1) Linked Cluster Algorithm (LCA) [5], [6], [7]:
LCA, was one of the initial clustering algorithms evolved. It was primarily developed for wired sensors, but later applied in wireless sensor networks. In LCA, a unique ID number is allotted to each node and has two means of becoming a cluster head. The first way is that if the node has the greatest ID number in the set including all neighbor nodes and the node itself. The second way is to assume that none of its neighbors are cluster heads, then it becomes a cluster head. In this way, LCA search a solution which is surely not an optimal solution.
2) Linked Cluster Algorithm (LCA) [5], [6], [7]:
LCA2 was anticipated to reduce the selection of an unnecessary number of cluster heads, as in LCA. In LCA2, the concept of a node being covered and non-covered was introduced. A node is considered as covered if one of its neighbors is a cluster head. Cluster heads are primarily selected from nodes which are having lowest ID among non-covered neighbors. Again the probability of achieving success is less.
3) Highest-Connectivity Cluster Algorithm [7]:
This algorithm is analogous to LCA. In …show more content…
This algorithm offers a load balancing among cluster heads. The cluster head selection criteria are developed by having each node initiate 2d rounds of flooding, from that the results are logged. Then every node follows a simple set of rules to determine their respective cluster head. The first d rounds are referred to as flood max, used to propagate the largest node IDs. After this is complete, the second d rounds of flooding occur. This round is called flood min, used to allow the smaller node ids to reclaim a number of their territory. Then every node evaluates the logged entries following the rules listed
LCA, was one of the initial clustering algorithms evolved. It was primarily developed for wired sensors, but later applied in wireless sensor networks. In LCA, a unique ID number is allotted to each node and has two means of becoming a cluster head. The first way is that if the node has the greatest ID number in the set including all neighbor nodes and the node itself. The second way is to assume that none of its neighbors are cluster heads, then it becomes a cluster head. In this way, LCA search a solution which is surely not an optimal solution.
2) Linked Cluster Algorithm (LCA) [5], [6], [7]:
LCA2 was anticipated to reduce the selection of an unnecessary number of cluster heads, as in LCA. In LCA2, the concept of a node being covered and non-covered was introduced. A node is considered as covered if one of its neighbors is a cluster head. Cluster heads are primarily selected from nodes which are having lowest ID among non-covered neighbors. Again the probability of achieving success is less.
3) Highest-Connectivity Cluster Algorithm [7]:
This algorithm is analogous to LCA. In …show more content…
This algorithm offers a load balancing among cluster heads. The cluster head selection criteria are developed by having each node initiate 2d rounds of flooding, from that the results are logged. Then every node follows a simple set of rules to determine their respective cluster head. The first d rounds are referred to as flood max, used to propagate the largest node IDs. After this is complete, the second d rounds of flooding occur. This round is called flood min, used to allow the smaller node ids to reclaim a number of their territory. Then every node evaluates the logged entries following the rules listed