An adaptive localized scheme for energy-efficient broadcasting in ad hoc networks with directional antennas

Abstract. Several solutions for energy-efficient broadcasting, mostly centralized, have been proposed with directional antennas. However, such globalized protocols are not suitable for ad hoc networks, because each node needs a full knowledge of the topology. Recently, a localized algorithm, called DRBOP, using one-to-one communication model has been proposed. It uses RNG graphs, which can be locally computed by each node. However, for energy consumption reasons, it can be useful to reach more than one neighbor at a time. In this paper, we propose an efficient protocol which uses both one-to-one and one-to-many communication models. First, we present a variant of DRBOP efficient for sparse networks, based on LMST graph which is a local adaptation of minimal spanning tree. Then, a one-to-many protocol efficient for dense networks is proposed. From these two algorithms we derive an adaptive protocol which is shown to be efficient for both sparse and dense networks.

Development of an efficient Ad Hoc broadcasting scheme for critical networking environments

Mobile ad hoc network has been widely deployed in support of the communications in hostile environment without conventional networking infrastructure, especially in the environments with critical conditions such as emergency rescue activities in burning building or earth quick evacuation. However, most of the existing ad hoc based broadcasting schemes either rely on GPS location or topology information or angle-of-arrival (AoA) calculation or combination of some or all to achieve high reachability. Therefore, these broadcasting schemes cannot be directly used in critical environments such as battlefield, sensor networks and natural disasters due to lack of node location and topology information in such critical environments. This research work first begins by analyzing the broadcast coverage problem and node displacement form ideal locations problem in ad hoc networks using theoretical analysis. Then, this research work proposes an efficient broadcast relaying scheme, called Random Directional Broadcasting Relay (RDBR), which greatly reduces the number of retransmitting nodes and end-to-end delay while achieving high reachability. This is done by selecting a subset of neighboring nodes to relay the packet using directional antennas without relying on node location, network topology and complex angle-of-arrival (AoA) calculations. To further improve the performance of the RDBR scheme in complex environments with high node density, high node mobility and high traffic rate, an improved RDBR scheme is proposed. The improved RDBR scheme utilizes the concept of gaps between neighboring sectors to minimize the overlap between selected relaying nodes in high density environments. The concept of gaps greatly reduces both contention and collision and at the same time achieves high reachability. The performance of the proposed RDBR schemes has been evaluated by comparing them against flooding and Distance-based schemes. Simulation results show that both proposed RDBR schemes achieve high reachability while reducing the number of retransmitting nodes and end-to-end delay especially in high density environments. Furthermore, the improved RDBR scheme achieves better performance than RDBR in high density and high traffic environment in terms of reachability, end-to-end delay and the number of retransmitting nodes

Simulating Network Structure, Layering Multi-layer Network System and Developing Network Block Configuration Model to Understand and Improve Energy Conservation in Residential Buildings

The building sector is a major contributor to total energy consumption in most countries. Traditionally, researchers have focused on leveraging energy efficiency by improving building materials, in-house facilities and transmission equipment. More recently, however, there has been increased focus on research concerning demand-side energy consumption behavior. Current research suggests that energy efficient behavior of a building's occupants can be extensively enhanced through the sharing of energy consumption information among residents in a peer network. However, most of this research relies on experimental tests and does not theorize concepts related to peer network energy efficiency systematically. My dissertation addresses this research gap on two levels. First, I examined if and how the structure of peer networks can impact residents' conservation behaviors through network analysis by employing agent-based simulation techniques. Following confirmation of the impact that network structure has on user behavior, I created a layered network model to integrate information from various network layers and a block configuration model to reconstruct increasingly reliable random networks. In contrast to controlled energy efficiency experiments, real-world networks are large in size, heterogeneous in nature and regularly interact with other networks. By utilizing models developed in this dissertation, we are able to estimate the contribution of network structural coefficients to the energy consumption performance of peer networks. By comparing the layered network and block configuration model I developed with other conventional models, I prove the efficiency, accuracy and reliability of these improved models. These findings have implications for assessing network performance, creating accurate complex random networks for large-scale research, and developing strategies for network design to improve building energy efficiency. This research establishes a system to study residents' energy efficient behaviors from the perspective of peer networks and proposes some instructive models for further energy feedback system design