In opportunistic networks, the nature of intermittent and disruptive connections degrades the efficiency of routing. Epidemic routing protocol is used as a benchmark for most of routing protocols in opportunistic mobile social networks (OMSNs) due to its high message delivery and latency. However, Epidemic incurs high cost in terms of overhead and hop count. In this paper, we propose a hybrid routing protocol called EpSoc which utilizes the Epidemic routing forwarding strategy and exploits an important social feature, that is, degree centrality. Two techniques are used in EpSoc. Messages’ TTL is adjusted based on the degree centrality of nodes, and the message blocking mechanism is used to control replication. Simulation results show that EpSoc increases the delivery ratio and decreases the overhead ratio, the average latency, and the hop counts as compared to Epidemic and Bubble Rap.

Background: In traditional networks, nodes drop messages in order to free up enough space for buffer optimization. However, keeping messages alive until it reaches its destination is crucial in Opportunistic Networks. Therefore, this paper proposes an Acumen Message Drop scheme (AMD) that consider the impact of the message drop decision on data dissemination performance. Methods: In order to achieve this goal, AMD drops the message based on the following considerations: the estimated time of message's arrival to its destination, message time to live, message transmission time, and the waiting time of the message in the queue. AMD scheme works as a plug-in in any routing protocol. Results: Performance evaluation shows that the integration of the proposed scheme with the PRoPHET routing protocol may increase efficiency by up to 80%, while if integrated with Epidemic routing protocol, efficiency increases by up to 35%. Moreover, the proposed system significantly increases performance in the case of networks with limited resources. Conclusion: To the best of our knowledge, most of the previous works did not address the issue of formulating the message drop decision in the non-social stateless opportunistic networks without affecting performance.

Recently, opportunistic networks (OppNets) are considered as one of the most attractive developments of mobile ad hoc networks that have emerged, thanks to the development of intelligent devices. Owing to the harsh and dynamic topology of these networks, attaining high delivery ratio is a challenging issue. Hence, it is imperative to select which node's attribute must be adjusted to achieve a higher performance in such unpredictable networks. A mutual information-based weighting scheme (MIWS) that exploits the entropy concept to assess the impact of the nodes' attributes on the network performance was proposed. The weighting procedure aims to figure out the correlative relations between different attributes and delivery ratio performance of the network. The high weight of certain attributes implies a correspondingly high impact in achieving efficient data forwarding. The proposed scheme is proofed conceptually and simulated using the Opportunistic Network Environment simulator. In contrast to previous studies conducted in the context of weight resolution, the proposed approach allows us to address this issue in real-time stateless non-social OppNets. Regardless of the deployed routing protocol, experiments show that adjusting nodes' attributes based on the proposed MIWS can improve the performance up to encouraging delivery ratios. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Recently, opportunistic networks are considered as one of the most attractive developments of ad hoc mobile networks (MANETs) that have emerged thanks to the development of intelligent devices. Due to the mobility-related instability of the paths between nodes and due to the limited buffer and energy resources, the ultimate objective of routing protocols in opportunistic networks is to enable the exchange of information between users. In such harsh environments, it is difficult to exactly pin down the services provided by these networks. To this end, we present in this paper a study on the performance analysis of six of the most popular routing protocols in opportunistic networks, namely, epidemic, PRoPHET, MaxProp, Spray and Wait, Spray and Focus, and Encounter-Based Routing (EBR). We firstly described these protocols and presented their algorithms. Thereafter, we carried out a comparative study of these protocols using exhaustive performance testing experiments with different numbers of nodes, traffic loads, message lifetime, and buffer size. The results of this investigation are with an important role in helping network designers to improve performance in such challenging networks.

Exploiting social information to improve routing performance is an increasing trend in Opportunistic Mobile Social Networks (OMSNs). Selecting the next message’s relay node based on the user’s social behavior is a critical factor in attaining a high delivery rate. So, to ascertain the most efficient selection of the next relay, the correlation between daily social activities and the social characteristics in the user profiles can be exploited. In this paper, we consider the impact of the social characteristics on mobile user activities during certain periods of the day and then rank these characteristics based on their relative importance in order to be included in the routing protocol. These processes consolidate the proposed Ranked Social-based Routing (R-SOR) protocol to provide an effective way for data dissemination in OMSN. We use the real data set INFOCOM06 to evaluate the proposed protocol. The experimental results show that the proposed protocol has higher routing efficiency than flooding-based protocols such as Epsoc and Epidemic, prediction-based protocols such as PRoPHET, and social-based protocols such as MSM and Bubble Rap.