Social-aware Opportunistic Routing Protocol based on User's Interactions and Interests

Nowadays, routing proposals must deal with a panoply of heterogeneous devices, intermittent connectivity, and the users' constant need for communication, even in rather challenging networking scenarios. Thus, we propose a Social-aware Content-based Opportunistic Routing Protocol, SCORP, that considers the users' social interaction and their interests to improve data delivery in urban, dense scenarios. Through simulations, using synthetic mobility and human traces scenarios, we compare the performance of our solution against other two social-aware solutions, dLife and Bubble Rap, and the social-oblivious Spray and Wait, in order to show that the combination of social awareness and content knowledge can be beneficial when disseminating data in challenging networks

Innovative coordination of agribusiness chains and networks

To facilitate scientifically grounded innovative forms of strategic network coordination, this paper integrates two major bodies of literature on competitive advantage. The two bodies of literature are the industry-oriented outside-in approach, and the competence-oriented inside-out approach, here homogenized along the dimensions of degrees of firm embeddedness, respectively, the broadness of shared resource bases. The elements detailed are interfirm relationships, resource bases, network governance instruments, coordination mechanisms, the impact of events on network structures, and the active mobilisation of actors and resource. Thereby, the paper is able to detail 5 generic types of business networks. Next, it relates 21 network governance instruments to type of partnerships (binding vs loosening), forms of interaction (cooperative vs opportunistic). The realized reduction of network complexity enhances conceptual transparency and increases the instrumental usage of this research for effective network coordination by businesses. An integrated case illustrates the usefulness of the various concepts and the coherency of the different elements

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure