This document proposes a context as a service approach to address challenges in pervasive computing related to dynamic discovery of context providers and quality of context. It describes a context model and ontology, context offering and query language, and mechanisms for discovery, selection and binding of context providers. The approach aims to support dynamic appearing and disappearing of context providers while considering quality of context and cost of context.
This document summarizes a research paper that proposes an implementation of location monitoring services based on an anonymization algorithm. The paper describes a system architecture that uses wireless sensor nodes to monitor locations while preserving privacy. It proposes two anonymization algorithms: a resource-aware algorithm that minimizes communication costs, and a quality-aware algorithm that provides accurate locations. The resource-aware algorithm consists of three steps - a broadcast step to share location data between sensors, finding a cloaked area that maintains anonymity, and reporting aggregate location information to the server.
Estimating Parameters of Multiple Heterogeneous Target Objects Using Composit...ambitlick
This article proposes a method for estimating parameters of multiple heterogeneous target objects (objects with different sizes and shapes) using networked binary sensors. The sensors are simple and only report detections, but no individual sensor location is known. The method introduces "composite sensor nodes" containing multiple sensors in a fixed arrangement. This provides relative location information to help distinguish individual target objects. As an example, the article considers a composite node with two sensors on a line segment. Measures from these nodes can identify target shapes and estimate object parameters like radius and side lengths. Numerical tests demonstrate networked composite sensors can estimate parameters of multiple target objects.
Communication cost minimization in wirelessambitlick
The document discusses minimizing communication costs in wireless sensor and actor networks (WSANs) used for road surveillance. It proposes using Dijkstra's algorithm and dynamic programming to determine an optimal set of working actors to coordinate data transmission with minimum communication costs. Sensors detect events and transmit data to nearby actors. Actors can then perform long-range communication to transmit the data to a sink, reducing overall communication costs. The algorithms produce near-optimal solutions when accounting for limitations of real networks where actors may not be deployed at all intersections.
CONTRADICTION COMMUNICATION RANGE OF SENSOR NETWORKSpharmaindexing
This document discusses location verification in wireless sensor networks. It describes two categories of location verification: on-spot verification and in-region verification. On-spot verification checks if a sensor's estimated location matches its true location, while in-region verification checks if a sensor is located within an application-specific region. The document proposes two lightweight algorithms, GFM and GFT, for on-spot verification using neighborhood observations. It also describes a probabilistic algorithm to compute the confidence that a sensor is inside the verification region for in-region verification. The proposed verification system can effectively verify sensor locations without relying on specialized hardware or deployment knowledge, making it suitable for low-cost wireless sensor networks.
IEEE PROJECTS IN CHENNAI FOR FINAL YEAR PROJECTS @ XLNC INFOTECH 9941958222— Chennai
XLNC INFOTECH IS THE BEST PROJECT CENTRES IN CHENNAI WHICH DEALS WITH THE FOLLOWING PROJECTS FOR FINAL YEAR ENGINEERING AND SCIENCE STUDENTS
*IEEE PROJECTS
*M.E PROJECTS IN ALL THE DOMAINS
*SOFTWARE ENGINEERING PROJECTS
*MATLAB BASED PROJECTS
*NS2 BASED PROJECTS
*EMBEDDED PROJECTS
*CLOUD COMPUTING PROJECTS
REAL TIME PROJECT TRAINING/FINAL YEAR ENGINEERING PROJECTS
(CSE, IT,ECE,EEE-BE/ME/MCA/MPHIL/MSC/B.SC)
We develop each and every project with our professionals. We don’t buy the projects from anybody. You can give your own ideas in developing your project.
We assist and deliver the following:-
1.Our real time project center supports with the projects that are based on the recommendations and standards of IEEE for the year 2013-2014.
2. Being the best project center in Chennai, we provide the complete documentation for M.E Projects even.
3. Each student will be guided, mentored, trained in their academic projects separately by our IT Professionals.
4. Each student will be trained in the architecture,design,development and execution of their IEEE projects.
5. Each student will be guided with tips for the project execution, VIVA and presentation
This document lists various 2013 IEEE project titles across different domains including mobile computing, wireless networks, network security, data mining, cloud computing, and parallel & distributed computing. It provides contact information for ECWAY Technologies with offices in multiple cities in India and lists their website and email for more information. The project titles are broken down by domain and include areas like distributed caching in social wireless networks, quality-differentiated video multicast, intrusion detection for MANETs, attribute-based encryption for health records, and task scheduling in heterogeneous multicore systems.
Conquering mobile advertising holy grail: Context-Awareness matters - Dilip M...McKinsey & Company
Mobile advertising that is context-aware can be more effective by being engaging, relevant, and intelligent. Context-aware systems can sense the user's physical environment and behavior to deliver more engaging ads suited to the time and situation. Location data plus details about the user's activity provides relevance by targeting ads based on whether the user is walking, running, or traveling. Developing new context pipelines using biometric data, behavioral patterns, and mood can help deliver smarter mobile ads.
This document summarizes a research paper that proposes an implementation of location monitoring services based on an anonymization algorithm. The paper describes a system architecture that uses wireless sensor nodes to monitor locations while preserving privacy. It proposes two anonymization algorithms: a resource-aware algorithm that minimizes communication costs, and a quality-aware algorithm that provides accurate locations. The resource-aware algorithm consists of three steps - a broadcast step to share location data between sensors, finding a cloaked area that maintains anonymity, and reporting aggregate location information to the server.
Estimating Parameters of Multiple Heterogeneous Target Objects Using Composit...ambitlick
This article proposes a method for estimating parameters of multiple heterogeneous target objects (objects with different sizes and shapes) using networked binary sensors. The sensors are simple and only report detections, but no individual sensor location is known. The method introduces "composite sensor nodes" containing multiple sensors in a fixed arrangement. This provides relative location information to help distinguish individual target objects. As an example, the article considers a composite node with two sensors on a line segment. Measures from these nodes can identify target shapes and estimate object parameters like radius and side lengths. Numerical tests demonstrate networked composite sensors can estimate parameters of multiple target objects.
Communication cost minimization in wirelessambitlick
The document discusses minimizing communication costs in wireless sensor and actor networks (WSANs) used for road surveillance. It proposes using Dijkstra's algorithm and dynamic programming to determine an optimal set of working actors to coordinate data transmission with minimum communication costs. Sensors detect events and transmit data to nearby actors. Actors can then perform long-range communication to transmit the data to a sink, reducing overall communication costs. The algorithms produce near-optimal solutions when accounting for limitations of real networks where actors may not be deployed at all intersections.
CONTRADICTION COMMUNICATION RANGE OF SENSOR NETWORKSpharmaindexing
This document discusses location verification in wireless sensor networks. It describes two categories of location verification: on-spot verification and in-region verification. On-spot verification checks if a sensor's estimated location matches its true location, while in-region verification checks if a sensor is located within an application-specific region. The document proposes two lightweight algorithms, GFM and GFT, for on-spot verification using neighborhood observations. It also describes a probabilistic algorithm to compute the confidence that a sensor is inside the verification region for in-region verification. The proposed verification system can effectively verify sensor locations without relying on specialized hardware or deployment knowledge, making it suitable for low-cost wireless sensor networks.
IEEE PROJECTS IN CHENNAI FOR FINAL YEAR PROJECTS @ XLNC INFOTECH 9941958222— Chennai
XLNC INFOTECH IS THE BEST PROJECT CENTRES IN CHENNAI WHICH DEALS WITH THE FOLLOWING PROJECTS FOR FINAL YEAR ENGINEERING AND SCIENCE STUDENTS
*IEEE PROJECTS
*M.E PROJECTS IN ALL THE DOMAINS
*SOFTWARE ENGINEERING PROJECTS
*MATLAB BASED PROJECTS
*NS2 BASED PROJECTS
*EMBEDDED PROJECTS
*CLOUD COMPUTING PROJECTS
REAL TIME PROJECT TRAINING/FINAL YEAR ENGINEERING PROJECTS
(CSE, IT,ECE,EEE-BE/ME/MCA/MPHIL/MSC/B.SC)
We develop each and every project with our professionals. We don’t buy the projects from anybody. You can give your own ideas in developing your project.
We assist and deliver the following:-
1.Our real time project center supports with the projects that are based on the recommendations and standards of IEEE for the year 2013-2014.
2. Being the best project center in Chennai, we provide the complete documentation for M.E Projects even.
3. Each student will be guided, mentored, trained in their academic projects separately by our IT Professionals.
4. Each student will be trained in the architecture,design,development and execution of their IEEE projects.
5. Each student will be guided with tips for the project execution, VIVA and presentation
This document lists various 2013 IEEE project titles across different domains including mobile computing, wireless networks, network security, data mining, cloud computing, and parallel & distributed computing. It provides contact information for ECWAY Technologies with offices in multiple cities in India and lists their website and email for more information. The project titles are broken down by domain and include areas like distributed caching in social wireless networks, quality-differentiated video multicast, intrusion detection for MANETs, attribute-based encryption for health records, and task scheduling in heterogeneous multicore systems.
Conquering mobile advertising holy grail: Context-Awareness matters - Dilip M...McKinsey & Company
Mobile advertising that is context-aware can be more effective by being engaging, relevant, and intelligent. Context-aware systems can sense the user's physical environment and behavior to deliver more engaging ads suited to the time and situation. Location data plus details about the user's activity provides relevance by targeting ads based on whether the user is walking, running, or traveling. Developing new context pipelines using biometric data, behavioral patterns, and mood can help deliver smarter mobile ads.
The document describes a visualization tool called HomeViz that was created to help users understand their household energy consumption from a smart home system. It discusses the design process, which involved paper prototypes, usability testing, and digital prototypes to refine the interface. The final implementation retrieves anonymous and aggregated energy usage data from a Loxone smart home platform. The tool is intended to help users gain awareness of their energy usage and identify opportunities to save energy.
This short document provides instructions for creating a Haiku Deck presentation on SlideShare and encourages the reader to get started making their own presentation. It includes stock photos without captions to illustrate the topic and ends by explicitly telling the reader to get started creating their own Haiku Deck presentation on SlideShare.
Context awareness and Resilience EngineeringHenry Muccini
The document discusses context-aware mobile applications and engineering resilient systems. It notes that context-aware applications are aware of and adapt to the computing environment, including connectivity, available resources, user context, and physical context. This contextual information can change and introduce bugs if assumptions are incorrect. Engineering resilient context-aware systems involves keeping them dependable when facing changes to resources, data, and the contextual environment. Strategies include continuous monitoring of networks and sensors and reliability requirements for varying conditions. Context-awareness could enable resilience but also introduces new vulnerabilities due to sensitivity to environmental changes.
This document discusses developing context-aware applications using anticipatory computing. It explains that anticipatory computing relies on context awareness which can be inferred from sensors on mobile devices. Backend systems can then infer a user's situation, activity, intent, and mood based on this context data. Recent advances in areas like speech recognition, computer vision, and knowledge graphs are enabling new context-aware and voice-driven applications. Challenges in building these applications include functionality, accuracy, scalability, latency, and different technical choices for aspects like machine learning and development platforms. The MindMeld API aims to provide powerful yet easy-to-use tools for building context-aware applications across various domains.
[SOCRS2013]Differential Context Modeling in Collaborative FilteringYONG ZHENG
This document discusses differential context modeling (DCM) in collaborative filtering recommender systems. DCM is a framework that separates recommender algorithms into components and applies differential context constraints to each component to maximize contextual effects. The document applies DCM using differential context relaxation and weighting to item-based collaborative filtering and Slope One recommender algorithms. Experimental results on movie and food rating datasets show that differential context weighting improves predictive performance over baselines and differential context relaxation. Future work involves expanding DCM to additional recommender algorithms and optimizing performance.
These are the slides of my PhD. thesis dissertation called "A Framework for Abstraction and Virtualization of Sensors in Mobile Context Aware Computing". It was presented on June 29 2015.
Adaptive middleware of context aware application in smart homesambitlick
This document proposes an adaptive middleware for context-aware applications in smart homes. The middleware abstracts applications from sensors providing context and chooses context providers to maximize total application satisfaction given multiple alternatives. It also implements autonomic properties like self-configuration and resilience to failures in context provision.
Tizen apps with Context Awareness and Machine LearningShashwat Pradhan
Using mobile sensor data tuned with Machine Learning models, developers can build advance context aware apps. The simple contextual lifecycle of Sense, Understand and Adapt can be implemented using simple APIs. The presentation focuses on User Experience and future applications with context. Machine Learning models on top of the sensor data will give developers better understanding about the user.
The document discusses context and context-aware applications. It notes that there are approximately 150 definitions of context from different domains, and researchers do not agree on a single definition as context is an ill-defined concept. Context-aware computing allows applications to use contextual information like user location, time of day, nearby people and devices, and activity to provide a better understanding of users. Context-aware applications are interdisciplinary and use context to enhance the user experience. Examples of contextual information that can be used include location, time, activity, and nearby people or devices.
This document discusses context-aware recommender systems for mobile devices. It introduces recommender systems and how they are used to help users find relevant information. It describes how mobile recommender systems can take into account contextual information like location and weather to provide personalized recommendations. As a practical example, it outlines the South Tyrol Suggests app, which provides point of interest recommendations for South Tyrol adapted to the user's context. It also discusses the challenges of building context-aware recommender systems and evaluating their performance.
Context-aware mobile computing allows mobile applications to take advantage of contextual information about the user's environment to provide better services. This literature review explores the evolution of context-aware technologies and their impact on society. Key developments include location sensing technologies like GPS and WiFi that provide context data, as well as augmented reality projects like Google Glass and Project Tango that give mobile devices a 3D understanding of space. Context-aware software like Google Now uses this information to deliver the right data to users at the appropriate time.
UX for emerging technologies & context-aware computingPrithvi Raj
Context-aware computing uses information about a user's environment and activities to provide relevant information and services. It aims to reduce manual configuration by allowing systems to self-monitor, self-heal, and self-configure based on contextual information such as location, identity, nearby resources, physiological measurements, and activity. By understanding context, applications can deliver personalized services at the right time without needing direct requests from the user. This leads to a better user experience and business value by providing the right service or information at the right moment through anticipating users' needs.
1) The document discusses the design of capability delivery adjustments for adaptive applications. It describes different types of adjustments like context calculations, performance calculations, scheduled adjustments, and event-based adjustments.
2) A capability delivery application is presented that uses adjustments to ensure business services can be delivered with minimum customization for different contexts. Adjustments decouple context-dependent processing from core applications.
3) An example image processing service is described that uses a scheduled adjustment to dynamically scale the number of processing containers up or down based on queue size and response times to ensure acceptable performance.
This document discusses context awareness in mobile computing. It defines context awareness and describes how mobile applications can utilize contextual information like user location, preferences, and device/network capabilities to provide more relevant services with less user interaction. The document presents several scenarios that demonstrate how context-aware applications could work and examines some challenges like imperfect context information. It also outlines typical components of context-aware applications like context modeling, acquisition, and adaptation.
This document presents a computational framework for multi-dimensional context-aware adaptation. It discusses the need for adaptation across different contexts of use like devices, platforms, users and environments. The challenges include considering multiple contexts to provide adapted interfaces with high usability. The methodology involves gathering context information, implementing adaptation algorithms using techniques like machine learning, and validating the framework through case studies. The goal is to develop a unified and consistent approach that can adapt applications across multiple dimensions like context, platform and user profile.
Context-aware application development with FIWARE #CPBR8Fermin Galan
Context-aware application development with FIWARE, used in the #CPBR8 workshop. It includes basic and advanced Orion topics, along with usage examples.
The document summarizes a session on context aware services from an IBBT Brokerage Event. The session chair was Piet Demeester and objectives included identifying research topics and interested parties. Topics discussed included the concept of context aware services, market potential, challenges, and requirements. Major challenges identified were accurate indoor positioning, different sensor types, communication between devices, and representing context information standardized. The session identified several interested parties and concluded that context detection infrastructure, context aware devices, service architectures, and addressing security, user requirements, and business models were important areas.
Automagically: A Primer to The Connection System of ThingsAynne Valencia
The document discusses the emerging field of connected systems and pervasive computing. It notes that sensors, mobile devices, and the internet are enabling new data-driven experiences and services beyond traditional products. Innovation in this area comes from rethinking existing interactions and finding new ways to leverage collected data. The connectivity of sensors, devices, and the cloud will allow for interesting applications across various domains from health to transportation. Designing experiences and systems for this new paradigm requires considering factors like physical interactions, data collection and analysis, social aspects, and service needs.
Mobile Web Services in Health Care and Sensor NetworksDr. Fahad Aijaz
The document summarizes a presentation on mobile web services in health care and sensor networks. It discusses using mobile web services with wireless sensor networks for applications like health monitoring. It presents an advanced mobile web services architecture that supports both synchronous and asynchronous interactions. It also describes using sensor networks in a healthcare scenario and future research on peer-to-peer service level agreements and integrating sensor networks with the IP Multimedia Subsystem.
The document describes a visualization tool called HomeViz that was created to help users understand their household energy consumption from a smart home system. It discusses the design process, which involved paper prototypes, usability testing, and digital prototypes to refine the interface. The final implementation retrieves anonymous and aggregated energy usage data from a Loxone smart home platform. The tool is intended to help users gain awareness of their energy usage and identify opportunities to save energy.
This short document provides instructions for creating a Haiku Deck presentation on SlideShare and encourages the reader to get started making their own presentation. It includes stock photos without captions to illustrate the topic and ends by explicitly telling the reader to get started creating their own Haiku Deck presentation on SlideShare.
Context awareness and Resilience EngineeringHenry Muccini
The document discusses context-aware mobile applications and engineering resilient systems. It notes that context-aware applications are aware of and adapt to the computing environment, including connectivity, available resources, user context, and physical context. This contextual information can change and introduce bugs if assumptions are incorrect. Engineering resilient context-aware systems involves keeping them dependable when facing changes to resources, data, and the contextual environment. Strategies include continuous monitoring of networks and sensors and reliability requirements for varying conditions. Context-awareness could enable resilience but also introduces new vulnerabilities due to sensitivity to environmental changes.
This document discusses developing context-aware applications using anticipatory computing. It explains that anticipatory computing relies on context awareness which can be inferred from sensors on mobile devices. Backend systems can then infer a user's situation, activity, intent, and mood based on this context data. Recent advances in areas like speech recognition, computer vision, and knowledge graphs are enabling new context-aware and voice-driven applications. Challenges in building these applications include functionality, accuracy, scalability, latency, and different technical choices for aspects like machine learning and development platforms. The MindMeld API aims to provide powerful yet easy-to-use tools for building context-aware applications across various domains.
[SOCRS2013]Differential Context Modeling in Collaborative FilteringYONG ZHENG
This document discusses differential context modeling (DCM) in collaborative filtering recommender systems. DCM is a framework that separates recommender algorithms into components and applies differential context constraints to each component to maximize contextual effects. The document applies DCM using differential context relaxation and weighting to item-based collaborative filtering and Slope One recommender algorithms. Experimental results on movie and food rating datasets show that differential context weighting improves predictive performance over baselines and differential context relaxation. Future work involves expanding DCM to additional recommender algorithms and optimizing performance.
These are the slides of my PhD. thesis dissertation called "A Framework for Abstraction and Virtualization of Sensors in Mobile Context Aware Computing". It was presented on June 29 2015.
Adaptive middleware of context aware application in smart homesambitlick
This document proposes an adaptive middleware for context-aware applications in smart homes. The middleware abstracts applications from sensors providing context and chooses context providers to maximize total application satisfaction given multiple alternatives. It also implements autonomic properties like self-configuration and resilience to failures in context provision.
Tizen apps with Context Awareness and Machine LearningShashwat Pradhan
Using mobile sensor data tuned with Machine Learning models, developers can build advance context aware apps. The simple contextual lifecycle of Sense, Understand and Adapt can be implemented using simple APIs. The presentation focuses on User Experience and future applications with context. Machine Learning models on top of the sensor data will give developers better understanding about the user.
The document discusses context and context-aware applications. It notes that there are approximately 150 definitions of context from different domains, and researchers do not agree on a single definition as context is an ill-defined concept. Context-aware computing allows applications to use contextual information like user location, time of day, nearby people and devices, and activity to provide a better understanding of users. Context-aware applications are interdisciplinary and use context to enhance the user experience. Examples of contextual information that can be used include location, time, activity, and nearby people or devices.
This document discusses context-aware recommender systems for mobile devices. It introduces recommender systems and how they are used to help users find relevant information. It describes how mobile recommender systems can take into account contextual information like location and weather to provide personalized recommendations. As a practical example, it outlines the South Tyrol Suggests app, which provides point of interest recommendations for South Tyrol adapted to the user's context. It also discusses the challenges of building context-aware recommender systems and evaluating their performance.
Context-aware mobile computing allows mobile applications to take advantage of contextual information about the user's environment to provide better services. This literature review explores the evolution of context-aware technologies and their impact on society. Key developments include location sensing technologies like GPS and WiFi that provide context data, as well as augmented reality projects like Google Glass and Project Tango that give mobile devices a 3D understanding of space. Context-aware software like Google Now uses this information to deliver the right data to users at the appropriate time.
UX for emerging technologies & context-aware computingPrithvi Raj
Context-aware computing uses information about a user's environment and activities to provide relevant information and services. It aims to reduce manual configuration by allowing systems to self-monitor, self-heal, and self-configure based on contextual information such as location, identity, nearby resources, physiological measurements, and activity. By understanding context, applications can deliver personalized services at the right time without needing direct requests from the user. This leads to a better user experience and business value by providing the right service or information at the right moment through anticipating users' needs.
1) The document discusses the design of capability delivery adjustments for adaptive applications. It describes different types of adjustments like context calculations, performance calculations, scheduled adjustments, and event-based adjustments.
2) A capability delivery application is presented that uses adjustments to ensure business services can be delivered with minimum customization for different contexts. Adjustments decouple context-dependent processing from core applications.
3) An example image processing service is described that uses a scheduled adjustment to dynamically scale the number of processing containers up or down based on queue size and response times to ensure acceptable performance.
This document discusses context awareness in mobile computing. It defines context awareness and describes how mobile applications can utilize contextual information like user location, preferences, and device/network capabilities to provide more relevant services with less user interaction. The document presents several scenarios that demonstrate how context-aware applications could work and examines some challenges like imperfect context information. It also outlines typical components of context-aware applications like context modeling, acquisition, and adaptation.
This document presents a computational framework for multi-dimensional context-aware adaptation. It discusses the need for adaptation across different contexts of use like devices, platforms, users and environments. The challenges include considering multiple contexts to provide adapted interfaces with high usability. The methodology involves gathering context information, implementing adaptation algorithms using techniques like machine learning, and validating the framework through case studies. The goal is to develop a unified and consistent approach that can adapt applications across multiple dimensions like context, platform and user profile.
Context-aware application development with FIWARE #CPBR8Fermin Galan
Context-aware application development with FIWARE, used in the #CPBR8 workshop. It includes basic and advanced Orion topics, along with usage examples.
The document summarizes a session on context aware services from an IBBT Brokerage Event. The session chair was Piet Demeester and objectives included identifying research topics and interested parties. Topics discussed included the concept of context aware services, market potential, challenges, and requirements. Major challenges identified were accurate indoor positioning, different sensor types, communication between devices, and representing context information standardized. The session identified several interested parties and concluded that context detection infrastructure, context aware devices, service architectures, and addressing security, user requirements, and business models were important areas.
Automagically: A Primer to The Connection System of ThingsAynne Valencia
The document discusses the emerging field of connected systems and pervasive computing. It notes that sensors, mobile devices, and the internet are enabling new data-driven experiences and services beyond traditional products. Innovation in this area comes from rethinking existing interactions and finding new ways to leverage collected data. The connectivity of sensors, devices, and the cloud will allow for interesting applications across various domains from health to transportation. Designing experiences and systems for this new paradigm requires considering factors like physical interactions, data collection and analysis, social aspects, and service needs.
Mobile Web Services in Health Care and Sensor NetworksDr. Fahad Aijaz
The document summarizes a presentation on mobile web services in health care and sensor networks. It discusses using mobile web services with wireless sensor networks for applications like health monitoring. It presents an advanced mobile web services architecture that supports both synchronous and asynchronous interactions. It also describes using sensor networks in a healthcare scenario and future research on peer-to-peer service level agreements and integrating sensor networks with the IP Multimedia Subsystem.
Presentation made at the Metadata Australia conference, Canberra, May 2010 (also available via metadataaustralia2010.com)
(Light) Introduction to work done in the Semantic Sensor Networks Incubator activity.
Analysis of the commonalities and differences for the adoption of semantic web standards by sensing web and eGov communities of practice.
The document presents a novel three-dimensional adaptive localization (T-Dial) algorithm for wireless sensor networks. The proposed algorithm works in four primary phases: 1) Neighbor formation where nodes broadcast information to nodes within transmission range to form neighbor tables; 2) Group formation where anchor nodes connect to nearby nodes to divide the network into manageable groups; 3) Edge node marking where edge nodes on the network boundary are detected and marked; and 4) Localization error correction where missing nodes from initial setup are rediscovered and corrected. Simulation results show the proposed algorithm improves localization rate, reduces localization error, and increases positioning rate compared to existing algorithms.
A Novel Three-Dimensional Adaptive Localization (T-Dial) Algorithm for Wirele...iosrjce
The document presents a novel three-dimensional adaptive localization (T-Dial) algorithm for wireless sensor networks. The proposed algorithm works in four primary phases: 1) Neighbor formation where nodes broadcast information to nodes within transmission range to form neighbor tables; 2) Group formation where anchor nodes connect to non-anchor nodes to divide the network into smaller manageable groups; 3) Edge node marking where edge nodes on the network boundary are detected and marked; and 4) Localization error correction where missing nodes from initial setup are rediscovered and corrected. Simulation results show the proposed algorithm improves localization rate, reduces localization error, and increases positioning rate compared to existing algorithms.
This document discusses wireless sensor networks and middleware approaches for them. It describes wireless sensor networks as consisting of distributed autonomous sensor nodes that monitor physical environments cooperatively. It outlines common sensor node components and network architectures. It then defines middleware as a software layer that manages complexity and heterogeneity. Key middleware design principles for wireless sensor networks include supporting limited resources, scalability, and data aggregation. The document outlines several middleware approaches, including those based on global behavior, local behavior, virtual machines, databases, and modular programming.
The document proposes a new localization method called A2L (Angle to Landmark) for wireless sensor networks. A2L uses angle of arrival measurements between sensor nodes and a subset of nodes equipped with GPS (landmarks) to determine the positions of non-landmark nodes. Compared to previous methods like APS and AHLoS that also use angle and distance measurements, simulations show that A2L can locate a greater number of nodes with higher accuracy while requiring fewer connections between nodes. The method is also low-cost since it does not require each node to have GPS or other expensive equipment.
This document discusses a research project using MEMS "smart dust motes" for intelligent lighting control. The goals are to use wireless sensor networks to better understand occupancy patterns, validate sensor readings, and optimize lighting for energy savings while considering user preferences. Researchers plan to characterize mote sensors, develop validation and fusion algorithms, and eventually implement a smart lighting system in the BEST Lab to automatically control dimming based on human presence and interactions. This would personalize lighting while reducing electricity costs.
Indoor Localization Using Local Node Density In Ad Hoc WSNsjoaquin_gonzalez
Presentation for Master Thesis "Indoor Localization Using Local Node Density In Ad Hoc WSNs", research supported by Free University Berlin. Coordinators: Freddy Lopez Villafuerte, Gianluca Cornetta.
The document describes 8 potential final year projects related to wireless networks and communication.
Project 1 involves developing a decremental algorithm for adaptive routing that incorporates real-time traveler information in dynamic networks.
Project 2 involves designing a global authentication system for distributed wireless networks.
Project 3 involves designing an IP-IP tunnel for remote authentication and resource utilization.
The remaining projects involve GSM encryption decryption, fault detection in wireless sensor networks, efficient code distribution in wireless sensor networks, and a novel agent-based user-network communication model for wireless sensor networks.
The Brussels Wind Energy Research Institute (BruWind) aims to consolidate wind energy research across several institutions in Brussels. It seeks to centralize knowledge, share expertise, increase visibility, and participate in European networks through a collaborative research program covering various aspects of modern wind turbine technology. The institute brings together research groups studying topics like power systems, operation and maintenance, noise and vibrations, materials testing, optical sensors, and corrosion management.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
The document discusses how networks and applications can become more aware of each other to improve the experience for end users. Currently, networks and applications operate independently without much visibility into each other. The document proposes that applications share information about end users and traffic with networks, and networks share information about topology, bandwidth, and resources with applications. This would allow applications to optimize content placement and resource usage, and networks to gain insights to better optimize traffic and provide new services. The document argues this type of programmable network can improve areas like security, performance, analytics and more.
Accurate and Energy-Efficient Range-Free Localization for Mobile Sensor Networksambitlick
The document summarizes an algorithm called WMCL that improves the sampling efficiency and localization accuracy of existing SMC-based localization algorithms for mobile sensor networks. WMCL achieves higher sampling efficiency by further reducing the size of sensor nodes' bounding boxes, which restrict the scope from which candidate samples are selected, by up to 87%. This improves the sampling efficiency by up to 95%. WMCL also improves localization accuracy by using estimated position information from sensor neighbors, achieving similar accuracy with less communication and computation compared to other algorithms using similar methods.
Juniper Networks introduced its SDN strategy during its 2013 Global Partner Conference. Executive Vice President of the Software Solutions Division, Bob Muglia, introduced the company's vision, strategy and licensing model for the SDN transition.
[SeNAmI'12] Towards a fuzzy-based multi-classifier selection module for activ...Josué Freelance
The document proposes a fuzzy-based multi-classifier selection module for activity recognition applications on smartphones. It presents a two-stage architecture: 1) An offline classifier evaluation module that analyzes the computational cost and performance of different classifier configurations for activity recognition. 2) An online fuzzy selector module that selects the best classifier based on criteria like accuracy, size, and response time to save device resources. The system aims to efficiently perform activity recognition using smartphones' processing capabilities by integrating multiple classifiers.
This document discusses multi-sensor data fusion techniques for target tracking. It begins by stating the objectives of performing data fusion within the sampling interval to send accurate information to the tracking center. It then discusses areas of use for target tracking including military and non-military applications. The key elements of multiple target tracking are outlined such as detection, recognition, identification, tracking, and decision making. The need for multiple sensors to improve performance is explained. Different data fusion techniques and architectures including centralized, distributed and hybrid are described. The implementation of the weighted least squares method for fusing sensor data is presented along with results showing improved tracking accuracy compared to other fusion techniques.
The document describes a new wavelet-based support vector machine (WSVM) classifier for wildfire detection using a decision fusion framework in video. The proposed system uses five subalgorithms: 1) slow moving object detection 2) smoke-colored region detection 3) region smoothness detection 4) shadow detection and elimination 5) covariance-matrix-based classification. Decision values from the subalgorithms are combined using an adaptive decision fusion method. A new wavelet kernel is also proposed to improve the generalization ability of the SVM classifier. The WSVM model utilizes wavelet analysis to extract nonlinear characteristics from image data for classification.
Adaptive Neighbor Discovery for Mobile and Low Power Wireless Sensor Networks Dimitrios Amaxilatis
Adaptive neighbor discovery is a technique that adapts beaconing rates in wireless sensor networks based on neighborhood changes. It uses a stability metric to determine if nodes can relax beaconing. Stable nodes with consistent neighborhoods reduce beaconing, while unstable nodes increase beaconing to update neighbors. Simulations show it reduces beacons by 90% in stable environments. Real world tests on a testbed show it extends network lifetime by 20% and handles mobility better than fixed neighbor discovery approaches. Further work includes evaluating duty cycling and using it with other network protocols.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
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Chris Bolin, Senior Intelligent Automation Architect Anika Systems
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
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An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
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Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
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How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
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Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
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We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
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The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
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The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
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- Review what KM ‘is’ and ‘isn’t’
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zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
Context as a Service
1. Introduction Approach Evaluation Conclusions
Context as a Service
Michael Wagner
Distributed Systems Group
University of Kassel
December 2010
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 1
2. Introduction Approach Evaluation Conclusions
Outline
Introduction
Motivation
Quality of context and cost of context
Challenges and objectives
Approach
Context model and ontology
Context Offering and Query Language
Discovery and matching
Selection
Binding
Evaluation
Conclusions
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 2
3. Introduction Approach Evaluation Conclusions
Introduction
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 3
4. Introduction Approach Evaluation Conclusions
Context provider
GPS Sensor
Digital compass
Context sensors
Proximity sensor
Light sensor
Accelerometer
Thermometer
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 4
5. Introduction Approach Evaluation Conclusions
Context provider
GPS Sensor Cell-ID based
Position
Digital compass
Context reasoner
Network based
Context sensors
Position
Proximity sensor
Calendar based
Light sensor Position
Activity
Accelerometer
Reasoner
Thermometer Network based
Temperature
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 4
6. Introduction Approach Evaluation Conclusions
Context provider
GPS Sensor Cell-ID based
Position Position
Digital compass
Context reasoner
Network based
Context sensors
Position
Proximity sensor
Similar type Calendar based
Light sensor of context Position
information Activity
Accelerometer
Reasoner
Thermometer Network based
Temperature Temperature
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 4
7. Introduction Approach Evaluation Conclusions
Additional external context provider
WiFi
Positioning
GPS
GPS
WiFi
Positioning
WiFi
Positioning
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 5
8. Introduction Approach Evaluation Conclusions
Additional external context provider
WiFi
Positioning
GPS
GPS
WiFi
Positioning
WiFi
Positioning
RFID WiFi
Positioning Positioning
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 5
9. Introduction Approach Evaluation Conclusions
Using context in context-aware self-adaptive
applications
Several types of context consumers:
Application business logic: Context-information used within
the actual application (e.g. navigation from the current
position to another position)
Adaptation reasoning: Selection of the “best” variant of the
application with regard to the execution context
Context reasoning and fusion:
Deducing high-level implicit context from low-level explicit
context
Checking the consistency of context
...
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 6
10. Introduction Approach Evaluation Conclusions
Various context providers and consumers
Several context providers
internal and external
potentially providing the same type of information
but differing in quality and cost
and the representation of the information, quality and cost
data
Several context consumers
internal and external
potentially requesting the same type of information
but differing in quality and cost preferences
and the requested representation of the information, quality
and cost data
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 7
11. Introduction Approach Evaluation Conclusions
Current solutions
Most commonly: hard-linked references to context sensors and
reasoners, but
no support for dynamically appearing new context providers.
Few approaches support the dynamic selection and discovery
of context sensors [CAS06, HM04], but
developers have to know the data representations of the
context provider,
no support for activation and deactivation (and the resulting
problems) of context providers in order to save resources.
However, dynamic discovery, data interpretation and energy-saving
are essential requirements in pervasive computing [SHB10].
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 8
12. Introduction Approach Evaluation Conclusions
Quality of Context
“Quality of Context (QoC) is any information that
describes the quality of information that is used as
context information. Thus, QoC refers to information
and not to the process nor the hardware component that
possibly provide the information.”
[BKS03]
Cost of Context
“Cost of Context (CoC) is a parameter associated to the
context that indicates the resource consumption used to
measure or calculate the piece of context information.”
[VRL+ 09]
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 9
13. Introduction Approach Evaluation Conclusions
Context providers differ in the provided QoC, required CoC and the
provided representation of the context information, QoC and CoC.
Problem
Selection and activation of one of the available context providers
and thereby . . .
estimating the QoC of deactivated context providers.
taking into account the heterogeneous representations of
context information and the according QoC and CoC.
trading off the provided QoC and required CoC against the
QoC as requested by the consumer and his preferences
regarding cost.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 10
14. Introduction Approach Evaluation Conclusions
Context providers differ in the provided QoC, required CoC and the
provided representation of the context information, QoC and CoC.
Problem
Selection and activation of one of the available context providers
and thereby . . .
estimating the QoC of deactivated context providers.
taking into account the heterogeneous representations of
context information and the according QoC and CoC.
trading off the provided QoC and required CoC against the
QoC as requested by the consumer and his preferences
regarding cost.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 10
15. Introduction Approach Evaluation Conclusions
Challenges, requirements and objectives
Local and remote context sensors and reasoners are abstracted as
context services.
Main challenges:
Dynamic selection of context providers based on QoC and
CoC
Activation and deactivation of context sensors
Additional requirements and objectives:
Exchange and interpretation of heterogeneously represented
context information, QoC and CoC
Loose coupling of context providers and consumers
Dynamic discovery of external context services
Estimation of QoC of deactivated context providers based on
historical context values
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 11
16. Introduction Approach Evaluation Conclusions
Approach
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 12
17. Introduction Approach Evaluation Conclusions
Overview - Context model and ontology
Challenges and requirements: Context model and ontology
Exchange and
interpretation of context
information, QoC and CoC
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 13
18. Introduction Approach Evaluation Conclusions
Meta-model and Ontology
owl:Thing
is-a
EntityType Scope Representation
characterizes* hasRepresentation*
is-a
hasDimension*
Composite Representation Basic Representation
Entity: Physical or logical entity of the world that is described
by the information, e.g. PDA
Scope: Refers to the type of the provided information, e.g.
Location; meta-data are also considered as scopes
Representation: Describes how the information is internally
structured, e.g. GPS data
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 14
19. Introduction Approach Evaluation Conclusions
Meta-model and Ontology
Ontology is used to provide a common vocabulary to bridge
semantic differences
Defines semantic concepts for entity (types), scopes and
representations
Captures relationships between the defined concepts
Information can be represented as individuals of ontological
concepts/classes
Data structures may be semantically annotated by references
to the ontology
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 15
20. Introduction Approach Evaluation Conclusions
Meta-model and Ontology
Ontology defines entity types, scopes, representations and
their relationships
Arbitrary number of representations for scopes
hasRepresentation*
Scope Representation
hasRepresentation*
is-a is-a is-a is-a
hasRepresentation*
LocationInfo DateTimeInfo DateTimeRep LocationRep
Date = 14011981
io is-a
is-a
DateTimeCustomRep LocationAddress
DateTimeInfo_Indv1
io hasRepresentation is-a
is-a
hasRepresentation DateTimeDefaultRep LocationWGS84
DateTimeInfo_Indv2
io
Day = 14 io
Month = Januar io
io Year = 1981 Street = Königstor
LocationInfo_Indv1 Number = 12
hasRepresentation City = Kassel
io
io
Latitute = 52.686
LocationInfo_Indv2
Longitude = -2.193
hasRepresentation
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 16
21. Introduction Approach Evaluation Conclusions
Meta-model and Ontology
Internal structuring of context information is defined as
representations in the ontology
Inter-Representation-Operations (IROs) allow conversion
between different representations
Simple conversions, e.g. of units, defined in the ontology itself
Grounding to methods in libraries or to a conversion service
More details of the context model and ontology in
[RWK+ 08a, Rei10, Pas09]
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 17
22. Introduction Approach Evaluation Conclusions
Overview - Context provider and consumer
Challenges and requirements: Context model and ontology
Exchange and interpretation
of context information, QoC
and CoC
Loose coupling
Context Consumer 0..* Context Provider 0..*
Reasoner 0..*
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 18
23. Introduction Approach Evaluation Conclusions
Context Offering and Query Language
Aligned with the context meta-model and the ontology
Simple EMF/XML based language based on the MUSIC
Context Query Language (CQL) [RWK+ 08b] and the
Information Offer and Request Language (IORL) [Rei10]
In difference to the CQL also support for context offers
Support for complex filters and conditions similar to the IORL
In difference to the IORL also support for the different
metadata representations and for context selection
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 19
24. Introduction Approach Evaluation Conclusions
Context Offering and Query Language
We can query for or offer context information
corresponding to a certain scope
characterizing a certain entity
having a certain representation
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 20
25. Introduction Approach Evaluation Conclusions
Context Offering and Query Language - Overview
Context Offer/Request
Scope Representation Subscription
Frequency Source SourceType
Characterized Entity * Selection Function
Entity Recursive Negotiable Utility
*
Entity Constraint Significant change spec.
Constraints
Scope Constraint *
ScopeProperty or ScopeID Operator *
Value Delta
Metadata Constraint *
Metadata class Operator Value Delta Representation
*
*
Sub-Offer/Sub-Request
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 21
26. Introduction Approach Evaluation Conclusions
COQL - Example
1 <c o q l : COQLDocument xmi : v e r s i o n = [ . . . ]
2 <C o n t e x t Q u e r i e s q u e r y I D=” q u e r y 1 ”
3 s c o p e=” P o s i t i o n ”
4 r e p r e s e n t a t i o n=” P o l a r C o o r d i n a t e ”
5 s u b s c r i p t i o n M o d e=”ONCHANGE”
6 f r e q u e n c y=” 100 ”>
7 < E n t i t i e s e n t i t y R e f=” U s e r | A r a g o r n ”/>
8 </ C o n t e x t Q u e r i e s >
9 </ c o q l : COQLDocument>
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 22
27. Introduction Approach Evaluation Conclusions
Overview - Discovery and matching
Challenges and requirements: Context model and ontology
Exchange and interpretation Discovery and Matching
of context information, QoC
and CoC
Context Requests
Context offers
Loose coupling
Dynamic discovery
Estimation of QoC
Context Consumer 0..* Context Provider 0..*
Reasoner 0..*
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 23
28. Introduction Approach Evaluation Conclusions
Matching problem
Combination of ontology reasoning and constraint matching
Usually, Constraint Satisfaction Problems (CSPs) are
NP-complete.
However, CSPs try to find an assignment of values to all the
variables so that none of the constraints is violated,
but we are only interested in the satisfiability in general.
→ Most of the solutions for CSPs are too heavy-weight.
→ Light-weight solution currently in research.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 24
29. Introduction Approach Evaluation Conclusions
Example for matching process
CONTEXT QUERY 1
Accuracy < BatteryCost <
Entity: User | Paul 1 km 0.1 mWh
Scope: Position Memory <
Rep: CartesianCoordinates 0.5 MB
CONTEXT OFFER 1 CONTEXT OFFER 2
Accuracy: BatteryCost <
Entity: User ∆_longitude < 10 m ᴧ Entity: User 0.1 mWh
Scope: Position ∆_latitude < 10 m Scope: Position
Rep: WGS84 Rep: CartesianCoordinates
BatteryCost < Accuracy =
0.5 mWh 1 cell
GPS Sensor Cell-ID based Location Sensor
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 25
30. Introduction Approach Evaluation Conclusions
Example for matching process
CONTEXT QUERY 1
Accuracy < BatteryCost <
Entity: User | Paul
Scope: Position
1 km 0.1 mWh
Memory < 1. Scope and scope
Rep: CartesianCoordinates 0.5 MB
constraints
2. Representation
CONTEXT OFFER 1
Accuracy:
CONTEXT OFFER 2
BatteryCost < 3. Entity and entity
Entity: User ∆_longitude < 10 m ᴧ Entity: User 0.1 mWh
Scope: Position
Rep: WGS84
∆_latitude < 10 m Scope: Position
Rep: CartesianCoordinates
constraints
BatteryCost < Accuracy =
0.5 mWh 1 cell 4. Metadata constraints
GPS Sensor Cell-ID based Location Sensor
Conditions: Scopeq = Scopeo or Scopeq is a generalization of Scopeo
or Scopeq = nested scope of Scopeo and scopeConstraint holds!
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 26
31. Introduction Approach Evaluation Conclusions
Example for matching process
CONTEXT QUERY 1
Accuracy < BatteryCost <
Entity: User | Paul
Scope: Position
1 km 0.1 mWh
Memory < 1. Scope and scope
Rep: CartesianCoordinates 0.5 MB
constraints
2. Representation
CONTEXT OFFER 1
Accuracy:
CONTEXT OFFER 2
BatteryCost < 3. Entity and entity
Entity: User ∆_longitude < 10 m ᴧ Entity: User 0.1 mWh
Scope: Position
Rep: WGS84
∆_latitude < 10 m Scope: Position
Rep: CartesianCoordinates
constraints
BatteryCost < Accuracy =
0.5 mWh 1 cell 4. Metadata constraints
GPS Sensor Cell-ID based Location Sensor
Conditions: Repq = Repo or Repq is a generalization of Repo or
Repo can be transformed to Repq by an IRO
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 26
32. Introduction Approach Evaluation Conclusions
Example for matching process
CONTEXT QUERY 1
Accuracy < BatteryCost <
Entity: User | Paul
Scope: Position
1 km 0.1 mWh
Memory < 1. Scope and scope
Rep: CartesianCoordinates 0.5 MB
constraints
2. Representation
CONTEXT OFFER 1
Accuracy:
CONTEXT OFFER 2
BatteryCost < 3. Entity and entity
Entity: User ∆_longitude < 10 m ᴧ Entity: User 0.1 mWh
Scope: Position
Rep: WGS84
∆_latitude < 10 m Scope: Position
Rep: CartesianCoordinates
constraints
BatteryCost < Accuracy =
0.5 mWh 1 cell 4. Metadata constraints
GPS Sensor Cell-ID based Location Sensor
Conditions: (Entity q = Entityo or Entityq is a generalization of
Entityo ) and entityConstraint holds!
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 26
33. Introduction Approach Evaluation Conclusions
Example for matching process
CONTEXT QUERY 1
Entity: User | Paul
Accuracy <
1 km
BatteryCost <
0.1 mWh
1. Scope and scope
Scope: Position Memory <
Rep: CartesianCoordinates 0.5 MB constraints
2. Representation
CONTEXT OFFER 1 CONTEXT OFFER 2
3. Entity and entity
Accuracy: BatteryCost <
Entity: User ∆_longitude < 10 m ᴧ
∆_latitude < 10 m
Entity: User 0.1 mWh constraints
Scope: Position Scope: Position
Rep: WGS84 Rep: CartesianCoordinates
BatteryCost < Accuracy =
1 cell
4. Metadata constraints
0.5 mWh
GPS Sensor Cell-ID based Location Sensor
1. Metadataq = Metadatao or Metadataq is a generalization of Metadatao
2. Repq = Repo or Repq is a generalization of Repo or Repo can be
transformed to Repo by a IRO
3. Constraintq ∧ Constrainto satisfiable!
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 26
34. Introduction Approach Evaluation Conclusions
Example for matching process - Result
CONTEXT QUERY 1
Accuracy < BatteryCost <
Entity: User | Paul 1 km 0.1 mWh
Scope: Position Memory <
Rep: CartesianCoordinates 0.5 MB
No Matching:
BatteryCost
CONTEXT OFFER 1 CONTEXT OFFER 2
Accuracy: BatteryCost <
Entity: User ∆_longitude < 10 m ᴧ Entity: User 0.1 mWh
Scope: Position ∆_latitude < 10 m Scope: Position
Rep: WGS84 Rep: CartesianCoordinates
BatteryCost < Accuracy =
0.5 mWh 1 cell
GPS Sensor Cell-ID based Location Sensor
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 27
35. Introduction Approach Evaluation Conclusions
Overview - Selection
Challenges and requirements: Context model and ontology
Exchange and interpretation Discovery and Matching
of context information, QoC Matching Results
and CoC Selection
function
Selection
Context Requests
Context offers
Loose coupling
Dynamic discovery
Estimation of QoC
Dynamic selection
Context Consumer 0..* Context Provider 0..*
Reasoner 0..*
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 28
36. Introduction Approach Evaluation Conclusions
Input for the selection: matching results
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 29
37. Introduction Approach Evaluation Conclusions
Problems during the selection
General approach: Calculation of an utility for each provider
by an utility function taking into account QoC and CoC and
selection of the provider with highest utility.
However, several additional problems to be handled in the
selection, because . . .
the selection algorithm has to use predefined QoC values for
deactivated context providers.
these predefined properties do not noteworthy reflect the
status of the provider after its activation.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 30
38. Introduction Approach Evaluation Conclusions
Problems during the selection
After activation, QoC values are much worse than predefined
QoC.
Solution:
Update of the predefined QoC values based on historical
values → Good result if QoC properties reflect malfunction of
the provider. Otherwise no improvement.
Ignoring the malfunctioned provider until a significant context
change has happened.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 31
39. Introduction Approach Evaluation Conclusions
Problems during the selection
After activation, QoC values are much worse than predefined
QoC.
Solution:
Update of the predefined QoC values based on historical
values → Good result if QoC properties reflect malfunction of
the provider. Otherwise no improvement.
Ignoring the malfunctioned provider until a significant context
change has happened.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 31
40. Introduction Approach Evaluation Conclusions
Problems during the selection
Additional optional requirement: Cost minimization
Same type of context information requested by different
consumers and with slightly different criteria.
Solution:
1. Check if intersection of matched context offers is nonempty
and if so
2. select context provider with the least cost.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 32
41. Introduction Approach Evaluation Conclusions
Problems during the selection
Additional optional requirement: Cost minimization
Same type of context information requested by different
consumers and with slightly different criteria.
Solution:
1. Check if intersection of matched context offers is nonempty
and if so
2. select context provider with the least cost.
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 32
42. Introduction Approach Evaluation Conclusions
Overview - Binding
Challenges and requirements: Context model and ontology
Exchange and interpretation Discovery and Matching
of context information, QoC Matching Results
and CoC Selection
function
Selection
Context Requests
Context offers
Loose coupling Selection Result
Dynamic discovery Binding
Estimation of QoC Inter Representation
Operation
Data
Data
Dynamic selection Converted Data
Activation and Context Consumer 0..* Context Provider 0..*
deactivation Reasoner 0..*
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 33
43. Introduction Approach Evaluation Conclusions
Evaluation
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 34
44. Introduction Approach Evaluation Conclusions
Demonstrator Meet-U
Planning Offline Navigation At Event
Context as a Service
Michael Wagner Distributed Systems Group University of Kassel 35
45. Introduction Approach Evaluation Conclusions
Demonstrator - Context dependencies
Adaptation decision
based on position, current activity and connectivity status.
Application Business Logic
Navigation mode requires precise position.
Planning mode requires information about current activity,
activity preferences and on current location of friends.
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46. Introduction Approach Evaluation Conclusions
Demonstrator - Context services
Build-in context providers:
Cell-id based location sensor (Low cost, low accuracy)
WiFi based location sensor (Medium cost, medium
accuracy)
GPS based location sensor (High cost, high accuracy)
Connectivity status reasoner
Activity reasoner estimating the activity based on position
and calendar data (Low costs, low accuracy)
Activity reasoner estimating the activity based on
microphone, accelerometers. calendar and position. (High
cost, medium accuracy)
External context provider:
Bluetooth-based location service (Medium costs, high acc.)
RFID-based location service (Low costs, high accuracy)
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47. Introduction Approach Evaluation Conclusions
Evaluation criteria
Questions
Does the approach meet the requirements?
Discovery and matching of context providers
Support for heterogeneous context information
Selection of context providers
Performance and scalability test in a simulator
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48. Introduction Approach Evaluation Conclusions
Conclusions and future work
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49. Introduction Approach Evaluation Conclusions
Conclusions
Abstraction of dynamically appearing and disappearing local
and remote context sensors and reasoners as context services.
Middleware for context-aware self-adaptive applications
supporting the selection of different context services based on
QoC and CoC criteria
Semantic interpretation of heterogeneously represented
context information, QoC and CoC
Flexible access of information in the required representation
and automatic conversions
Support for estimation of QoC of deactivated context
providers
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50. Introduction Approach Evaluation Conclusions
Future work
Very broad research topic with a lot of remaining open issues, e.g.
Privacy and security support (e.g. offering different context
levels based on privacy preferences)
Support for different discovery mechanisms and protocols
MDD support for context providers, consumers and reasoners
...
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Michael Wagner Distributed Systems Group University of Kassel 41
51. Introduction Approach Evaluation Conclusions
Thank you!
Thank you for your interest!
Questions?
Michael Wagner
University of Kassel
T. +49-(0)561-804-6281
eMail: wagner@vs.uni-kassel.de
net: http://www.vs.uni-kassel.de/
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Michael Wagner Distributed Systems Group University of Kassel 42
52. Literature I
Thomas Buchholz, Axel K¨pper, and Michael Schiffers.
u
Quality of context information: What it is and why we need it.
In In Proceedings of the 10th HP-OVUA Workshop, 2003, Geneva, Switzerland, Juli 2003.
Maria Chantzara, Miltiades Anagnostou, and Efstathios Sykas.
Designing a quality-aware discovery mechanism for acquiring context information.
In AINA ’06: Proceedings of the 20th International Conference on Advanced Information Networking and
Applications, pages 211–216, Washington, DC, USA, 2006. IEEE Computer Society.
Markus C. Huebscher and Julie A. McCann.
Adaptive middleware for context-aware applications in smart-homes.
In MPAC ’04: Proceedings of the 2nd workshop on Middleware for pervasive and ad-hoc computing, pages
111–116, New York, NY, USA, 2004. ACM.
Nearchos Paspallis.
Middleware-based development of context-aware applications with reusable components.
PhD thesis, Department of Computer Science, University of Cyprus, Nicosia, Cyprus, 2009.
Roland Reichle.
Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments.
PhD thesis, Distributed Systems Group, University of Kassel, Kassel, Germany, July 2010.
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53. Literature II
Roland Reichle, Michael Wagner, Mohammad Khan, Kurt Geihs, Jorge Lorenzo, Massimo Valla, Cristina
Fra, Nearchos Paspallis, and George Papadopoulos.
A comprehensive context modeling framework for pervasive computing systems.
In Distributed Applications and Interoperable Systems, pages 281–295, 2008.
Roland Reichle, Michael Wagner, Mohammad Ullah Khan, Kurt Geihs, Massimo Valla, Cristina Fra,
Nearchos Paspallis, and George A. Papadopoulos.
A context query language for pervasive computing environments.
In CoMoRea, pages 434–440, Hong Kong, Mar 2008. IEEE Computer Society Press.
Gregor Schiele, Marcus Handte, and Christian Becker.
Pervasive computing middleware.
In Hideyuki Nakashima, Hamid Aghajan, and Juan Carlos Augusto, editors, Handbook of Ambient
Intelligence and Smart Environments, pages 201–227. Springer US, 2010.
Claudia Villalonga, Daniel Roggen, Clemens Lombriser, Piero Zappi, and Gerhard Tr¨ster.
o
Bringing quality of context into wearable human activity recognition systems.
In Kurt Rothermel, Dieter Fritsch, Wolfgang Blochinger, and Frank D¨rr, editors, First International
u
Workshop on Quality of Context (QuaCon 2009), volume 5786 of LNCS, pages 164–173, Stuttgart, June
2009. Springer-Verlag.
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