Fair Routing in Delay Tolerant Networks

Abstract—The typical state-of-the-art routing algorithms for delay tolerant networks are based on best next hop hill-climbing heuristics in order to achieve throughput and efficiency. The combination of these heuristics and the social network structure leads the routing to direct most of the traffic through a small subset of good users. For instance, in the SimBet algorithm, the top 10 % of users carry out 54 % of all the forwards and 85 % of all the handovers. This unfair load distribution is not sustainable as it can quickly deplete constraint resources in heavily utilized mobile devices (e.g. storage, battery, budget, etc.). Moreover, because a small number of users carry a significant amount of the traffic, the system is not robust to random failures and attacks. To overcome these inefficiencies, this paper introduces Fair-Route, a routing algorithm for delay tolerant networks inspired by the social processes of perceived interaction strength, where messages are preferably forwarded to users that have a stronger social relation with the target of the message; and assortativity, that limits the exchange of messages to those users with similar ”social status”. We compare the performance of FairRoute to the state-of-the-art algorithms by extensive simulations on the MIT reality mining dataset. The results show that our algorithm outperforms existing algorithms in the de facto benchmark of throughput vs. forwards. Furthermore, it distributes better the load; the top 10 % carry out 26 % of the forwards and 28 % of the handovers without any loss in performance. I

Fair packet forwarding in opportunistic networks

Most replication-based packet forwarding algorithms in opportunistic networks neglect the fairness issue on the success rate distribution among all participants. In this paper we discuss the fairness evaluation on success rate, and propose a new fair packet forwarding strategy which operates as a plugin for traditional utility-based routing protocols. We compare the performance of our strategy with several well-known routing schemes via both a synthetic contact model and real human mobility traces. We find that our strategy improves the balance of success rates among users while maintaining approximately the same system throughput. In addition, our scheme reduces the cost of traditional utility-based routing protocols. © 2011 IEEE.published_or_final_versionThe 73rd IEEE Vehicular Technology Conference (VTC Spring), Budapest, Hungary, 15-18 May 2011. In Proceedings of IEEE VTC Spring, 2011, p. 1-

Increasing communication reliability in manufacturing environments

This paper is concerned with low cost mechanisms that can increase reliability of machine to machine and machine to cloud communications in increasingly complex manufacturing environments that are prone to disconnections and faults. We propose a novel distributed and cooperative sensing framework that supports localized real time predictive analytics of connectivity patterns and detection of a range of faults together with issuing of notifications and responding on demand queries. We show that our Fault and Disconnection Aware Smart Sensing (FDASS) framework achieves significantly lower packet loss rates and communication delays in the face of unreliable nodes and networks when compared to the state of the art and benchmark approaches

The effect of communication pattern on opportunistic mobile networks

Session - Smart Spaces and Personal Area NetworksSocial-based forwarding algorithms provide a new perspective on the study of routing in opportunistic mobile networks, and all of these schemes assume a uniform pattern for message generating rule. However, this is unconvincing due to the heterogeneity of contact rates in human communication patterns. In this paper we propose three social-based communication pattern models and utilize them to evaluate the network performance of different social-based routing protocols based on several human mobility traces. We find that communication patterns could significantly affect the network performance and the influence degree largely depends on the social metrics which these communication patterns are based on. We contend that considering communication pattern is quite important for designing a practical routing algorithm in opportunistic mobile networks. © 2011 IEEE.published_or_final_versionThe 8th IEEE Consumer Communications and Networking Conference (CCNC 2011), Las Vegas, NV., 9-12 January 2011. In Proceedings of the 8th CCNC, 2011, p. 1016-102

Recolha e análise de dados de contactos físicos e sociais numa rede tolerante a atrasos

As redes tolerantes a atrasos surgiram com o propósito de abordar o problema de comunicação em redes onde a ligação é intermitente e feita através de contactos oportunistas. Um caso particular destas redes são aquelas em que os nós são dispositivos transportados por pessoas, as Pocket Switch Networks. A relação social entre os nós tem sido recentemente explorada na decisão de encaminhamento neste tipo de redes.Neste trabalho, foi concebido um sistema de recolha de dados dos contactos físicos e sociais numa RTA com o objetivo de avaliar uma nova métrica social a ser usada na decisão de encaminhamento

Exploring centrality for message forwarding in opportunistic networks

In opportunistic networks, centrality characterizes a node's capability to act as a communication hub. In this paper, we provide an in-depth study of choosing effective centrality metrics for message forwarding in bandwidth-limited opportunistic networks. Based on this study, we propose a destination-unaware forwarding algorithm that accounts for the popularity of a node and the contact durations between nodes. We evaluate the algorithm on two experimental human mobility traces. The simulation results show that the proposed algorithm achieves higher system throughput while maintaining a lower forwarding cost compared with several known destination-unaware forwarding schemes. ©2010 IEEE.published_or_final_versionThe 2010 IEEE Conference on Wireless Communications and Networking (WCNC), Sydney, NSW, Australia, 18-21 April 2010. In Proceedings of the IEEE WCNC, 2010, p. 1-

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

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

GrAnt: Inferring Best Forwarders from Complex Networks' Dynamics through a Greedy Ant Colony Optimization

This paper presents a new prediction-based forwarding protocol for the complex and dynamic Delay Tolerant Networks (DTN). The proposed protocol is called GrAnt (Greedy Ant) as it uses a greedy transition rule for the Ant Colony Optimization (ACO) metaheuristic to select the most promising forwarder nodes or to provide the exploitation of good paths previously found. The main motivation for the use of ACO is to take advantage of its population-based search and of the rapid adaptation of its learning framework. Considering data from heuristic functions and pheromone concentration, the GrAnt protocol includes three modules: routing, scheduling, and buffer management. To the best of our knowledge, this is the first unicast protocol that employs a greedy ACO which: (1) infers best promising forwarders from nodes' social connectivity, (2) determines the best paths to be followed to a message reach its destination, while limiting the message replications and droppings, (3) performs message transmission scheduling and buffer space management. GrAnt is compared to Epidemic and PROPHET protocols in two different scenarios: a working day and a community mobility model. Simulation results obtained by ONE simulator show that in both environments, GrAnt achieves higher delivery ratio, lower messages redundancy, and fewer dropped messages than Epidemic and PROPHET.Cet article porte sur la proposition d'un protocole d'acheminement pour les réseaux complexes et dynamiques du type tolérants aux délais (DTN), qui est basé sur l'estimation de possibilités futures de contact. Le protocole proposé est appelé GrAnt (Greedy Ant) car il utilise une règle de transition greedy pour la méta-heuristique d'optimisation par colonies de fourmis (ACO). Cette méta-heuristique donne à GrAnt la possibilité de sélectionner les relais les plus prometteuses ou d'exploiter les bons chemins préalablement trouvé. La motivation principale pour l'utilisation de l'ACO est de profiter de son mécanisme de recherche basée sur population et de son apprentissage et adaptation rapide. En utilisant des simulations basées sur des modèles synthétiques de mobilité, nous montrons que GrAnt est en mesure d'adapter conformément son acheminement dans des différents scénarios et possède une meilleure performance comparée à des protocoles comme Epidemic et PROPHET, en plus de la génération de faible surcharge