Efficient data-forwarding strategies for wireless sensor networks with a mobile sink which visits rendezvous points (RPs) to gather data from sensor nodes are proposed. With the first proposed strategy, selections of the RP nodes and the final routing paths are based on the latest information of the already selected RP nodes. The second proposed strategy adopts a simpler RP node-and routing path-selection algorithm with the same level of complexity of an existing algorithm. Numerical results show that both of the proposed strategies result in more efficient energy consumption and reduce forwarding hop counts compared with the existing algorithm.

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We propose a new paging strategy to reduce paging cost by adding paging agents at base stations. When a mobile‐terminated call occurs, the base stations look up the paging agents to determine if terminal paging is actually to be made. An analytical model based on a Markov chain is used to evaluate the performance of the proposed strategy. The numerical results show that the proposed strategy significantly reduces the paging cost compared with the simultaneous paging strategy.

The existing data-forwarding strategies in wireless sensor networks (WSNs) may not be feasible for some applications where synchronisation and physical location information are not available. A novel asynchronous data-forwarding strategy for energy-harvesting WSNs is proposed, where the sleep duration, wake-up moment and the transmission coverage of a sensor node are determined independently on a per-node basis. This strategy obviates the need for synchronisation control and the precise location information of the sensor node. The numerical results show that the data-forwarding delay can be significantly reduced by the proposed strategy. The reduction in the delay is more notable for WSNs with more sensor nodes.Introduction: When direct transmission from the source sensor nodes to the data sink is not feasible in a wireless sensor network (WSN), multihop forwarding strategies using other sensor nodes as relays are usually used [1][2][3][4]. This necessarily incurs a longer data-forwarding delay and additional energy consumption at the sensor nodes. Considering that the sensor nodes are equipped with batteries with limited electrical energy, a basic and efficient way to solve this problem is for the sensor nodes to stay asleep for a proper period of time and to wake-up intermittently for active jobs such as wireless communications. Based on this concept, many studies have attempted to find efficient data-forwarding strategies that satisfy the criteria of low energyconsumption levels and forwarding delays, with many approaches being either synchronous or asynchronous [1,3], and geographical or non-geographical [2,5].In strategies based on a synchronous duty cycle, the sensor nodes must be synchronised globally or locally in time so as to become active at the same time. During the active time, connectivity among them is established and exchanges of data are accomplished with a relatively short delay. However, this approach with synchronised nodes requires the exchange of a synchronisation schedule with neighbouring nodes, which can be overhead on the network. On the other hand, asynchronous duty cycle-based sensor nodes in the network have independent wake-up moments, thus obviating the need for synchronisationrelated operations [1,4]. However, under asynchronous strategies, because the transmitting nodes should wait for the wake-up of the neighbouring relay node, the generated data can be expected to have longer latency of data-forwarding delay.It is reasonable to assume that a sensor node with more remaining energy should wake-up more frequently, thus a DSR (duty-cycle scheduling based on residual energy) scheme [4] for an energyharvesting WSN was proposed, in which the sleep period of the sensor nodes is a function of their residual energy. An additional assumption is that all the sensor nodes consume a fixed amount of transmission energy for data transmissions, which can be modified to improve performance. Using geographical information such as the positions of the sensor nodes can improve the performances of da...

In this paper 1 , we propose an optimal data forwarding strategy to minimize sleep duration time for one-dimensional wireless sensor networks with energy harvesting sensor nodes. Based on the values of remaining energy and harvested energy of sensor nodes, the base station (data sink) determines the sleep duration time and the data forwarding strategy for the next data gathering round. According to the proposed algorithm, each sensor node can act as a relay node that receives and forwards the data toward data sink. This strategy also guarantees that every sensor nodes do not reach the energy depletion while minimizing sleep duration time, resulting in the maximum data gathering frequency. From the mathematical analysis and the numerical simulation, the proposed strategy shows 2.5% to 50% smaller sleep duration time compared to the simple data forwarding algorithms such as single hop or multi-hop data forwarding only.