54 research outputs found

    Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

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    Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption

    An integrated security Protocol communication scheme for Internet of Things using the Locator/ID Separation Protocol Network

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    Internet of Things communication is mainly based on a machine-to-machine pattern, where devices are globally addressed and identified. However, as the number of connected devices increase, the burdens on the network infrastructure increase as well. The major challenges are the size of the routing tables and the efficiency of the current routing protocols in the Internet backbone. To address these problems, an Internet Engineering Task Force (IETF) working group, along with the research group at Cisco, are still working on the Locator/ID Separation Protocol as a routing architecture that can provide new semantics for the IP addressing, to simplify routing operations and improve scalability in the future of the Internet such as the Internet of Things. Nonetheless, The Locator/ID Separation Protocol is still at an early stage of implementation and the security Protocol e.g. Internet Protocol Security (IPSec), in particular, is still in its infancy. Based on this, three scenarios were considered: Firstly, in the initial stage, each Locator/ID Separation Protocol-capable router needs to register with a Map-Server. This is known as the Registration Stage. Nevertheless, this stage is vulnerable to masquerading and content poisoning attacks. Secondly, the addresses resolving stage, in the Locator/ID Separation Protocol the Map Server (MS) accepts Map-Request from Ingress Tunnel Routers and Egress Tunnel Routers. These routers in trun look up the database and return the requested mapping to the endpoint user. However, this stage lacks data confidentiality and mutual authentication. Furthermore, the Locator/ID Separation Protocol limits the efficiency of the security protocol which works against redirecting the data or acting as fake routers. Thirdly, As a result of the vast increase in the different Internet of Things devices, the interconnected links between these devices increase vastly as well. Thus, the communication between the devices can be easily exposed to disclosures by attackers such as Man in the Middle Attacks (MitM) and Denial of Service Attack (DoS). This research provided a comprehensive study for Communication and Mobility in the Internet of Things as well as the taxonomy of different security protocols. It went on to investigate the security threats and vulnerabilities of Locator/ID Separation Protocol using X.805 framework standard. Then three Security protocols were provided to secure the exchanged transitions of communication in Locator/ID Separation Protocol. The first security protocol had been implemented to secure the Registration stage of Locator/ID separation using ID/Based cryptography method. The second security protocol was implemented to address the Resolving stage in the Locator/ID Separation Protocol between the Ingress Tunnel Router and Egress Tunnel Router using Challenge-Response authentication and Key Agreement technique. Where, the third security protocol had been proposed, analysed and evaluated for the Internet of Things communication devices. This protocol was based on the authentication and the group key agreement via using the El-Gamal concept. The developed protocols set an interface between each level of the phase to achieve security refinement architecture to Internet of Things based on Locator/ID Separation Protocol. These protocols were verified using Automated Validation Internet Security Protocol and Applications (AVISPA) which is a push button tool for the automated validation of security protocols and achieved results demonstrating that they do not have any security flaws. Finally, a performance analysis of security refinement protocol analysis and an evaluation were conducted using Contiki and Cooja simulation tool. The results of the performance analysis showed that the security refinement was highly scalable and the memory was quite efficient as it needed only 72 bytes of memory to store the keys in the Wireless Sensor Network (WSN) device

    Developing a dynamic digital twin at a building level: Using Cambridge campus as case study

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    A Digital Twin (DT) refers to a digital replica of physical assets, processes and systems. DTs integrate artificial intelligence, machine learning and data analytics to create dynamic digital models that are able to learn and update the status of the physical counterpart from multiple sources. A DT, if equipped with appropriate algorithms will represent and predict future condition and performance of their physical counterparts. Current developments related to DTs are still at an early stage with respect to buildings and other infrastructure assets. Most of these developments focus on the architectural and engineering/construction point of view. Less attention has been paid to the operation & maintenance (O&M) phase, where the value potential is immense. A systematic and clear architecture verified with practical use cases for constructing a DT is the foremost step for effective operation and maintenance of assets. This paper presents a system architecture for developing dynamic DTs in building levels for integrating heterogeneous data sources, support intelligent data query, and provide smarter decision-making processes. This will further bridge the gaps between human relationships with buildings/regions via a more intelligent, visual and sustainable channels. This architecture is brought to life through the development of a dynamic DT demonstrator of the West Cambridge site of the University of Cambridge. Specifically, this demonstrator integrates an as-is multi-layered IFC Building Information Model (BIM), building management system data, space management data, real-time Internet of Things (IoT)-based sensor data, asset registry data, and an asset tagging platform. The demonstrator also includes two applications: (1) improving asset maintenance and asset tracking using Augmented Reality (AR); and (2) equipment failure prediction. The long-term goals of this demonstrator are also discussed in this paper

    Over the air computing for satellite networks in 6G

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    6G and beyond networks will merge communication and computation capabilities in order to adapt to changes. As they will consist of many sensors gathering information from its environment, new schemes for managing these large amounts of data are needed. For this purpose, we review Over the Air (OTA) computing in the context of estimation and detection. For distributed scenarios, such as a Wireless Sensor Network, it has been proven that a separation theorem does not necessarily hold, whereas analog schemes may outperform digital designs. We outline existing gaps in the literature, evincing that current state of the art requires a theoretical framework based on analog and hybrid digital-analog schemes that will boost the evolution of OTA computing. Furthermore, we motivate the development of 3D networks based on OTA schemes, where satellites function as sensors. We discuss its integration within the satellite segment, delineate current challenges and present a variety of use cases that benefit from OTA computing in 3D networks.This work has received funding by the Spanish ministry of science and innovation under project IRENE (PID2020-115323RB-C31) funded by MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (author's final draft

    Over the Air Computing for Satellite Networks in 6G

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    6G and beyond networks will merge communication and computation capabilities in order to adapt to changes. As they will consist of many sensors gathering information from its environment, new schemes for managing these large amounts of data are needed. For this purpose, we review Over the Air (OTA) computing in the context of estimation and detection. For distributed scenarios, such as a Wireless Sensor Network, it has been proven that a separation theorem does not necessarily hold, whereas analog schemes may outperform digital designs. We outline existing gaps in the literature, evincing that current state of the art requires a theoretical framework based on analog and hybrid digital-analog schemes that will boost the evolution of OTA computing. Furthermore, we motivate the development of 3D networks based on OTA schemes, where satellites function as sensors. We discuss its integration within the satellite segment, delineate current challenges and present a variety of use cases that benefit from OTA computing in 3D networks.Comment: Paper accepted in 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON

    Data fusion and type-2 fuzzy inference in contextual data stream monitoring

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    Data stream monitoring provides the basis for building intelligent context-aware applications over contextual data streams. A number of wireless sensors could be spread in a specific area and monitor contextual parameters for identifying phenomena e.g., fire or flood. A back-end system receives measurements and derives decisions for possible abnormalities related to negative effects. We propose a mechanism, which based on multivariate sensors data streams, provides real-time identification of phenomena. The proposed framework performs contextual information fusion over consensus theory for the efficient measurements aggregation while time-series prediction is adopted to result future insights on the aggregated values. The unanimous fused and predicted pieces of context are fed into a Type-2 fuzzy inference system to derive highly accurate identification of events. The Type-2 inference process offers reasoning capabilities under the uncertainty of the phenomena identification. We provide comprehensive experimental evaluation over real contextual data and report on the advantages and disadvantages of the proposed mechanism. Our mechanism is further compared with Type-1 fuzzy inference and other mechanisms to demonstrate its false alarms minimization capability
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