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An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks.

Penumalli C, Palanichamy Y - ScientificWorldJournal (2015)

Bottom Line: The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN].The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks.The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Science & Technology, Anna University, Chennai 600025, India.

ABSTRACT
A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results.

No MeSH data available.


Related in: MedlinePlus

The energy efficient optimal CDS maintenance phase after ΔT time with new nodes 29 and 31. Moved-out node 17, drained-out node 5.
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fig6: The energy efficient optimal CDS maintenance phase after ΔT time with new nodes 29 and 31. Moved-out node 17, drained-out node 5.

Mentions: These phases are illustrated in Figures 4 and 5. According to the algorithm, all the dominators (BLACK) select the counterparts locally and perform activity scheduling. Here in the MANET node 5 selects node 2 as the counterpart and node 1 selects the union of node 8 and node 24 as counterparts, because their combined N1 list is equivalent to the neighbour list of node 1. Similarly node 17 and node 30 are counterparts. Node 18 selects union of node 25 and node 23 as the counterparts. Node 13 has no equivalent node or union of nodes with similar N1 list; in this case node 13 will not perform activity scheduling locally until an equivalent node/nodes join. When compared to other nodes node 13 drains out quickly. These cases are handled by maintenance phase. Activity scheduling is performed as shown in Figure 6. Nodes {(2,5), (1, (8,24)), (17,30), (18, (23,25))} perform activity scheduling locally. BLACK slashed lines (active connection) and RED slashed lines (inactive connection) indicate the scheduling. When compared to other algorithms the dominators will not run out of energy and lifetime of the network increases as shown in Figure 5.


An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks.

Penumalli C, Palanichamy Y - ScientificWorldJournal (2015)

The energy efficient optimal CDS maintenance phase after ΔT time with new nodes 29 and 31. Moved-out node 17, drained-out node 5.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4477438&req=5

fig6: The energy efficient optimal CDS maintenance phase after ΔT time with new nodes 29 and 31. Moved-out node 17, drained-out node 5.
Mentions: These phases are illustrated in Figures 4 and 5. According to the algorithm, all the dominators (BLACK) select the counterparts locally and perform activity scheduling. Here in the MANET node 5 selects node 2 as the counterpart and node 1 selects the union of node 8 and node 24 as counterparts, because their combined N1 list is equivalent to the neighbour list of node 1. Similarly node 17 and node 30 are counterparts. Node 18 selects union of node 25 and node 23 as the counterparts. Node 13 has no equivalent node or union of nodes with similar N1 list; in this case node 13 will not perform activity scheduling locally until an equivalent node/nodes join. When compared to other nodes node 13 drains out quickly. These cases are handled by maintenance phase. Activity scheduling is performed as shown in Figure 6. Nodes {(2,5), (1, (8,24)), (17,30), (18, (23,25))} perform activity scheduling locally. BLACK slashed lines (active connection) and RED slashed lines (inactive connection) indicate the scheduling. When compared to other algorithms the dominators will not run out of energy and lifetime of the network increases as shown in Figure 5.

Bottom Line: The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN].The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks.The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Science & Technology, Anna University, Chennai 600025, India.

ABSTRACT
A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results.

No MeSH data available.


Related in: MedlinePlus