On Leveraging Partial Paths in Partially-Connected Networks

Mobile wireless network research focuses on scenarios at the extremes of the network connectivity continuum where the probability of all nodes being connected is either close to unity, assuming connected paths between all nodes (mobile ad hoc networks), or it is close to zero, assuming no multi-hop paths exist at all (delay-tolerant networks). In this paper, we argue that a sizable fraction of networks lies between these extremes and is characterized by the existence of partial paths, i.e. multi-hop path segments that allow forwarding data closer to the destination even when no end-to-end path is available. A fundamental issue in such networks is dealing with disruptions of end-to-end paths. Under a stochastic model, we compare the performance of the established end-to-end retransmission (ignoring partial paths), against a forwarding mechanism that leverages partial paths to forward data closer to the destination even during disruption periods. Perhaps surprisingly, the alternative mechanism is not necessarily superior. However, under a stochastic monotonicity condition between current v.s. future path length, which we demonstrate to hold in typical network models, we manage to prove superiority of the alternative mechanism in stochastic dominance terms. We believe that this study could serve as a foundation to design more efficient data transfer protocols for partially-connected networks, which could potentially help reducing the gap between applications that can be supported over disconnected networks and those requiring full connectivity.Comment: Extended version of paper appearing at IEEE INFOCOM 2009, April 20-25, Rio de Janeiro, Brazi

Leveraging information in vehicular parking games

Our paper approaches the parking assistance service in urban environments as an instance of service provision in non-cooperative network environments. We propose normative abstractions for the way drivers pursue parking space and the way they respond to partial or complete information for parking demand and supply as well as specific pricing policies on public and private parking facilities. The drivers are viewed as strategic agents who make rational decisions attempting to minimize the cost of the acquired parking spot. We formulate the resulting games as resource selection games and derive their equilibria under different expressions of uncertainty about the overall parking demand. The efficiency of the equilibrium states is compared against the optimal assignment that could be determined by a centralized entity and conditions are derived for minimizing the related price of anarchy value. Our results provide useful hints for the pricing and practical management of on-street and private parking resources. More importantly, they exemplify counterintuitive less-is-more effects about the way information availability modulates the service cost, which underpin general competitive service provision settings and contribute to the better understanding of effective information mechanisms

ISCoDe: A framework for interest similarity-based community detection in social networks

Abstract—This paper proposes a framework for node clus-tering in computerized social networks according to common interests. Communities in such networks are mainly formed by user selection, which may be based on various factors such as acquaintance, social status, educational background. However, such selection may result in groups that have a low degree of similarity. The proposed framework could improve the effective-ness of these social networks by constructing clusters of nodes with higher interest similarity, and thus maximize the benefit that users extract from their participation. The framework is based on methods for detecting communities over weighted graphs, where graph edge weights are defined based on measures of similarity between nodes ’ interests in certain thematic areas. The capacity of these measures to enhance the sensitivity and resolution of community detection is evaluated with concrete benchmark scenarios over synthetic networks. We also use the framework to assess the level of common interests among sample users of a popular online social application. Our results confirm that clusters formed by user selection have low degrees of similarity; our framework could, hence, be valuable in forming communities with higher coherence of interests. I

5G and the Internet of everyone: motivation, enablers, and research agenda

As mobile broadband subscriptions grow twice as fast as the fixed ones and the Internet of Things comes forth, the 5G vision of the Internet of Everything (people, devices, and things), becomes a substantial and credible part of the near future. In this paper, we argue that the 5G vision is still missing a fundamental concept to realize its societal promise: the Internet of EveryOne (IoEO), i.e., means and principles to overcome the concerns that the current 5G perspective raises for the digital divide and the network neutrality principle. We discuss open-source software and hardware, Community Networks, mobile edge computing and blockchains as enablers of the IoEO and highlight open research challenges with respect to them. The ultimate objective of our paper is to stimulate research with a short-term, lasting impact also on that 50% (or more) of population that will not enjoy 5G anytime soon. Internet of EveryOne, community networks, 5G, mobile edge computing, network neutrality, community cloud computing.Peer ReviewedPostprint (author's final draft

Exploiting user interest similarity and social links for micro-blog forwarding in mobile opportunistic networks

Micro-blogging services have recently been experiencing increasing success among Web users. Differ- ent to traditional online social applications, micro-blogs are lightweight, require small cognitive effort and help share real-time information about personal activities and interests. In this article we explore scalable pushing protocols that are particularly suited to the delivery of this type of service in a mobile pervasive environment. Here, micro-blog updates are generated and carried by mobile (smart-phone type) devices and are exchanged through opportunistic encounters. We enhance primitive push mechanisms using social information concerning the interests of network nodes as well as the frequency of encounters with them. This information is collected and shared dynamically, as nodes initially encounter each other and exchange their preferences, and directs the forwarding of micro-blog updates across the network. Also incorporated is the spatiotemporal scope of the updates, which is only partially considered in current Internet services. We introduce several new protocol variants that differentiate the forwarding strategy towards interest- similar and frequently encountered nodes, as well as the amount of updates forwarded upon each encounter. In all cases, the proposed scheme outperforms the basic flooding dissemination mechanism in delivering high numbers of micro-blog updates to the nodes interested in them. Our extensive evaluation highlights how use can be made of different amounts of social information to trade performance with complexity and computational effort. However, hard performance bounds appear to be set by the level of coincidence between interest-similar node communities and meeting groups emerging due to the mobility patterns of the nodes