1,721,148 research outputs found
Secure aggregation in hybrid mesh/sensor networks
No full textSeveral researchers are proposing information systems-based wireless sensor networks (WSNs) that provide an extensible and effective means to monitor large and diverse geographical areas. Nodes in a WSN are characterized by very limited computing capabilities and energy consumption is a major concern, which implies that communications should be minimized, thus unorthodox solutions are required for many situations. The definition of secure and privacy aware solutions, ensuring at the same time limited power consumption of transmitted data is then a great challenge. In this paper we present an hybrid mesh/sensor network, which allows to deliver a transparent multi-hop wireless backhaul able to handle in a secure way different kinds of data (temperature, humidity, etc.), coming from different kinds of wireless sensor networks. The main idea is based on a sharing of tasks between wireless mesh networks and wireless sensor networks. Our architecture is particularly suitable to realize an application agnostic mesh backhaul able to concurrently support multiple WSNs, while ensuring both end-to-end encryption and hop-by-hop authentication. Hence, in order to evaluate the performance of the proposed architecture an ad-hoc prototype is realized
Roadrunner: O-RAN-based Cell Selection in Beyond 5G Networks
No full textO-RAN is currently emerging as the way to build a virtualized 5G and beyond Radio Access Network (RAN) that is based on open interfaces and off-the-shelf hardware. O-RAN consolidates the intelligence of several gNodeBs at the Near-realtime RAN Intelligent Controller (RIC) making it more programmable and aware of the mobile users’ surroundings. In this paper we present Roadrunner, an O-RAN-based solution designed to improve cell selection in 5G and beyond networks. Our work has been motivated by the fact that the legacy cell selection procedure in both 4G and 5G networks tends to prefer radio quality and seamless connectivity to high data rates. The reason for this can be traced back to the older releases of the mobile network architecture that were optimized for the circuit-switched communication paradigm and for sparse network deployments. However, with an O-RAN-based approach we can leverage the global network view built and maintained by the Near-realtime RIC to jointly optimize mobility management for channel quality and bitrate. We have designed Roadrunner following the O-RAN Alliance design principles and without requiring any change to the existing 3GPP signaling. No changes to the mobile devices are required either. Performance measurements carried out on a small scale testbed show how Roadrunner can almost double the median throughput in some specific traffic scenarios while also achieving better network fairness
A Network Graph Approach for Network Energy Saving in Small Cell Networks
No full textSmall cell networks are key components in 5G networks to boost the network capacity, improve spectrum and energy efficiency, and enable flexible and new services. Due to the flexible spectrum access among and flexible deployment of small cells, the inter- cell coordination becomes critical for the performance of the network. In this paper, based on the key concept in software defined networking (SDN) for Internet, we first introduce the network graph approach as a tool for the control and coordination among small cells. The network graph is constructed from the abstracted network state information extracted from underlying base stations. It shields the logical centralized control unit from implementation details of the underlying physical layer and thus reduces the control overhead in a centralized solution. We use the network graph for network energy saving in small cell networks, in which network graphs are used to decide the optimal set of small cells in the network. For cells outside this set we can switch them off for energy saving. We propose three types of network graphs with different network state details. Based on these graphs, we formulate the energy saving problem as an integer linear programming (ILP) problem, and propose the practical algorithms to solve the problem. The performance of the algorithms are studied by simulation. It shows the potential of the proposed network graph approach for the inter-cell resource coordination in small cell networks
Interference Management in Software-Defined Mobile Networks
No full textSoftware-Defined Networking promises to deliver more flexible and manageable networks by providing a clear decoupling between control plane and data plane and by implementing the latter in a logically centralized controller. However, if such principles are to be applied also to wireless networks, new primitives and abstractions capable of providing programmers with a global view of the network capturing channel quality and interference must be devised. Moreover, the dynamic radio environment necessitates fast adaptation of physical parameters such as power, modulation and coding schemes. So the wireless SDN abstractions should allow for such adaptations to happen closer to the air interface. In this paper, we present high level abstractions for channel quality, interference and network reconfiguration; the latter permits operations differing in timescales to be carried out at different controller entities. The proposed concepts have been implemented and evaluated over a WiFi-based WLAN. Empirical measurements show that the proposed platform can be used to implement typical WiFi network management tasks such as channel assignment and interference monitoring
Centralized and Federated Learning for Predictive VNF Autoscaling in Multi-Domain 5G Networks and beyond
Full text linkNetwork Function Virtualization (NFV) and Multi-access Edge Computing (MEC) are two technologies expected to play a vital role in 5G and beyond networks. However, adequate mechanisms are required to meet the dynamically changing network service demands to utilize the network resources optimally and also to satisfy the demanding QoS requirements. Particularly in multi-domain scenarios, the additional challenge of isolation and data privacy among domains needs to be tackled. To this end, centralized and distributed Artificial Intelligence (AI)-driven resource orchestration techniques (e.g., virtual network function (VNF) autoscaling) are foreseen as the main enabler. In this work, we propose deep learning models, both centralized and federated approaches, that can perform horizontal and vertical autoscaling in multi-domain networks. The problem of autoscaling is modelled as a time series forecasting problem that predicts the future number of VNF instances based on the expected traffic demand. We evaluate the performance of various deep learning models trained over a commercial network operator dataset and investigate the pros and cons of federated learning over centralized learning approaches. Furthermore, we introduce the AI-driven Kubernetes orchestration prototype that we implemented by leveraging our MEC platform and assess the performance of the proposed deep learning models in a practical setup
Leakage Detection in Waterpipes Networks using Acoustic Sensors and Identifying Codes
No full textIn future smart cities a grand challenge will be to sensorize large urban infrastructures at a feasible cost. In this paper we tackle the case of efficient leakage detection in water distribution systems. Deploying leakage detectors can cut operational costs for water utility providers. But, the cost for deploying them with sufficient granularity poses an high entrance barrier due to the scale of such infrastructures. We propose an algorithmic framework to efficiently deploy sensors in order to perform leakage/fault localization over large scale lattice-shaped networks. The novelty of our solution, combining covering sets and identifying codes is that it initially covers the network with low resolution, and thus fewer sensors. The set of sensors can then be extended in a way to progressively improve the resolution by which leakages are located. The proposed solution is validated through extensive numerical experiments
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