Adaptive and occupancy-based channel selection for unreliable cognitive radio networks

In this paper, we propose an adaptive and occupancy-based channel selection for unreliable cognitive radio networks

Toward Reliable Contention-aware Data Dissemination in Multi-hop Cognitive Radio Ad Hoc Networks

This paper introduces a new channel selection strategy for reliable contentionaware data dissemination in multi-hop cognitive radio network. The key challenge here is to select channels providing a good tradeoff between connectivity and contention. In other words, channels with good opportunities for communication due to (1) low primary radio nodes (PRs) activities, and (2) limited contention of cognitive ratio nodes (CRs) acceding that channel, have to be selected. Thus, by dynamically exploring residual resources on channels and by monitoring the number of CRs on a particular channel, SURF allows building a connected network with limited contention where reliable communication can take place. Through simulations, we study the performance of SURF when compared with three other related approaches. Simulation results confirm that our approach is effective in selecting the best channels for efficient and reliable multi-hop data dissemination

Architectural Considerations for a Self-Configuring Routing Scheme for Spontaneous Networks

Decoupling the permanent identifier of a node from the node's topology-dependent address is a promising approach toward completely scalable self-organizing networks. A group of proposals that have adopted such an approach use the same structure to: address nodes, perform routing, and implement location service. In this way, the consistency of the routing protocol relies on the coherent sharing of the addressing space among all nodes in the network. Such proposals use a logical tree-like structure where routes in this space correspond to routes in the physical level. The advantage of tree-like spaces is that it allows for simple address assignment and management. Nevertheless, it has low route selection flexibility, which results in low routing performance and poor resilience to failures. In this paper, we propose to increase the number of paths using incomplete hypercubes. The design of more complex structures, like multi-dimensional Cartesian spaces, improves the resilience and routing performance due to the flexibility in route selection. We present a framework for using hypercubes to implement indirect routing. This framework allows to give a solution adapted to the dynamics of the network, providing a proactive and reactive routing protocols, our major contributions. We show that, contrary to traditional approaches, our proposal supports more dynamic networks and is more robust to node failures

The Power of Hood Friendship for Opportunistic Content Dissemination in Mobile Social Networks

We focus on dissemination of content for delay tolerant applications/services, (i.e. content sharing, advertisement propagation, etc.) where users are geographically clustered into communities. Due to emerging security and privacy related issues, majority of users are only willing to share information/content with the users who are previously identified as friends. In this environment, opportunistic communication will not be effective due to the lack of known friends within the communication range. In this paper, we propose a novel architecture that addresses the issues of lack of trust, timeliness of delivery, loss of user control, and privacy-aware distributed mobile social networking by combining the advantages of distributed decentralised storage and opportunistic communications. We formally define a content replication problem in mobile social networks and show that it is computationally hard to solve optimally. Then, we propose a community based greedy heuristic algorithm with novel dynamic centrality metrics to replicate content in well-selected users, to maximise the content dissemination with limited number of replication. Using both real world and synthetic traces, we show that content replication can attain a large coverage gain and reduce the content delivery latency

Proactive Data Dissemination in Wireless Sensor Networks with Uncontrolled Sink Mobility

This paper investigates Wireless Sensor Networks (WSNs) with mobile sinks that collect data from sensors by following uncontrolled trajectories. In particular, the paper focuses on proactive data dissemination strategies in which the trajectory of the mobile sink is unknown to the sensors. These strategies attempt to obtain a good trade-off between the number of sensors the mobile sinks has to visit in order to collect representative data of all sensors, and the communication effort required by the sensors. All the investigated techniques also avoid the use of multi-hop routing, due to its high cost. Some of them are based on random walks whereas others are based on a combination of probabilistic forwarding and probabilistic storage. An analysis of the various methods in terms of the performance trade-off between the efficiency of the data gathering and communication overhead is also presented

From your routine to hotspot deployment for data offloading

International audienceThis paper provides the framework to transform mobility of people in an urban scenario into a set of well-positioned places likely to receive wireless hostspots to support data offloading

Activity Pattern Impact of Primary Radio Nodes on Channel Selection Strategies

International audienceThe performance of cognitive radio network is highly dependent upon the primary radio nodes activity pattern. In this paper, we study and analyze the impact of different PR nodes activity pattern with the help of three performance metrics. In this perspective, we use our channel selection strategy SURF and three other channel selection strategies i.e., Random (RD), Highest Degree (HD), and Selective Broadcasting (SB). We analyze the performance of these channel selection strategies through extensive NS-2 simulations. Moreover, we also analyze how these strategies respond to different PR nodes activity. Simulation results confirm that SURF outperforms RD, HD, and SB in terms of delivery ratio and causes less harmful interference to PR nodes, in all primary radio nodes activity pattern

SURF: A Distributed Channel Selection Strategy for Data Dissemination in Multi-Hop Cognitive Radio Networks

In this paper, we propose an intelligent and distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio network. Our strategy, SURF, classifies the available channels and uses them efficiently to increase data dissemination reliability in multi-hop cognitive radio networks. The classification is done on the basis of primary radio unoccupancy and of the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we study the performance of SURF compared to three related approaches. Simulation results confirm that our approach is effective in selecting the best channels for efficient communication (in terms of less primary radio interference) and for highest dissemination reachability in multi-hop cognitive radio networks

Routine-based network deployment for data offloading in metropolitan area

International audienceThis paper tackles the WiFi hotspot deployment problem in a metropolitan area by leveraging mobile users' context, i.e., their trajectories and scenario interaction. The careful deployment of hotspots in such areas allow to maximize WiFi offloading, a viable solution to the recent boost up of mobile data consumption.Our proposed strategy considers the restrictions imposed by transportation modes to people trajectories and the space-time interaction between people and urban locations, key points for an efficient network planning. Using a real-life metropolitan trace, we show our strategy guarantees high coverage time with a small set of deployed hotspots