Mobile users are envisioned to exploit direct communication opportunities between their portable devices, in order to enrich the set of services they can access through cellular or WiFi networks. Sharing contents of common interest or providing access to resources or services between peers can enhance a mobile node's capabilities, offload the cellular network, and disseminate information to nodes without Internet access. Interest patterns, i.e. how many nodes are interested in each content or service (popularity), as well as how many users can provide a content or service (availability) impact the performance and feasibility of envisioned applications. In this paper, we establish an analytical framework to study the effects of these factors on the delay and success probability of a content service access request through opportunistic communication. We also apply our framework to the mobile data offloading problem and provide insights for the optimization of its performance. We validate our model and results through realistic simulations, using datasets of real opportunistic networks.
Recently, further novel content-centric application have been proposed, like location-based applications @cite_9 @cite_1 and mobile data offloading @cite_27 @cite_34 @cite_32 . The latter category, due to the rapid increase of mobile data demand, has attracted a lot of attention. In the setting of @cite_27 , content copies are initially distributed (through the infrastructure) to a subset of mobile nodes, which then start propagating the contents epidemically. Differently, in @cite_34 the authors consider a limited number of holders, and study how to select the best holders-target-set for each message. @cite_21 , the same problem is considered, and (centralized) optimization algorithms are proposed that take into account more information about the network: namely, size and lifetimes of different contents, and interests, privacy policies and buffer sizes of each node.
@cite_9 @cite_21 @cite_1 @cite_32 @cite_27 @cite_34
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This paper proposes a novel network architecture based on content routing and dissemination techniques, expressly adapted for hybrid mobile and vehicular ad-hoc networks. Hybrid vehicular ad-hoc networks (VANETs) are a subclass of mobile ad-hoc networks (MANETs) where each node is a moving vehicle equipped with one or more communication devices, potentially having access to several different physical communication channels. This results in a partly decentralized, self-organizing mobile radio network with a fast changing topology. Applications designed for VANETs still require efficient mapping techniques to associate content to the host serving it, as well as centralized databases associating vehicles and mobile nodes to a persistent and unique identifier. They also assume that the content providers are located in the infrastructure, but nodes and vehicles can be equipped with sensors and as such produce information. This means that dissemination and retrieval algorithms have to take into account the distribution of the consumers, providers and forwarder all over the network. We propose an architecture based on Van Jacobson's Content Centric Networking, extended and modified to solve some of the issues related to content access and dissemination across hybrid VANETs. The implementation and simulation on a realistic platform are presented as well as an application to a real case scenario, demonstrating the efficiency of the approach. Location-based services have become widely available on mobile devices. Existing methods employ a pull model or user-initiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish subscribe system to deliver publishers' messages to relevant subscribers.In this paper, we address the research challenges that arise in designing a location-aware publish subscribe system. We propose an rtree based index structure by integrating textual descriptions into rtree nodes. We devise efficient filtering algorithms and develop effective pruning techniques to improve filtering efficiency. Experimental results show that our method achieves high performance. For example, our method can filter 500 tweets in a second for 10 million registered subscriptions on a commodity computer. We suggest a novel approach to handle the ongoing explosive increase in the demand for video content in mobile devices. We envision femtocell-like base stations, which we call helpers, with weak backhaul links but large storage capabilities. These helpers form a wireless distributed caching network that assists the macro base station by handling requests of popular files that have been cached. We formalize the wireless distributed caching optimization problem for the case that files are encoded using fountain MDS codes. We express the problem as a convex optimization. By adding additional variables we reduce it to a linear program. On the practical side, we present a detailed simulation of a university campus scenario covered by a single 3GPP LTE R8 cell and several helper nodes using a simplified 802.11n protocol. We use a real campus trace of video requests and show how distributed caching can increase the number of served users by as much as 600–700 . Emerging challenged networks require new protocols and strategies to cope with a high degree of mobility, high delays and unknown, possibly non-existing routes within the network. Researchers have proposed different store-carry-and-forward protocols for data delivery in challenged networks. These have been complemented with appropriate drop and scheduling policies that deal with the limitations of the nodes' buffers and the limited duration of opportunistic encounters in these networks. Nevertheless, the vast majority of these protocols and strategies are designed for end-to-end transmissions. Yet, a paradigm shift from the traditional way of addressing the endpoints in the network has been occurring towards content-centric networking. To this end, we present CEDO, a content-centric dissemination algorithm for challenged networks. CEDO aims at maximizing the total delivery-rate of distributed content in a setting where a range of contents of different popularity may be requested and stored, but nodes have limited resources. It achieves this by maintaining a delivery-rate utility per content that is proportional to the content miss rate and that is used by the nodes to make appropriate drop and scheduling decisions. This delivery-rate utility can be estimated locally by each node using unbiased estimators fed by sampled information on the mobile network obtained by gossiping. Both simulations and theory suggest that CEDO achieves its set goal, and outperforms a baseline LRU-based policy by 72 , even in relatively small scenarios. The framework followed by CEDO is general enough to be applied to other global performance objectives as well.