Opportunistic Forwarding Algorithms Research Articles

Activity-based routing algorithm in opportunistic mobile social networks

In opportunistic mobile social networks, nodes are clustered according to their interests or hobbies and take part in different activities regularly. We delve into the temporal and spatial mobility characteristics of network nodes and put forward an activity-based message opportunistic forwarding algorithm. The main idea of the algorithm is that we choose different message forwarding methods according to the situation of nodes participating in activities. If the source node and the destination node are both attend in the same activities, we select the best relay node which has the biggest delivery probability. While the source node and the destination node are not in the same activities at the same time, we need to find the optimal path which owns highest indirect delivery probability, and messages will be transmitted through the optimal path. The simulation results show that the proposed routing algorithm can not only improve the successful delivery ratio of messages but also reduce the network delay and the network overhead obviously, in comparison with the classical opportunistic routing algorithms, such as community-aware message opportunistic transmission algorithm, community-based message transmission scheme algorithm, PRoPHET, Epidemic algorithm, and interest characteristic probability prediction algorithm.

On the integration of interest and power awareness in social-aware opportunistic forwarding algorithms

Social-aware Opportunistic forwarding algorithms are much needed in environments which lack network infrastructure or in those that are susceptible to frequent disruptions. However, most of these algorithms are oblivious to both the user’s interest in the forwarded content and the limited power resources of the available mobile nodes. This paper proposes PI-SOFA, a framework for integrating the awareness of both interest and power capability of a candidate node within the forwarding decision process. Furthermore, the framework adapts its forwarding decisions to the expected contact duration between message carriers and candidate nodes. The proposed framework is applied to three state-of-the-art social-aware opportunistic forwarding algorithms that target mobile opportunistic message delivery. A simulation-based performance evaluation demonstrates the improved effectiveness, efficiency, reduction of power consumption, and fair utilization of the proposed versions in comparison to those of the original algorithms. The results show more than 500% extra f-measure, mainly by disregarding uninterested nodes while focusing on the potentially interested ones. Moreover, power awareness preserves up to 8% power with 41% less cost to attain higher utilization fairness by focusing on power-capable interested nodes. Finally, this paper analyzes the proposed algorithms’ performance across various environments. These findings can benefit message delivery in opportunistic mobile networks.

Message Forwarding in Sparsely Connected Wireless Networks Using Rateless Codes

Rateless codes can reduce retransmission costs over erasure channels. Existing routing algorithms using rateless codes assume densely connected networks and predecide the forwarder nodes, which subsequently participate in message forwarding. Using a rateless code, which is easy to analyze and implement, we propose practically implementable opportunistic message forwarding algorithms for sparsely connected networks, in which all the nodes can potentially participate in forwarding, and study their performance through simulations.

Multihop-Delivery-Quality-Based Routing in DTNs

In delay-tolerant networks (DTNs), stable end-to-end connections do not always exist. Messages are forwarded, assisted by the mobility of nodes, in a store-carry-forward paradigm. The mobility of nodes in most DTNs has a certain statistical regularity; thus, using historical information in DTNs to compute the delivery quality of nodes can help to select good forwarding nodes. This paper aims to establish a routing scheme based on multihop delivery quality, which is designed to reduce the energy consumption of message forwarding while maintaining a high delivery rate. We characterized the multihop delivery quality of each node with an expected delay and an expected probability, parameterized by the remaining hop count. Based on these two quality metrics, we developed two algorithms, namely, the delay-inferred forwarding (DIF) algorithm and the probability-inferred forwarding (PIF) algorithm. The basic idea of DIF and PIF is to find the optimal forwarding path by minimizing the expected delay and by maximizing the expected probability, respectively, in the hop graph that is defined in this paper. We performed extensive trace-driven simulations to compare our algorithm to other representative routing algorithms using several real traces. We observed the following: 1) Compared with the delegation algorithm, which uses one-hop delivery quality, both DIF and PIF significantly improve the message delivery rate, and they yield more improvements as the mobility of nodes becomes more regular; and 2) compared with the state-of-the-art optimal opportunistic forwarding (OOF) algorithm, which also uses a multihop delivery quality, DIF and PIF have significantly smaller forwarding overhead (with the maximum reduction in the number of forwarding being over 40%), whereas they are quite close to OOF in terms of both delivery rate and average delay.

LAOF: location‐aware opportunistic forwarding scheme in mobile Ad hoc networks

AbstractDue to the high mobility of the nodes, the mobile ad hoc networks are expected to provide many opportunities for message forwarding in delay tolerant networks. Considering the typical mobility models, for example, the random waypoint (RWP) model and Manhattan model, we explore the probabilistic characteristics of the node contact provided by the mobile nodes. Following a progressive approach, we propose a location‐aware opportunistic forwarding scheme, which exploits the location information of the messages and the node mobility to conduct message forwarding. In order to provide a stable delivery ratio and avoid the extra network overhead, the message is forwarded to its destination regions or neighbor regions, which offer a better chance to reach the destination node. We construct a simulation environment, integrated with the RWP mobility trace and the Shanghai city taxis traces. Through extensive simulations, our scheme is demonstrated to outperform the best known opportunistic forwarding algorithms in terms of both delivery ratio/latency and transmission overhead. Copyright © 2014 John Wiley & Sons, Ltd.

Routing Optimization for Delay Tolerant Networks in Rural Applications Using a Distributed Algorithm

Internet access can improve people’s life quality by helping them to reduce and overcome the poverty and educational gaps. However, most rural communities in the world, specially in underdeveloped countries, do not have access to the Internet. Delay/Disruption Tolerant Networking (DTN) is a recent low-cost technology now being used to provide connectivity to rural towns were some transportation means periodically arrive. DTNs can be implemented to connect communities to Internet, since this technology takes advantage of the existing people’s transportation infrastructure using it to move packets and messages to and from Internet. This paper proposes a DTN mathematical optimization model that maximizes the availability probabilities of the paths from sources to destinations. We also present an opportunistic forwarding algorithm that takes into account the availability probability of a node’s neighbors to decide if a node should forward a message or store the message until a node with a higher availability probability contacts it. This algorithm was tested in five different scenarios and in all of them it found a path to the destination.

Fairness-related challenges in mobile opportunistic networking

The fundamental challenge in opportunistic networking, regardless of the application, is when and how to forward a message. Rank-based forwarding techniques currently represent one of the most promising methods for addressing this message forwarding challenge. While these techniques have demonstrated great efficiency in performance, they do not address the rising concern of fairness amongst various nodes in the network. Higher ranked nodes typically carry the largest burden in delivering messages, which creates a high potential of dissatisfaction amongst them. In this paper, we adopt a real-trace driven approach to study and analyze the trade-offs between efficiency, cost, and fairness of rank-based forwarding techniques in mobile opportunistic networks.Our work comprises three major contributions. First, we quantitatively analyze the trade-off between fair and efficient environments. Second, we demonstrate how fairness coupled with efficiency can be achieved based on real mobility traces. Third, we propose FOG, a real-time distributed framework to ensure efficiency–fairness trade-off using local information. Our framework, FOG, enables state-of-the-art rank-based opportunistic forwarding algorithms to ensure a better fairness–efficiency trade-off while maintaining a low overhead. Within FOG, we implement two real-time distributed fairness algorithms; Proximity Fairness Algorithm (PFA), and Message Context Fairness Algorithm (MCFA). Our data-driven experiments and analysis show that mobile opportunistic communication between users may fail with the absence of fairness in participating high-ranked nodes, and an absolute fair treatment of all users yields inefficient communication performance. Finally our analysis shows that FOG-based algorithms ensure relative equality in the distribution of resource usage among neighbor nodes while keeping the success rate and cost performance near optimal.

Impact of Human Mobility on Opportunistic Forwarding Algorithms

We study data transfer opportunities between wireless devices carried by humans. We observe that the distribution of the intercontact time (the time gap separating two contacts between the same pair of devices) may be well approximated by a power law over the range [10 minutes; 1 day]. This observation is confirmed using eight distinct experimental data sets. It is at odds with the exponential decay implied by the most commonly used mobility models. In this paper, we study how this newly uncovered characteristic of human mobility impacts one class of forwarding algorithms previously proposed. We use a simplified model based on the renewal theory to study how the parameters of the distribution impact the performance in terms of the delivery delay of these algorithms. We make recommendations for the design of well-founded opportunistic forwarding algorithms in the context of human-carried devices