MADServer: An Architecture for Opportunistic Mobile Advanced Delivery

Rapid increases in cellular data traffic demand creative alternative delivery vectors for data. Despite the conceptual attractiveness of mobile data offloading, no concrete web server architectures integrate intelligent offloading in a production-ready and easily deployable manner without relying on vast infrastructural changes to carriers’ networks. Delay-tolerant networking technology offers the means to do just this. We introduce MADServer, a novel DTN-based architecture for mobile data offloading that splits web con- tent among multiple independent delivery vectors based on user and data context. It enables intelligent data offload- ing, caching, and querying solutions which can be incorporated in a manner that still satisfies user expectations for timely delivery. At the same time, it allows for users who have poor or expensive connections to the cellular network to leverage multi-hop opportunistic routing to send and receive data. We also present a preliminary implementation of MADServer and provide real-world performance evaluations

Context-based adaptation in delay-tolerant networks

textDelay-tolerant networks (DTNs) are dynamic networks in which senders and receivers are often completely disconnected from each other, often for long periods of time. DTNs are enjoying a burgeoning interest from the research community largely due to the vast potential for meaningful applications, e.g., to enable access to the Internet in remote rural areas, monitor animal behavioral patterns, connect participants in mobile search and rescue applications, provide connectivity in urban environments, and support space communications. Existing work in DTNs generally focuses either on solutions for very specific applications or domains, or on general-purpose protocol-level solutions intended to work across multiple domains. In this proposal, we take a more systems-oriented approach to DTNs. Since applications operating in these dynamic environments would like their connections to be supported by the network technology best suited to the combination of the communication session's requirements and instantaneous network context, we develop a middleware architecture that enables seamless migrations from one communication style to another in response to changing network conditions. We also enable context-awareness in DTNs, using this awareness to adapt communications to more efficiently use network resources. Finally, we explore the systems issues inherent to such a middleware and provide an implementation of it that we test on a mobile computing testbed made up of autonomous robots.Electrical and Computer Engineerin