# A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach
## 1 Introduction  
DTNs refers to Delay Tolerant Networks, a particular category of the ad-hoc networks characterized by consistent low density levels which result in an intermittent connectivity between nodes [1]. The architecture of DTNs [2] is the appropriate communication paradigm for numerous applications such as the ones spread in [3]. DTN routing relies on the Store-Carry-and-Forward (SCF) principle [4] which consists of storing bundles (data packets) in the buffer cache of the host node for undefined duration when better relay nodes to forward bundles are not available. The bundle is carried until at least one better relay node opportunity arises. Then, the bundle are either replicated or forwarded to the selected SCF node according to the adopted routing policy of the DTN protocol [5].  
The DTN routing have been extended to vehicular networks (VANETs) introducing the Vehicular DTNs (VDTNs) seen in the intermittent routing conditions that characterize different vehicular mobility scenarios [6]. The SCF principle is more required for VDTNs than DTNs so that the vehicular communication constraints such as high speed, traffic lights, predefined mobility direction and radio obstacles are better handled [7].  
The probabilistic, or prediction-based, VDTN forwarding is one of the most effective routing policies in DTN-based networks [8]. This DTN routing mode consists of exploiting the forwardinghistoric of nodes to predict their future routing abilities in order to make SCF forwarding decision and define the appropriate buffer management policy [9]. The illustration of the prediction-based routing mode amongst the VDTN routing categories is spread in [10].  
The probabilistic DTN routing has been cited in few taxonomies such as in [11] which introduced the founded DTN routers based on the Probabilistic Routing Protocol using History of Encounters and Transitivity (PRoPHET) [12], deriving different modifications on the basis of delivery predictability concept notably the contact duration and the distance-based delivery probability.  
The swarm optimization is one of the most effective techniques for combinatorial and hard problems [13]. Such approaches have been opted for solving the problem of routing in conventional VANETs [14] and responded with improved performances comparing to the conventional routing solutions. Hence, the challenge of extending the stochastic swarm computation techniques to the vehicular DTN routing became highly solicited. The bio-inspired metaheuristics are the mostly optimization techniques adapted to the stochastic search of better candidate solutions which fits with the nature of probabilistic routing in VDTNs. Such optimization methods have been involved in VANET routing enhancement, as in [15], which discussed realized bio-inspired routing contributions in VANETs. As illustration, the social-based DTN routing has been discussed as well by [16] showing the utility of human social behaviors as grouping in improving the quality of SCF routing.  
In this paper, we propose an extension of the bio-inspired DTN routing through the application of a new swarm-based forwarding strategy for VDTNs founded on the stochastic search of two combined swarm-inspired techniques.  
This manuscript is organized as follows: Section 2 gathers together the literature works in probabilistic VDTN routing field. Section 3 introduces the implemented swarm-inspired optimization approaches for supporting probabilistic VDTN routing. Section 4 details the suggested swarm VDTN solution with illustrated examples. Section 5 follows with the simulation phase and discussed results. Section 6 finalizes with the conclusion and perspectives of this work.