ABSTRACT

This PhD thesis endorses the research hypothesis through the proposal of an algorithm for Wireless Sensor Netwoks (WSNs) that is energy, delay and throughput efficient, and supports mobility. The author developed energy-efficient hybrid cross-layer routing algorithms using multi-objective optimization for the WSNs that are useful for Internet of Things (IoT) applications.

The PhD thesis addresses the challenge of green multi-objective hybrid routing, focuses on the development of multi-objective hybrid routing algorithms, investigates the mobility, heterogeneity aware routing in WSN, reveals a smart method of sensor node deployment meeting criterion and explores the business model with focusing points on VANET and cloud computing. The major contribution of the thesis lies in designing Multi-Objective hybrid routing methods that are energy efficient. Further, the thesis explores the use of cross-layer optimizations to enhance energy efficiency of the proposed routing methods. The PhD work constitutes a solid body of applied research that has following main contributions:

• Original MOHRA designed in view of hierarchical, cluster-based networks. Based on a critical analysis Multi-objective Hybrid Solutions for WSNs provides significant improvements regarding energy savings, throughput, and packet delivery.
• Proposed algorithm MMOHRA designed for hierarchical network topologies with mobile sensor nodes. MMOHRA deals with dynamically changing connections due to mobility.
• G-MOHRA routing mechanism, which uses hierarchical clustering for static sensor nodes. G-MOHRA utilizes independent metrics that are said to be clashing with one another and delivers Pareto-optimal solutions.
• QoS Assured MOHRA algorithm designed for Heterogeneous WSN. QMOHRA balances the performance of the network in different traffic conditions. Satisfying linking among the nodes and exploiting the network lifespan is needed consideration in WSN. To tackle these two problems, the thesis explores MOHRA for heterogeneous WSNs (H-MOHRA).

All proposed schemes extend the network lifetime, and they are efficient despite the scarcity of resources. In WSN, deciding ideal node location of sensor nodes is a very exciting and difficult task. The research investigates different deployment strategies and recommends an innovative positioning policy called as QRD to escalate the lifespan of WSN. The performance of QRD compared with the traditional random and fixed node deployment strategies in WSN. A novel idea for the convergence of VANET and Cloud is presented here as a case study for MOHRA, taking into accounts IoT vehicular applications. The prime goal of this work is utilize MOHRA for routing VANET data to the sink and further sending it on cloud. Furthermore, the contribution of the proposed system is that it reduces storage overhead on the cloud server. Taxonomy of VCC is also the substantial contribution of this thesis to give scope to VANET and Cloud researchers. The contributions have resulted in one book chapter; three published peer-reviewed international journal papers; and eight peer-reviewed international conference publications.

PhD supervisor:
Professor Ramjee Prasad, CTIF Global Capsule (CGC), Department of Business Development and Technology, Aarhus University, Herning, Denmark.

PhD co-supervisor:
Professor Neeli Rashmi Prasad, International Technological University (ITU), San Jose, USA.

PhD committee:
Dr. Sofoklis Kyriazakos, Associate Professor, Business Development and Technology, Aarhus University, Chairman of Assessment Committee

Professor Kwang Cheng Chen, Department of Electrical Engineering, University of South Florida, Member of Assessment Committee

Professor Frederic Harris, Department of Electrical and Computer Engineering, University of California San Diego, Member of Assessment Committee