In-network caching is one of the most important issues in content centric networking(CCN), which may extremely influence the performance of the caching system. Although much work has been done for in-network caching scheme design in CCN, most of them have not addressed the multiple network attribute parameters jointly during caching algorithm design. Hence, to fill this gap, a new in-network caching based on grey relational analysis(GRA) is proposed. The authors firstly define two newly metric parameters named request influence degree(RID) and cache replacement rate, respectively. The RID indicates the importance of one node along the content delivery path from the view of the interest packets arriving. The cache replacement rate is used to denote the caching load of the node. Then combining hops a request traveling from the users and the node traffic, four network attribute parameters are considered during the in-network caching algorithm design. Based on these four network parameters, a GRA based in-network caching algorithm is proposed, which can significantly improve the performance of CCN. Finally, extensive simulation based on ndnSIM is demonstrated that the GRA-based caching scheme can achieve the lower load in the source server and the less average hops than the existing the betweeness(Betw) scheme and the ALWAYS scheme. In-network caching is one of the most important issues in content centric networking (CCN), which may extremely influence the performance of the caching system. Although much work has been done for in-network caching scheme design in CCN, most of them have not addressed the multiple network attribute parameters jointly during caching algorithm design. Therefore, to fill this gap, a new in-network caching based on gray relational analysis (GRA) is proposed. The authors first define two newly metric parameters named request influence degree ( The RID indicates the importance of one node along the content delivery path from the view of the interest packets arriving. The cache replacement rate is used to denote the caching load of the node. Then combining hops a request traveling from the users and the node traffic, four network attribute parameters are considered during the in-network caching algorithm design. Based on these four network parameters Finally, an extensive simulation based on ndnSIM is demonstrated that the GRA-based caching algorithm can achieve the lower load in the source server and the less average hops than the existing the betweeness (Betw) scheme and the ALWAYS scheme.