Dynamic energy efficient routing protocol for wireless ad-hoc and sensor network

Currently IEEE 802.11 standard for ad-hoc wireless mode is not sufficient for multi-hop mesh. Recent efforts for the advancement of 802.11 standards, such as 11e for QoS support or 11n for high data rates (100Mbps), are still limited due to their inherent dependency upon the wired infrastructure backbones and single- hop wireless communication. One major challenge in quality-of-service (QoS) oriented routing in wireless ad-hoc networks is to find a route satisfying multiple constraints that includes but not limited to minimizing energy consumption, delay, node failure and maximizing throughput. In the first part of this thesis, a novel dynamic energy efficient routing (DEER) protocol with guaranteed message delivery, maximum network lifetime and message flow is proposed. DEER uses those specific nodes for relaying message from source to destination which have maximum residual energy above some defined energy level. The model is evaluated based on the comparison with Dijkstra, Geographic Location Aware-DEER, and Random neighbor selection models. In the second part of this thesis, another routing protocol is proposed and evaluated for monitoring electrical power generators to be used in the smart grid environment. The protocol works by dynamically selecting data source initiators (called leaders) using LEADER (Leader Election in Ad Hoc Networks for Efficient Routing) algorithm, and the round robin scheduling of the cluster heads. All the nodes in the network have the provision to be selected as a cluster head which then changes the prospective leaders as well. There are four variant of the proposed LEADER protocols based on the type of traffic: basic homogeneous and heterogeneous, improved homogeneous and heterogeneous. All the four variants of LEADER protocol are simulated and evaluated with different performance parameters (message flow, energy consumption, energy harvesting, node failure, etc.). LEADER protocol initiates new type of challenges (scalability, energy usage, failure, etc.) when being employed in smart grid consisting of large number of power generators. Both the protocols are developed based on the energy harvesting issue present in sensor network. Ambient energy sources are used for sensor recharging in the LEADER protocols and proper sustainability curve is provided for choosing the optimum parameters for different application specific scenarios in smart grid monitoring.