Simulation is one of the most powerful tools we have for evaluating the performance of Opportunistic Networks. In this survey, we focus on available tools and models, compare their performance and precision and experimentally show the scalability of different simulators. We also perform a gap analysis of state-of-the-art Opportunistic Network simulations and sketch out possible further development and lines of research. This survey is targeted at students starting work and research in this area while also serving as a valuable source of information for experienced researchers.

Seismic data acquisition in oil and gas exploration employs a large-scale network of geophone sensors deployed in thousands across a survey field. A central control unit acquires and processes measured data from geophones to come up with an image of the earth’s subterranean structure to locate oil and gas traps. Conventional seismic acquisition systems rely on cables to connect each sensor. Although cable-based systems are reliable, the sheer amount of cable required is tremendous, causing complications in survey logistics as well as survey downtime. The need for a cable-free seismic data acquisition system has attracted much attention from contractors, exploration companies, and researchers to lay out the enabling wireless technology and architecture in seismic explorations. This paper gives a general overview of land seismic data acquisition and also presents a current and retrospective review of the state-of-the-art wireless seismic data acquisition systems. Furthermore, a simulation-based performance evaluation of real-time, small-scale wireless geophone subnetwork is carried out using the IEEE 802.11 g technology based on the concept of seismic data acquisition during the geophone listen or recording period. In addition, we investigate an optimal number of seismic samples that could be sent by each geophone during this period.

Infrastructure‐less networks connect communication devices end‐to‐end by managing links and routes independent of fixed networking facilities, relying on dedicated protocols running on end‐user devices. The large variety of infrastructure‐less concepts and related aspects can be confusing both for beginning Ph.D. students as well as experienced researchers who wish to get an overview of neighbouring areas to their own research foci. Frequently discussed topics such as different types of sensor‐, vehicular‐, or opportunistic networks are covered. The authors describe different networking concepts by looking at aspects such as the main properties, common applications, and ongoing research. Furthermore, the concepts by common characteristics such as node mobility, network density, or power consumption are compared. The authors also discuss network performance evaluation by describing commonly used metrics, different evaluation techniques, and software tools for simulation‐based evaluation. The references given in each section help obtain in‐depth information about the presented topics and give hints about open research questions, which can be a starting point for own investigations.

An ad-hoc network is a network whose particular characteristics include absence of any kind of infrastructure, dynamic topology and limited resources. Up to day, several routing protocols have been proposed to face such a hostile environment. These solutions usually provide to the sources of data flows with single valid paths towards their destinations. However, it has been proven that maintaining multiple paths can be favorable to the network, either using the paths at the same time (for load balancing) or using an alternative path, when the primary one fails. It is also a way to meet the Quality of Service requirements demanded by some particular applications. In this paper, we propose a novel routing mechanism based on Dynamic MANET On-demand (DYMO) routing protocol, in order to enable the establishment of more than one node disjoint routes towards the same destination. Simulation results show that there is a significant gain in end-to-end delay for data packets and a reduction in the number of the transmitted routing packets.

Opportunistic networks have recently seen increasing interest in the networking community. They can serve a range of application scenarios, most of them being destination-less, i.e., without a-priori knowledge of who is the final destination of a message. In this paper, we explore the usage of data popularity for improving the efficiency of data forwarding in opportunistic networks. Whether a message will become popular or not is not known before disseminating it to users. Thus, popularity needs to be estimated in a distributed manner considering a local context. We propose Keetchi, a data forwarding protocol based on Q-Learning to give more preference to popular data rather than less popular data. Our extensive simulation comparison between Keetchi and the well known Epidemic protocol shows that the network overhead of data forwarding can be significantly reduced while keeping the delivery rate the same.