Energy-efficient Scalable Self-organizing Routing for Wireless Mobile Networks

2012 ◽  
pp. 390-406
Author(s):  
Melody Moh ◽  
Xuquan Lin ◽  
Subhankar Dhar
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Medium Access ◽  
Hierarchical Routing ◽  
Time Space ◽  
Power Saving Mode ◽  
Saving Mode ◽  
Hoc Networks ◽  
Self Organizing

The instant deployment without relying on an existing infrastructure makes the mobile ad hoc networks (MANET) an attractive choice for many dynamic situations. An efficient MANET protocol may be applied to other important emerging wireless technologies such as wireless mesh and sensor networks. This chapter proposes a hierarchical routing scheme that is scalable, energy-efficient, and self-organizing. This chapter presents a new algorithm: the Dynamic Leader Set Generation (DLSG). This algorithm dynamically selects leader nodes based on traffic demand, locality, and residual energy level, and de-selects them based on residual energy. Therefore, energy consumption and traffic load are distributed throughout the network. The network also reorganizes itself surrounding the dynamically selected leader nodes. Time, space, and message complexities are formally analyzed; implementation issues are also addressed. Incorporating the IEEE 802.11 medium access control mechanism including the power saving mode, performance evaluation is carried out by simulating DLSG and four existing hierarchical routing algorithms. It shows that DLSG successfully extends network lifetime by 20-50% while achieves a comparable level of network performance.

Energy-efficient Scalable Self-organizing Routing for Wireless Mobile Networks

2011 ◽  
pp. 291-307
Author(s):  
Melody Moh ◽  
Xuquan Lin ◽  
Subhankar Dhar
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Medium Access ◽  
Hierarchical Routing ◽  
Time Space ◽  
Power Saving Mode ◽  
Saving Mode ◽  
Hoc Networks ◽  
Self Organizing

The instant deployment without relying on an existing infrastructure makes the mobile ad hoc networks (MANET) an attractive choice for many dynamic situations. An efficient MANET protocol may be applied to other important emerging wireless technologies such as wireless mesh and sensor networks. This chapter proposes a hierarchical routing scheme that is scalable, energy-efficient, and self-organizing. This chapter presents a new algorithm: the Dynamic Leader Set Generation (DLSG). This algorithm dynamically selects leader nodes based on traffic demand, locality, and residual energy level, and de-selects them based on residual energy. Therefore, energy consumption and traffic load are distributed throughout the network. The network also reorganizes itself surrounding the dynamically selected leader nodes. Time, space, and message complexities are formally analyzed; implementation issues are also addressed. Incorporating the IEEE 802.11 medium access control mechanism including the power saving mode, performance evaluation is carried out by simulating DLSG and four existing hierarchical routing algorithms. It shows that DLSG successfully extends network lifetime by 20-50% while achieves a comparable level of network performance.

Energy-Efficient Self-Organizing Routing for Wireless Mobile Networks

2009 ◽  
Vol 5 (4) ◽  
pp. 52-69 ◽  
Author(s):  
Melody Moh ◽  
Rashmi Kukanur ◽  
Xuquan Lin ◽  
Subhankar Dhar
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Network Performance ◽  
Power Saving ◽  
Residual Energy ◽  
Traffic Load ◽  
Hierarchical Routing ◽  
Traffic Demand ◽  
Time Space ◽  
Self Organizing

The instant deployment without relying on an existing infrastructure makes mobile ad hoc networks (MANET) a striking choice for many dynamic situations. An efficient MANET protocol may be applied to other important emerging wireless technologies, such as wireless mesh and sensor networks. This article proposes a hierarchical routing scheme that is scalable, energy efficient, and self-organizing. The new algorithm that is discussed in this article is the Dynamic Leader Set Generation (DLSG). This algorithm dynamically selects leader nodes based on traffic demand, locality, and residual energy level, and de-selects them based on residual energy. Therefore, energy consumption and traffic load are balanced throughout the network, and the network reorganizes itself around the dynamically selected leader nodes. Time, space, and message complexities are formally analyzed and implementation issues are also addressed. Incorporating the IEEE 802.11 medium access control mechanism and including the power saving mode, performance evaluation is carried out by simulating DLSG and four existing hierarchical routing algorithms. It shows that DLSG successfully extends network lifetime by 20 to 50% while achieving a comparable level of network performance.

A Reliable Energy Efficient Wireless Sensor Network Hierarchical Routing Algorithm

2013 ◽  
Vol 475-476 ◽  
pp. 569-572
Author(s):  
Kai Guo Qian ◽  
Lin Ou
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Hierarchical Routing

The existing clustering protocols exists shortages that the nodes with small residual energy may be choose as cluster nodes, which communicate directly with sink causes more energy consumption. Member nodes transmit data directly to cluster head also caused more energy consumption. A reliable energy efficient wireless sensor network hierarchical routing algorithm (REHRA) is proposed to further improve energy efficiency. It introduces residual energy factor for election of heads that makes nodes with more residual energy priority become heads. The data transmission for heads to sink uses flooding algorithm that ensures reliability. Routing tree is formed within local cluster and data delivers from leaf nodes to the cluster head. Performance analysis and simulation experiment shows that the new algorithm provides higher energy efficiency and longer lifetime.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

Sign in / Sign up

Export Citation Format

Share Document