Eva Jaho

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.

Access network synthesis game in next generation networks

In next generation communication networks, multiple access networks will coexist on a common service platform. In cases where network resource planning indicates that individual access network resources are insufficient to meet service demands, these networks can cooperate and combine their resources to form a unified network that satisfies these demands. We introduce and study the Network Synthesis game, in which individual access networks with insufficient resources form coalitions in order to satisfy service demands. The formation of stable coalitions in the core of the game is investigated, in both cases where payoffs are transferable or are attributed in proportion to the contribution of each member of the coalition. We also consider an alternative payoff allocation approach, according to the value of the well-known Shapley-Shubik, Banzhaf and Holler-Packel power indices, which represent the relative power each player has in the formation of coalitions. Using the knowledge attained from the coalition game analysis, we propose a new power index, called Popularity Power Index, which is based on the number of stable coalitions an access network would participate in if payoffs were assigned in a fair manner.

Modeling gossip-based content dissemination and search in distributed networking

This paper presents a rigorous analytic study of gossip-based message dissemination schemes that can be employed for content/service dissemination or discovery in unstructured and distributed networks. When using random gossiping, communication with multiple peers in one gossiping round is allowed. The algorithms studied in this paper are considered under different network conditions, depending on the knowledge of the state of the neighboring nodes in the network. Different node behaviors, with respect to their degree of cooperation and compliance with the gossiping process, are also incorporated. From the exact analysis, several important performance metrics and design parameters are analytically determined. Based on the proposed metrics and parameters, the performance of the gossip-based dissemination or search schemes, as well as the impact of the design parameters, are evaluated.

Social Similarity Favors Cooperation: The Distributed Content Replication Case

This paper explores how the degree of similarity within a social group can dictate the behavior of the individual nodes, so as to best tradeoff the individual with the social benefit. More specifically, we investigate the impact of social similarity on the effectiveness of content placement and dissemination. We consider three schemes that represent well the spectrum of behavior-shaped content storage strategies: the selfish, the self-aware cooperative, and the optimally altruistic ones. Our study shows that when the social group is tight (high degree of similarity), the optimally altruistic behavior yields the best performance for both the entire group (by definition) and the individual nodes (contrary to typical expectations). When the group is made up of members with almost no similarity, altruism or cooperation cannot bring much benefit to either the group or the individuals and thus, selfish behavior emerges as the preferable choice due to its simplicity. Notably, from a theoretical point of view, our “similarity favors cooperation” argument is inline with sociological interpretations of human altruistic behavior. On a more practical note, the self-aware cooperative behavior could be adopted as an easy to implement distributed alternative to the optimally altruistic one; it has close to the optimal performance for tight social groups and the additional advantage of not allowing mistreatment of any node, i.e., its induced content retrieval cost is always smaller than the cost of the selfish strategy.

Social similarity as a driver for selfish, cooperative and altruistic behavior

This paper explores how the degree of similarity within a social group can be exploited in order to dictate the behavior of the individual nodes, so as to best accommodate the typically non-coinciding individual and social benefit maximization. More specifically, this paper investigates the impact of social similarity on the effectiveness of content dissemination, as implemented through three classes representing well the spectrum of behavior-shaped content storage strategies: the selfish, the self-aware cooperative and the optimally altruistic ones. This study shows that when the social group is tight (high degree of similarity), the optimally altruistic behavior yields the best performance for both the entire group (by definition) and the individual nodes (contrary to typical expectations). When the group is made up of foreigners with almost no similarity, altruism or cooperation cannot bring much benefits to either the group or the individuals and thus, a selfish behavior would make sense due to its simplicity. Finally, the self-aware cooperative behavior could be adopted as an easy to implement distributed scheme — compared to the optimally altruistic one — that has close to the optimal performance for tight social groups, and has the additional advantage of not allowing mistreatment to any node (i.e., the content retrieval cost become larger compared to the cost of the selfish strategy).

OnMove: a protocol for content distribution in wireless delay tolerant networks based on social information

We present OnMove, a protocol for content distribution in wireless delay tolerant networks for use by handheld devices. To improve content distribution, OnMove exploits social characteristics (social similarities and physical encounters) between individuals. We motivate the problem and describe a content sharing protocol based on a ranking algorithm that exploits the social and networking characteristics of individuals.

Cooperative content retrieval in nomadic sensor networks

A nomadic sensor network consists of: (a) sensor nodes, that are fixed at some points and collect information about states or variables of the environment, and (b) mobile nodes that collect and disseminate this information. Mobile nodes usually belong to different classes, and are thus interested in different subsets of sensor node information. In such networks, dissemination of information content at smaller costs can be achieved if mobile nodes are cooperative and collect and carry information not only in their own interest, but also in the interest of other mobile nodes. A specific modeling scenario is considered in this paper where the network has the form of a graph; sensor nodes are located on the vertices of the graph and U-nodes move along the edges according to a random waypoint model. We present a game-theoretic analysis to find conditions under which a cooperative equilibrium can be sustained.