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

Chakradhar Penumalli,Yogesh Palanichamy

doi:10.1155/2015/842346

Chakradhar Penumalli, Yogesh Palanichamy

Open Access

https://doi.org/10.1155/2015/842346

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Journal: TheScientificWorldJournal	Publication Date: Jan 1, 2015
Citations: 30	License type: CC BY 3.0

Affiliation: Anna University, Chennai

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.

Highlights

Mobile ad hoc networks appear in a wide variety of applications such as the military, disaster relief, surveillance, sensing, and monitoring
The simulation results of some energy efficient Connected Dominating Set (CDS) algorithms are compared with our energy efficient optimal CDS algorithm with activity scheduling
We present simulations that illustrate the results of the algorithm and analyse the behaviour of our algorithm in various scenarios

Summary

Introduction

Mobile ad hoc networks appear in a wide variety of applications such as the military, disaster relief, surveillance, sensing, and monitoring. REd is calculated at regular intervals, if this ratio for the dominator becomes less than the threshold (TH) it will choose another equivalent node and performs activity scheduling. In this algorithm we have put TH as 10% of Emax because of energy requirement. N, ΔT: random time interval, δT: small time interval used for activity scheduling, Φ: null set (or) empty set, n: number of nodes in the network, s: time duration, REd: the residual energy of the dominator, Ecur: current residual energy, DEs: the energy dissipated during duration “s,” |OPT|: the optimal value, |MCDS|: size of MCDS

Literature Survey

Proposed Work

Simulation Results