Detailed Design and Implementation Robust Networking architecture Construction of chnetarch CHNetArch Self-Formation Reconfiguration Data routing/relay a General Assumptions Communication range: H-node(D)and L-node(d Algorithms run in rounds .o Each round consists of I transmission, I reception, and data processing 口 Data structures H-node: list of L-nodes in its region, parent and children on the backbone tree L-node: cluster head, region head Cluster head: its cluster member list, the parent and children on the backbone tree
Detailed Design and Implementation – Robust Networking Architecture ❑ General Assumptions ➢ Communication range: H-node (D) and L-node (d) ➢ Algorithms run in rounds. ❖ Each round consists of 1 transmission, 1 reception, and data processing ❑ Data Structures ➢ H-node: list of L-nodes in its region, parent and children on the backbone tree ➢ L-node: cluster head, region head ❖ Cluster head: its cluster member list, the parent and children on the backbone tree CHNetArch Data routing/relay Self-Formation Reconfiguration Construction of CHNetArch 16
Detailed Design and Implementation Robust Networking Architecture(CHNetArch CHNetArch Self-formation Head rotation Node move-in Node move-out
17 CHNetArch Self-formation Head Rotation Node Move-in Node Move-out Detailed Design and Implementation – Robust Networking Architecture (CHNetArch)
Detailed Design and Implementation Robust Networking Architecture(CHNetArch) Self-formation of chnetarch Cluster member Step3-Allyorithmforilag SINK Cluster head Regional head L-hode Rdgipadead RouRleggdbalrtdaiskboeieytrees farad eedipoadadstathieir lEsaeddres ICes eeeiueddttedeglsaneealegb b PLaster Yith strongest signal HE The active nodes find children then nasac tinedes erem casters bycshoesinw th ghboring node with the lowest id to be repeats unti regional backbone tree is complete B- Connect Regional backbone trees Sink and regional heads form a tree rooted t the sink in the same way as regional backbone tree formation H
L-node H H SINK H H H H H H SINK Cluster head Cluster member Regional head Step 1 – Algorithm for region formation Round 1 H-nodes broadcast their IDs and Lnodes receive H-nodes IDs and select H-node with strongest signal 18 Self-formation of CHNetArch Region head H-node Step 2 – Algorithm for cluster formation A – Neighbor discovery Round 1 L-nodes broadcast their IDs and receive IDs B – Clustering Rounds 1 - 4 L-nodes form clusters by choosing the neighboring node with the lowest ID to be its cluster head Step 3 – Algorithm for BT formation A – Regional backbone trees Start at region head: region head becomes active Rounds 1 – 3 (1) The active nodes find children, then turn to inactive (2) Then the children become active The above process repeats until the regional backbone tree is complete B – Connect Regional backbone trees Sink and regional heads form a tree rooted at the Sink in the same way as regional backbone tree formation Detailed Design and Implementation – Robust Networking Architecture (CHNetArch)
Detailed Design and Implementation Robust Networking Architecture(CHNetArch) Theorem 1 Given a heterogeneous wireless sensor network (HWSN), its cluster-based hierarchical networking architecture (CHNetArch) can be formed in O(T) rounds, where T is the height of the backbone tree of CHNetarch
19 Theorem 1 Given a heterogeneous wireless sensor network (HWSN), its cluster-based hierarchical networking architecture (CHNetArch) can be formed in O(T) rounds, where T is the height of the backbone tree of CHNetArch. Detailed Design and Implementation – Robust Networking Architecture (CHNetArch)