Opportunistic networks are constructed by devices carried by people and vehicles. The devices use short range radio to communicate. Since the network is mobile and often sparse in terms of node contacts, nodes store messages in their buffers, carrying them, and forwarding them upon node encounters. This form of communication leads to a set of challenging issues that we investigate: congestion, transfer ordering, and resilience. Congestion occurs in opportunistic networks when a node's buffers becomes full. To be able to receive new messages, old messages have to be evicted. We show that buffer eviction strategies based on replication statistics perform better than strategies that evict messages based on the content of the message. We show that transfer ordering has a significant impact on the dissemination of messages during time limited contacts. We find that transfer strategies satisfying global requests yield a higher delivery ratio but a longer delay for the most requested data compared to satisfying the neighboring node's requests. Finally, we assess the resilience of opportunistic networks by simulating different types of attacks. Instead of enumerating all possible attack combinations, which would lead to exhaustive evaluations, we introduce a method that use heuristics to approximate the extreme outcomes an attack can have. The method yields a lower and upper bound for the evaluated metric over the different realizations of the attack. We show that some types of attacks are harder to predict the outcome of and other attacks may vary in the impact of the attack due to the properties of the attack, the forwarding protocol, and the mobility pattern. / WISENET

Mobile communication devices may be used for spreading multimedia data without support of an infrastructure. Such a scheme, where the data is carried by people walking around and relayed from device to device by means of short range radio, could potentially form a public content distribution system that spans vast urban areas. The transport mechanism is the flow of people and it can be studied but not engineered. We study the efficiency of pedestrian content distribution by modeling the mobility of people moving around in a city, constrained by a given topology. The model is supplemented by simulation of similar or related scenarios for validation and extension. The results show that contents spread well with pedestrian speeds already at low arrival rates into a studied region. Our contributions are both the queuing analytic model that captures the flow of people and the results on the feasibility of pedestrian content distribution. / <p>QC 20130109</p>