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See detailService Performance Pattern Analysis and Prediction of Commercially Available Cloud Providers
Wagle, Shyam Sharan UL; Guzek, Mateusz UL; Bouvry, Pascal UL

in Service Performance Pattern Analysis and Prediction of Commercially Available Cloud Providers (in press)

The knowledge of service performance of cloud providers is essential for cloud service users to choose the cloud services that meet their requirements. Instantaneous performance readings are accessible ... [more ▼]

The knowledge of service performance of cloud providers is essential for cloud service users to choose the cloud services that meet their requirements. Instantaneous performance readings are accessible, but prolonged observations provide more reliable information. However, due to technical complexities and costs of monitoring services, it may not be possible to access the service performance of cloud provider for longer time durations. The extended observation periods are also a necessity for prediction of future behavior of services. These predictions have very high value for decision making both for private and corporate cloud users, as the uncertainty about the future performance of purchased cloud services is an important risk factor. Predictions can be used by specialized entities, such as cloud service brokers (CSBs) to optimally recommend cloud services to the cloud users. In this paper, we address the challenge of prediction. To achieve this, the current service performance patterns of cloud providers are analyzed and future performance of cloud providers are predicted using to the observed service performance data. It is done using two automatic predicting approaches: ARIMA and ETS. Error measures of entire service performance prediction of cloud providers are evaluated against the actual performance of the cloud providers computed over a period of one month. Results obtained in the performance prediction show that the methodology is applicable for both short- term and long-term performance prediction. [less ▲]

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See detailHigh-Precision Design of Pedestrian Mobility for Smart City Simulators
Vitello, Piergiorgio; Capponi, Andrea UL; Fiandrino, Claudio UL et al

in IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018 (2018, May)

The unprecedented growth of the population living in urban environments calls for a rational and sustainable urban development. Smart cities can fill this gap by providing the citizens with high-quality ... [more ▼]

The unprecedented growth of the population living in urban environments calls for a rational and sustainable urban development. Smart cities can fill this gap by providing the citizens with high-quality services through efficient use of Information and Communication Technology (ICT). To this end, active citizen participation with mobile crowdsensing (MCS) techniques is a becoming common practice. As MCS systems require wide participation, the development of large scale real testbeds is often not feasible and simulations are the only alternative solution. Modeling the urban environment with high precision is a key ingredient to obtain effective results. However, currently existing tools like OpenStreetMap (OSM) fail to provide sufficient levels of details. In this paper, we apply a procedure to augment the precision (AOP) of the graph describing the street network provided by OSM. Additionally, we compare different mobility models that are synthetic and based on a realistic dataset originated from a well known MCS data collection campaign (ParticipAct). For the dataset, we propose two arrival models that determine the users’ arrivals and match the experimental contact distribution. Finally, we assess the scalability of AOP for different cities, verify popular metrics for human mobility and the precision of different arrival models. [less ▲]

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See detailCollision Avoidance Effects on the Mobility of a UAV Swarm Using Chaotic Ant Colony with Model Predictive Control
Dentler, Jan Eric UL; Rosalie, Martin UL; Danoy, Grégoire UL et al

in Journal of Intelligent \& Robotic Systems (2018)

The recent development of compact and economic small Unmanned Aerial Vehicles (UAVs) permits the development of new UAV swarm applications. In order to enhance the area coverage of such UAV swarms, a ... [more ▼]

The recent development of compact and economic small Unmanned Aerial Vehicles (UAVs) permits the development of new UAV swarm applications. In order to enhance the area coverage of such UAV swarms, a novel mobility model has been presented in previous work, combining an Ant Colony algorithm with chaotic dynamics (CACOC). This work is extending CACOC by a Collision Avoidance (CA) mechanism and testing its efficiency in terms of area coverage by the UAV swarm. For this purpose, CACOC is used to compute UAV target waypoints which are tracked by model predictively controlled UAVs. The UAVs are represented by realistic motion models within the virtual robot experimentation platform (V-Rep). This environment is used to evaluate the performance of the proposed CACOC with CA algorithm in an area exploration scenario with 3 UAVs. Finally, its performance is analyzed using metrics. [less ▲]

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See detailProfiling Energy Efficiency of Mobile Crowdsensing Data Collection Frameworks for Smart City Applications
Tomasoni, Mattia; Capponi, Andrea UL; Fiandrino, Claudio UL et al

in The 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (IEEE Mobile Cloud 2018) (2018, March)

Mobile crowdsensing (MCS) has emerged in the last years and has become one of the most prominent paradigms for urban sensing. In MCS, citizens actively participate in the sensing process by contributing ... [more ▼]

Mobile crowdsensing (MCS) has emerged in the last years and has become one of the most prominent paradigms for urban sensing. In MCS, citizens actively participate in the sensing process by contributing data with their smartphones, tablets, wearables and other mobile devices to a collector. As citizens sustain costs while contributing data, i.e., the energy spent from the batteries for sensing and reporting, devising energy efficient data collection frameworks (DCFs) is essential. In this work, we compare the energy efficiency of several DCFs through CrowdSenSim, which allows to perform large-scale simulation experiments in realistic urban environments. Specifically, the DCFs under analysis differ one with each other by the data reporting mechanism implemented and the signaling between users and the collector needed for sensing and reporting decisions. Results reveal that the key criterion differentiating DCFs' energy consumption is the data reporting mechanism. In principle, continuous reporting to the collector should be more energy consuming than probabilistic reporting. However, DCFs with continuous reporting that implement mechanisms to block sensing and data delivery after a certain amount of contribution are more effective in harvesting data from the crowd. [less ▲]

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See detailBayesian optimization to enhance coverage performance of a swarm of UAV with chaotic dynamics
Kieffer, Emmanuel UL; Rosalie, Martin UL; Danoy, Grégoire UL et al

Scientific Conference (2018, February 26)

We introduce the optimization of CACOC through Bayesian Optimization. CACOC is based on a chaotic system, i.e. Rossler system whose behavior can be modified by tuning the α parameter. In order to evaluate ... [more ▼]

We introduce the optimization of CACOC through Bayesian Optimization. CACOC is based on a chaotic system, i.e. Rossler system whose behavior can be modified by tuning the α parameter. In order to evaluate the performance of CACOC for different value of α, the coverage metric has to be evaluated after simulation. The latter is time-consuming. Therefore, a surrogate-based optimization, i.e. Bayesian Optimization has been privilegied to tackle this issue. An analysis of the chaotic system with the obtained α value has been performed to compare the periodic orbits and their associated patterns. Numerical results show that the best α value avoid a waste of time in periodic region of the bifurcation diagram. Future works will focus on more complex chaotic system as well as new application domain of the optimized CACOC approach. [less ▲]

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See detailProceedings - 2017 ILILAS Distinguished Lectures
Bouvry, Pascal UL; Bisdorff, Raymond; Schommer, Christoph UL et al

Report (2018)

The Proceedings summarizes the 12 lectures that have taken place within the ILIAS Dinstguished Lecture series 2017. It contains a brief abstract of the talks as well as some additional information about ... [more ▼]

The Proceedings summarizes the 12 lectures that have taken place within the ILIAS Dinstguished Lecture series 2017. It contains a brief abstract of the talks as well as some additional information about each speaker. [less ▲]

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See detailChaos-enhanced mobility models for multilevel swarms of UAVs
Rosalie, Martin UL; Danoy, Grégoire UL; Chaumette, Serge et al

in Swarm and Evolutionary Computation (2018)

The number of civilian and military applications using Unmanned Aerial Vehicles (UAVs) has increased during the last years and the forecasts for upcoming years are exponential. One of the current major ... [more ▼]

The number of civilian and military applications using Unmanned Aerial Vehicles (UAVs) has increased during the last years and the forecasts for upcoming years are exponential. One of the current major challenges consist in considering UAVs as autonomous swarms to address some limitations of single UAV usage such as autonomy, range of operation and resilience. In this article we propose novel mobility models for multi-level swarms of collaborating UAVs used for the coverage of a given area. These mobility models generate unpredictable trajectories using a chaotic solution of a dynamical system. We detail how the chaotic properties are used to structure the exploration of an unknown area and enhance the exploration part of an Ant Colony Optimization method. Empirical evidence of the improvement of the coverage efficiency obtained by our mobility models is provided via simulation. It clearly outperforms state-of-the-art approaches. [less ▲]

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See detailRapidRMSD: Rapid determination of RMSDs corresponding to motions of flexible molecules
Neveu, Emilie; Popov, Petr; Hoffmann, Alexandre et al

in Bioinformatics (2018)

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See detailSingle and Multiobjective Evolutionary Algorithms for Clustering Biomedical Information with Unknown Number of Clusters
Curi, María Eugenia; Carozzi, Lucía; Massobrio, Renzo et al

in Bioinspired Optimization Methods and Their Applications (2018)

This article presents single and multiobjective evolutionary approaches for solving the clustering problem with unknown number of clusters. Simple and ad-hoc operators are proposed, aiming to keep the ... [more ▼]

This article presents single and multiobjective evolutionary approaches for solving the clustering problem with unknown number of clusters. Simple and ad-hoc operators are proposed, aiming to keep the evolutionary search as simple as possible in order to scale up for solving large instances. The experimental evaluation is performed considering a set of real problem instances, including a real-life problem of analyzing biomedical information in the Parkinson's disease map project. The main results demonstrate that the proposed evolutionary approaches are able to compute accurate trade-off solutions and efficiently handle the problem instance involving biomedical information. [less ▲]

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See detailChaotic Traversal (CHAT): Very Large Graphs Traversal Using Chaotic Dynamics
Changaival, Boonyarit UL; Rosalie, Martin UL; Danoy, Grégoire UL et al

in International Journal of Bifurcation and Chaos (2017), 27(14), 1750215

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first ... [more ▼]

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first stepping stone into knowledge extraction from the graph which is now a popular topic. Classical solutions such as Breadth First Search (BFS) and Depth First Search (DFS) require huge amounts of memory for exploring very large graphs. In this research, we present a novel memoryless graph traversal algorithm, Chaotic Traversal (CHAT) which integrates chaotic dynamics to traverse large unknown graphs via the Lozi map and the Rössler system. To compare various dynamics effects on our algorithm, we present an original way to perform the exploration of a parameter space using a bifurcation diagram with respect to the topological structure of attractors. The resulting algorithm is an efficient and nonresource demanding algorithm, and is therefore very suitable for partial traversal of very large and/or unknown environment graphs. CHAT performance using Lozi map is proven superior than the, commonly known, Random Walk, in terms of number of nodes visited (coverage percentage) and computation time where the environment is unknown and memory usage is restricted. [less ▲]

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See detailIntelligent Gaming for Mobile Crowd-Sensing Participants to Acquire Trustworthy Big Data in the Internet of Things
Pouryazdan, Maryam; Fiandrino, Claudio; Kantarci, Burak et al

in IEEE Access (2017), 5

In mobile crowd-sensing systems, the value of crowd-sensed big data can be increased by incentivizing the users appropriately. Since data acquisition is participatory, crowd-sensing systems face the ... [more ▼]

In mobile crowd-sensing systems, the value of crowd-sensed big data can be increased by incentivizing the users appropriately. Since data acquisition is participatory, crowd-sensing systems face the challenge of data trustworthiness and truthfulness assurance in the presence of adversaries whose motivation can be either manipulating sensed data or collaborating unfaithfully with the motivation of maximizing their income. This paper proposes a game theoretic methodology to ensure trustworthiness in user recruitment in mobile crowd-sensing systems. The proposed methodology is a platform-centric framework that consists of three phases: user recruitment, collaborative decision making on trust scores, and badge rewarding. In the proposed framework, users are incentivized by running sub-game perfect equilibrium and gami cation techniques. Through simulations, we showthat approximately 50% and a minimum of 15% improvement can be achieved by the proposed methodology in terms of platform and user utility, respectively, when compared with fully distributed and user-centric trustworthy crowd-sensing. [less ▲]

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See detailCoverage optimization with connectivity preservation for UAV swarms applying chaotic dynamics
Rosalie, Martin UL; Brust, Matthias UL; Danoy, Grégoire UL et al

in IEEE International Conference on Autonomic Computing (ICAC), Columbus 17-21 July 2017 (2017, August 11)

Cooperative usage of multiple UAVs as a swarm can deliver high-quality surveillance performance. However, the communication capabilities within the UAV swarm must be maintained for local data propagation ... [more ▼]

Cooperative usage of multiple UAVs as a swarm can deliver high-quality surveillance performance. However, the communication capabilities within the UAV swarm must be maintained for local data propagation to swarm members in favor of achieving an efficient global behavior. In this paper, we address the problem of optimizing two adversary criteria for such a UAV swarm: (a) maximizing the area coverage, while (b) preserving network connectivity. Our approach, called CACOC², solves the problem with a novel chaotic ant colony optimization approach, which combines an Ant Colony Optimization approach (ACO) with a chaotic dynamical system. CACOC² employs swarming behavior to obtain UAV clustering that result in maximized area coverage and preserved network connectivity. We show by extensive simulations how the size of the UAV swarm influences the coverage and connectivity. A metrics comparison chart shows the correlation of coverage and connectivity metrics. [less ▲]

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See detailArea exploration with a swarm of UAVs combining deterministic Chaotic Ant Colony Mobility with position MPC
Rosalie, Martin UL; Dentler, Jan Eric UL; Danoy, Grégoire UL et al

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, July 27)

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already ... [more ▼]

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already proposed a new mobility model using Ant Colony Algorithms combined with chaotic dynamics (CACOC) to enhance the coverage of an area by a swarm of UAVs. In this paper we propose to consider this mobility model as waypoints for real UAVs. A control model of the UAVs is deployed to test the efficiency of the coverage of an area by the swarm. We have tested our approach in a realistic robotics simulator (V-Rep) which is connected with ROS. We compare the performance in terms of coverage using several metrics to ensure that this mobility model is efficient for real UAVs. [less ▲]

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See detailMeasuring data locality ratio in virtual MapReduce cluster using WorkflowSim
Wangsom, Peerasak; Lavangnananda, Kittichai; Bouvry, Pascal UL

in Proceedings of the 14th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2017 14th (2017, July)

The data locality is significant factor which has a direct impact on the performance of MapReduce framework. Several previous works have proposed alternative scheduling algorithms for improving the ... [more ▼]

The data locality is significant factor which has a direct impact on the performance of MapReduce framework. Several previous works have proposed alternative scheduling algorithms for improving the performance by increasing data locality. Nevertheless, their studies had focused the data locality on physical MapReduce cluster. As more and more deployment of MapReduce cluster have been on virtual environment, a more suitable evaluation of MapReduce cluster may be necessary. This study adopts a simulation based approach. Five scheduling algorithms were used for the simulation. WorkflowSim is extended by inclusion of three implemented modules to assess the new performance measure called `data locality ratio'. Comparison of their results reveals interesting findings. The proposed implementation can be used to assess `data locality ratio' and allows users prior to efficiently select and tune scheduler and system configurations suitable for an environment prior to its actual physical MapReduce deployment. [less ▲]

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See detailASIMUT project: Aid to SItuation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques
Bouvry, Pascal UL; Chaumette, Serge; Danoy, Grégoire UL et al

in DroNet'17 Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications (2017, June 23)

This document summarizes the activities and results of the ASIMUT project (Aid to SItuation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques) carried out by the consortium ... [more ▼]

This document summarizes the activities and results of the ASIMUT project (Aid to SItuation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques) carried out by the consortium composed of Thales, Fraunhofer IOSB, Fly-n-Sense, University of Bordeaux and University of Luxembourg. Funded by the European Defence Agency (EDA), the objectives of the ASIMUT project are to design, implement and validate algorithms that will allow the efficient usage of autonomous swarms of Unmanned Aerial Vehicles (UAVs) for surveillance missions. [less ▲]

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See detailA Scalable Parallel Cooperative Coevolutionary PSO Algorithm for Multi-objective Optimization
Atashpendar, Arash UL; Dorronsoro, Bernabé; Danoy, Grégoire UL et al

in Journal of Parallel & Distributed Computing (2017)

We present a parallel multi-objective cooperative coevolutionary variant of the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm. The algorithm, called CCSMPSO, is the first ... [more ▼]

We present a parallel multi-objective cooperative coevolutionary variant of the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm. The algorithm, called CCSMPSO, is the first multi-objective cooperative coevolutionary algorithm based on PSO in the literature. SMPSO adopts a strategy for limiting the velocity of the particles that prevents them from having erratic movements. This characteristic provides the algorithm with a high degree of reliability. In order to demonstrate the effectiveness of CCSMPSO, we compare our work with the original SMPSO and three different state-of-the-art multi-objective CC metaheuristics, namely CCNSGA-II, CCSPEA2 and CCMOCell, along with their original sequential counterparts. Our experiments indicate that our proposed solution, CCSMPSO, offers significant computational speedups, a higher convergence speed and better or comparable results in terms of solution quality, when evaluated against three other CC algorithms and four state-of-the-art optimizers (namely SMPSO, NSGA-II, SPEA2, and MOCell), respectively. We then provide a scalability analysis, which consists of two studies. First, we analyze how the algorithms scale when varying the problem size, i.e., the number of variables. Second, we analyze their scalability in terms of parallelization, i.e., the impact of using more computational cores on the quality of solutions and on the execution time of the algorithms. Three different criteria are used for making the comparisons, namely the quality of the resulting approximation sets, average computational time and the convergence speed to the Pareto front. [less ▲]

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See detailReal-Time Virtual Network Function (VNF) Migration toward Low Network Latency in Cloud Environments
Cho, Daewoong; Taheri, Javid; Zomaya, Albert Y. et al

in IEEE 10th International Conference on Cloud Computing (CLOUD), 2017 (2017, June)

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers ... [more ▼]

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers (CDCs). One of the main challenges for the NFV environment is how to minimize network latency in the rapidly changing network environments. Although many researchers have already studied in the field of Virtual Machine (VM) migration and Virtual Network Function (VNF) placement for efficient resource management in CDCs, VNF migration problem for low network latency among VNFs has not been studied yet to the best of our knowledge. To address this issue in this article, we i) formulate the VNF migration problem and ii) develop a novel VNF migration algorithm called VNF Real-time Migration (VNF-RM) for lower network latency in dynamically changing resource availability. As a result of experiments, the effectiveness of our algorithm is demonstrated by reducing network latency by up to 70.90% after latency-aware VNF migrations. [less ▲]

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See detailLoad-Aware Strategies for Cloud-Based VoIP Optimization with VM Startup Prediction
Cortes-Mendoza, Jorge M.; Tchernykh, Andrei; Feoktistov, Alexander et al

in IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017 (2017, June)

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and ... [more ▼]

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of twenty three on-line non-clairvoyant scheduling strategies with fixed threshold of utilization to request VMs, and twenty strategies with dynamic prediction of the load. We show that our load-aware with predictions strategies outperform the known ones providing suitable quality of service and lower cost. The robustness of these strategies is also analyzed varying VM startup time delays to deal with realistic VoIP cloud environments. [less ▲]

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See detailCost analysis of Smart Lighting Solutions for Smart Cities
Cacciatore, Giuseppe; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE International Conference on Communications (ICC), Paris, France, 2017 (2017, May)

Lighting is an essential community service, but current implementations are not energy efficient and impact on the energy budget of the municipalities for at least 40\%. In this paper, we propose ... [more ▼]

Lighting is an essential community service, but current implementations are not energy efficient and impact on the energy budget of the municipalities for at least 40\%. In this paper, we propose heuristics and devise a comparison methodology for new smart lighting solutions in next generation smart cities. The proposed smart lighting techniques make use of Internet of Things (IoT) augmented lamppost, which save energy by turning off or dimming the light according to the presence of citizens. Assessing costs and benefits in adopting the new smart lighting solutions is a pillar step for municipalities to foster real implementation. For evaluation purposes, we have developed a custom simulator which enables the deployment of lampposts in realistic urban environments. The citizens travel on foot along the streets and trigger activation of the lampposts according to the proposed heuristics. For the city of Luxembourg, the results highlight that replacing all existing lamps with LEDs and dimming light intensity according to the presence of users nearby the lampposts is convenient and provides an economical return already after the first year of deployment. [less ▲]

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See detailEnergy Efficient Data Collection in Opportunistic Mobile Crowdsensing Architectures for Smart Cities
Capponi, Andrea UL; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in 3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing (2017, May)

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile ... [more ▼]

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile Crowdsensing (MCS), citizens participate in the sensing process contributing data with their mobile devices such as smartphones, tablets and wearables. To be effective, MCS systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and energy-efficient framework for data collection in opportunistic MCS architectures. Opportunistic sensing systems require minimal intervention from the user side as sensing decisions are application- or device-driven. The proposed framework minimizes the cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. We evaluate performance of the framework with simulations, performed in a real urban environment and with a large number of participants. The simulation results verify cost-effectiveness of the framework and assess efficiency of the data generation process. [less ▲]

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