Improvement of non-uniform node deployment mechanism for corona-based wireless sensor networks

The promising technology of Wireless Sensor Networks (WSNs), lots of applications have been developed for monitoring and tracking in military, commercial, and educational environments. Imbalance energy of sensors causes significant reduction in the lifetime of the network. In corona-based Wireless Sensor Networks (WSNs), nodes that are positioned in coronas near the sink drain their energy faster than others as they are burdened with relaying traffic come from distant coronas forming energy holes in the network. This situation shows significant effects on the network efficiency in terms of lifetime and energy consumption. The network may stop operation prematurely even though there is much energy left unused at the distant nodes. In this thesis, non-uniform node deployments and energy provisioning strategies are proposed to mitigate energy holes problem. These strategies concerns the optimal number of sensors required in each corona in order to balance the energy consumption and to meet the coverage and connectivity requirements in the network. In order to achieve this aim, the number of sensors should be optimized to create sub-balanced coronas in the sense of energy consumption. The energy provisioning technique is proposed for harmonizing the energy consumption among coronas by computing the extra needed energy in every corona. In the proposed mechanism, the energy required in each corona for balanced energy consumption is computed by determining the initial energy in each node with respect to its corona, and according to the corona load while satisfying the network coverage and connectivity requirements. The theoretical design and modeling of the proposed sensors placement strategy promise a considerable improvement in the lifetime of corona-based networks. The proposed technique could improve the network lifetime noticeably via fair balancing of energy consumption ratio among coronas about 9.4 times more than other work. This is confirmed by the evaluation results that have been showed that the proposed solution offers efficient energy distribution that can enhance the lifetime about 40% compared to previous research works

Energy-efficient routing protocols in heterogeneous wireless sensor networks

Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints and limited battery energy. The usage of cheap and tiny wireless sensors will allow very large networks to be deployed at a feasible cost to provide a bridge between information systems and the physical world. Such large-scale deployments will require routing protocols that scale to large network sizes in an energy-efficient way. This thesis addresses the design of such network routing methods. A classification of existing routing protocols and the key factors in their design (i.e., hardware, topology, applications) provides the motivation for the new three-tier architecture for heterogeneous networks built upon a generic software framework (GSF). A range of new routing algorithms have hence been developed with the design goals of scalability and energy-efficient performance of network protocols. They are respectively TinyReg - a routing algorithm based on regular-graph theory, TSEP - topological stable election protocol, and GAAC - an evolutionary algorithm based on genetic algorithms and ant colony algorithms. The design principle of our routing algorithms is that shortening the distance between the cluster-heads and the sink in the network, will minimise energy consumption in order to extend the network lifetime, will achieve energy efficiency. Their performance has been evaluated by simulation in an extensive range of scenarios, and compared to existing algorithms. It is shown that the newly proposed algorithms allow long-term continuous data collection in large networks, offering greater network longevity than existing solutions. These results confirm the validity of the GSF as an architectural approach to the deployment of large wireless sensor networks