Routing In Opportunistic Networks Research Articles

Adaptive Fuzzy Routing in Opportunistic Network (AFRON)

Adaptive Fuzzy Routing in Opportunistic Network (AFRON)

Analysis and improvement of TCP performance in opportunistic networks

Opportunistic networks have attracted attention due to their inherent characteristics, such as long latency, low data rate, and intermittent connectivity. Extensive research has been conducted on opportunistic networks, including the architecture, and routing. However, few in the literature report the performance of TCP in opportunistic networks, especially in the case of Epidemic Routing. In this paper, we first evaluate the performance of TCP in opportunistic networks with Epidemic Routing. Our results show that the Epidemic Routing in opportunistic networks degrades the performance of TCP because multicopy data packets cause duplicate ACKs, and in turn reduce the transmission rate of TCP. Then an enhanced algorithm for TCP, named A-TCP/Reno is proposed to solve the above problem. A-TCP/Reno avoids the duplicate ACK problem caused by Epidemic Routing. The simulation results show that A-TCP/Reno outperforms the TCP/Reno in opportunistic networks with Epidemic Routing protocol.

Analyzing History Quality for Routing Purposes in Opportunistic Network Using Max-Flow

Most of the existing opportunistic network routing protocols are based on some type of utility function that is directly or indirectly dependent on the past behavior of devices. The past behavior or history of a device is usually referred to as contacts that the device had in the past. Whatever may be the metric of history, most of these routing protocols work on the realistic premise that node mobility is not truly random. In contrast, there are several oracles based methods where such oracles assist these methods to gain access to information that is unrealistic in the real world. Although, such oracles are unrealistic, they can help to understand the nature and behavior of underlying networks. In this paper, we have analyzed the gap between these two extremes. We have performed max-flow computations on three different opportunistic networks and then compared the results by performing max-flow computations on history generated by the respective networks. We have found that the correctness of the history based prediction of history is dependent on the dense nature of the underlying network. Moreover, the history based prediction can deliver correct paths but cannot guarantee their absolute reliability.

Context information prediction for social-based routing in opportunistic networks

Context information can be used to streamline routing decisions in opportunistic networks. We propose a novel social context-based routing scheme that considers both the spatial and the temporal dimensions of the activity of mobile nodes to predict the mobility patterns of nodes based on the BackPropagation Neural Networks model.

TTL based routing in opportunistic networks

One of the major problem in routing messages in an Opportunistic Network (OpNet) is the absence of a complete end-to-end path from the source to the destination. To deal with such adversity many routing protocols employ epidemic techniques to flood the network with multiple copies of a message. Although flooding many copies of a message in the network increases the chance of the message delivery, it can lead to a very high network overhead and can cause network congestion. On the other hand, the quota based routing protocols restrict the maximum number of copies of a message in the network by setting a replication factor. Such protocols maintain comparatively low overhead but suffer from low delivery ratio. In this paper, we introduce a novel quota based routing protocol, TTL Based Routing (TBR). TBR prioritizes both the schedule of messages to be forwarded to the neighbor and the schedule of messages to be dropped from the buffer. These priorities are based on massage time to live (TTL), message hop count, message replication count and message size. The TTL based message priority enhances the chance of message delivery by giving preference to the messages having the earliest deadline. Our simulation results show that, TBR achieves more than 10–15% higher delivery ratio than that of the available quota based routing protocols while incurring 10% to 15% less overhead. TBR not only matches the delivery ratio of flooding based routing protocols but also achieves better delivery ratio with 70% to 75% less overhead.

Opportunistic Data Collection in Sparse Wireless Sensor Networks

Opportunistic wireless sensor networks (WSNs) have recently been proposed as solutions for many remote monitoring problems. Many such problems, including environmental monitoring, involve large deployment scenarios with lower-than-average node density, as well as a long time scale and limited budgets. Traditional approaches designed for conventional situations, and thus not optimized for these scenarios, entail unnecessary complexity and larger costs. This paper discusses the issues related with the design and test of opportunistic architectures, and presents one possible solution—CHARON (Convergent Hybrid-replication Approach to Routing in Opportunistic Networks). Both algorithm-specific and comparative simulation results are presented, as well as real-world tests using a reference implementation. A comprehensive experimental setup was also used to seek a full characterization of the devised opportunistic approach including the derivation of a simple analytical model that is able to accurately predict the opportunistic message delivery performance in the used test bed.

Routing in Opportunistic Networks

In Opportunistic Networks (OppNets), mobile devices transmit messages by exploiting the direct contacts, without the need of an end-to-end infrastructure. Disconnections of nodes and high churn rates are normal features of opportunistic networks. Hence, routing is one of the main challenges in this environment. In this article, we provide a survey of the main routing approaches in OppNets and classify them into three classes: context-oblivious, mobility-based, and social context-aware routing. We emphasize the role of context information in forwarding data in OppNets, and evaluate the relative performance of the three routing techniques. Finally, we present how context-based information is used to route data in a specific subclass of OppNets: Sensor Actor Networks (SANETs).

Exploiting users’ social relations to forward data in opportunistic networks: The HiBOp solution

Opportunistic networks, in which nodes opportunistically exploit any pair-wise contact to identify next hops towards the destination, are one of the most interesting technologies to support the pervasive networking vision. Opportunistic networks allow content sharing between mobile users without requiring any pre-existing Internet infrastructure, and tolerate partitions, long disconnections, and topology instability in general. In this paper we propose a context-aware framework for routing and forwarding in opportunistic networks. The framework is general, and able to host various flavors of context-aware routing. In this work we also present a particular protocol, HiBOp, which, by exploiting the framework, learns and represents through context information, the users’ behavior and their social relations, and uses this knowledge to drive the forwarding process. The comparison of HiBOp with reference to alternative solutions shows that a context-aware approach based on users’ social relations turns out to be a very efficient solution for forwarding in opportunistic networks. We show performance improvements over the reference solutions both in terms of resource utilization and in terms of user perceived QoS.

Autonomic behaviour of opportunistic network routing

In opportunistic networks, end-to-end communication among users does not require a continuous end-to-end path between source and destination. Network protocols are designed to be extremely resilient to events such as long partitions, node disconnections, etc. which are very features of this type of self-organising ad hoc networks. This is achieved by temporarily storing messages at intermediate nodes, waiting for future opportunities to forward them towards the destination. Clearly, designing routing and forwarding schemes is one of the main challenges in this environment. In this article, we provide a survey of the main approaches to routing in purely infrastructure-less opportunistic networks, by classifying protocols based on the amount of context information they exploit. Then, we provide an extensive quantitative comparison between representatives of protocols that do not use any context information, and protocols that manage and exploit a rich set of context information. Mainly, we focus on the suitability of protocols to adapt to the dynamically changing network features, as resulting from the user movement patterns that are driven by their social behaviour. Our results show that context aware routing is extremely adaptive to dynamic networking scenarios, and, with respect to protocols that do not use any context information, is able to provide similar performance in terms of delay and loss rate, by using just a small fraction of the network resources.