CALAR: Community Aware Location Assisted Routing Framework for Delay Tolerant Networks

Infrastructure less communication strategies havegreatly evolved and found its way to most of our real lifeapplications like sensor networks, terrestrial communications,military communications etc. The communication pattern for allthese scenarios being identical i.e. encounter basedcommunication,characteristics of each communication domainare distinct. Hence the protocols applied for each environmentshould be defined carefully by considering its owncommunication patterns. While designing a routing protocol themain aspects under consideration include delay, connectivity,cost etc. In case of applications having limited connectivity,concept of Delay tolerant network (DTN) is deployed, whichassists delivering messages even in partitioned networks withlimited connectivity by using store and forward architecture.Node properties like contact duration, inter contact duration,location, community, direction of movement, angle of contact etc.were used for designing different classes of routing protocols forDTN. This paper introduces a new protocol that exploits thefeatures of both community based as well as location basedrouting protocols to achieve higher data delivery ratio invehicular scenarios. Results obtained show that proposedalgorithms have much improved delivery ratio comparedtoexisting routing algorithms which use any one of the aboveproperty individually

Enhanced Community-Based Routing for Low-Capacity Pocket Switched Networks

Sensor devices and the emergent networks that they enable are capable of transmitting information between data sources and a permanent data sink. Since these devices have low-power and intermittent connectivity, latency of the data may be tolerated in an effort to save energy for certain classes of data. The BUBBLE routing algorithm developed by Hui et al. in 2008 provides consistent routing by employing a model which computes individual nodes popularity from sets of nodes and then uses these popularity values for forwarding decisions. This thesis considers enhancements to BUBBLE based on the hypothesis that nodes do form groups and certain centrality values of nodes within these groups can be used to improve routing decisions further. Built on this insight, there are two algorithms proposed in this thesis. First is the Community-Based- Forwarding (CBF), which uses pairwise group interactions and pairwise node-to-group interactions as a measure of popularity for routing messages. By having a different measure of popularity than BUBBLE, as an additional factor in determining message forwarding, CBF is a more conservative routing scheme than BUBBLE. Thus, it provides consistently superior message transmission and delivery performance at an acceptable delay cost in resource constrained environments. To overcome this drawback, the concept of unique interaction pattern within groups of nodes is introduced in CBF and it is further renewed into an enhanced algorithm known as Hybrid-Community-Based- Forwarding (HCBF). Utilizing this factor will channel messages along the entire path with consideration for higher probability of contact with the destination group and the destination node. Overall, the major contribution of this thesis is to design and evaluate an enhanced social based routing algorithm for resource-constrained Pocket Switched Networks (PSNs), which will optimize energy consumption related to data transfer. It will do so by explicitly considering features of communities in order to reduce packet loss while maintaining high delivery ratio and reduced delay

Social relationship based routing for delay tolerant Bluetooth-enabled PSN communications

PhDOpportunistic networking is a concept derived from the mobile ad hoc networking in which devices have no prior knowledge of routes to the intended destinations. Content dissemination in opportunistic networks thus is carried out in a store and forward fashion. Opportunistic routing poses distinct challenges compared to the traditional networks such as Internet and mobile ad hoc networks where nodes have prior knowledge of the routes to the intended destinations. Information dissemination in opportunistic networks requires dealing with intermittent connectivity, variable delays, short connection durations and dynamic topology. Addressing these challenges becomes a significant motivation for developing novel applications and protocols for information dissemination in opportunistic networks. This research looks at opportunistic networking, specifically at networks composed of mobile devices or, pocket switched networks. Mobile devices are now accepted as an integral part of society and are often equipped with Bluetooth capabilities that allow for opportunistic information sharing between devices. The ad hoc nature of opportunistic networks means nodes have no advance routing knowledge and this is key challenge. Human social relationships are based on certain patterns that can be exploited to make opportunistic routing decisions. Targeting nodes that evidence high popularity or high influence can enable more efficient content dissemination. Based on this observation, a novel impact based neighbourhood algorithm called Lobby Influence is presented. The algorithm is tested against two previously proposed algorithms and proves better in terms of message delivery and delay. Moreover, unlike other social based algorithms, which have a tendency to concentrate traffic through their identified routing nodes, the new algorithm provides a fairer load distribution, thus alleviating the tendency to saturate individual nodes

SOCIAL AND LOCATION BASED ROUTING IN DELAY TOLERANT NETWORKS

Delay tolerant networks (DTNs) are a special type of wireless mobile networks which may lack continuous network connectivity. Routing in DTNs is very challenging as it must handle network partitions, long delays, and dynamic topology in such networks. Recently, the consideration of social characteristics of mobile nodes provides a new angle of view in the design of DTNs routing protocols. In many DTNs, a multitude of mobile devices are used and carried by people (e.g. pocket switched networks and vehicular networks), whose behaviors are better described by social models. This opens the new possibilities of social-based routing, in which the knowledge of social characteristics is used for making better forwarding decision. However, the social relations do not necessarily reflect the true device communication opportunities in a dynamic DTN. On the other hand, the increasing availability of location technologies (GPS, GSM networks, etc.) enables mobile devices to obtain their locations easily. Consider that an individual’s location history in the real world implies his/her social interests and behaviors to some extent, in this dissertation, we study new social based DTN routing protocols, which utilize location and/or social features to achieve efficient and stable routing for delay tolerant networks. We first incorporate the location features into the social-based DTN routing methods to improve their performance by treating location similarity among nodes as possible social relationship. Then, we dis- cuss the possibility and methods to further improve routing performance by adding limited amount of throw-boxes into the networks to aid the DTN relay. Several throw-boxes based routing protocols and location selection methods for throw-boxes are proposed. All pro- posed routing methods are evaluated via extensive simulations with real life trace data (such as MIT reality, Nokia MDC, and Orange D4D)

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

Complex Network Analysis and the Applications in Vehicle Delay-Tolerant Networks

Vehicle Delay Tolerant Networks (VDTNs) is a particular kind of Delay Tolerant Networks (DTNs), where vehicles equipped with transmission capabilities are interconnected to form Vehicle NETworks (VNETs). Some applications and services on the top of VDTNs have raised a lot of attention, especially by providing information about weather conditions, road safety, traffic jams, speed limit, and even video streamings without the need of infrastructures. However, due to features such as high vehicle mobility, dynamic scenarios, sparsity of vehicles, short contact durations, disruption and intermittent connectivity and strict requirements for latency, many VDTNs do not present satisfactory performance, because no path exists between a source and its target. In this dissertation, we propose three routing methods to solve the problem as follows. Our first VDTN system focuses on the multi-copy routing in Vehicle Delay Tolerant Networks (VDTNs). Multi-copy routing can balance the network congestion caused by broadcasting and the efficiency limitation in single-copy routing. However, the different copies of each packet search the destination node independently in current multi-copy routing algorithms, which leads to a low utilization of copies since they may search through the same path repeatedly without cooperation. To solve this problem, we propose a fractal Social community based efficient multi-coPy routing in VDTNs, namely SPread. First, we measure social network features in Vehicle NETworks (VNETs). Then, by taking advantage of weak ties and fractal structure feature of the community in VNETs, SPread carefully scatters different copies of each packet to different communities that are close to the destination community, thus ensuring that different copies search the destination community through different weak ties. For the routing of each copy, current routing algorithms either fail to exploit reachability information of nodes to different nodes (centrality based methods) or only use single-hop reachability information (community based methods), e.g., similarity and probability. Here, the reachability of node $i$ to a destination $j$ (a community or a node) means the possibility that a packet can reach $j$ through $i$. In order to overcome above drawbacks, inspired by the personalized PageRank algorithm, we design new algorithms for calculating multi-hop reachability of vehicles to different communities and vehicles dynamically. Therefore, the routing efficiency of each copy can be enhanced. Finally, extensive trace-driven simulation demonstrates the high efficiency of SPread in comparison with state-of-the-art routing algorithms in DTNs. However, in SPread, we only consider the VNETs as complex networks and fail to use the unique location information to improve the routing performance. We believe that the complex network knowledge should be combined with special features of various networks themselves in order to benefit the real application better. Therefore, we further explore the possibility to improve the performance of VDTN system by taking advantage of the special features of VNETs. We first analyze vehicle network traces and observe that i) each vehicle has only a few active sub-areas that it frequently visits, and ii) two frequently encountered vehicles usually encounter each other in their active sub-areas. We then propose Active Area based Routing method (AAR) which consists of two steps based on the two observations correspondingly. AAR first distributes a packet copy to each active sub-area of the target vehicle using a traffic-considered shortest path spreading algorithm, and then in each sub-area, each packet carrier tries to forward the packet to a vehicle that has high encounter frequency with the target vehicle. Furthermore, we propose a Distributed AAR (DAAR) to improve the performance of AAR. Extensive trace-driven simulation demonstrates that AAR produces higher success rates and shorter delay in comparison with the state-of-the-art routing algorithms in VDTNs. Also, DAAR has a higher success rate and a lower average delay compared with AAR since information of dynamic active sub-areas tends to be updated from time to time, while the information of static active sub-areas may be outdated due to the change of vehicles\u27 behaviors. Finally, we try to combine different routing algorithms together and propose a DIstributed Adaptive-Learning routing method for VDTNs, namely DIAL, by taking advantages of the human beings communication feature that most interactions are generated by pairs of people who interacted often previously. DIAL consists of two components: the information fusion based routing method and the adaptive-learning framework. The information fusion based routing method enables DIAL to improve the routing performance by sharing and fusing multiple information without centralized infrastructures. Furthermore, based on the information shared by information fusion based routing method, the adaptive-learning framework enables DIAL to design personalized routing strategies for different vehicle pairs without centralized infrastructures. Therefore, DIAL can not only share and fuse multiple information of each vehicle without centralized infrastructures, but also design each vehicle pair with personalized routing strategy. Extensive trace-driven simulation demonstrates that DIAL has better routing success rate, shorter average delays and the load balance function in comparison with state-of-the-art routing methods which need the help of centralized infrastructures in VDTNs

Message forwarding techniques in Bluetooth enabled opportunistic communication environment

These days, most of the mobile phones are smart enough with computer like intelligence and equipped with multiple communication technologies such as Bluetooth, wireless LAN, GPRS and GSM. Different communication medium on single device have unlocked the new horizon of communication means. Modern mobile phones are not only capable of using traditional way of communication via GSM or GPRS; but, also use wireless LANs using access points where available. Among these communication means, Bluetooth technology is very intriguing and unique in nature. Any two devices equipped with Bluetooth technology can communicate directly due to their unique IDs in the world. This is opposite to GSM or Wireless LAN technology; where devices are dependent on infrastructure of service providers and have to pay for their services. Due to continual advancement in the field of mobile technology, mobile ad-hoc network seems to be more realised than ever using Bluetooth. In traditional mobile ad-hoc networks (MANETs), before information sharing, devices have partial or full knowledge of routes to the destinations using ad-hoc routing protocols. This kind of communication can only be realised if nodes follow the certain pattern. However, in reality mobile ad-hoc networks are highly unpredictable, any node can join or leave network at any time, thus making them risky for effective communication. This issue is addressed by introducing new breed of ad-hoc networking, known as opportunistic networks. Opportunistic networking is a concept that is evolved from mobile ad-hoc networking. In opportunistic networks nodes have no prior knowledge of routes to intended destinations. Any node in the network can be used as potential forwarder with the exception of taking information one step closer to intended destination. The forwarding decision is based on the information gathered from the source node or encountering node. The opportunistic forwarding can only be achieved if message forwarding is carried out in store and forward fashion. Although, opportunistic networks are more flexible than traditional MANETs, however, due to little insight of network, it poses distinct challenges such as intermittent connectivity, variable delays, short connection duration and dynamic topology. Addressing these challenges in opportunistic network is the basis for developing new and efficient protocols for information sharing. The aim of this research is to design different routing/forwarding techniques for opportunistic networks to improve the overall message delivery at destinations while keeping the communication cost very low. Some assumptions are considered to improved directivity of message flow towards intended destinations. These assumptions exploit human social relationships analogies, approximate awareness of the location of nodes in the network and use of hybrid communication by combining several routing concept to gain maximum message directivity. Enhancement in message forwarding in opportunistic networks can be achieved by targeting key nodes that show high degree of influence, popularity or knowledge inside the network. Based on this observation, this thesis presents an improved version of Lobby Influence (LI) algorithm called as Enhanced Lobby Influence (ELI). In LI, the forwarding decision is based on two important factors, popularity of node and popularity of node’s neighbour. The forwarding decision of Enhanced Lobby Influence not only depends on the intermediate node selection criteria as defined in Lobby Influence but also based on the knowledge of previously direct message delivery of intended destination. An improvement can be observed if nodes are aware of approximate position of intended destinations by some communication means such as GPS, GSM or WLAN access points. With the knowledge of nodes position in the network, high message directivity can be achieved by using simple concepts of direction vectors. Based on this observation, this research presents another new algorithm named as Location-aware opportunistic content forwarding (LOC). Last but not least, this research presents an orthodox yet unexplored approach for efficient message forwarding in Bluetooth communication environment, named as Hybrid Content Forwarding (HCF). The new approach combines the characteristics of social centrality based forwarding techniques used in opportunistic networks with traditional MANETs protocols used in Bluetooth scatternets. Simulation results show that a significant increase in delivery radio and cost reduction during content forwarding is observed by deploying these proposed algorithms. Also, comparison with existing technique shows the efficiency of using the new schemes

FSF: Applying machine learning techniques to data forwarding in socially selfish Opportunistic Networks

[EN] Opportunistic networks are becoming a solution to provide communication support in areas with overloaded cellular networks, and in scenarios where a fixed infrastructure is not available, as in remote and developing regions. A critical issue, which still requires a satisfactory solution, is the design of an efficient data delivery solution trading off delivery efficiency, delay, and cost. To tackle this problem, most researchers have used either the network state or node mobility as a forwarding criterion. Solutions based on social behaviour have recently been considered as a promising alternative. Following the philosophy from this new category of protocols, in this work, we present our ¿FriendShip and Acquaintanceship Forwarding¿ (FSF) protocol, a routing protocol that makes its routing decisions considering the social ties between the nodes and both the selfishness and the device resources levels of the candidate node for message relaying. When a contact opportunity arises, FSF first classifies the social ties between the message destination and the candidate to relay. Then, by using logistic functions, FSF assesses the relay node selfishness to consider those cases in which the relay node is socially selfish. To consider those cases in which the relay node does not accept receipt of the message because its device has resource constraints at that moment, FSF looks at the resource levels of the relay node. By using the ONE simulator to carry out trace-driven simulation experiments, we find that, when accounting for selfishness on routing decisions, our FSF algorithm outperforms previously proposed schemes, by increasing the delivery ratio up to 20%, with the additional advantage of introducing a lower number of forwarding events. We also find that the chosen buffer management algorithm can become a critical element to improve network performance in scenarios with selfish nodes.This work was partially supported by the "Camilo Batista de Souza/Programa Doutorado-sanduiche no Exterior (PDSE)/Processo 88881.133931/2016-01" and by the Ministerio de Ciencia, Innovacion y Universidades, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018, Spain, under Grant RTI2018-096384-B-I00".Souza, C.; Mota, E.; Soares, D.; Manzoni, P.; Cano, J.; Tavares De Araujo Cesariny Calafate, CM.; Hernández-Orallo, E. (2019). FSF: Applying machine learning techniques to data forwarding in socially selfish Opportunistic Networks. Sensors. 19(10):1-26. https://doi.org/10.3390/s19102374S1261910Trifunovic, S., Kouyoumdjieva, S. T., Distl, B., Pajevic, L., Karlsson, G., & Plattner, B. (2017). A Decade of Research in Opportunistic Networks: Challenges, Relevance, and Future Directions. IEEE Communications Magazine, 55(1), 168-173. doi:10.1109/mcom.2017.1500527cmLu, X., Lio, P., & Hui, P. (2016). Distance-Based Opportunistic Mobile Data Offloading. Sensors, 16(6), 878. doi:10.3390/s16060878Zeng, F., Zhao, N., & Li, W. (2017). Effective Social Relationship Measurement and Cluster Based Routing in Mobile Opportunistic Networks. Sensors, 17(5), 1109. doi:10.3390/s17051109Khabbaz, M. J., Assi, C. M., & Fawaz, W. F. (2012). Disruption-Tolerant Networking: A Comprehensive Survey on Recent Developments and Persisting Challenges. IEEE Communications Surveys & Tutorials, 14(2), 607-640. doi:10.1109/surv.2011.041911.00093Miao, J., Hasan, O., Mokhtar, S. B., Brunie, L., & Yim, K. (2013). An investigation on the unwillingness of nodes to participate in mobile delay tolerant network routing. International Journal of Information Management, 33(2), 252-262. doi:10.1016/j.ijinfomgt.2012.11.001CRAWDAD Dataset Uoi/Haggle (v. 2016-08-28): Derived from Cambridge/Haggle (v. 2009-05-29)https://crawdad.org/uoi/haggle/20160828Eagle, N., Pentland, A., & Lazer, D. (2009). Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences, 106(36), 15274-15278. doi:10.1073/pnas.0900282106Tsai, T.-C., & Chan, H.-H. (2015). NCCU Trace: social-network-aware mobility trace. IEEE Communications Magazine, 53(10), 144-149. doi:10.1109/mcom.2015.7295476Hui, P., Crowcroft, J., & Yoneki, E. (2011). BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks. IEEE Transactions on Mobile Computing, 10(11), 1576-1589. doi:10.1109/tmc.2010.246Lindgren, A., Doria, A., & Schelén, O. (2003). Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mobile Computing and Communications Review, 7(3), 19-20. doi:10.1145/961268.961272Cao, Y., & Sun, Z. (2013). Routing in Delay/Disruption Tolerant Networks: A Taxonomy, Survey and Challenges. IEEE Communications Surveys & Tutorials, 15(2), 654-677. doi:10.1109/surv.2012.042512.00053Zhu, Y., Xu, B., Shi, X., & Wang, Y. (2013). A Survey of Social-Based Routing in Delay Tolerant Networks: Positive and Negative Social Effects. IEEE Communications Surveys & Tutorials, 15(1), 387-401. doi:10.1109/surv.2012.032612.00004Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Networks, 1(2-3), 215-233. doi:10.1016/s1570-8705(03)00003-9Burns, B., Brock, O., & Levine, B. N. (2008). MORA routing and capacity building in disruption-tolerant networks. Ad Hoc Networks, 6(4), 600-620. doi:10.1016/j.adhoc.2007.05.002Shaghaghian, S., & Coates, M. (2015). Optimal Forwarding in Opportunistic Delay Tolerant Networks With Meeting Rate Estimations. IEEE Transactions on Signal and Information Processing over Networks, 1(2), 104-116. doi:10.1109/tsipn.2015.2452811Li, L., Qin, Y., & Zhong, X. (2016). A Novel Routing Scheme for Resource-Constraint Opportunistic Networks: A Cooperative Multiplayer Bargaining Game Approach. IEEE Transactions on Vehicular Technology, 65(8), 6547-6561. doi:10.1109/tvt.2015.2476703Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L. S., & Rubenstein, D. (2002). Energy-efficient computing for wildlife tracking. ACM SIGPLAN Notices, 37(10), 96-107. doi:10.1145/605432.605408Spyropoulos, T., Psounis, K., & Raghavendra, C. S. (2008). Efficient Routing in Intermittently Connected Mobile Networks: The Single-Copy Case. IEEE/ACM Transactions on Networking, 16(1), 63-76. doi:10.1109/tnet.2007.897962Zhang, L., Wang, X., Lu, J., Ren, M., Duan, Z., & Cai, Z. (2014). A novel contact prediction-based routing scheme for DTNs. Transactions on Emerging Telecommunications Technologies, 28(1), e2889. doi:10.1002/ett.2889Okasha, S. (2005). Altruism, Group Selection and Correlated Interaction. The British Journal for the Philosophy of Science, 56(4), 703-725. doi:10.1093/bjps/axi143Hernandez-Orallo, E., Olmos, M. D. S., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2015). CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes. IEEE Transactions on Mobile Computing, 14(6), 1162-1175. doi:10.1109/tmc.2014.234362