape zones (square). Each mobile node is a member of one of those zones and its zone membership is determined based on its location in the network area.

The clusterheads of adjacent zones can communication to each other directly. If the zone has only short range nodes, the zone is further divided into four sub-zones.

On the optimal clustering in mobile ad hoc networks- heuristic(5/7)

The extension to diagonal routing, henceforth called Diagonal VGA (D-VGA), is possible but it may complicate routing since the number of potential neighbor zones doubles.

In D-VGA CHs can communication with CHs of diagonal zones besides the vertical and horizontal zones.

On the optimal clustering in mobile ad hoc networks- formulation(6/7)

ILP notation

On the optimal clustering in mobile ad hoc networks- formulation(7/7)Formulation

The belonging constraint

The link usage constraint

The xii constraint

The existence of inter-cluster routing

The inter-cluster routing constraint use CH as intermediate nodes

Outline

Problem statement

Previous work Mobility research Cluster construction Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

Energy-efficient multicasting and wireless advantage(1/6)

Algorithms for energy-efficient multicasting in static ad hoc network [Mobile Networks and Applications 6,251-263,2001][Author ： JEFFREY E. , WIESELTHIER, GAM D. NGUYEN Information Technology Division, Naval Research Laboratory, Washington]

On reducing broadcasting redundancy in ad hoc network [IEEE transactions on mobile computing April-June 2002][Author: Wei Lou, Student Member, IEEE, and Jie Wu, Senior Member]

Algorithms for energy-efficient multicasting in static ad hoc network - Wireless communication advantage (2/6)

Normalize transmission power on link (I,j) by range r and proportional factor Pij = power needed to support link between nodes i and j =rα where r is the distance between nodes i and j and α is the decade factor

Pi,(j,k) Pi,(j,k) = max{= max{Pij, Pik Pij, Pik } is sufficient } is sufficient to reach both node to reach both node j j and node and node kk, , based on our assumption of based on our assumption of omnidirectional antennas.“omnidirectional antennas.“Wireless Wireless Multicast advantage”Multicast advantage”

Cited from [Algorithms for Energy-Cited from [Algorithms for Energy-Efficient Multicasting in Static Ad Hoc Efficient Multicasting in Static Ad Hoc Wireless Networks] Mobile Networks Wireless Networks] Mobile Networks and Applications 6,251-263,2001and Applications 6,251-263,2001

Algorithms for energy-efficient multicasting in static ad hoc network - suggested approach (3/6)

By the way, transmission power range affect connectivity and construction of spanning tree. Some additional nodes may be needed as relay to provided connectivity to all memberships of the multicast group. (relayed nodes)

Two basic approaches to construct multicast tree and using PIM (Spare mode of the protocol independent Multicasting) on the trees

- Source-Based Tree (SBT) - Core-Based Tree (CBT)

On reducing broadcasting redundancy in ad hoc network (DP) – energy-efficient consideration (4/6)

For reducing redundancy transmissions and prolong the life of the network, the DP algorithm utilizes 2-hops neighborhood information.

Node v uses N(N(u)), N(u), and N(v) to obtain U(u, v) = N(N(v)) - N(u) - N(v) and B(u, v) = N(v) - N(u). Node v then calls the selection process to determine F(u, v) (forward node list).

Cited from [On Reducing Broadcast Redundancy in Wireless Ad Hoc Network] Wei Lou, Student Member, IEEE, and Jie Wu, Senior Member, IEEE From IEEE transactions on mobile computing April-June 2002

On reducing broadcasting redundancy in ad hoc network (TDP) – energy-efficient consideration (5/6)

If node v can receive a packet piggybacked with N(N(u)) from node u, the 2-hop neighbor set that needs to be covered by v’s forward node list F is reduced to U = N(N(v)) – N(N(u)).

Node v uses N(N(u)), N(u), and N(v) to obtain U(u, v) = N(N(v)) – N(N(u)) and B(u, v) = N(v) - N(u).

On reducing broadcasting redundancy in ad hoc network (PDP) – energy-efficient consideration (6/6)

)()( vNuN

Node v uses N(N(u)), N(u), and N(v) to obtain and U = N(N(u)) - N(u) - N(v) – P, B = N(v) – N(u).

Besides excluding N(u) and N(v) from N(N(v)), as addressed in the DP algorithm, more nodes can be excluded from N(N(v)). These nodes are the neighbors of each node in . Such a node set is donated as.

( , ) ( ( ) ( ))P u v N N v N u

( , ) ( ( ) ( ))P u v N N v N u

Outline

Problem statement

Previous work Mobility research Cluster construction Integer formulation for clustering Energy-efficient multicasting and wireless advantage

My work

My work- problem statement Assumption (given parameter and environment situation)

Node set and link set All possible paths between any node pair (pre-computed) O-D pair and desired traffic load Capacity for each node Mobility information of each node (location, velocity and direction)

For location-based management and resource allocation in dynamic MANETs, I want to group the nodes into cluster including the following considerations: Determine the relationship for clusterhead and cluster member for each node pair Determine which node would be selected as a CH Determine the inter-cluster routing between the clusterhead and cluster members Determine the gateway node between two clusters Determine the link used for the cluster construction Determine the O-D pair routing path

My work-notation

od uvP P

Given parameters

Notation Definition

VThe set of nodes which is also the candidate clusterhead nodes set

L The set of links

dThe max hop count to construct a cluster which is the longest distance between a cluster member and the selected clusterhead

Puv Candidate path set from node u to the node v

W The set of all O-D pairs

PodThe set of candidate paths for O-D pair (o,d) which will be included by Puv,

CnCapacity for the node n which is evaluated by residual battery power seconds

awTraffic demand for the O-D pair which is evaluated by transmission time seconds

Hw Maximum allowed hop count for the O-D pair w

pl 1 if the link l is on the path p, and 0 otherwise

pn 1 if the node n is on the path p, and 0 otherwise

xn(t) The x-axis coordinate of the node n at time t

yn(t) The y-axis coordinate of the node n at time t

Vx(t) The x-axis velocity of the node n at time t

Vy(t) The y-axis velocity of the node n at time t

tij The link duration between node i and node j

My work- notation

odq P

Decision variables

Notation Definition

hg 1 if node g is selected to be a clusterhead. 0 otherwise.

bvg 1 if node v belongs to cluster g. 0 otherwise

xpvg The node v choices the path p connect to the clusterhead g.

γvmn1 if node v is belong to the cluster m and is selected as the gateway to the cluster n.

ygl 1 if clusterhead g selects the link l for the cluster g construction

ηqod 1 if path is used to transmit the packet for the O-D pair w. Otherwise, 0.

My work- formulationmaxT WObjective function: Maximize the minimum link T

duration and node duration W

Subject to:

1vgg V

b

v V

vg gb h ,v g V

vg

pvg vgp P

x b

,v g V

(1)

pvg pL

x d

,vgp P v g V

1g vgL v V

y b

g V

vg

pvg pl gp P

x y

, v g V L

(2)

(4)

(3)

(5)

(6)

The cluster member belonging constraint

The intra-cluster routing constraint

The d-hop routing constraint

The intra-cluster routing constraint for sub-tree-construction

My work- formulation

CH

Constraint (3):Node v 到 CH間存在多條paths

v

Cluster member

Clusterhead

Constraint (5) (6):Node v 到 CH間存在多條paths

My work- formulation

,v m V

, , ,u v m n V

vmn vmb

(7)

1vmnv V

r

m V

gT y t ,g V L

1 2 3T t t t

( )uv vm un vmn unmb b

(2 2 2)vmn unm uv vm unb b

, , ,u v m n V

(8)

(9)

(10)

(11)

(12)

The cluster gateway node constraint

The cluster gateway node belonging constraint

The cluster connectivity constraint

The cluster duration constraint

t0 t0+t1 t0+t1+t2 t0+t1+t2+t3 t0+t1+t2+t3+TT

My work- formulation

Cluster m and CH m

Cluster n and CH n

Gateway node v, u between cluster m and n

Constraint (7) (8):The cluster gateway node constraint

若 u 、 v 兩個 nodes 相鄰 ( 存在有 hop count 為一的路徑 ) ，且 u 、 v 兩個 nodes 分屬不同的 cluster m 和 n 。則 u 、 v為兩 cluster 的 gateway node 。

uv umb vnb umn vnm

0 0 0 0 0

0 1 0 0 0

0 0 1 0 0

0 1 1 0 0

1 0 0 0 0

1 1 0 0 0

1 0 1 0 0

1 1 1 1 1

My work- formulation

1w

pp P

x

w W (13)

p pn wn V

x H

,wp P w W

w

p pl gp P

x y

w W L

w

n w p pn nw W p P

L a x C

n V

n n nW C L n V (18)

(14)

(17)

(15)

The O-D pair routing constraint

The node capacity constraint

( , ) p n,m Vngo d W P qod qn png pm qmx (16)

The inter-cluster routing constraint

My work- formulation

0 1gh or g V (19)

0 1vgb or ,v g V

0 1pvgx or ; ,uvp P u v V

0 1vmn or , ,v m n V

0 1gy or;g V L

0 1px or wp P

(20)

(21)

(23)

(22)

(24)

The integer constraint x 6

End

Thanks for your attention

Discussion