## 1 Introduction  
A class of networks where the devices connect and exchange data whenever they come in contact are called opportunistic networks (OppNets). As the name suggests, these networks get formed whenever the opportunity arises. Since an OppNet is formed by the availability of the devices in the connection range of each other, device-to-device communication technologies such as Bluetooth, ZigBee and WiFi-direct are used for communication in opportunistic networks. Although it seems straight-forward to deploy OppNets, real testbeds to study and evaluate OppNets are quite uncommon. A typical testbed for OppNets consists of real users with their mobility patterns, traffic generation, buffer management in each device, a data dissemination protocol and post processing methods to obtain the necessary metrics. Although these modules can be developed and integrated in testbeds, the main challenge is in the repeatability of the experimental setup. Simply put, the dynamics of the network and, especially, the real users' mobility makes it impossible to repeat the experiment in the same manner again. Thus, simulators are the most common way of evaluating OppNets as they support the flexibility and ease of implementation. One of the approaches in bridging the gap between real world and simulation-based evaluations is to attempt to precisely capture the properties of a real-world scenario and reproduce it in a simulator. This is often done by capturing various types of real world traces, e.g., mobility or application traces. A different, but not contradicting approach is to perform evaluations with a large range of scenarios, so that the evaluation has statistical significance. Moreover, benchmarks for OppNets do not exist to the best of our knowledge and, hence, the responsibility lies with the researchers to identify suitable evaluation configurations and experimental setups for evaluating their OppNet protocols. In this paper, we study the aspects of OppNet performance evaluations in simulators and how they match with the real-world expectations for OppNets. Further, we briefly discuss the challenges in conducting OppNet evaluations, and present a gap analysis with respect to the evaluation of OppNets protocols. It is important to note that we do not evaluate the discussed protocols; rather, we explore their evaluation methodologies to derive best practices for future evaluation studies. A detailed analysis of Mobile Ad-hoc Networks (MANET) evaluations was presented by [PERSON] et al. [1] and this survey attempts to provide a similar analysis for OppNet evaluations. A number of relevant surveys on OppNets exists in the literature, which focuses on the protocols themselves, their taxonomy and classifications based on specific aspects such as group dynamics or parameter optimizations. A general overview and analysis of protocols, models and tools for OppNets were discussed by [PERSON] et al. [2]. The evolution of OppNets research and challenges were presented by [PERSON] et al. [3]. Neighbor discovery approaches were explored in detail by [PERSON] et al. [4]. Routing protocols and data dissemination protocols were summarized by [PERSON] et al. [5] and [PERSON] et al. [6], whereas the impact of mobility models was discussed by [PERSON] et al. [7]. Simulating OppNets, in terms of the scalability, realistic models and metrics, were analyzed by [PERSON] et al. [8] and [PERSON] et al. [2]. Further, an evaluation methodology was proposed by [PERSON] et al. [9] pertaining to simulation studies for Vehicular Ad-hoc Networks (VANETs). This paper complements these existing surveys by extending the focus to evaluation procedures used in OppNet literature. The main goal of the paper is three-fold: firstly, we analyze the assessment environments and methodologies of OppNet protocol evaluations adopted in current simulators; secondly, we discuss how they align with the realistic considerations for OppNets; and, thirdly, we propose a range of scenarios that these evaluations can span to show the potential of OppNets.