It has been established for a long time and has evolved correspondingly that actuators and sensorsystems may be connected to the internet for the purpose of continuously monitoring and controlling biological phenomen...
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The proceedings contain 77 papers. The topics discussed include: distributed computation in the physical world;exploring the Energy-Latency Trade-Off for broadcasts in Energy-Saving sensor networks;the impossibility o...
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ISBN:
(纸本)0769523285
The proceedings contain 77 papers. The topics discussed include: distributed computation in the physical world;exploring the Energy-Latency Trade-Off for broadcasts in Energy-Saving sensor networks;the impossibility of boosting distributed service resilience;explicit combinatorial structures for cooperative distributed algorithms;efficient wait-free implementation of Multiword LL/SC variables;adaptive collaboration in peer-to-peer systems;on cooperative content distribution and the price of barter;non-cooperation in competitive P2P networks;systems support for pervasive query processing;supporting complex multi-dimensional Queries in P2P systems;optimal asynchronous garbage collection for RDT checkpointing protocols;application-driven coordination-free distributed checkpointing;flexible consistency for wide area peer replication;and adaptive counting networks.
The aim of this paper is to provide an advanced WSN solution for power-sustainable energy management and efficient communication, integrating the latest developments from the SEMS. This work will focus on the research...
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ISBN:
(数字)9798331542726
ISBN:
(纸本)9798331542733
The aim of this paper is to provide an advanced WSN solution for power-sustainable energy management and efficient communication, integrating the latest developments from the SEMS. This work will focus on the research effort directed at improving M2M communication and integrating WSNs with wireless mobile networks, as well as addressing PAPR, energy consumption, and scalability. It now applies to real-time monitoring of power usage, room temperature, and lighting by integrating renewable resources of energy with sophisticated algorithms and sensor networks. Key results include a 16.6% saving in energy consumptions, 78% in system delay improvements, and the implementation of solar energy systems that have realized significant cost savings while assuring environmental sustainability. This work proves the ability of the approach through wide simulations and real-world deployments for scalable and eco-friendly energy management solutions. Besides, this work is closely related to worldwide goals for reduction of carbon footprints and efficient resource utilization.
The estimation of indoor occupancy rates has become increasingly important, especially for accident prevention at events and providing critical rescue information during disasters. However, conventional systems requir...
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ISBN:
(数字)9798331508180
ISBN:
(纸本)9798331508197
The estimation of indoor occupancy rates has become increasingly important, especially for accident prevention at events and providing critical rescue information during disasters. However, conventional systems require significant effort and cost for installation, such as the need for dedicated servers and internet connectivity, making them difficult to deploy conveniently. This study proposes the design of an indoor occupancy estimation system based on the Wireless Brain-Inspired computing (WiBIC) platform. By equipping each IoT device with neuron functionality, environmental data is compressed into spike signals directly at the source. These signals are processed using intelligent information processing techniques based on the principles of brain-inspired computing, enabling the estimation of indoor occupancy. The WiBIC platform's serverless architecture and low-power characteristics allow for easy and efficient deployment of the system in various indoor environments. The proposed system further emphasizes energy efficiency by incorporating FPGA implementation and the Asynchronous Pulse Code Multiple Access (APCMA) protocol. Experimental evaluations were conducted using data collected from illuminance sensors, human detection sensor, and current sensors to estimate occupancy rates. The results show that the system achieves practical accuracy, validating its effectiveness. The accuracy achieved is sufficient for practical applications, demonstrating the effectiveness of the proposed system.
Multi-agent collaboration enhances situational awareness in intelligence, surveillance, and reconnaissance (ISR) missions. Ad hoc networks of unmanned aerial vehicles (UAVs) allow for real-time data sharing, but they ...
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ISBN:
(纸本)9798400714986
Multi-agent collaboration enhances situational awareness in intelligence, surveillance, and reconnaissance (ISR) missions. Ad hoc networks of unmanned aerial vehicles (UAVs) allow for real-time data sharing, but they face security challenges due to their decentralized nature, making them vulnerable to cyber-physical attacks. This paper introduces a trust-based framework for assured sensor fusion in distributed multi-agent networks, utilizing a hidden Markov model (HMM)-based approach to estimate the trustworthiness of agents and their provided information in a decentralized fashion. Trust-informed data fusion prioritizes fusing data from reliable sources, enhancing resilience and accuracy in contested environments. To evaluate the assured sensor fusion under attacks on system/mission sensing, we present a novel multi-agent aerial dataset built from the Unreal Engine simulator. We demonstrate through case studies improved ISR performance and an ability to detect malicious actors in adversarial settings.
The proceedings contain 165 papers. The topics discussed include: overlapped mobile charging for sensor networks;SAFEPAY on ethereum: a framework for detecting unfair payments in smart contracts;continuous, real-time ...
ISBN:
(纸本)9781728170022
The proceedings contain 165 papers. The topics discussed include: overlapped mobile charging for sensor networks;SAFEPAY on ethereum: a framework for detecting unfair payments in smart contracts;continuous, real-time object detection on mobile devices without offloading;distributionally robust edge learning with dirichlet process prior;CAPMAN: cooling and active power management in *** battery supported devices;PerDNN: offloading deep neural network computations to pervasive edge servers;more realistic website fingerprinting using deep learning;exact consensus under global asymmetric byzantine links;communication-efficient decentralized learning with sparsification and adaptive peer selection;and energy efficient in-memory integer multiplication based on racetrack memory.
The feedback gain in the traditional economic dispatch consensus algorithm is a fixed value, which leads to a slow convergence speed. To solve the problem, a novel distributed economic dispatch method for smart grid w...
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This paper addresses the distributed load frequency control (LFC) problem for multi-area interconnected power systems (MAIPSs) with thermal and wind power generations, considering both inter-area and intra-area transm...
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The proceedings contain 30 papers. The topics discussed include: resource management problems in cloud computing;continuously improving the resource utilization of iterative parallel dataflows;throughput: a key perfor...
ISBN:
(纸本)9781509014828
The proceedings contain 30 papers. The topics discussed include: resource management problems in cloud computing;continuously improving the resource utilization of iterative parallel dataflows;throughput: a key performance measure of content-defined chunking algorithms;using text analytics to discover online newspapers' role in disseminating government policy - a Malaysian PDPA context;efficient embedding of dynamic languages in big-data analytics;elastic scaling in the cloud: a multi-tenant perspective;abstraction layer based virtual data center architecture for network function chaining;energy-aware HTTP data transfers;machine learning-based elastic cloud resource provisioning in the solvency II framework;and a misbehavior node detection algorithm for 6LoWPAN wireless sensor networks.
This is a practitioner paper focused on a new mission engineering approach for adapting to varying processing requirements for platforms, e.g., Unmanned Autonomous systems (UAS), aircraft, and satellites, that have se...
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ISBN:
(数字)9798331508180
ISBN:
(纸本)9798331508197
This is a practitioner paper focused on a new mission engineering approach for adapting to varying processing requirements for platforms, e.g., Unmanned Autonomous systems (UAS), aircraft, and satellites, that have severe Size, Weight and Power and Cost (SWaP-C) limitations. When used for some missions, such as those for the military, these platforms are considered to be edge-based entities, where the term edge refers to the far boundaries of the battle space. The challenge for mission engineering in this environment is to specify and design a system that fully supports mission requirements, where high SWaP-C is not an option. One way to achieve this is through reduction of processing circuitry. Traditional means to do so apply logic gate reduction using combinatorial logic design based on algebraic mathematics and graph theoretical approaches. An alternative to this is to apply distributed quantum computing gate-model principles. Presently, these approaches have been implemented independently, thereby fail to take advantage of overlapping principles that could provide greater reduction in logic and corresponding SWaP-C at the edge. What is needed is a new break-through approach, derived through mission engineering, that combines these technologies to provide high Gate Reduction at the distributed Edge (GRaDE), and that allows adaptability to constantly changing processing requirements during a mission. This paper describes the novel GRaDE approach, along with its process, algorithms, and description of reduction to practice for solving the above problem.
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