Due to the increased capabilities of mobile devices and through wireless opportunistic contacts, users can experience new ways to share and retrieve content anywhere and anytime, even in the presence of link intermittency. Due to the significant number of available routing solutions, it is difficult to understand which one has the best performance, since all of them follow a different evaluation method. This paper proposes an assessment model, based on a new taxonomy, which comprises an evaluation guideline with performance metrics and experimental setup to aid designers in evaluating solutions through fair comparisons. Simulation results based on the proposed model revisit the performance results published by Epidemic, PROPHET, and BubbleRap, showing how they perform under the same set of metrics and scenario.
The most recent classification proposed by (2010) @cite_11 groups opportunistic routing proposals according to the message exchange scheme they employ: forwarding, replication, and coding. Authors also identify different types of utility functions that can be applied to such schemes. Additionally, Disruption Tolerant Networks (DTN) are classified based on characteristics that have major impact on routing such as connectivity and mobility. Authors succeed in mapping routing solutions to the different DTN types, which allows them to evaluate proposals accordingly.
@cite_11
1974702288 2150346466 2129565328 2096841105
Opportunistic networks (ONs) are a newly emerging type of delay tolerant network ( DTN) systems that opportunistically exploit unplanned contacts among nodes to share information. As with all DTN environments ONs experience frequent and large delays, and an end-to-end path from the source to destination may only exist for a brief and unpredictable period of time. Such network conditions present unique challenges to message routing. In this paper, we present the design and performance analysis of a novel core-based routing protocol for ON routing. Under the assumption that messages will have a delivery time constraint, we then provide a set of analytical results for rapid modeling and performance evaluation for the basic performance metrics of message delay, message delivery ratio, and buffer occupancy. We have implemented our protocol in ns-2, and our simulation results show that our protocol is quite effective and our analysis is accurate. Opportunistic Networks (ONs) utilize the communication opportunity with a hop-by-hop behavior, and implement communication between encountered nodes based on the Store-and-Forward routing pattern. This approach, which is totally different from the traditional communication model, has received extensive interests from academic community. We consider the ONs are a type of Delay Tolerant Networks (DTNs) since their routing behavior are quite same regardless of the bundle layer protocol. Until currently, a set of congestion control mechanisms have been proposed in Deterministic DTNs, which is mainly implemented in the network with limited mobility or the static network with scheduled disruption interval. However, regarding the networks with large topology variation, known as Opportunistic DTNs, to design a congestion control mechanism is difficult. In this paper, we propose an active congestion control based routing algorithm that pushes the selected message before the congestion happens. In order to predict the future congestion situation, a corresponding estimation function is designed and our proposed algorithm works based on two asynchronous routing functions, which are scheduled according to the decision of estimation function. Simulation results show our proposed algorithm efficiently utilizes the distributed storage to achieve a quite low overhead ratio and also performs well in the realistic scenario. Due to the uncertainty of transmission opportunities between mobile nodes, the routing of delay-tolerant networks (DTNs) exploits the mechanism of opportunistic forwarding. Efficient algorithms and policies for opportunistic forwarding are crucial for maximizing the message delivery probability while reducing the delivery cost. In this paper, we investigate the problem of energy-efficient opportunistic forwarding for DTNs. First, we model the message dissemination by introducing a continuous-time Markov framework. Based on this framework, we formulate the optimization problem of opportunistic forwarding, with the constraint of energy consumed by the message delivery for both two-hop and epidemic forwarding. Then, based on the solution of the optimization problem, we design different kinds of forwarding policies such as static and dynamic policies. Among these policies, we find that the threshold dynamic policy is optimal for both two-hop and epidemic forwarding. By simulation results, we show the accuracy of our continuous-time Markov analysis model. Furthermore, through extensive numerical results, we demonstrate that the performance of the threshold dynamic policy is the best among the static and continuous dynamic policies, and among the continuous dynamic policies, the negative-power policy provides relatively better performance. We consider the problem of routing in a delay tolerant network (DTN) in the presence of path failures. Previous work on DTN routing has focused on using precisely known network dynamics, which does not account for message losses due to link failures, buffer overruns, path selection errors, unscheduled delays, or other problems. We show how to split, replicate, and erasure code message fragments over multiple delivery paths to optimize the probability of successful message delivery. We provide a formulation of this problem and solve it for two cases: a 0 1 (Bernoulli) path delivery model where messages are either fully lost or delivered, and a Gaussian path delivery model where only a fraction of a message may be delivered. Ideas from the modern portfolio theory literature are borrowed to solve the underlying optimization problem. Our approach is directly relevant to solving similar problems that arise in replica placement in distributed file systems and virtual node placement in DHTs. In three different simulated DTN scenarios covering a wide range of applications, we show the effectiveness of our approach in handling failures.