Wireless Sensor Networks (WSNs) are a particular type of distributed self-managed network with limited energy supply and communication ability. The most significant challenge of a routing protocol is the energy consumption and the extension of the network lifetime. Many energy-efficient routing algorithms were inspired by the development of Ant Colony Optimisation (ACO). However, due to the inborn defects, ACO-based routing algorithms have a slow convergence behaviour and are prone to premature, stagnation phenomenon, which hinders further route discovery, especially in a large-scale network. This paper proposes a hybrid routing algorithm by combining the Artificial Fish Swarm Algorithm (AFSA) and ACO to address these issues. We utilise AFSA to perform the initial route discovery in order to find feasible routes quickly. In the route discovery algorithm, we present a hybrid algorithm by combining the crowd factor in AFSA and the pseudo-random route select strategy in ACO. Furthermore, this paper presents an improved pheromone update method by considering energy levels and path length. Simulation results demonstrate that the proposed algorithm avoids the routing algorithm falling into local optimisation and stagnation, whilst speeding up the routing convergence, which is more prominent in a large-scale network. Furthermore, simulation evaluation reports that the proposed algorithm exhibits a significant improvement in terms of network lifetime.

Power control techniques for IEEE 802.11 wireless networks have already gained much attention. Such techniques are particularly attractive because they can improve various aspects of wireless network operation such as interference mitigation, spatial reuse in dense wireless deployments, topology control, and link quality enhancement. However, until recently implementing such advanced power control using off-the-shelf wireless devices was not considered possible. For example, Abdesslem et al. [1] stated that ldquomany novel power control solutions cannot be efficiently implemented over existing IEEE 802.11 cardsrdquo. However, in this paper we demonstrate that power control is now feasible and can be implemented in current IEEE 802.11 cards with per-packet granularity and low power switching latency.