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Critical Transmission Range for Mobile Clustered Wireless Networks. Qi Wang, Liang Liu, Xinbing Wang Department of Electronic Engineering Shanghai Jiao Tong University, China. Outline. Preliminary knowledge Wireless Network Structure I.I.D . model K-Hop in mobile network - PowerPoint PPT Presentation
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Critical Transmission Range for Mobile Clustered Wireless Networks
Qi Wang, Liang Liu, Xinbing WangDepartment of Electronic EngineeringShanghai Jiao Tong University, China
2
OutlinePreliminary knowledge
Wireless Network Structure I.I.D. modelK-Hop in mobile networkNetwork Deployment
Network model
Main results
Discussion
Wireless Network Structure
BS
BS
MN
MN
MN
MN
Wireless Network Structure
cluster headcluster member transmission range
r
Wireless Network Structure
Mobility Model - I.I.D. Model
At the beginning of each time slot, each cluster member
node randomly and uniformly choose a position within
the region and remain static for the rest of the time slot.
[1] Wang Q, Wang X, Lin X. Mobility increases the connectivity of k-hop clustered wireless networks[C]//Proceedings of the 15th annual
international conference on Mobile computing and networking. ACM, 2009: 121-132.
Explanation of -hop in mobile network
Data transmission is divided into time slots.
For each cluster member node, if it can move within the transmission region of a certain cluster
head in time slots, then it is connected. Otherwise it is disconnected.
If all the member nodes are connected, then the network is fully connected.
Explanation of -hop in mobile network
Connectivity illustration
connected node
disconnected node
Network Deployment
Cluster head nodes are initially distributed randomly and uniformly within the unit square and always
remain static. There is a path that connects all the cluster heads in the initial graph .
Cluster member nodes are initially distributed randomly and uniformly within the unit square and move
according to the I.I.D. model. If at time slot , member node is within the transmission range of head ,
an edge is added to .
The number of cluster member nodes is .
The number of cluster heads is , where is the cluster head exponent, and .
log 1, 1cnr
k n k
Previous result:
10
Outline
Preliminary knowledge
Network modelNetwork ParametersCorrelated Mobility ModelCluster Scalability
Main results
Discussion
Network Parameters
: the number of clusters.
: the radius of each cluster.
: the number of nodes in each cluster.
[2] Ciullo D, Martina V, Garetto M, et al. Impact of correlated mobility on delay-throughput performance in mobile ad hoc networks[J].
IEEE/ACM Transactions on Networking (TON), 2011, 19(6): 1745-1758.
Correlated Mobility Model
After deploying the initial network architecture, the cluster heads will remain stationary while the
cluster members will move.
The movement of a cluster-member node consists of two steps.
The movement of home point. At the beginning of each time slot, each home point will
randomly and independently choose a position within the unit square.
The relative movement of cluster member. Each cluster member will uniformly and
independently choose its location within its corresponding cluster region.
Correlated Mobility Model
Correlated Mobility illustration
Cluster Scalability
: cluster-sparse state.
: cluster-dense state.
: cluster-inferior dense state.
Cluster Scalability
Correlated Mobility and Cluster Scalability
16
Outline
Preliminary knowledge
Network Model
Main ResultsCritical Transmission RangeMain Results
Discussion
Critical Transmission Range
Connectivity with probability (w.p.):
Let denote the event that the network with cluster member nodes is fully connected, then is the critical transmission
range with which the network will be connected with probability (w.p.) if
if and ;
if and .
Critical Transmission Range
Connectivity almost surely (a.s.):
Let denote the event that the network with cluster member nodes is fully connected, then is the critical transmission
range with which the network will be connected almost surely (a.s.) if
if and ;
if and .
“lim inf” denotes limit inferior of a sequence of events and
“lim sup” denotes limit superior of a sequence of events and
Main Results
Cluster-sparse state:
Cluster-dense state:
Cluster-inferior dense state:
Cluster-mixed state (w.p.):
Cluster-mixed state (a.s.):
Main Results
Cluster-Sparse State (, )
Proposition 1: Let denote the probability that the network is disconnected. If , where , , and , we have
. ._inf ( , , ,l ) (1 )im , w pf css cn
n r e e
P
Main Results
Cluster-Sparse State (, )
.
1_
1
. ( )( , , , , ) ( ) ( )w pf c
m m
i i ji i j i
ss c F F Fn r
P P P
Clustering effect is dominant in this state.
() is due to the principle of inclusion-exclusion.
denotes the probability that the th cluster is disconnected.
, .
. . logw pc
nrk n
Main Results
Cluster-Dense State (, )
Cluster members behave more like independent nodes.
, .
. . logw pc
nrk n
Main Results
Cluster-Inferior Dense State (, )
Cut out non-overlapping circular areas (sub-areas), with radius .
Considering time slots, we obtain sub-clusters.
, , .
. . [ ( 2 ) ]logw pc
k nrk n
Main Results
Cluster-Inferior Dense State (, )
E.g.
sub-area during time slot ,
sub-area during time slot ,
sub-area during time slot ,
sub-area during time slot .
We use a sequence to denote a sub-cluster, where , .
A node if and only if is in sub-area during time slot .
Main Results
Cluster-Mixed State (w.p.)
This state is a generalization of the three separate states.
In this state, we denote the network as , the th cluster has members and radius .
, , . There is no linear relation between and .
32( 2 )
11 1
i
mmk
ii i
m m n
: number of clusters in the cluster-sparse state ().
: number of clusters in the cluster-inferior dense state ().
: number of clusters in the cluster-dense state ().
Main Results
. . logw pc
mrk n
Cluster-Mixed State (w.p.)
denotes the number of node groups in the whole network.
Main Results
Cluster-Mixed State (a.s.)
. . . . 2log2a s w pc c
mr rk n
A stronger connectivity condition than w.p. connectivity.
Major approach: Borel-Cantelli lemma.
Price from w.p. connectivity to a.s. connectivity: .
28
Outline
Preliminary knowledge
Network Model
Main Results
Discussion
Discussion
Comparisonbetween correlatedmobility∧ i . i . d .mobility
𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐦𝐨𝐛𝐢𝐥𝐢𝐭𝐲𝐚𝐧𝐝 𝐜𝐥𝐮𝐬𝐭𝐞𝐫 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐜𝐚𝐧𝐡𝐞𝐥𝐩𝐬𝐚𝐯𝐞𝐭𝐫𝐚𝐧𝐬𝐦𝐢𝐬𝐬𝐢𝐨𝐧 𝐩𝐨𝐰𝐞𝐫 .
Discussion
Price from w.p. connectivity to a.s.
connectivity:
Thank you!