Aline Carneiro Viana

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 four 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.

Gossiping on MANETs: the beauty and the beast

Gossip protocols have emerged as a powerful technique for implementing highly scalable and robust services, such as information dissemination and aggregation. The fact that gossip protocols require very little or no structure to operate makes them particularly appealing to apply in dynamic systems, where topology changes are common (for instance, due to frequent faults or high churn rates). Therefore, gossip protocols seem particularly well fit to operate in wireless self-organizing networks. Unfortunately, these networks have a number of characteristics that impede the deployment of gossip protocols designed for wired networks. In this work we identify the inherent differences in communication between wired and wireless networks and their impact on the design and implementation of gossip protocols. In particular, our comparison includes drawing a distinction between the gossiping primitives suitable for each of these environments. In the context of this analysis, we conclude by presenting a list of open research questions.

DEEP: Density-based proactive data dissemination protocol for wireless sensor networks with uncontrolled sink mobility

This paper investigates proactive data dissemination and storage schemes for wireless sensor networks (WSNs) with mobile sinks. The focus is on schemes that do not impose any restrictions on the sinks mobility pattern. The goal is to enable the sink to collect a representative view of the networks sensed data by visiting any set of x out of n nodes, where x@?n. The question is how to obtain this while maintaining a good trade-off between the communication overhead of the scheme, the storage space requirements on the nodes, and the ratio between the number of visited nodes x and the representativeness of the gathered data. To answer this question, we propose density-based proactivE data dissEmination Protocol (DEEP), which combines a probabilistic flooding with a probabilistic storing scheme. The DEEP protocol is formally analyzed and its performance is studied under simulations using different network densities and compared with a scheme based on random walks, called RaWMS.

VIP delegation: Enabling VIPs to offload data in wireless social mobile networks

We propose the use of opportunistic delegation as a data traffic offload solution to the recent boost up of mobile data consumption in metropolitan areas, by investigating two main questions: (i) “How to gain insights into social mobile networking scenarios?” and (ii) “How to utilize such insights to design solutions to alleviate overloaded 3G networks?”. The purpose of our solution is to leverage usage of mobile applications requiring large data transfers by channeling the traffic to a few, socially selected important users in the network called VIP delegates. The proposed VIP selection strategies are based on social network properties and are compared to the optimal solution (that covers 100% of users with minimum number of VIPs). Our extensive experiments with real and synthetic traces show the effectiveness of VIP delegation both in terms of coverage and required number of VIPs — down to 7% in average of VIPs are needed in campuslike scenarios to offload about 90% of the traffic.

A Smart Parking Lot Management System for Scheduling the Recharging of Electric Vehicles

In this paper, we propose a centralized electric vehicles (EVs) recharge scheduling system for parking lots using a realistic vehicular mobility/parking pattern focusing on individual parking lots. We consider two different types of EV based on their mobility/parking patterns: 1) regular EVs; and 2) irregular EVs. An extensive trace-based vehicular mobility model collected from the Canton of Zurich is used for the regular EVs, and a probabilistic pattern built on top of this trace is used for modeling the behavior of irregular EVs. To the extent of our knowledge, this is the first EV charging scheduling study in the literature that takes into account a realistic vehicular mobility pattern focusing on individual parking lots. We compare the performance of our proposed system with two well-known basic scheduling mechanisms, first come first serve and earliest deadline first, with regard to two objective functions: 1) maximizing the total parking lot revenue; and 2) maximizing the total number of EVs fulfilling their requirements. Comparison results show that our proposed system outperforms well-known basic scheduling mechanisms with regards to both objectives. Parking lots managing the recharging of a high number of EVs will greatly benefit from using such recharge scheduling systems in the context of smart cities.

Indirect routing using distributed location information

This paper proposes the Tribe protocol, an indirect routing strategy for wireless self-organizing networks. The protocol is intended to be applied in environments with large number of users, where mobility is taken into account, and the correct operation of the system does not require the support of a fixed (wired or wireless) infrastructure. In Tribe, nodes build a network infrastructure which describes the nodes relative location according to the current nodes neighborhood. Furthermore, routing is unique and completely independent of any global connectivity ensured by a network-level routing protocol. The architecture is generic, self-organizing, and independent of IP-like addressing limitations.

Data communication in VANETs: Protocols, applications and challenges

Abstract VANETs have emerged as an exciting research and application area. Increasingly vehicles are being equipped with embedded sensors, processing and wireless communication capabilities. This has opened a myriad of possibilities for powerful and potential life-changing applications on safety, efficiency, comfort, public collaboration and participation, while they are on the road. Although, considered as a special case of a Mobile Ad Hoc Network, the high but constrained mobility of vehicles bring new challenges to data communication and application design in VANETs. This is due to their highly dynamic and intermittent connected topology and different application’s QoS requirements. In this work, we survey VANETs focusing on their communication and application challenges. In particular, we discuss the protocol stack of this type of network, and provide a qualitative comparison between most common protocols in the literature. We then present a detailed discussion of different categories of VANET applications. Finally, we discuss open research problems to encourage the design of new VANET solutions.

A distributed data storage protocol for heterogeneous wireless sensor networks with mobile sinks

Abstract This paper presents ProFlex, a distributed data storage protocol for large-scale Heterogeneous Wireless Sensor Networks (HWSNs) with mobile sinks. ProFlex guarantees robustness in data collection by intelligently managing data replication among selected storage nodes in the network. Contrarily to related protocols in the literature, ProFlex considers the resource constraints of sensor nodes and constructs multiple data replication structures, which are managed by more powerful nodes. Additionally, ProFlex takes advantage of the higher communication range of such powerful nodes and uses the long-range links to improve data distribution by storage nodes. When compared with related protocols, we show through simulation that Proflex has an acceptable performance under message loss scenarios, decreases the overhead of transmitted messages, and decreases the occurrence of the energy hole problem. Moreover, we propose an improvement that allows the protocol to leverage the inherent data correlation and redundancy of wireless sensor networks in order to decrease even further the protocol’s overhead without affecting the quality of the data distribution by storage nodes.

Data offloading in social mobile networks through VIP delegation

Abstract The recent boost up of mobile data consumption is straining cellular networks in metropolitan areas and is the main reason for the ending of unlimited data plans by many providers. To address this problem, we propose the use of series opportunistic delegation as a data traffic offload solution by investigating two main questions: (i) “Can we characterize a given social mobile scenario by observing only a small portion of it?”. (ii) “How to exploit this characterization so to design solutions that alleviate overloaded cellular networks?”. In our solution we build a social-graph of the given scenario by observing it for a period as short as 1-week, and then leverage a few, socially important users in the social-graph—the VIPs—to offload the network. The proposed VIP selection strategies are based on social network properties and are compared to the optimal (offline) solution. Through extensive evaluations with real and synthetic traces we show the effectiveness of VIP delegation both in terms of coverage and required number of VIPs – down to 7% in average of VIPs are needed in campus-like scenarios to offload about 90% of the traffic.

Optimized Asynchronous Multichannel Discovery of IEEE 802.15.4-Based Wireless Personal Area Networks

Network discovery is a fundamental task in different scenarios of IEEE 802.15.4-based wireless personal area networks. Scenario examples are body sensor networks requiring health- and wellness-related patient monitoring or situations requiring opportunistic message propagation. In this paper, we investigate optimized discovery of IEEE 802.15.4 static and mobile networks operating in multiple frequency bands and with different beacon intervals. We present a linear programming model that allows finding two optimized strategies, named OPT and SWOPT, to deal with the asynchronous and multichannel discovery problem. We also propose a simplified discovery solution, named SUBOPT, featuring a low-complexity algorithm requiring less memory usage. A cross validation between analytical, simulation, and experimental evaluation methods is performed. Finally, a more detailed simulation-based evaluation is presented, when considering varying sets of parameters (i.e., number of channels, network density, beacon intervals, etc.) and using static and mobile scenarios. The performance studies confirm improvements achieved by our solutions in terms of first, average, and last discovery time as well as discovery ratio, when compared to IEEE 802.15.4 standard approach and the SWEEP approach known from the literature.