Spray And Wait Algorithm Based On Node Interest Preference And Fuzzy Comprehensive Evaluation In DTN

Delay Tolerant Network(DTN)is a new self-organizing network with no stable links between nodes,and it has a unique architecture.Different from the traditional network,the node resources in the DTN are limited,and the communication environment is harsh,resulting in frequent splitting of communication links and high network delay.Therefore,the DTN adopts the "store-carry-forward" method for data transmission,and uses the occasional encounter between nodes to communicate.Due to the above characteristics,how to select nodes to carry message copies and ensure the successful delivery of messages is still a hot topic in routing algorithms for DTN.Based on domestic and foreign research,this paper proposes a probabilistic spray and wait routing algorithm based on node interest preference in delay tolerant networks(NIPPSW).First,considering the influence of the social attributes of nodes on message delivery,social networks are introduced,the active area of nodes and historical encounter node information are counted,and the regional similarity and friend similarity are defined based on historical information.Node interest preferences are defined by regional similarity and friend similarity,and the degree of interest between nodes is measured.Secondly,considering that the transmission of messages is also affected by node resources and the connection status between nodes to a certain extent,the delivery probability is introduced to estimate the ability of nodes to transmit messages.Finally,the node interest similarity is defined according to the node’s active area and historical encounter node records,and the degree of interest similarity between two nodes is measured.NIP-PSW algorithm is divided into Spray phase and Wait phase.In the Spray phase,in order to prevent the source node from blindly selecting nodes to cause message spam and resource waste,the node interest preference and delivery probability are used as metrics for screening relay nodes,and the node with a higher interest preference and higher delivery probability to the destination node is preferred to carry messages.In the Wait phase,considering nodes with high interest preference and high delivery probability for the destination node,there may be a dead end problem.In order to prevent the message from being carried by such nodes and cannot be forwarded and make full use of the encounter opportunities between nodes,replication is adopted.Strategy,copy the message to the node with higher interest similarity with the destination node.Then this paper proposes a spray and wait routing algorithm based on fuzzy comprehensive evaluation(FCE-SW).This algorithm takes into account the relativity of node resources and the subjectivity of node social attributes,resulting in the lack of a clear "boundary" when quantifying the information of node.Therefore,the method of fuzzy mathematics is introduced to process and quantify the node information.First of all,this algorithm sets evaluation metrics of nodes based on node resources and node social attributes.The node quality is defined by the cache and energy of the node,and judges the status of node on resources.Secondly,consider the information of nodes in social areas and historical encounter nodes,and define the activity of nodes,including geographical activity and social activity to reflect the degree of activity of nodes in society.Finally,the delivery contribution is defined by the node’s historical ability to process messages,and the historical information is used to estimate the node’s ability to deliver messages.Then set the evaluation set for the nodes,divide the nodes into three grades of high quality,common and inferior,and set the membership function for these three evaluation grades,which is used to calculate the membership degree of each metric belonging to each grade and construct the fuzzy matrix.Since node resources and node social attributes are located in different fields,although they can be quantified by mathematical methods,they cannot be generalized.Therefore,a relatively subjective AHP is used to assign weights to the four node evaluation metrics.Finally,the node evaluation model based on fuzzy comprehensive evaluation is constructed by fuzzy comprehensive evaluation method,and the nodes can be rated.In the Spray phase,high-quality nodes and ordinary nodes are selected to forward messages to prevent inferior-quality nodes from participating in the forwarding process and affecting algorithm performance.Among them,high-quality nodes use dichotomy to distribute message copies,and ordinary nodes only receive one message copy.In the Wait phase,in order to reduce the delay of the algorithm,make full use of the chance of meeting between nodes,replicate a copy of the message to the high-quality node.Finally,set the message value for cache management to prevent high-quality nodes from becoming inferior-quality nodes due to too many copies of received messages,and to avoid network congestion.Finally,build experimental system and network environment through Opportunity Network Environment(ONE),and do simulation experiments on the above two algorithms.Both algorithms show excellent performance in message delivery probability and network average delay.In addition,the average network overhead and the average message hops of the two algorithms are not high,showing good performance.