For a smart grid network, the communication infrastructure is an important part to provide the stability and reliability. To build an efficient communication network is crucial for the success of a smart grid network. This study improves the previous published work by proposing two novel evolutionary heuristic approaches (discrete differential evolutionary clustering approach and particle swarm optimisation clustering approach) to obtain the minimum number and location of the powerful nodes to fulfil the connectivity requirement of a smart meters network. The contribution of this study includes the designing and implementing of the two novel evolutionary heuristic approaches which could significantly improve the optimal solution [the least number of the local data centres (powerful nodes)] for a smart meter network which has arbitrary number of smart meters (ordinary nodes) with arbitrary transmission range. Comprehensive case studies and numerical statistical analysis demonstrate that the approaches could efficiently obtain better optimal results, and the connectivity of the smart meter network could be fulfilled with minimum number of the powerful nodes.

The traditional network architecture cannot meet the growing needs of increasingly diverse network applications. The new generation network architectures, software defined network (SDN) which have features of high openness, flexibility, scalability and high controllability have widely been studied. However, a series of new problems are also produced in this new architecture, such as security problem resulted from the high openness, and performance problem resulted from the high flexibility. Currently, the researchers are mainly concentrated in the implementation and standardisation of SDN. There is no good approach to evaluate and optimise the system performance. This studies the performance problems unresolved in SDN research area, and proposed an idea and method to analyse the control channel of ForCES (Forwarding and Control Element Separation)-based SDN by using the stochastic network calculus theory. First, the architecture of ForCES-based SDN is introduced. Then, the performance model of the channel is given. Based on the model, an optimisation method to performance is detailed. This study also gives a simulation by using NS-2 (Network Simulator, Version 2) to verify the correctness and reliability of the performance model.

Proliferation in Micro-Electro-Mechanical-Systems (MEMS) technology along with advancement in distributed computing infrastructure has facilitated the versatile usage and deployment of wireless sensors networks (WSNs) in last one and half decades. WSNs support large number of applications from the civilian and military regimes. Irrespective of these regimes; owing to difficulty associated with battery replenishment, proper energy usage has been at centre stage in WSNs operations. The lifetime of WSNs typically depends upon sensor's energy dissipation pattern, which is non-homogeneous with respect to spatial distribution over any short epochs. The genesis behind this non-homogeneity is random generation of queries, which owes to application specific spatio-temporal parameters. Importance of spatio-temporal parameters is ubiquitous in WSNs paradigm and uncertainties are inevitable with these parameters, although the degree of uncertainties varies in accordance to applications served. Thus, from network design perspectives, precision involved with spatio-temporal aspects must be given due priority to obtain a mathematical model that maintains a good rapport with realistic query generation process. With these motivations, the study explores: (i) uses of energy-efficient clustering schemes, (ii) incorporation of spatio-temporal parameters uncertainties into probabilistic model of query generation using fuzzy-intervals bound, and (iii) sink attributes to enhance network lifetime. For various network surveillance scenarios; the performance measures average residual energy status and service-time-duration are estimated and analysed.