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EdgeCEP: Fully-distributed Complex Event Processing on IoT Edges 13

EdgeCEP: Fully-distributed Complex Event Processing on IoT E...

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13th ieee international conference on distributed computing in sensor systems (dcoss)

作者： Choochotkaew, Sunyanan Yamaguchi, Hirozumi Higashino, Teruo Shibuya, Megumi Hasegawa, Teruyuki Osaka Univ Graduat Sch Informat Sci & Technol Osaka Japan KDDI Res Inc Fujimino Saitama Japan

ISBN: (纸本)9781538639917

In this paper, we propose a general complex event processing (CEP) engine aiming for accomplishing at smart IoT edge devices in a fully distributed manner. We introduce a pseudo-source mechanism to cover a wide range of processing and obsolete prerequisite of source-specification at the same time, along with a brand-new event specification language defined to support relation-based processing. Against cloud-based approaches, our behind-edge approach can prevent data overflow and privacy issues, and fully distributed processing can draw the power of the edge devices. To achieve that in a resource limited edge environment, we formulate an optimization problem of processing task assignment and stream delivery, and propose a fully-autonomous workload distribution mechanism. A large-scale simulation with a realistic smart-building scenario shows that our proposed method achieves about 6.6 times smaller flow volume and 2 times lower loss rate compared to centralization and is relatively superior to a hop-based distribution approach. Notably, a prototype engine is successfully deployed over an ad hoc wireless sensor and actuator network through Intel Edison modules in the real environment.

关键词： Engines Task analysis Wireless sensor networks Data models Cloud computing distributed databases Wireless communication

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Bipartite Grid Partitioning of a Random Geometric Graph 13

Bipartite Grid Partitioning of a Random Geometric Graph

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13th ieee international conference on distributed computing in sensor systems (dcoss)

作者： Chen, Zizhen Matula, David W. Southern Methodist Univ Dept Comp Sci & Engn Dallas TX 75275 USA

ISBN: (纸本)9781538639917

We investigate the problem of efficient computation of a partition of a Random Geometric Graph (RGG) into a limited number of densely packed bipartite grid sub graphs. The study focuses on the collection of subgraphs each individually having similar size and structure and the union employing most (e.g. over 85%) of the vertices. The residual vertices we seek to minimize are attributed to the inherent variations in densities of the randomly placed vertices and to any shortcomings of our greedy algorithms. RGG's have been extensively employed in recent times to model the deployment of numerous instances of Wireless sensor Networks (WSN's) Pl. The properties investigated in our selected bipartite grid backbones are those deemed most relevant for applications to the foundations of this widely growing field. distributed algorithms are primarily used to determine backbones. Our results review what backbone grid partitions exist in the data. This provides a metric to measure the effectiveness of any distributed algorithm against an existing optimal result. The visual display of selected backbone grids suggests local algorithm design strategies. Furthermore, these partitions must be efficiently computable for highly scalable computation, e.g. WSN's with 100's of thousands of vertices and millions of edges in the resulting RGG. We consider distributions over a segment of the plane and over the surface of the sphere to model sensor distributions both in limited planar regions, all around the globe or on distant planets.

关键词： Random Geometric Graph Wireless sensor Network Bipartite Subgraph Grid Partitioning Linear Time Algorithm

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Signal Selection in a Complex Environmental distributed Sensing Problem 13

Signal Selection in a Complex Environmental Distributed Sens...

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13th ieee international conference on distributed computing in sensor systems (dcoss)

作者： Makrai, Gabor Bate, Iain Univ York Dept Comp Sci Real Time Syst Grp York N Yorkshire England

ISBN: (纸本)9781538639917

Supporting sustainable development for the urban environment is crucial in the age of rapid urbanisation. Air pollution modelling is one of the key tools for researchers, scientists, and urban planners to understand pollution behaviour. Recent updates in air quality regulations are challenging the state-of-the-art air pollution modelling techniques by requiring accurate predictions on a high temporal level, i.e. predictions at the hourly level rather than the annual level. Current stateof-the-art models designed to have good prediction accuracy on the low temporal resolution by assuming that the pollution is in steady state. Making predictions on higher temporal resolution violates this assumption and causing inaccurate predictions. We introduce a novel statistical regression based air pollution model which produces accurate hourly predictions by using data with high temporal resolution and advanced regression algorithms. We conducted an analysis which shows that the state-of-the-art evaluation techniques (e.g. RMSE) do not describe the nature of the mispredictions of the models built on different data subsets. We carried out an extensive input data evaluation experiment where we concluded that our approach could achieve further accuracy improvement by training the models on a carefully selected subset of the input data.

关键词： Predictive models Data models Atmospheric modeling Monitoring Roads Buildings Prediction algorithms

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White Space Prediction for Low-Power Wireless Networks: A Data-Driven Approach

White Space Prediction for Low-Power Wireless Networks: A Da...

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international conference on distributed computing in sensor systems (dcoss)

作者： Indika S.A. Dhanapala Ramona Marfievici Sameera Palipana Piyush Agrawal Dirk Pesch Cork Institute of Technology Cork Cork IE Cork Institute of Technology Cork Ireland United Technologies Research Centre Cork Ireland

In the 2.4 GHz unlicensed spectrum, the coexistence of WiFi, Bluetooth and ieee 802.15.4 devices generates increased channel contention. Notably, low-power wireless networks experience packet loss and delays due to interference. To improve the performance of low-power wireless networks under interference, we propose a data driven proactive approach based on interference modeling for white space prediction. We leverage statistical analysis of real-world traces from two indoor environments characterized by varying channel conditions to identify interference patterns. We characterize interference in terms of Inter-Arrival Time (IAT) and number of interfering signals and use a Gaussian Mixture Model (GMM) to accurately estimate the interference distribution as observed by the low-power wireless nodes. Then, we use a Hidden Markov Model (HMM) for white space prediction. Our validation w.r.t. real-world traces from two environments show that our GMM model can estimate interference with an accuracy higher than 94:7%. Moreover, the white space prediction evaluation shows an average accuracy of 97:7% and 89:5% across the two environments.

关键词： Interference Hidden Markov models White spaces Wireless communication Predictive models Wireless fidelity Wireless sensor networks

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PHASER - A Phase-Shifting Antenna for Low-Power Directional Communication 13

PHASER - A Phase-Shifting Antenna for Low-Power Directional ...

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13th ieee international conference on distributed computing in sensor systems (dcoss)

作者： Selavo, Leo Vyas, Dhruv Yahyazadeh, Moosa Chipara, Octav Univ Latvia Riga Latvia Univ Iowa Iowa City IA 52242 USA

ISBN: (纸本)9781538639917

This paper describes the design and empirical evaluation of PHASER a mote prototype for low-power directional communication in wireless sensor networks. PHASER has a modular design that includes three components: a low power radio, an RF signal processing chip, and two off-the-shelf antennas. Directional communication is achieved by splitting the output signal from the low-power radio chip and controlling programmatically the phase of each signal as it transmitted to each antenna. The net effect of controlling the phase of the signals is that they generate patterns of constructive and destructive interference as signals propagate. PHASER is well-suited for wireless sensor networks as it does not require heavyweight signal processing techniques and consumes minimal additional energy. We have extensively evaluated the performance of five PHASER prototypes. Empirical results clearly demonstrate that changing the phase configuration of PHASER can generate diverse anisotropic radiation patterns. The diverse radiation patterns may be used to increase the signal strength at an intended receiver. Our data indicates that the signal strength of a link can be increased by at least 13 dBm. We also show it is possible to take advantage of the anisotropy of the radiation patterns to facilitate spatial reuse. More importantly, we show that the quality of the links from the same PHASER mote has a common pattern that can be predicted using a simple model. Our evaluation shows that model introduces an median absolute error of about 2 dBm. The model may be used for realistic simulations or integrated into protocol stacks to identify the phase configurations that improve link quality or spatial reuse.

关键词： Wireless sensor networks Antenna radiation patterns Receivers Transmitting antennas Directive antennas Phase measurement

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Proceedings - 2017 13th international conference on distributed computing in sensor systems, dcoss 2017

Proceedings - 2017 13th International Conference on Distribu...

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13th international conference on distributed computing in sensor systems, dcoss 2017

ISBN: (纸本)9781538639917

The proceedings contain 33 papers. The topics discussed include: novel WSN hardware for long range low power monitoring;scheduling high-rate unpredictable traffic in ieee 802.15.4 TSCH networks;sensor selection for heterogeneous coverage measures;opportunistic routing in underwater sensor networks: potentials, challenges and guidelines;LoRa transmission parameter selection;efficient many-to-many data sharing using synchronous transmission and TDMA;TSCH and 6TiSCH for Contiki: challenges, design and evaluation;and ELOC: locating wild elephants using low-cost infrasonic detectors.

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Power-Aware Population Protocols 37

Power-Aware Population Protocols

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37th ieee international conference on distributed computing systems (ICDCS)

作者： Xu, Chuan Burman, Janna Beauquier, Joffroy Univ Paris Saclay LRI Paris France

ISBN: (纸本)9781538617915

In this paper, we propose a formal energy model which allows an analytical study of energy consumption, for the first time in the context of population protocols (PP). In PP, anonymous and bounded memory agents move unpredictably and communicate in pairs. In order to illustrate the power and the usefulness of the proposed energy model, we develop a new power-aware protocol (EB-TTFM) for the task of data collection. The analytical results show that, in terms of energy consumption, EB-TTFM outperforms a known data collection protocol under certain conditions. Finally, we present a lower bound concerning energy consumption of any possible data collection protocol in PP, which also justifies the efficiency of EB-TTFM.

关键词： mobile sensor networks population protocols energy consumption data collection

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Leveraging Target k-Coverage in Wireless Rechargeable sensor Networks 37

Leveraging Target <i>k</i>-Coverage in Wireless Rechargeable...

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37th ieee international conference on distributed computing systems (ICDCS)

作者： Zhou, Pengzhan Wang, Cong Yang, Yuanyuan SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (纸本)9781538617915

Energy remains a major hurdle in running computation-intensive tasks on wireless sensors. Recent efforts have been made to employ a Mobile Charger (MC) to deliver wireless power to sensors, which provides a promising solution to the energy problem. Most of previous works in this area aim at maintaining perpetual network operation at the expense of high operating cost of MC. In the meanwhile, it is observed that due to low cost of wireless sensors, they are usually deployed at high density so there is abundant redundancy in their coverage in the network. For such networks, it is possible to take advantage of the redundancy to reduce the energy cost. In this paper, we relax the strictness of perpetual operation by allowing some sensors to temporarily run out of energy while still maintaining target k-coverage in the network at lower cost of MC. We first establish a theoretical model to analyze the performance improvements under this new strategy. Then we organize sensors into load-balanced clusters for target monitoring by a distributed algorithm. Next, we propose a charging algorithm named lambda-GTSP Charging Algorithm to determine the optimal number of sensors to be charged in each cluster to maintain k-coverage in the network and derive the route for MC to charge them. We further generalize the algorithm to encompass mobile targets as well. Our extensive simulation results demonstrate significant improvements of network scalability and cost saving that MC can extend charging capability over 2-3 times with a reduction of 40% of moving cost without sacrificing the network performance.

关键词： Wireless sensor networks wireless charging target k-coverage route planning

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Kinaara: distributed discovery and allocation of mobile edge resources 14

<i>Kinaara</i>: Distributed discovery and allocation of mobi...

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14th ieee international conference on Mobile Ad Hoc and sensor systems (MASS)

作者： Salem, Ahmed Salonidis, Theodoros Desai, Nirmit Nadeem, Tamer Old Dominion Univ Norfolk VA 23529 USA IBM TJ Watson Res Ctr Yorktown Hts NY USA Virginia Commonwealth Univ Richmond VA USA

ISBN: (纸本)9781538623237

Edge computing is an increasingly popular paradigm, wherein computation comes closer to the sources of data. A key challenge for edge computing is discovering and utilizing the heterogeneous resources of the vast number of mobile devices at the network edge. Mobile edge devices hide behind private networks, they are mobile and their owners hesitate to share them due to privacy considerations. We propose Kinaara1 a framework for discovering and allocating collective resources for edge computing applications. first, Kinaara uses a multi-tier architecture to organize geographically proximal edge devices in clusters and provide their resources via trusted mediator entities. Second, it uses a novel resource representation to name and encode devices in terms of the resources advertised by their users. Third, it uses a novel distributed indexing scheme to organize devices in a proximal cluster on a ring logical structure based on their resource similarity. Our extensive experimental evaluation on a large Wi-Fi mobility dataset of 150K users and 345 APs show that compared to existing approaches Kinaara reduces resource discovery overhead by up to 70% and is robust to device mobility.

关键词： Edge computing sensors Mobile communication Computer architecture Mobile handsets Indexing Servers Mobile phones Computer Architecture mobile communication Servers sensors Exploration Indexing Mobile Edge of a figure or solid Private networks Edge Device allocation Data sources

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Hardware Acceleration Landscape for distributed Real-time Analytics: Virtues and Limitations 37

Hardware Acceleration Landscape for Distributed Real-time An...

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37th ieee international conference on distributed computing systems (ICDCS)

作者： Najafi, Mohammadreza Zhang, Kaiwen Jacobsen, Hans-Arno Sadoghi, Mohammad Tech Univ Munich Munich Germany Purdue Univ W Lafayette IN 47907 USA Univ Toronto Toronto ON Canada

ISBN: (纸本)9781538617915

We are witnessing a technological revolution with a broad impact ranging from daily life (e.g., personalized medicine and education) to industry (e.g., data-driven health-care, commerce, agriculture, and mining). At the core of this transformation lies "data". This transformation is facilitated by embedded devices, collectively known as Internet of Things (IoT), which produce real-time feeds of sensor data which are collected and processed to produce a dynamic physical model used for optimized real-time decision making. At the infrastructure level, there is a need to develop a scalable architecture for processing massive volumes of present and historical data at an unprecedented velocity to support the IoT paradigm. To cope with such extreme scale, we argue for the need to revisit the hardware and software co-design landscape in light of two key technological advancements. first is the virtualization of computation and storage over highly distributed data centers spanning across continents. Second is the emergence of a variety of specialized hardware accelerators that complement traditional general-purpose processors. Further efforts are required to unify these two trends in order to harness the power of big data. In this paper, we present a formulation and characterization of the hardware acceleration landscape geared towards real-time analytics in the cloud. Our goal is to assist both researchers and practitioners navigating the newly revived field of software and hardware co-design for building next generation distributed systems. We further present a case study to explore software and hardware interplay for designing distributed real-time stream processing.

关键词： Hardware Field programmable gate arrays Program processors Acceleration distributed databases Real-time systems Computer architecture

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