Topology Cluster-Tree Characterization

The network formation of th eIEEE 802.15.4 does not impose constraints on the topology. The ZigBee alliance uses the IEEE 802.15.4 layers to build a complete  protocol stack for the implementation of wireless sensor networks. ZigBee specifies the network layer for star, tree and peer-to-peer topologies. Starting from these, more complex cluster tree topologies can be formed. To control the network topology, ZigBee fixes the maximum number of routers and end-devices that each router may have as children and also fixes the maximum depth of the tree.In this paper, the authors simulate and analyze the IEEE 802.15.4 formation procedure in different network settings (single-sink and multi-sink scenario).

The contribution is the analysis of both networks where a single sink is present and networks where multiple sinks are used. Special attention is given of cluster-tree height statistics as well as the statistics of the number of children per node.

Simulation Model :
The network scenario consisting of N sensor nodes and S sinks (PAN coordinators). The sensor nodes are randomly deployed in a dquare of side L and area A = L^2. All nodes are static.

aBaseSuperframeDuration = aBaseSlotDuration * aNumSuperframeSlots.
Set BO = SO = 7, BO = SO means no active part of the superframe present. A low value of BO and SO imply a great probability of collision of beacon frames, since these would be transmitted very frequently by coordinators. On the other hand, a high value of BO introduces a significant delay in the time required to perform the MAC association procedure, since the duration of the channel scan (part of the association procedure) is proportionalto BO. The power aatenuation nodes follows an inverse power law, and random channel flctuations.
La = K0 + K1 ln r + s
(check to paper)

In case of single sink scenario, the sink is always located in the centre of the monitored region. In case of multiple sinks these are randomly deployed in the area.

Simulation Metrics ;
– the mean number of children per parent.
– the max number of children per parent.
– the tree height, computed as the maximum tree depth

The results :
– Probability density function of the tree height T, single  scenario.
– Mean number of children per parent as a function of the parent level with  95% confidence interval, single sink scenario.
– Maximum number of children per parents as a function of the parent level, single sink scenario.
– Mean number of children per parent as a function of the parent level for tree with T = 6,8, and 10, single scenario.
– Cumulative distribution Function of the tree height T, multi-sink scenario
– Mean number of children per parents as a function of the parent level with 95% confidence interval, multi-sink scenario.
– Probability that a% of nodes are connected to the network as a function of T_Max.

Source :

Overview if the IEEE 802.15.4/4a standards for low data rate Wireless Personal Data Networks.
ByLuaca De Bardis and Maria-Gabriella

Note : This resume is created for self-learning only. Author and Publisher hold copyrights

Difficulties  make strong

October 27, 2008
Taipei City
High Speed Network Lab

Udin Harun

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