# Context-Aware Pending Interest Table Management Scheme for NDN-Based VANETs
## 1 Introduction
For example, safety applications have low latency requirements, whereas non-safety applications do not have low latency requirements. Inefficient safety-related content dissemination could result in fatalities and disabilities. In the event of a road hazard, information must be received at the nearest traffic police station as soon as possible. Otherwise, it may cause traffic congestion, resulting in injuries, property damage, and lost time for motorists and passengers. In VANET applications, a vehicle is highly dependent on information about the content, network, and application, which can be obtained from a variety of sources [8; 9]. The information gathered can be used as context to make better decisions [8; 9]. In the case of VANETs, the context may include node position, speed, time when the content is generated, location where the content is generated, content type (safety, non-safety), application to which the content belongs, content format, application popularity, neighbourhood conditions, and many others. Recently, NDN has gained increasing attention for content distribution in VANETs [4; 5; 6]. Taking into consideration the VANET characteristics, wireless environment, and applications, efficient and effective content dissemination in NDN-based VANETs is a well-known problem and faces unique challenges [5; 6] including content naming, forwarding, and PIT management. Context information can be used to not only improve the performance of routing (forwarding) protocols, but can also be exploited in making dynamic decisions such as those related to selecting the appropriate forwarding protocol and making NDN's pending interest table (PIT) management decisions. Context information (embedded in Interest messages, content names, and collected by vehicles) can be used to enable efficient and effective content distribution in NDN-based VANETs [5; 8; 9]. While it is difficult to obtain the necessary context information at the IP network layer, the emergence of NDN is changing the tide. The Pending Information Table (PIT) is a key player in finding content in NDN. Due to the limited opportunities offered by current memory technologies, PIT size is a bottleneck. The stored PIT Entry (PITE) is removed either when the PIT Entry Lifetime (PEL) expires or the vehicle with \(PITE\) receives the required Data packet. Flooding of Interest packets in NDN-based VANETs can quickly increase PIT size. In VANETs, Interest flooding and a large PEL can exhaust the PIT, impacting the overall Interest Satisfaction Rate (ISR). PIT overflow result in service disruptions as new Interest messages PIT entries cannot be added to PIT. In case of overload, to make space for the future PIT entries, the current state-of-the-art method removes entries with low priority. Priority is computed based on the PEL and number of requests received for the content [10]. The existing state-of-the-art methods do not consider context such as application type or content type while computing the priority. Different delivery priorities may be necessitated for traffic of the same type. For example, the delivery of a video required for safe driving (to raise awareness about the area in bad weather) should take priority over the delivery of a cartoon film video to a child. The later video type is less critical. In this work, therefore, we focus on PIT management. More specifically, the major contributions of this paper can be summarized as follows:  
* In this work, we focus on the context-aware adaptive PIT management scheme named Context-aware PIT Entry Management (CPITEM). The CPITEM scheme supports efficient use of PIT, taking into the consideration that VANET applications may have different QoS needs. CPITEM exploits the context information collected by the vehicle and presents it in the Context-aware Content Name (CACN) [9]. CACN is one of the important information components of the Interest and Data packet header.