Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks

Several social-aware forwarding strategies have been recently introduced in opportunistic networks, and proved effective in considerably in- creasing routing performance through extensive simulation studies based on real-world data. However, this performance improvement comes at the expense of storing a considerable amount of state information (e.g, history of past encounters) at the nodes. Hence, whether the benefits on routing performance comes directly from the social-aware forwarding mechanism, or indirectly by the fact state information is exploited is not clear. Thus, the question of whether social-aware forwarding by itself is effective in improving opportunistic network routing performance remained unaddressed so far. In this paper, we give a first, positive answer to the above question, by investigating the expected message delivery time as the size of the net- work grows larger

Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks

Several social-aware forwarding strategies have been recently intro- duced in opportunistic networks, and proved eective in considerably in- creasing routing performance through extensive simulation studies based on real-world data. However, this performance improvement comes at the expense of storing a considerable amount of state information (e.g, history of past encounters) at the nodes. Hence, whether the benets on routing performance comes directly from the social-aware forwarding mechanism, or indirectly by the fact state information is exploited is not clear. Thus, the question of whether social-aware forwarding by itself is eective in im- proving opportunistic network routing performance remained unaddressed so far. In this paper, we give a rst, positive answer to the above question, by investigating the expected message delivery time as the size of the net- work grows larger. In order to make a fair comparison with stateless, social oblivious forwarding mechanisms such as BinarySW, we introduce a simple stateless, social-aware forwarding mechanism exploiting a notion of similarity between individual interests. We then compare the asymp- totic performance of interest-based forwarding with that of BinarySW under two mobility scenarios, modeling situations in which node pairwise meeting rates are independent of or correlated to the similarity of their in- terests. We formally prove that, while asymptotic expected delivery time of BinarySW is highly dependent on the underlying mobility model, with unbounded expected delivery time in presence of correlated mobility, this is not the case with interest-based forwarding, which provides bounded expected delivery time with both mobility models. Thus, our ndings for- mally prove that social-aware forwarding, even when not exploiting state information, has the potential to considerably improve routing perfor- mance in opportunistic networks over traditional forwarding mechanisms

Pervasive intelligent routing in content centric delay tolerant networks

This paper introduces a Swarm-Intelligence based Routing protocol (SIR) that aims to efficiently route information in content centric Delay Tolerant Networks (CCDTN) also dubbed pocket switched networks. First, this paper formalizes the notion of optimal path in CCDTN and introduces an original and efficient algorithm to process these paths in dynamic graphs. The properties and some invariant features of these optimal paths are analyzed and derived from several real traces. Then, this paper shows how optimal path in CCDTN can be found and used from a fully distributed swarm-intelligence based approach of which the global intelligent behavior (i.e. shortest path discovery and use) emerges from simple peer to peer interactions applied during opportunistic contacts. This leads to the definition of the SIR routing protocol of which the consistency, efficiency and performances are demonstrated from intensive representative simulations

Swarm-based Intelligent Routing (SIR) - a new approach for efficient routing in content centric delay tolerant networks

This paper introduces Swarm-based Intelligent Routing (SIR), a swarm intelligence based approach used for routing content in content centric Pocket Switched Networks. We first formalize the notion of optimal path in DTN, then introduce a swarm intelligence based routing protocol adapted to content centric DTN that use a publish/subscribe communication paradigm. The protocol works in a fully decentralized way in which nodes do not have any knowledge about the global topology. Nodes, via opportunistic contacts, update utility functions which synthesizes their spatio-temporal proximity from the content subscribers. This individual behavior applied by each node leads to the collective formation of gradient fields between content subscribers and content providers. Therefore, content routing simply sums up to follow the steepest slope along these gradient fields to reach subscribers who are located at the minima of the field. Via real traces analysis and simulation, we demonstrate the existence and relevance of such gradient field and show routing performance improvements when compared to classical routing protocols previously defined for information routing in DTN

Performance comparison of baseline routing protocols in pocket switched network

Pocket Switched Network (PSN) is a branch of Delay Tolerant Network (DTN) which is intended to work in a challenged network. Challenged network is network with lack of infrastructure such as disaster area. As such, the network has intermittent connectivity. PSN provides a new paradigm to distribute messages in the network by taking advantage of roaming nodes from one place to another. In this paper, network performances of eight PSN routing protocols are investigated namely, First Contact, Direct Delivery, Epidemic, PRotocol using History of Encounter and Transitivity (PRoPHET), Spray and Wait, Binary Spray and Wait, Fuzzy Spray, Adaptive Fuzzy Spray and Wait. The performance metrics are packet delivery ratio, overhead ratio and average latency. Opportunistic Network Environment (ONE) simulator is used to evaluate the network performance. Experiments show that Epidemic has the best performance in term of message delivery ratio, but it has the highest overhead ratio. Direct Delivery has the lowest overhead ratio (zero overhead ratio) and PRoPHET has the lowest latency average

Community-based Message Opportunistic Transmission

Mobile Social Networks (MSNs) is a kind of opportunistic networks, which is composed of a large number of mobile nodes with social characteristic. Up to now, the prevalent communitybased routing algorithms mostly select the most optimal social characteristic node to forward messages. But they almost don\u27t consider the effect of community distribution on mobile nodes and the time-varying characteristic of network. These algorithms usually result in high consumption of network resources and low successful delivery ratio if they are used directly in mobile social networks. We build a time-varying community-based network model, and propose a community-aware message opportunistic transmission algorithm (CMOT) in this paper. For inter-community messages transmission, the CMOT chooses an optimal community path by comparing the community transmission probability. For intra-community in local community, messages are forwarded according to the encounter probability between nodes. The simulation results show that the CMOT improves the message successful delivery ratio and reduces network overhead obviously, compared with classical routing algorithms, such as PRoPHET, MaxProp, Spray and Wait, and CMTS

Reputation and credit based incentive mechanism for data-centric message delivery in delay tolerant networks

In a Data-centric Delay Tolerant Networks (DTNs), it is essential for nodes to cooperate in message forwarding in order to enable successful delivery of a message in an opportunistic fashion with nodes having their social interests defined. In the data-centric dissemination protocol proposed here, a source annotates messages (images) with keywords, and then intermediate nodes are presented with an option of adding keyword-based annotations in order to create higher content strength messages on path toward the destination. Hence, contents like images get enriched as there is situation evolution or learned by these intermediate nodes, such as in a battlefield, or in a disaster situation. Nodes might turn selfish and not participate in relaying messages due to relative scarcity of battery and storage capacity in mobile devices. Therefore, in addition to content enrichment, an incentive mechanism is proposed in this thesis which considers factors like message quality, battery usage, level of interests, etc. for the calculation of incentives. Moreover, with the goal of preventing the nodes from turning malicious by adding inappropriate message tags in the quest of acquiring more incentive, a distributed reputation model (DRM) is developed and consolidated with the proposed incentive scheme. DRM takes into account inputs from multiple users like ratings for the relevance of annotations in the message, message quality, etc. The proposed scheme safeguards the network from congestion due to uncooperative or selfish nodes in the system. The performance evaluation shows that our approach delivers more high priority and high quality messages while reducing traffic at a slightly lower message delivery ratio compared to ChitChat --Abstract, page iv

Congestion aware forwarding in delay tolerant and social opportunistic networks

We propose an approach for opportunistic forwarding that supports optimization of multipoint high volume data flow transfer while maintaining high buffer availability and low delays. This paper explores a number of social, buffer and delay heuristics to offload the traffic from congested parts of the network and spread it over less congested parts of the network in order to keep low delays, high success ratios and high availability of nodes. We conduct an extensive set of experiments for assessing the performance of four newly proposed heuristics and compare them with Epidemic, Prophet, Spay and Wait and Spay and Focus protocols over real connectivity driven traces (RollerNet) and with a realistic publish subscribe filecasting application. We look into success ratio of answered queries, download times (delays) and availability of buffer across eight protocols for varying congestion levels in the face of increasing number of publishers and topic popularity. We show that all of our combined metrics perform better than Epidemic protocol, Prophet, Spray and Wait, Spray and Focus and our previous prototype across all the assessed criteria