Researching on Delay Tolerant Networks is an emerging field. Many researchers are dedicated to the approach of the routing algorithms and its applications. With sufficient energy in the core-nodes in the networks, a nested source spray and wait routing algorithm, which is ameliorated from source spray and wait routing algorithm (1), has been put forward in this paper. The simulation results indicate that by increasing the cost of energy consumption at the core-nodes, this routing algorithm has better performances in terms of delivery probability and the average delay. I INTRODUCTION Delay tolerant networks (DTNs) are a class of networks that experience frequently partitions which are difficult to predict. In DTNs, an end-to-end path between the source and the destination may not exist most of time, or such a path is highly unstable and may change or break soon (2). In the real world, with the growth of wireless communication equipments, many network applications fall into this category, such as Human Networks (3), VANET Networks (4), Sensor Networks (5), Inter-planetary Networks (6), etc. Since DTNs are characterized by a lack of consistent end-to-end paths due to interruptions that may be either predict or unpredicted, traditional proactive and reactive routing schemes based on end-to-end path fail to work in DTN. Multiple-copy routing algorithms are commonly adopted for DTNs to increase the messages delivery probability by looking for more possible paths (7, 8), such as Epidemic (9). A number of DTN routing schemes (such as MED, ED, EDLQ, EDAQ, etc (10)) assume that prior knowledge about mobility and connectivity, or oracles, or information about the complete contact schedules are known, this allows routing strategies to make efficient use of network resources by forwarding a message along the best path (8,11). Unfortunately, the information may be imprecise or completely unpredictable. In this paper, we assume that nodes have zero knowledge about the network, except available contacts. The rest of the paper is structured as follow. Section 2 goes over related work. Section 3 describes the nested spray and wait routing algorithm we proposed. Section 4 describes simulation results of the routing approaches. Finally, Section 5 makes the conclusion.