Papers by Novella Bartolini
arXiv (Cornell University), Sep 30, 2010
In this paper we address the problem of prolonging the lifetime of wireless sensor networks (WSNs... more In this paper we address the problem of prolonging the lifetime of wireless sensor networks (WSNs) deployed to monitor an area of interest. In this scenario, a helpful approach is to reduce coverage redundancy and therefore the energy expenditure due to coverage. We introduce the first algorithm which reduces coverage redundancy by means of Sensor Activation and sensing Radius Adaptation (SARA) in a general applicative scenario with two classes of devices: sensors that can adapt their sensing range (adjustable sensors) and sensors that cannot (fixed sensors). In particular, SARA activates only a subset of all the available sensors and reduces the sensing range of the adjustable sensors that have been activated. In doing so, SARA also takes possible heterogeneous coverage capabilities of sensors belonging to the same class into account. It specifically addresses device heterogeneity by modeling the coverage problem in the Laguerre geometry through Voronoi-Laguerre diagrams. SARA executes quickly and is guaranteed to terminate. It provides a configuration of the active set of sensors that meets lifetime and coverage requirements of demanding WSN applications, not met by current solutions. By means of extensive simulations we show that SARA achieves a network lifetime that is significantly superior to that obtained by previous algorithms in all the considered scenarios.
This paper addresses the problem of efficiently restoring sufficient resources in a communication... more This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large scale disruption. We give a formulation of the problem as an MILP and show that it is NP-hard. We propose a polynomial time heuristic, called Iterative Split and Prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared to several greedy approaches ISP performs better in terms of number of repaired components, and does not result in any demand loss. It performs very close to the optimal when the demand is low with respect to the supply network capacities, thanks to the ability of the algorithm to maximize sharing of repaired resources.
Towards realistic market simulations
This paper addresses the call admission control problem for the multimedia services that characte... more This paper addresses the call admission control problem for the multimedia services that characterize the third generation of wireless networks. In the proposed model each cell has to serve a variety of classes of requests that differ in their traffic parameters, bandwidth requirements and in the priorities while ensuring proper quality of service levels to all of them. A Semi Markov Process is used to model multi-class multimedia systems with heterogeneous traffic behavior, allowing for call transitions among classes. It is shown that the derived optimal policy establishes state-related threshold values for the admission policy of handoff and new calls in the different classes, while minimizing the blocking probabilities of all the classes and prioritizing the handoff requests. It is proven that in restrictive cases the optimal policy has the shape of a Multi-Threshold Priority policy, while in general situations the optimal policy has a more complex shape.
Message from the Conference Chairs
Lecture Notes in Computer Science, 2019
Wireless sensor networks (WSNs) are widely used to assist monitoring of an area of interest whene... more Wireless sensor networks (WSNs) are widely used to assist monitoring of an area of interest whenever manual monitoring by skilled personnel is not convenient if not prohibitive. In this paper, we propose a step ahead with respect to the current status of art, with the design and implementation of a novel networked architecture which integrates a set of static ground nodes, an Unmanned Ground Vehicle (UGV), and an Unmanned Aerial Vehicle (UAV) in a unique monitoring system. All these devices are equipped with sensors, a microcontroller and a wireless communication module such that they are capable of covering an AoI in the terrestrial and aerial dimension. In the proposed architecture, the mobile robot can inspect areas which have no fixed ground sensors, whereas sensors installed on the UAV cover the ground areas from above, ensuring wider coverage. Once data is collected by the ground sensors, it is sent via the UAV to a remote processing center, which elaborates the gathered data for decision making.
IEEE ACM Transactions on Networking, Apr 1, 2023
Boolean Network Tomography (BNT) aims at identifying failures of internal network components by m... more Boolean Network Tomography (BNT) aims at identifying failures of internal network components by means of endto-end monitoring paths. However, when the number of failures is not known a priori, failure identification may require a huge number of monitoring paths. We address this problem by designing a Bayesian approach that progressively selects the next path to probe on the basis of its expected information utility, conditioned on prior observations. As the complexity of the computation of posterior probabilities of node failures is exponential in the number of failed paths, we propose a polynomial-time greedy strategy which approximates these values. To consider aging of information in dynamic failure scenarios where node states can change during a monitoring period, we propose a monitoring technique based on a sliding observation window of adaptive length. By means of numerical experiments conducted on real network topologies we demonstrate the practical applicability of our approach, and the superiority of our algorithms with respect to state of the art solutions based on classic BNT as well as sequential group testing.
Distributed Deployment in UAV-Assisted Networks for a Long-Lasting Communication Coverage
IEEE Systems Journal, Sep 1, 2022
Quality of service in heterogeneous networks: 6th International ICST conference on heterogeneous networking for quality, reliability, security and robusteness, QSHINE 2009 and 3rd International workshop on advanced architectures and algorithms for internet delivery and applications, AAA-IDEA 2009
Stop & Route: Periodic Data Offloading in UAV Networks
2023 18th Wireless On-Demand Network Systems and Services Conference (WONS)
arXiv (Cornell University), Mar 31, 2021
We aim at assessing the states of the nodes in a network by means of end-to-end monitoring paths.... more We aim at assessing the states of the nodes in a network by means of end-to-end monitoring paths. The contribution of this paper is twofold. First, we consider a static failure scenario. In this context, we aim at minimizing the number of probes to obtain failure identification. To face this problem we propose a progressive approach to failure localization based on stochastic optimization, whose solution is the optimal sequence of monitoring paths to probe. We address the complexity of the problem by proposing a greedy strategy in two variants: one considers exact calculation of posterior probabilities of node failures, given the observation, whereas the other approximates these values by means of a novel failure centrality metric. Secondly, we adapt these two strategies to a dynamic failure scenario where nodes states can change throughout a monitoring period. By means of numerical experiments conducted on real network topologies, we demonstrate the practical applicability of our approach. Our performance evaluation evidences the superiority of our algorithms with respect to state of the art solutions based on classic Boolean Network Tomography as well as approaches based on sequential group testing.
IEEE Networking Letters
This letter discusses the parallelism between the concept of network identifiability introduced b... more This letter discusses the parallelism between the concept of network identifiability introduced by Boolean Network Tomography (BNT), and the theory of separating systems, highlighting applications of interest to research in networking. This letter evidences how recent results of BNT have direct implications to the formulation of new bounds to the size of separating systems over finite sets. Grounding on these theoretical results, we provide an efficient algorithm for the design of separating systems that meet the bound tightly. We extend the proposed results, bounds and algorithm, to networking applications, including network failure assessment, robust network design and compressed sensing. Index Terms-Computer network reliability, information theory, compressed sensing, combinatorial testing. I. INTRODUCTION B OOLEAN Network Tomography (BNT) is a powerful technique for inferring the binary state (failed/working) of internal elements of a network (nodes/links) by means of endto-end measurement paths. Network Tomography (NT) has gained wide attention in the networking research community in the past years. Its applications span from failure localization, [1], [2], [3], delay and bandwidth inference [4], [5], topology discovery [6], as it provides techniques that overcome monitoring issues due to network heterogeneity and multi-proprietary nature. These techniques are very versatile and prove to be useful in many application contexts, including urban traffic monitoring [7]. Although born before the advent of the latest centralized network frameworks (e.g., softwaredefined networks and network function virtualization), NT techniques can provide efficient monitoring also in these contexts with negligible traffic overhead [8], [9]. However, BNT also brings about many challenges, mostly related to the computational intractability of data interpretation. Identifiability is a core concept in BNT [3]. Roughly, we say that a network node v is identifiable with respect to a set of paths traversing the network, P, if, when it fails, it is possible to identify its state without ambiguity by observing the binary outcome (failed or working) of the paths in P. Our works in [10], [11] provide fundamental bounds for network node identifiability. We notice a strong connection between the concepts of BNT
2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS), 2017
Vulnerability due to inter-connectivity of multiple networks has been observed in many complex ne... more Vulnerability due to inter-connectivity of multiple networks has been observed in many complex networks. Previous works mainly focused on robust network design and on recovery strategies after sporadic or massive failures in the case of complete knowledge of failure location. We focus on cascading failures involving the power grid and its communication network with consequent imprecision in damage assessment. We tackle the problem of mitigating the ongoing cascading failure and providing a recovery strategy. We propose a failure mitigation strategy in two steps: 1) Once a cascading failure is detected, we limit further propagation by redistributing the generator and load's power. 2) We formulate a recovery plan to maximize the total amount of power delivered to the demand loads during the recovery intervention. Our approach to cope with insufficient knowledge of damage locations is based on the use of a new algorithm to determine consistent failure sets (CFS). We show that, given knowledge of the system state before the disruption, the CFS algorithm can find all consistent sets of unknown failures in polynomial time provided that, each connected component of the disrupted graph has at least one line whose failure status is known to the controller.
Abstract. In this paper, a non-preemptive prioritization scheme for access control in cellular ne... more Abstract. In this paper, a non-preemptive prioritization scheme for access control in cellular networks is analyzed. Two kinds of users are assumed to compete for the access to the limited number of frequency channels available in each cell: the high priority users represent handoff requests, while the low priority users correspond to initial access requests originated within the same cell. Queueing of handoff requests is also considered. The research for the best access policy is carried out by means of a Markov decision model which allows us to study a very wide class of policies which includes some well known pure stationary policies, as well as randomized ones. The cutoff priority policy, consisting in reserving a certain number of channels to the high priority stream of requests, is proved to be optimal within this class while using an objective function in the form of a linear combination of some quality of service parameters, when no queueing device is considered. Numerical r...
SIDE : Self Driving Drones Embrace Uncertainty
IEEE Transactions on Mobile Computing, 2021
Poster: a minimally disruptive network reconfiguration approach in SDN
2019 IFIP Networking Conference (IFIP Networking), 2019
When routing flows in a software defined network (SDN), service disruption and inconsistencies ca... more When routing flows in a software defined network (SDN), service disruption and inconsistencies can occur during the updates of routing tables leading to degraded QoS or interruption of existing services. We study the problem of rerouting existing flows in an SDN to enable the admission of new flows while minimizing the disruption of existing flows, under link capacity and Quality of Service (QoS) constraints. We formulate the problem as an integer linear programming problem and propose two randomized rounding algorithms with bounded congestion and demand loss to solve this problem.
Optimal Deployment in Crowdsensing for Plant Disease Diagnosis in Developing Countries
IEEE Internet of Things Journal, 2020
In most of the developing countries, the economy is largely based on agriculture. The poor availa... more In most of the developing countries, the economy is largely based on agriculture. The poor availability of skilled personnel and of appropriate supporting infrastructure, make crop fields vulnerable to the outbreak of plant diseases, possibly due to spreading viruses and fungi, or to adverse environmental conditions, such as drought. The mobile application PlantVillage Nuru provides an invaluable tool for early detection of plant diseases and sustainable food production. A mobile device endowed with Nuru is a powerful mobile sensor: it analyzes plant images and uses an AI engine to recognize health issues. In this article, we propose a crowdsensing framework, where Nuru is adopted at large scale in the farmer population. We tackle the device deployment problem, where device mobility is only partially controllable, mostly in an indirect manner, through incentives. We propose two problem formulations, and related algorithms, to minimize the number of required smartphones while providing sufficient geographical coverage. We study the proposed models in simulated as well as real scenarios, showing that they outperform the current solutions in terms of monitoring accuracy and completeness, with lower cost. Then, we describe the testbed implementation, confirming the applicability of the proposed crowdsensing framework in a real scenario in Kenya.
arXiv (Cornell University), Jul 5, 2023
The recent advancements in Deep Learning (DL) research have notably influenced the finance sector... more The recent advancements in Deep Learning (DL) research have notably influenced the finance sector. We examine the robustness and generalizability of fifteen stateof-the-art DL models focusing on Stock Price Trend Prediction (SPTP) based on Limit Order Book (LOB) data. To carry out this study, we developed LOBCAST, an open-source framework that incorporates data preprocessing, DL model training, evaluation and profit analysis. Our extensive experiments reveal that all models exhibit a significant performance drop when exposed to new data, thereby raising questions about their real-world market applicability. Our work serves as a benchmark, illuminating the potential and the limitations of current approaches and providing insight for innovative solutions. Preprint. Under review.
IEEE Access, 2021
In Boolean Network Tomography (BNT), node identifiability is a crucial property that reflects the... more In Boolean Network Tomography (BNT), node identifiability is a crucial property that reflects the possibility of unambiguously classifying the state of the nodes of a network as 'working' or 'failed' through end-to-end measurement paths. Designing a monitoring scheme satisfying network identifiability is an NP problem. In this article, we provide theoretical bounds on the minimum number of necessary measurement paths to guarantee identifiability of a given number of nodes. The bounds take into consideration two different classes of routing schemes (arbitrary and consistent routing) as well as quality of service (QoS) requirements. We formally prove the tightness of such bounds for the arbitrary routing scheme, and provide an algorithmic approach to the design of network topologies and path deployment that meet the discussed limits. Due to the computational complexity of the optimal solution, We evaluate the tightness of our lower bounds by comparing their values with an upper bound, obtained by a state-of-the-art heuristic for node identifiability. For our experiments we run extensive simulations on both synthetic and real network topologies, for which we show that the two bounds are close to each other, despite the fact that the provided lower bounds are topology agnostic. INDEX TERMS Boolean network tomography, identifiability, network topology, optimal bounds.
Deployment of UAV-BSs for on-demand full communication coverage
Ad Hoc Networks
Uploads
Papers by Novella Bartolini