Cross-layer optimized routing in wireless sensor networks with duty cycle and energy harvesting

In this paper, we propose a cross-layer optimized geographic node-disjoint multipath routing algorithm, that is, two-phase geographic greedy forwarding plus. To optimize the system as a whole, our algorithm is designed on the basis of multiple layers' interactions, taking into account the following. First is the physical layer, where sensor nodes are developed to scavenge the energy from environment, that is, node rechargeable operation (a kind of idle charging process to nodes). Each node can adjust its transmission power depending on its current energy level (the main object for nodes with energy harvesting is to avoid the routing hole when implementing the routing algorithm). Second is the sleep scheduling layer, where an energy-balanced sleep scheduling scheme, that is, duty cycle (a kind of node sleep schedule that aims at putting the idle listening nodes in the network into sleep state such that the nodes will be awake only when they are needed), and energy-consumption-based connected k-neighborhood is applied to allow sensor nodes to have enough time to recharge energy, which takes nodes' current energy level as the parameter to dynamically schedule nodes to be active or asleep. Third is the routing layer, in which a forwarding node chooses the next-hop node based on 2-hop neighbor information rather than 1-hop. Performance of two-phase geographic greedy forwarding plus algorithm is evaluated under three different forwarding policies, to meet different application requirements. Our extensive simulations show that by cross-layer optimization, more shorter paths are found, resulting in shorter average path length, yet without causing much energy consumption. On top of these, a considerable increase of the network sleep rate is achieved.