This document discusses an open IoT testbed and architectural framework. It describes IoT systems as consisting of interconnected devices that can communicate and exchange data. A core component is embedded systems/devices that include sensors to measure the environment and actuators to perform physical actions. Microcontrollers interface with these devices and communicate via various protocols. The document proposes an open IoT testbed with a control plane that can discover resources/services, orchestrate based on user demands, and resolve conflicts through a lock release model. It provides a functional and detailed architecture for the proposed framework.
The document discusses Internet of Things (IoT) network architecture and design. It provides an overview of key aspects of IoT architecture including drivers behind new network architectures, comparing IoT architectures from ETSI and IoT World Forum, and presenting a simplified IoT architecture model. The core IoT functional stack is also explained, covering the things layer, communications network layer, and application and analytics layer. Specific protocols and technologies for each layer are described such as LoRa, CoAP, MQTT, and more.
Internet Of Things(IoT) is emerging technology in future world.The term IoT comprises of Cloud computing, Data mining,
Big data analytics, hardware board. The Security and Interoperability is a main factor that influences the IoT Enegy
consumption is also main fator for IoT application designing.The various protocols such as MQTT,AMQP,XMPP are used in
IoT.This paper analysis the various protocols used in Internet of Things.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document provides an introduction to IoT including definitions and key characteristics. It discusses the four layers of an IoT architecture: sensing, network, data processing, and application. Common IoT protocols at each layer like MQTT, CoAP, and HTTP are also outlined. The document then covers microprocessors, comparing CISC and RISC architectures. Microcontrollers are defined as specialized microprocessors used in embedded systems. ARM is highlighted as a popular architecture for IoT devices due to its low power consumption and integrated components.
IoT ( M2M) - Big Data - Analytics: Emulation and DemonstrationCHAKER ALLAOUI
The document discusses Internet of Things (IoT) concepts including emulation and demonstration of IoT platforms, architectures, and technologies. It provides examples of using sensors, MQTT brokers, Node-Red, and IBM IoT platforms to collect, transmit, and analyze IoT data from devices. Sections include presentations on IoT history and monitoring, as well as emulations of Philips Hue lighting and sensors to demonstrate IoT data collection and control capabilities.
The document discusses the Cortex-A11 multicore processor and its components. It describes the processor's architecture including the snoop control unit, accelerator coherence port, generic interrupt controller, advanced bus interface unit, floating point unit, NEON media processing engine, L2 cache controller, program trace macrocell, and memory management unit. The purpose of these components is to provide efficient performance, low power consumption, and scalability for applications such as mobile devices and infotainment systems.
F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-...Istabraq M. Al-Joboury
Internet of Things (IoT) evolves very rapidly over time, since everything such as sensors/actuators linked together from around the world with use of evolution of ubiquitous computing through the Internet. These devices have a unique IP address in order to communicate with each other and transmit data with features of wireless technologies. Fog computing or so called edge computing brings all Cloud features to embedded devices at edge network and adds more features to servers like pre-store data of Cloud, fast response, and generate overhasty users reporting. Fog mediates between Cloud and IoT devices and thus enables new types of computing and services. The future applications take the advantage of combing the two concepts Fog and Cloud in order to provide low delay Fog-based and high capacity of storage Cloud-based. This paper proposes an IoT architecture for healthcare network based on Fog to Cloud and Data in Motion (F2CDM). The proposed architecture is designed and implemented over three sites: Site 1 contains the embedded devices layer, Site 2 consists of the Fog network layer, while Site 3 consists of the Cloud network. The Fog layer is represented by a middleware server in Al-Nahrain University with temporary storage such that the data lives inside for 30 min. During this time, the selection of up-normality in behavior is send to the Cloud while the rest of the data is wiped out. On the other hand, the Cloud stores all the incoming data from Fog permanently. The F2CDM works using Message Queue Telemetry Transport (MQTT) for fast response. The results show that all data can be monitored from the Fog in real time while the critical data can be monitored from Cloud. In addition, the response time is evaluated using traffic generator called Tsung. It has been found that the proposed architecture reduces traffic on Cloud network and provides better data analysis.
The document discusses Internet of Things (IoT) network architecture and design. It provides an overview of key aspects of IoT architecture including drivers behind new network architectures, comparing IoT architectures from ETSI and IoT World Forum, and presenting a simplified IoT architecture model. The core IoT functional stack is also explained, covering the things layer, communications network layer, and application and analytics layer. Specific protocols and technologies for each layer are described such as LoRa, CoAP, MQTT, and more.
Internet Of Things(IoT) is emerging technology in future world.The term IoT comprises of Cloud computing, Data mining,
Big data analytics, hardware board. The Security and Interoperability is a main factor that influences the IoT Enegy
consumption is also main fator for IoT application designing.The various protocols such as MQTT,AMQP,XMPP are used in
IoT.This paper analysis the various protocols used in Internet of Things.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document discusses providing sensor data as a service. It proposes an event collaboration model where sensor data is pushed to a database when it changes, rather than requiring polling. This would allow users to access up-to-date data through queries. The system would contain various sensors that store data in a database, and provide an interface for users to access visualizations and downloads of the sensor data in different formats like CSV and JSON.
This document provides an introduction to IoT including definitions and key characteristics. It discusses the four layers of an IoT architecture: sensing, network, data processing, and application. Common IoT protocols at each layer like MQTT, CoAP, and HTTP are also outlined. The document then covers microprocessors, comparing CISC and RISC architectures. Microcontrollers are defined as specialized microprocessors used in embedded systems. ARM is highlighted as a popular architecture for IoT devices due to its low power consumption and integrated components.
IoT ( M2M) - Big Data - Analytics: Emulation and DemonstrationCHAKER ALLAOUI
The document discusses Internet of Things (IoT) concepts including emulation and demonstration of IoT platforms, architectures, and technologies. It provides examples of using sensors, MQTT brokers, Node-Red, and IBM IoT platforms to collect, transmit, and analyze IoT data from devices. Sections include presentations on IoT history and monitoring, as well as emulations of Philips Hue lighting and sensors to demonstrate IoT data collection and control capabilities.
The document discusses the Cortex-A11 multicore processor and its components. It describes the processor's architecture including the snoop control unit, accelerator coherence port, generic interrupt controller, advanced bus interface unit, floating point unit, NEON media processing engine, L2 cache controller, program trace macrocell, and memory management unit. The purpose of these components is to provide efficient performance, low power consumption, and scalability for applications such as mobile devices and infotainment systems.
F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-...Istabraq M. Al-Joboury
Internet of Things (IoT) evolves very rapidly over time, since everything such as sensors/actuators linked together from around the world with use of evolution of ubiquitous computing through the Internet. These devices have a unique IP address in order to communicate with each other and transmit data with features of wireless technologies. Fog computing or so called edge computing brings all Cloud features to embedded devices at edge network and adds more features to servers like pre-store data of Cloud, fast response, and generate overhasty users reporting. Fog mediates between Cloud and IoT devices and thus enables new types of computing and services. The future applications take the advantage of combing the two concepts Fog and Cloud in order to provide low delay Fog-based and high capacity of storage Cloud-based. This paper proposes an IoT architecture for healthcare network based on Fog to Cloud and Data in Motion (F2CDM). The proposed architecture is designed and implemented over three sites: Site 1 contains the embedded devices layer, Site 2 consists of the Fog network layer, while Site 3 consists of the Cloud network. The Fog layer is represented by a middleware server in Al-Nahrain University with temporary storage such that the data lives inside for 30 min. During this time, the selection of up-normality in behavior is send to the Cloud while the rest of the data is wiped out. On the other hand, the Cloud stores all the incoming data from Fog permanently. The F2CDM works using Message Queue Telemetry Transport (MQTT) for fast response. The results show that all data can be monitored from the Fog in real time while the critical data can be monitored from Cloud. In addition, the response time is evaluated using traffic generator called Tsung. It has been found that the proposed architecture reduces traffic on Cloud network and provides better data analysis.
This document summarizes the internship work conducted by Marta de la Cruz Martos at CITSEM within the GRyS group. The internship focused on developing algorithms to analyze energy consumption for smart grids as part of the I3RES project, which aims to integrate renewable energy sources into distributed networks using artificial intelligence. Specifically, the internship involved studying relevant technologies, participating in software component design, developing and implementing algorithms, and preparing reports. The document provides background on distributed systems and databases, describes the work conducted, and presents results and conclusions.
The document discusses Grid Computing, which uses distributed computing resources like computer clusters connected via high-speed networks to provide high computational power. It describes the Globus Toolkit, an open-source software toolkit that provides basic services for building Grids. Key components of the Globus Toolkit allow for resource management, security, data management, and communication. The document also discusses parallel programming using MPI (Message Passing Interface) and potential applications of Grid Computing such as distributed supercomputing, real-time systems, and data-intensive processing.
An Event-based Middleware for Syntactical Interoperability in Internet of Th...IJECEIAES
Internet of Things (IoT) connecting sensors or devices that record physical observations of the environment and a variety of applications or other Internet services. Along with the increasing number and diversity of devices connected, there arises a problem called interoperability. One type of interoperability is syntactical interoperability, where the IoT should be able to connect all devices through various data protocols. Based on this problem, we proposed a middleware that capable of supporting interoperability by providing a multi-protocol gateway between COAP, MQTT, and WebSocket. This middleware is developed using event-based architecture by implementing publish-subscribe pattern. We also developed a system to test the performance of middleware in terms of success rate and delay delivery of data. The system consists of temperature and humidity sensors using COAP and MQTT as a publisher and web application using WebSocket as a subscriber. The results for data transmission, either from sensors or MQTT COAP has a success rate above 90%, the average delay delivery of data from sensors COAP and MQTT below 1 second, for packet loss rate varied between 0% - 25%. The interoperability testing has been done using Interoperability assessment methodology and found out that ours is qualified.
IRJET- A Review Paper on Internet of Things(IoT) and its ApplicationsIRJET Journal
This document provides an overview of the Internet of Things (IoT) including its definition, architecture, applications, and advantages/disadvantages. The key points are:
1. IoT allows both things and people to be connected anytime, anywhere through any network or service. It enables communication between machines (M2M).
2. The IoT architecture has two main components - the edge (sensors, devices, gateways) and cloud. Field protocols like Bluetooth, Zigbee, and WiFi enable communication at the edge, while cloud protocols like MQTT, CoAP, and HTTP connect to cloud services.
3. Important applications of IoT discussed are smart homes, farming, healthcare, cities
The Indo-American Journal of Agricultural and Veterinary Sciences is an online international journal published quarterly. It is a peer-reviewed journal that focuses on disseminating high-quality original research work, reviews, and short communications of the publishable paper.
Internet is the networking infrastructure which helps in connecting many users through interconnected networks through which users can communicate to each other. The World Wide Web is built on top of the internet to share information. The grid is again a service that is built on top of internet but is able to share computational power, databases, disk storage and software applications. The paper mainly focuses on significance Grid computing, its architecture, the grid middleware Globus toolkit and wireless grid computing.
Intelligent Internet of Things (IIoT): System Architectures and Communica...Raghu Nandy
Internet of Things (IoT) can be designed by various approaches with optimistic technology choices. This paper focuses on comparing recent studies on architectural choices and communication approaches for IoT Systems. Understanding Goals of an IoT system and inventing a general prototype for general IoT solutions is uniquely challenging. Existing research prototypes provide us information about IoT systems and their challenges. Existing architectures and communication approaches such as such as Service Oriented Architecture (SOA), Instant Messaging (XMPP) and Web-Sockets Service can be used to develop a general IoT System prototype. SOA provides centralized/decentralized IoT systems. Instant Message services such as XMPP can be used to build distributed and secure IoT platforms. Web-sockets also used to build scalable IoT systems. Overall the choice depends on IoT system Goal and limitations. Intelligent IoT (IIoT) Systems can be seen as decision making system. IoT systems can be built on Cloud infrastructures With Sensor Event as a Service (SEaaS) - Cloud Sensor networks can enable applications to access on-demand real-time sensor data. A generic IoT platform can be built and extended to newer applications and platforms.
IRJET- Photogroup: Decentralized Web Application using Ethereum BlockchainIRJET Journal
This document describes a proposed decentralized photo sharing application called Photogroup that is built using blockchain technology. Photogroup allows users to view, like, comment on and share photos in a peer-to-peer network without a central server. It uses Ethereum for the blockchain platform and smart contracts to manage transactions and the addition of new blocks. When a user shares a photo, the transaction is added to the blockchain through smart contracts to ensure the data is distributed and immutable across all nodes. The system aims to provide more security than centralized social networks by avoiding single points of failure and making the data difficult to hack or tamper with.
The Internet of Things has changed the dimensions of traditional Business IT. To tap the potential need for a highly scalable and reliable IT Infrastructure, they should be on standardized components and open protocols and include the three layer Devices, Controllers and Data Center or the Cloud solutions.
Here is the table with the characteristics of the given access technologies:
Access Technology | Wired/Wireless | Frequency Band | Topology | Range | Data Rate
-|-|-|-|-|-
IEEE 802.15.4 | Wireless | 2.4GHz ISM band | Star, Mesh | 10-100m | 20-250 kbps
IEEE 802.15.4g | Wireless | Sub-1GHz ISM bands | Star, Mesh | 100-1000m | 20-250 kbps
IEEE 1901.2a | Wired | Broadband over powerline | Star | Within building | Up to 500 Mbps
IEEE 802.11ah | Wireless | Sub-1GHz ISM bands |
Ant colony Optimization: A Solution of Load balancing in Cloud dannyijwest
As the cloud computing is a new style of computing over internet. It has many advantages along with some
crucial issues to be resolved in order to improve reliability of cloud environment. These issues are related
with the load management, fault tolerance and different security issues in cloud environment. In this paper
the main concern is load balancing in cloud computing. The load can be CPU load, memory capacity,
delay or network load. Load balancing is the process of distributing the load among various nodes of a
distributed system to improve both resource utilization and job response time while also avoiding a
situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work.
Load balancing ensures that all the processor in the system or every node in the network does
approximately the equal amount of work at any instant of time. Many methods to resolve this problem has
been came into existence like Particle Swarm Optimization, hash method, genetic algorithms and several
scheduling based algorithms are there. In this paper we are proposing a method based on Ant Colony
optimization to resolve the problem of load balancing in cloud environment.
This document summarizes a study of latencies in the ThingSpeak IoT platform. The study measured roundtrip times for data packets sent to and received from the ThingSpeak cloud using different access methods: the REST API, MQTT API, and MQTT broker alone. Roundtrip times ranged from 1 to 3 seconds for the REST and MQTT APIs, and were below 250ms for the MQTT broker alone. Uploads generally took longer than downloads. The results provide insights into ThingSpeak's performance and can serve as a reference for other IoT platforms.
IRJET- Secure Scheme For Cloud-Based Multimedia Content StorageIRJET Journal
This document proposes a secure scheme for cloud-based multimedia content storage. It has two novel components: (1) a method to create signatures for 3D videos that captures depth signals efficiently, and (2) a distributed matching engine for multimedia objects that achieves high scalability. The system was implemented and deployed on Amazon and private clouds. Experiments on over 11,000 3D videos and 1 million images showed the system accurately detects over 98% of copies, outperforming YouTube's protection system which fails to detect most 3D video copies. The system provides cost-efficient, scalable multimedia content protection leveraging cloud infrastructure.
IoT-Lite: A Lightweight Semantic Model for the Internet of ThingsPayamBarnaghi
This document presents IoT-Lite, a lightweight semantic model for annotating data in the Internet of Things. IoT-Lite aims to address issues of heterogeneity and interoperability in IoT systems by providing a simple way to semantically describe sensors, actuators, and other devices. It reuses existing models like SSN and defines best practices for annotation. Evaluations show IoT-Lite imposes minimal overhead on data size and query time compared to other semantic models. The goal of IoT-Lite is to make semantic descriptions transparent and easy to implement for both end users and data producers.
Understanding the Information Architecture, Data Management, and Analysis Cha...Cognizant
As the Internet of Things (IoT) becomes increasingly prevalent, organizations must build the enterprise information architecture required to gather, manage, and analyze vast troves of rich real-time data. We offer an IoT framework, use cases, and a maturity model that helps enable you to choose an adoption approach.
The Internet of Things - White paper - version 1.0andrepferreira
The document discusses the Internet of Things (IoT) by providing an overview of the IoT reference model and architecture. It describes a 7-layer reference model that abstracts IoT systems into physical entities, communication layers, and application layers. It also outlines an architecture framework with layers for devices, communications, data aggregation, processing, access, management, and security. Finally, it examines the typical components of an IoT system in more detail, including sensors, actuators, gateways, and applications.
This document provides an overview of the Internet of Things (IoT). It defines IoT as a network of physical objects embedded with software and sensors that allows them to connect and exchange data. Examples of IoT applications are given such as smart homes, healthcare devices, and mobile phones. The need for IoT is discussed in terms of connecting everyday objects to share data with minimal human intervention. An overview of the evolution and growth of IoT is provided from the 1970s to present day. Key characteristics and architectural models of IoT systems are described. Popular technologies that power IoT such as hardware, communication protocols, and cloud platforms are outlined. Development tools for building IoT solutions like Arduino, Raspberry Pi, and Eclipse
This document discusses the need for an open source IoT development environment and testbed to allow software developers to create IoT applications without requiring hardware expertise. It notes that existing IoT testbeds often use proprietary hardware and software, limiting interoperability. The proposed solution aims to provide virtual access to sensors and actuators through an API, as well as a microcontroller platform as a service. This would allow developers to write code without worrying about hardware integration and deployment details. The goal is to make IoT development and testing more accessible through an open testbed that addresses issues like sensor availability and cost.
The document discusses the design and implementation of an Internet of Things (IoT) testbed framework with an enhanced performance approach. It aims to create an open IoT testbed that is accessible locally and over the internet for developers to create and test IoT applications and for data engineers to perform analytics on generated data. The testbed will host a range of sensors and be able to interface with microcontrollers like Arduino and Raspberry Pi to account for heterogeneous devices. It seeks to address challenges with proprietary systems like vendor lock-in and provide solutions for insufficient control, lack of concurrency, and diminished reusability.
This document summarizes the internship work conducted by Marta de la Cruz Martos at CITSEM within the GRyS group. The internship focused on developing algorithms to analyze energy consumption for smart grids as part of the I3RES project, which aims to integrate renewable energy sources into distributed networks using artificial intelligence. Specifically, the internship involved studying relevant technologies, participating in software component design, developing and implementing algorithms, and preparing reports. The document provides background on distributed systems and databases, describes the work conducted, and presents results and conclusions.
The document discusses Grid Computing, which uses distributed computing resources like computer clusters connected via high-speed networks to provide high computational power. It describes the Globus Toolkit, an open-source software toolkit that provides basic services for building Grids. Key components of the Globus Toolkit allow for resource management, security, data management, and communication. The document also discusses parallel programming using MPI (Message Passing Interface) and potential applications of Grid Computing such as distributed supercomputing, real-time systems, and data-intensive processing.
An Event-based Middleware for Syntactical Interoperability in Internet of Th...IJECEIAES
Internet of Things (IoT) connecting sensors or devices that record physical observations of the environment and a variety of applications or other Internet services. Along with the increasing number and diversity of devices connected, there arises a problem called interoperability. One type of interoperability is syntactical interoperability, where the IoT should be able to connect all devices through various data protocols. Based on this problem, we proposed a middleware that capable of supporting interoperability by providing a multi-protocol gateway between COAP, MQTT, and WebSocket. This middleware is developed using event-based architecture by implementing publish-subscribe pattern. We also developed a system to test the performance of middleware in terms of success rate and delay delivery of data. The system consists of temperature and humidity sensors using COAP and MQTT as a publisher and web application using WebSocket as a subscriber. The results for data transmission, either from sensors or MQTT COAP has a success rate above 90%, the average delay delivery of data from sensors COAP and MQTT below 1 second, for packet loss rate varied between 0% - 25%. The interoperability testing has been done using Interoperability assessment methodology and found out that ours is qualified.
IRJET- A Review Paper on Internet of Things(IoT) and its ApplicationsIRJET Journal
This document provides an overview of the Internet of Things (IoT) including its definition, architecture, applications, and advantages/disadvantages. The key points are:
1. IoT allows both things and people to be connected anytime, anywhere through any network or service. It enables communication between machines (M2M).
2. The IoT architecture has two main components - the edge (sensors, devices, gateways) and cloud. Field protocols like Bluetooth, Zigbee, and WiFi enable communication at the edge, while cloud protocols like MQTT, CoAP, and HTTP connect to cloud services.
3. Important applications of IoT discussed are smart homes, farming, healthcare, cities
The Indo-American Journal of Agricultural and Veterinary Sciences is an online international journal published quarterly. It is a peer-reviewed journal that focuses on disseminating high-quality original research work, reviews, and short communications of the publishable paper.
Internet is the networking infrastructure which helps in connecting many users through interconnected networks through which users can communicate to each other. The World Wide Web is built on top of the internet to share information. The grid is again a service that is built on top of internet but is able to share computational power, databases, disk storage and software applications. The paper mainly focuses on significance Grid computing, its architecture, the grid middleware Globus toolkit and wireless grid computing.
Intelligent Internet of Things (IIoT): System Architectures and Communica...Raghu Nandy
Internet of Things (IoT) can be designed by various approaches with optimistic technology choices. This paper focuses on comparing recent studies on architectural choices and communication approaches for IoT Systems. Understanding Goals of an IoT system and inventing a general prototype for general IoT solutions is uniquely challenging. Existing research prototypes provide us information about IoT systems and their challenges. Existing architectures and communication approaches such as such as Service Oriented Architecture (SOA), Instant Messaging (XMPP) and Web-Sockets Service can be used to develop a general IoT System prototype. SOA provides centralized/decentralized IoT systems. Instant Message services such as XMPP can be used to build distributed and secure IoT platforms. Web-sockets also used to build scalable IoT systems. Overall the choice depends on IoT system Goal and limitations. Intelligent IoT (IIoT) Systems can be seen as decision making system. IoT systems can be built on Cloud infrastructures With Sensor Event as a Service (SEaaS) - Cloud Sensor networks can enable applications to access on-demand real-time sensor data. A generic IoT platform can be built and extended to newer applications and platforms.
IRJET- Photogroup: Decentralized Web Application using Ethereum BlockchainIRJET Journal
This document describes a proposed decentralized photo sharing application called Photogroup that is built using blockchain technology. Photogroup allows users to view, like, comment on and share photos in a peer-to-peer network without a central server. It uses Ethereum for the blockchain platform and smart contracts to manage transactions and the addition of new blocks. When a user shares a photo, the transaction is added to the blockchain through smart contracts to ensure the data is distributed and immutable across all nodes. The system aims to provide more security than centralized social networks by avoiding single points of failure and making the data difficult to hack or tamper with.
The Internet of Things has changed the dimensions of traditional Business IT. To tap the potential need for a highly scalable and reliable IT Infrastructure, they should be on standardized components and open protocols and include the three layer Devices, Controllers and Data Center or the Cloud solutions.
Here is the table with the characteristics of the given access technologies:
Access Technology | Wired/Wireless | Frequency Band | Topology | Range | Data Rate
-|-|-|-|-|-
IEEE 802.15.4 | Wireless | 2.4GHz ISM band | Star, Mesh | 10-100m | 20-250 kbps
IEEE 802.15.4g | Wireless | Sub-1GHz ISM bands | Star, Mesh | 100-1000m | 20-250 kbps
IEEE 1901.2a | Wired | Broadband over powerline | Star | Within building | Up to 500 Mbps
IEEE 802.11ah | Wireless | Sub-1GHz ISM bands |
Ant colony Optimization: A Solution of Load balancing in Cloud dannyijwest
As the cloud computing is a new style of computing over internet. It has many advantages along with some
crucial issues to be resolved in order to improve reliability of cloud environment. These issues are related
with the load management, fault tolerance and different security issues in cloud environment. In this paper
the main concern is load balancing in cloud computing. The load can be CPU load, memory capacity,
delay or network load. Load balancing is the process of distributing the load among various nodes of a
distributed system to improve both resource utilization and job response time while also avoiding a
situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work.
Load balancing ensures that all the processor in the system or every node in the network does
approximately the equal amount of work at any instant of time. Many methods to resolve this problem has
been came into existence like Particle Swarm Optimization, hash method, genetic algorithms and several
scheduling based algorithms are there. In this paper we are proposing a method based on Ant Colony
optimization to resolve the problem of load balancing in cloud environment.
This document summarizes a study of latencies in the ThingSpeak IoT platform. The study measured roundtrip times for data packets sent to and received from the ThingSpeak cloud using different access methods: the REST API, MQTT API, and MQTT broker alone. Roundtrip times ranged from 1 to 3 seconds for the REST and MQTT APIs, and were below 250ms for the MQTT broker alone. Uploads generally took longer than downloads. The results provide insights into ThingSpeak's performance and can serve as a reference for other IoT platforms.
IRJET- Secure Scheme For Cloud-Based Multimedia Content StorageIRJET Journal
This document proposes a secure scheme for cloud-based multimedia content storage. It has two novel components: (1) a method to create signatures for 3D videos that captures depth signals efficiently, and (2) a distributed matching engine for multimedia objects that achieves high scalability. The system was implemented and deployed on Amazon and private clouds. Experiments on over 11,000 3D videos and 1 million images showed the system accurately detects over 98% of copies, outperforming YouTube's protection system which fails to detect most 3D video copies. The system provides cost-efficient, scalable multimedia content protection leveraging cloud infrastructure.
IoT-Lite: A Lightweight Semantic Model for the Internet of ThingsPayamBarnaghi
This document presents IoT-Lite, a lightweight semantic model for annotating data in the Internet of Things. IoT-Lite aims to address issues of heterogeneity and interoperability in IoT systems by providing a simple way to semantically describe sensors, actuators, and other devices. It reuses existing models like SSN and defines best practices for annotation. Evaluations show IoT-Lite imposes minimal overhead on data size and query time compared to other semantic models. The goal of IoT-Lite is to make semantic descriptions transparent and easy to implement for both end users and data producers.
Understanding the Information Architecture, Data Management, and Analysis Cha...Cognizant
As the Internet of Things (IoT) becomes increasingly prevalent, organizations must build the enterprise information architecture required to gather, manage, and analyze vast troves of rich real-time data. We offer an IoT framework, use cases, and a maturity model that helps enable you to choose an adoption approach.
The Internet of Things - White paper - version 1.0andrepferreira
The document discusses the Internet of Things (IoT) by providing an overview of the IoT reference model and architecture. It describes a 7-layer reference model that abstracts IoT systems into physical entities, communication layers, and application layers. It also outlines an architecture framework with layers for devices, communications, data aggregation, processing, access, management, and security. Finally, it examines the typical components of an IoT system in more detail, including sensors, actuators, gateways, and applications.
This document provides an overview of the Internet of Things (IoT). It defines IoT as a network of physical objects embedded with software and sensors that allows them to connect and exchange data. Examples of IoT applications are given such as smart homes, healthcare devices, and mobile phones. The need for IoT is discussed in terms of connecting everyday objects to share data with minimal human intervention. An overview of the evolution and growth of IoT is provided from the 1970s to present day. Key characteristics and architectural models of IoT systems are described. Popular technologies that power IoT such as hardware, communication protocols, and cloud platforms are outlined. Development tools for building IoT solutions like Arduino, Raspberry Pi, and Eclipse
This document discusses the need for an open source IoT development environment and testbed to allow software developers to create IoT applications without requiring hardware expertise. It notes that existing IoT testbeds often use proprietary hardware and software, limiting interoperability. The proposed solution aims to provide virtual access to sensors and actuators through an API, as well as a microcontroller platform as a service. This would allow developers to write code without worrying about hardware integration and deployment details. The goal is to make IoT development and testing more accessible through an open testbed that addresses issues like sensor availability and cost.
The document discusses the design and implementation of an Internet of Things (IoT) testbed framework with an enhanced performance approach. It aims to create an open IoT testbed that is accessible locally and over the internet for developers to create and test IoT applications and for data engineers to perform analytics on generated data. The testbed will host a range of sensors and be able to interface with microcontrollers like Arduino and Raspberry Pi to account for heterogeneous devices. It seeks to address challenges with proprietary systems like vendor lock-in and provide solutions for insufficient control, lack of concurrency, and diminished reusability.
The document lists 57 references related to the Internet of Things (IoT). It covers topics such as the evolution of wireless sensor networks towards IoT, future directions for IoT, clustering techniques in wireless sensor networks, applications of wireless sensors, deployment algorithms for sensor networks, energy efficient routing protocols, performance of sensor network motes, adding value to sensor network simulations, overviews and definitions of IoT, enabling technologies and protocols for IoT, applications of IoT such as smart cities and healthcare, security and privacy issues in IoT, IoT testbeds and experimental platforms, middleware for IoT, and data analytics and management for large-scale IoT systems.
This document contains a list of 7 tables across 4 chapters. The tables summarize the differences between CoAP and MQTT protocols, propose a service mapping scheme, provide examples of data formats and sample sensor readings, perform a scenario-based comparison and measure service performance, reliability, and demand through various matrices and probability functions. The tables collectively analyze IoT service architectures, communication protocols, data generation and usage.
This document contains a list of 7 tables across 4 chapters. The tables summarize the differences between CoAP and MQTT protocols, propose a service mapping scheme, provide examples of data formats and sample sensor readings, perform a scenario-based comparison and analyze services feedback through various matrices to measure performance, reliability, and demand.
The document contains the declaration by Kayalvizhi Jayavel that the work presented in her thesis titled "DESIGN AND IMPLEMENTATION OF INTERNET OF THINGS TESTBED FRAMEWORK- A PERFORMANCE ENHANCED APPROACH" was carried out by her under the supervision of Dr. Revathi Venkataraman. She declares that the work has not been submitted for any other degree and that she has properly cited any works of other researchers that were referenced. Dr. Revathi Venkataraman certifies that the candidate's statements are correct and that a plagiarism check found the thesis contents to be free of plagiarism.
The document discusses providing actuator and sensor access as a service over the internet. It proposes an algorithm for resource requisition that creates locks on actuator instances to prevent multiple simultaneous requests. This ensures actuators can only respond to one command at a time. The algorithm also analyzes request volume to optimize traffic to unavailable resources. An API is developed to abstract away hardware details and provide platform-independent parameter retrieval and actuation. This allows developers to focus on application logic rather than hardware integration.
This document provides a list of 57 references related to the Internet of Things (IoT). The references cover topics such as the evolution of wireless sensor networks towards IoT, future Internet and IoT, clustering techniques in wireless sensor networks for IoT scenarios, civil applications of wireless sensors, deployment algorithms for coverage and connectivity in wireless sensor networks, energy efficient routing techniques for wireless sensor networks, performance analysis of sensor motes used in wireless sensor networks, adding value to wireless sensor network simulations using experimental IoT platforms, overviews of IoT, data fusion and IoT for smart environments, challenges of waste management in IoT-enabled smart cities, enabling IoT technologies and protocols, IoT gateways, semantics for IoT,
The document summarizes a research project that designed and implemented an open IoT testbed framework. The framework includes modules for sensor data, actuators, and APIs. It uses open source platforms to achieve interoperability, scalability, and reusability. Algorithms for code compilation and upload showed improved performance even with increased code size. Response times for remote sensors and actuators were only mildly increased compared to local access. A ranking model tested proved able to recommend the best services for different user types. The testbed was found to satisfactorily utilize resources based on user feedback. Future work could extend it to support mobile devices, include security software, test it with more users, and explore other statistical models.
This document contains the declaration by Kayalvizhi Jayavel that the work presented in her thesis titled "Design and Implementation of Internet of Things Testbed Framework- A Performance Enhanced Approach" was carried out by her under the supervision of Dr. Revathi Venkataraman. She declares that the work has not been submitted for any other degree and that she has properly cited all sources. Dr. Revathi Venkataraman certifies that the candidate's statements are correct and that a plagiarism check found the thesis contents to be within permissible limits.
This document contains a list of abbreviations and symbols used in the paper. It includes over 50 common abbreviations related to Internet of Things, wireless sensor networks, communication protocols, and more. It also defines several symbols used to represent concepts in the paper such as sensors, actuators, platforms, reliability, and various users.
The document discusses analyzing testbed utilization through a feedback-based ranking system. It proposes an algorithm that ranks services based on user feedback scores. Services are initially given a high score of 1, which gets replaced by the new user feedback score after each usage. The algorithm aims to enhance testbed utilization, performance, reliability and usability by allocating the highest ranked services to users. An analysis of 500 users' feedback on various services shows the testbed was reliable even when feedback scores were moderate, accurately predicting user satisfaction over 86% of the time. The most demanded services and combination of services and users are also identified to guide testbed scalability.
The document contains a list of 15 figures referenced throughout a thesis on an IoT testbed architecture. Figure 1.1-1.6 describe common sensors and components used in IoT systems. Figures 3.1-3.9 illustrate the proposed testbed architecture and performance results. Figures 4.1-4.14 provide details on the sensor database design and experimental setup. Figures 5.1-5.16 demonstrate the actuator client, platform as a service prototype, APIs, and performance comparisons. Figures 6.1-6.5 analyze service allocation strategies and expected usage patterns by user types.
The document contains a list of 15 figures referenced throughout a thesis on an IoT testbed architecture. Figure 1.1-1.6 describe common sensors and components used in IoT systems. Figures 3.1-3.9 illustrate the proposed testbed architecture and performance results. Figures 4.1-4.14 provide details on the sensor database design and experimental setup. Figures 5.1-5.16 demonstrate the actuator client, platform as a service prototype, API functions and performance tests. Figures 6.1-6.5 analyze the resource allocation and usage patterns for different user types.
This document provides an introduction to Internet of Things (IoT) testbeds. It discusses that testbeds help validate research findings through real experimental setups, as opposed to simulations alone. IoT is described as an extension of wireless sensor networks, but with some prominent differences that demand exclusive IoT testbed models. The document outlines key IoT concepts like ingredients, features, and characteristics. It emphasizes the need for open source IoT testbeds to improve reusability, scalability, and utilization compared to existing proprietary testbeds primarily designed for wireless sensor networks. The goal of this research is to develop an open source heterogeneous IoT testbed framework with enhanced algorithms.
This document contains lists of abbreviations and symbols used throughout a paper on Internet of Things. There are over 50 abbreviations for concepts, protocols, and technologies related to IoT listed, such as IoT, WSN, MQTT, CoAP, HTTP, and more. There are also over 20 symbols defined for variables, parameters, and mathematical terms used in equations and formulas relating to reliability, performance, and probability distributions for IoT systems.
The document proposes a feedback-based ranking system to maximize utilization of a testbed. It develops an algorithm that initially assigns all platforms a high score of 1, then updates scores based on user feedback. A decision tree is used to select the highest-scoring available platform for the next user. Data from 500 users on service quality is analyzed to evaluate the testbed's reliability when user feedback scores differ from actual performance logs. Statistical analysis shows the testbed reliably performed at a moderate or high level even when user feedback scores were low or moderate, demonstrating high utilization.
The document summarizes a research project that designed and implemented an open IoT testbed framework. The framework includes modules for sensor data, actuators, and APIs. It uses open source platforms to achieve interoperability, scalability, and reusability. Algorithms for code compilation and upload showed improved performance even with increased code size. Response times for remote sensors and actuators were only mildly increased compared to local access. A ranking model tested proved able to recommend the best services for different user types. The testbed was found to satisfactorily utilize resources based on performance and reliability feedback. Future work could extend the framework to mobile devices, add security software, test with more users, and explore other statistical models.
This document discusses an open IoT testbed and architectural framework. It describes IoT systems as consisting of interconnected devices that can communicate and exchange data. A core component is embedded systems/devices that include sensors to measure the environment and actuators to perform physical actions. Microcontrollers interface with these devices and communicate via various protocols. The document proposes an open IoT testbed with a control plane that can discover resources/services, orchestrate based on user demands, and resolve conflicts through a lock release model. It provides a functional and detailed architecture for the proposed framework.
This document summarizes existing IoT testbed frameworks and identifies gaps. It describes the proposed research which aims to address these gaps by developing an open IoT testbed that offers sensors, actuators, platforms and APIs as interoperable services. The testbed would improve on existing approaches by standardizing data formats, optimizing data collection and handling errors. It explores publishing sensor data using a message broker to reduce dependencies and learning curves.
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chapter 3.pdf
1. 26
CHAPTER 3
OPEN IoT TESTBED- UTILITY
IoT is a system of interconnected things that can communicate with each other
to interact and exchange data. IoT aims at connecting anything, anytime and anywhere
in the world. In 2013, the Global Standards Initiative on Internet of Things (IoT-GSI)
defined the IoT as "the infrastructure of the information society" [100].
A typical information processing system of today’s world consists of one or
more inputs, an application to process the input into the output of the system, and can
also communicate with other such systems. Figure 3.1 is a typical information
processing system.
Figure 3.1 A typical information processing system
A core component of an IoT system is the underlying embedded system/device.
These embedded systems include sensors that are used to measure physical parameters
of the environment such as temperature, light intensity, humidity, etc., or user
interactive inputs such as push buttons or potentiometers, etc., The sensors can be
digital or analog. Outputs include actuators, devices that can perform physical actions
such as emitting light as in the case of a LED, or producing wind as in the case of a fan,
etc., The actuators usually digital, but many of them do support analog operations via
Pulse Width Modulation (PWM).
2. 27
3.1 BACKGROUND
The processing unit of these systems is microcontrollers. The sensors, actuators
and the communication devices are interfaced with the microcontrollers and the
application code is flashed onto the microcontroller. The entire processing can be done
by the microcontroller itself or it can simply send data to an aggregator, which gets the
data from multiple sources, and the application is deployed on the aggregator. The
aggregator is usually a high-powered microcontroller or a microcomputer. One
important fact to keep in mind is that these microcontrollers are highly resource
constrained devices. Resources such as the computational power, the memory, etc., are
constrained on these microcontrollers. They can be in the form of motes, which are
proprietary and user/owner specific, or they can be open source platforms such as the
Arduino [101], which are not proprietary. The open source platforms benefit from a
large community support and are preferred over the proprietary boards. They have
libraries being developed for different sensors, actuators and communication devices.
SimpleDHT.h, LiquidCrystal.h and Ethernet.h are a few of the many libraries available
to use, developed for the Arduino platform.
IoT systems use a range of communication protocols. The systems can
communicate with each other via protocols such as Ethernet [102], Wi-Fi [103],
Bluetooth Low Energy [104], ZigBee [63], Radio Waves, to name a few. Typical
application protocols developed for the internet include HTTP [105], HTTPS [106],
FTP [107], Telnet [108], etc., These protocols are highly resource intensive and are not
best suited for resource constrained devices which are usually used in IoT systems.
There are several application level protocols developed for IoT systems, two
major protocols are Constrained Application Protocol (CoAP) [109] and Message
Queuing Telemetry and Transport (MQTT) [110]. CoAP works on a client server model
and is thus synchronous in nature. MQTT works on a publish subscribe model and the
communication is thus asynchronous in nature. Differences between the two protocols
are tabulated in Table 3.1.
The architecture proposed in this research work uses the MQTT protocol for
data transfer. This protocol requires a protocol broker to manage the data transfer
between the clients. Multiple clients can publish data to a MQTT protocol broker at a
3. 28
time and multiple clients can subscribe to the broker for the same data at the same time.
The protocol uses topics, a client will publish a message on a topic and all the clients
that are subscribed to the same topic will receive the message at the same time.
Table 3.1 Difference between CoAP And MQTT protocols
CoAP MQTT
Model Request/Response
(Synchronous)
Publish/Subscribe
(Asynchronous)
Creator IETF IBM
Abbreviation Constrained Application
Protocol
Message Queue Telemetry
Transport
Transport Layer UDP TCP
Security DTLS TLS/SSL
Mode of operation Client should request for an
update to the server
The client receive updates
automatically on those topics
to which it is subscribed with
the broker
Merits Light weight (due to UDP).
Less overhead is required
for reliability
Lower network bandwidth
utilization.
Less message processing,
saving battery life.
Security achieved through
username/password at broker
via TLS/SSL
Less packet loss achieved by
TCP retransmission
Demerits No native security.
Likely more loss of packets.
Some overhead due to the
underlying TCP protocol
Figure 3.2 shows a basic IoT architecture. P. Fremantle has provided similar
architecture [96] level detailing of IoT. A typical IoT system comprises of many input
and output devices. The input devices can be of analog or digital. The system has to do
4. 29
necessary conversions if there is incompatibility in its support. It becomes pretty
obvious, that having connected with so many input devices, the amount of data that
pool in exceedingly high. Mechanisms need to be incorporated to handle such
scenarios. With the advent of technologies like big data and cloud in collaboration with
IoT is becoming a reality. There can be varied mechanisms with which a researcher or
academician or industrialist would handle or process the data. The goal is to reduce
his/her burden to understand the underlying infrastructure and provide it abstracted as
he or she can focus on the research/business logic at hand. Even if they did develop and
implement these systems on their own, they would have to repeat it for different
locations or different scenarios and this would result in an unnecessary learning curve
that they would have to go through.
Figure 3.2 Basic IoT architecture
This proposal provides a solution for this problem by providing the dynamic
sensor data as service, resolves actuator conflicts through the proposed algorithm, offers
dynamic resource discovery and mapping through control plane driven architecture.
5. 30
3.2 PROPOSED OPEN IoT ARCHITECTURAL FRAMEWORK
Building reliable IoT based technology solutions and services that can be
deployed at scale require adequate experimentation environments. Testbeds are
preferred tools to validate research contributions and to provide platform for
development. They provide remote access to test technological solutions and there by
validate. Most of the existing IoT testbeds are extension attempt towards IoT, not native
IoT testbeds.
Figure 3.3 Proposed testbed architecture
Most of the existing testbeds are local and proprietary testbeds, which are used
by industries [111] for their product testing purposes. The academics do have testbeds
for their testing on new protocols they develop, but they too are localized. Few testbeds
are available which can be accessed remotely, but they are platform and language
dependent, free style third party development not available. Most importantly all that
6. 31
which are available are made with tech-savvy or developers in mind, what if an end
user wants a small modified application to be deployed and tested, such a simplified
composition layer is still missing. Free available APIs which can be used by everyone
irrespective of their skill sets is yet in its infancy and also the modality (methodology
used to communicate like: HTTP, TCP model) used favors much of a traditional
systems, which will definitely be heavy on constrained things which is addressed in
IoT. In order to address the above issues, this research work proposes an open IoT
testbed cum development environment with a control plane capable of discovering
resources/services, orchestrate based on user demands, communicate through pub-sub
model, resolve conflicts and interference through lock release model. Figure 3.3 is the
architectural framework of the proposed testbed.
3.2.1 Implementation of Solution
Figure 3.4a Functional architecture of the proposed open IoT architectural
framework
A utility is a composition of services which are offered in controlled manner.
The proposed research work is to design a control plane which is capable of
7. 32
resource/service discovery, orchestration and resolving conflict. Figure 3.4a illustrates
the functional architecture of the proposed open IoT architectural framework.
Resources refer to boards and the sensors and actuators connected to it. These
underlying resources are discovered and the data generated from them or their
functionality is offered as service. Once the above phase of discovery is over, the system
is ready to accept and cater user demands at run time.
Figure 3.4b Detailed architecture of the proposed open IoT architectural
framework
8. 33
The needed user interface is designed which receives user demands and
communicates to the underlying control plane orchestration service to decide on the
availability mapping. Virtualizing actuator is never the same as sensor. A sensor can be
virtualized and the data can be shared to all without due interference. Such is not the
case with actuators. In case of actuators, they can receive commands, what if multiple
users issue multiple commands to a single actuator. This needs to be resolved. This is
resolved by the control plane’s conflict resolve module. This proposed framework is
designed along with an API capable of reserving and releasing locks. The proposed
system has shown better utilization after the incorporation of this API at the control
plane.
The detailed architecture of the proposed architectural framework in Figure 3.4b
provides with particulars dissected at each layer. The users have been broadly classified
as academician, naive user, industrialist, analyst and researcher. The classification is
arrived based on the most probable clients of the testbed. The services provided can be
used by each user depending on their application needs and requirements. The services
offered can be categorized as sensor, actuator, platform and API. The operations that
can be performed on or using each of the services vary based on the potential and
capability offered by the service. For instance, read from sensor, write command on to
actuator, read, write and execute on a platform and API can be downloaded,
incorporated and executed. Now having said this, there should be a module that
discovers the available services, maps it appropriately with demands of the users,
resolve conflict if needed. Thus to achieve this, the control plane offers three main
services discovery, orchestrate and conflict resolve. This is achieved using underlying
blocks namely registration, provisioning, conflict resolve, persistence and application
data transmission. Service discovery involves two phases namely registration of
services in the testbed and provisioning. This is achieved using an automated polling
model to develop a look up table of available services. Then the provisioning model
inspects the user requests and maps appropriately with the available services. If the
service demanded is actuator, then the same procedure is followed along with the
conflict resolve which determines, the service to be offered to one among many requests
using lock and release model. In case of sensor as service, it is proposed to optimize the
service based on time stamping and change capture. The database queried is updated
only on change as to reduce the unnecessary traffic and the sensor is not queried every
9. 34
time a request arises. This provides substantial performance improvement compared to
query every request model. This is taken care of by the persistence block. The
application data transmission takes care of data being retrieved and offered to user in
the data format demanded by the user. There are logical layers that do the magical
integration between the user end and the control plane blocks. The status reflects the
availability to the user of the underlying services, time slot booking etc., Also there is
a parameter block which comes handy in case of double service offered by single sensor
say humidity and temperature measured from a single DHT11. In this proposed
research, it is not addressed as a single service instead as two independent services for
optimized performance.
3.2.1.1 Resource Discovery
Resource/Service discovery: Resources refer to boards and the sensors and
actuators connected to it. These underlying resources are discovered and the data
generated from them or their functionality is offered as service. In existing systems
there is fixed set up of resources which user has to access from the user interface portal
[112]. No research has reported yet on automated resource/service discovery on the
dynamic addition of sensors/ actuators. The resource discovery layer in the proposed
architecture is capable of finding the resources newly added and update without human
intervention to the user interface. This has improved the overall performance and
availability of the proposed testbed in the user’s point of view.
3.2.1.2 Orchestration
After the completion of discovery phase, the system is ready to accept requests
from users. The interface behaves as a communication link between the user commands
and the underlying resources. The interface talks to the underlying orchestration control
plane which does the final availability check and mapping. The orchestrator is a script
which runs every time the user request reaches the interface. The sole purpose of
orchestrator is to avoid unnecessary requests reaching the underlying layers. If not taken
care of, there will be wastage of precious computational resource and energy. An
empirical result showed that a device can generate around 18000 requests per second.
The point to be noted is that the ratio of availability vs. requests is alarmingly less. Thus
this proposed orchestrator layer will provide optimized mapping eliminating or in other
10. 35
words filtering out unnecessary requests to travel down the other layers.
3.2.1.3 Resource Conflict
Virtualizing the actuator is a bit challenging when compared to virtualizing the
sensors. The reading from the sensor can be shared across multiple users without the
issue of interference. The only concern would be the format of data demanded by the
user. In this research work, appropriate scripts have been developed and incorporated
which is capable of converting to any standard format needed for transfer. XML, JSON,
CSV are the available data formats, a user can choose from. The case with actuator is
being an output device, it receives commands from outside. The real challenge is when
multiple commands are targeted to available actuators. There are decisions needed as
how many actuators are available, which command to be given to which actuator etc.,
Half of this problem is already addressed by the resource discovery and orchestration
layer as to provide availability and instances. Moreover, an actuator under use and the
time it is available for next usage also needs to be known. This research proposal also
proposes API’s exclusively for lock and release. This keeps track of which user, which
actuator and when it is released. This history also helps to filter out unnecessary
requests to the same actuator, thereby resolving conflict. The proposed system has
shown improved performance after the incorporation of this API at the control plane.
3.3 RESULTS AND DISCUSSION
The resource discovery provides the available resources in the testbed. The
resources can be accessed through the service list provided in Figure 3.5. The
underlying protocol adopted is MQTT with Mosquito as the protocol broker. It follows
publish- subscribe model which works with topics. But in the proposed system, a
mapping scheme is created as shown in Table 3.2.
11. 36
Figure 3.5 Consolidated service set
Table 3.2 Proposed service mapping scheme
Category ID Resource Sub-Resource ID
Instance
ID
REST Mapping
ID
(Hex)
Data 1 Sensor Temperature 1 NA GET 0001
Humidity 2 NA GET 0001
Gas leakage 3 NA GET 0001
Rainfall detection 4 NA GET 0001
Color 5 NA GET 0001
Actuation 2 Actuator Buzzer 1 1…n GET/POST 0101
LCD Display 2 1…n GET/POST 0101
Fan 3 1…n GET/POST 0101
GSM 4 1…n GET/POST 0101
RGB LED 5 1…n GET/POST 0101
Code port 3 Platform Arduino 1 1…n GET/PUT/POST 0111
Galileo 2 1…n GET/PUT/POST 0111
Pi 3 1…n GET/PUT/POST 0111
Software 4 API Sensor 1…n NA GET/PUT/POST/
DOWNLOAD
1111
Actuator 1…n NA GET/PUT/POST/
DOWNLOAD
1111
12. 37
This scheme provides saving in memory when compared to the traditional string
based approach. Thus for instance the topic iottestbed/dht11/+/humidity will reduce to
<~/1.1.1.2>. The “+” is the service specific ID which helps identify the root of the
parameter. Thus the proposed mapping scheme takes far less memory compared to the
generic topic based approach. The reason being obvious with string stored in heap and
integer stored right at stack along with the memory allotted for each character makes
the string based topic more memory hungry compared to the proposed approach. Thus
this approach takes 8 bytes, whereas string delegated as character array may occupy
~27 to 30 bytes neglecting the language specific details like class pointers, flags, locks,
hash, offset and size.
Thus, Pc=(Be-Bp)/Be*100=~70%,
where, Pc is percentage change in memory requirement, Be is bytes for existing
models, Bp is bytes for proposed model.
Figure 3.6a is the output showing the boards discovered. Figure 3.6b is the
screen shot showing the result of the script exposing the gas, rainfall and temperature
sensors being active and ready to be offered as service to users/developers/analysts.
Figure 3.6a-3.6b: Boards discovered as resources; Screenshot of sensor resource
discovery
The details acquired are updated in the database for orchestrator to map based
on user needs and resource availability. The screen shot in Figure 3.7 shows the status
of gas sensor on two respective boards.
Figure 3.7 Screenshot of database update
13. 38
The time taken by the resource/service discovery module to explore the
underlying sensor/actuator clients, sensors/actuators is provided in Figure 3.8a-3.8c.
Figure 3.8a illustrates that the time involved to detect the sensor/actuator clients
resource is not greater than 8ms. Though this is an overhead, this helps to achieve
efficient resource discovery and orchestration in the proposed research claim. The
experiment was conducted with 100 trials.
Figure 3.8a: Sensor/actuator clients detection time
Figure 3.8b significantly illustrates the time taken to detect the underlying
sensor/actuator resource is not greater than 2.5s. This is the extra cost incurred in order
to achieve efficient resource discovery and mapping. The experiment was conducted
with 100 trials.
Figure 3.8b: Sensor/actuator detection time
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0 20 40 60 80 100
Time
(s)
Trial
Time (s)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
0 20 40 60 80 100 120
Time
(s)
Trial
Time (s)
14. 39
Figure 3.8c signifies the time taken to detect the disconnected sensor/actuator
resource. The time measured is not more than 6ms. This cost is tradeoff with
unnecessary requests aimed at a non-existing service. The experiment was conducted
with 100 trials.
Figure 3.8c: Disconnected sensor/actuator time
Figure 3.9 shows the user request hit ratio. The system is tested with and without
lock of actuator instances. The graph clearly illustrates that proposed system
outperforms in the request hit ratio compared to the systems without dynamic update
of resources using lock and release in which case there is a clear degradation of hit ratio
on increasing request rates.
Figure 3.9: User request hit ratio
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0 20 40 60 80 100
Time
(s)
Trial
Time (s)
0%
20%
40%
60%
80%
100%
120%
0 25 50 75 100
Response
Rate
(%)
Trial (User Request)
Hit Ratio (without
Lock_Release)
Hit Ratio (With
Lock_Release)
15. 40
The reason for the degradation of hit ratio can be justified with an example.
Assume there is one actuator service. There is no way in existing systems the user is
updated of the available and under use service, due to which there will be n requests of
which only one gets served. This is mitigated in this work, through lock acquire and
update, based on which no unwanted requests are initiated thereby. The results
demonstrate the improvement in utilization and reusability through the inclusion of the
virtualization, concurrency enabled and orchestrated control plane.
3.4 CONCLUSION
This research work proposes an open IoT testbed framework as a utility. The
existing testbeds are extrapolation of wireless sensor motes and in most cases the
prevailing testbeds are proprietary [13] [37] [48] [82]. As already stated most of
experimental results are tested and verified using simulation tools which lag real time
accuracy. Unexpected device failure due to various reasons like fault, wear/tear, and
energy drains where never considered on real grounds. This proposed framework has
sorted the issues through the resource detection via control plane orchestration and the
heterogeneity is achieved through various board and component variants. The open
source boards are deployed to overcome vendor lock in and proprietorship.
The proposed framework is also incorporated with resource/service discovery,
orchestration and conflicts resolve. The newly added boards/sensors/actuators can be
discovered at runtime through the resource discovery/service discovery algorithm
eliminating the existing static models. The orchestration algorithm dynamically maps
the request with the availability status arrived with resource discovery algorithm. The
resource conflict algorithm eliminates the excessive request initiation as against the
availability status. This provides the needed optimization and performance
enhancement in terms of time and service utilization as depicted in the results section.