An Infrastructure for Robotic Applications as Cloud Computing Services

Robotic applications are becoming ubiquitous. They are widely used in several areas (e.g., healthcare, disaster management, and manufacturing). However, their provisioning still faces several challenges such as cost efficiency. Cloud computing is an emerging paradigm that may aid in tackling these challenges. It has three main facets: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Virtualization is a technique that allows the abstraction of actual physical computing resources into logical units; it enables efficient usage of resources by multiple users. Its role is a key to resource efficiency. Virtualization can be performed at both node and network level. This thesis focuses on the IaaS aspects of robotic applications as cloud computing services. It starts by defining a set of requirements on the infrastructure for cost efficient robotic applications provisioning. It then reviews the state of the art. After pinpointing the shortcoming of the state of the art, it proposes an architecture that enables cost efficiency through virtualization and dynamic task delegation to robots, including robots that might belong to other clouds. Overlays and RESTful Web services are used as cornerstones. The virtualization in the IaaS is achieved by providing a coalition formation algorithm, which is the cooperation between several robots to perform a task that either cannot be solved individually or can be solved more efficiently as a group. Forming the effective coalitions is another big challenge. We adapted heuristic-based Multi Objective- Particle Swarm Optimization (MO-PSO) algorithm to solve this specific problem. As a proof of concept, a prototype is built using LEGO Mindstorms NXT as the robotic platform, and JXTA as the overlay middleware and the prototype architecture is presented along with the implemented scenario (i.e., wildfire suppression). Performance measurements have also been made to evaluate viability. To evaluate the effectiveness of our algorithm, WEBOTS simulation software is used

Mobile Cloud Robotics as a Service with OCCIware

Best Paper AwardInternational audienceWe have recently witnessed the emerging of cloud computing on one hand and robotics platforms on the other hand. Naturally, these two visions have been merging to give birth to the Cloud Robotics paradigm in order to offer even more remote services. But such a vision is still in its infancy. Architectures and platforms are still to be defined to efficiently program robots so they can provide different services, in a standardized way masking their heterogeneity. This paper introduces Open Mobile Cloud Robotics Interface (OMCRI), a Robot-as-a-Service vision based platform, which offers a unified easy access to remote heterogeneous mobile robots. OMCRI encompasses an extension of the Open Cloud Computing Interface (OCCI) standard and a gateway hosting mobile robot resources. We then provide an implementation of OMCRI based on the open source model-driven Eclipse-based OCCIware tool chain and illustrates its use for three off-the-shelf mobile robots: Lego Mindstorm NXT, Turtlebot, and Parrot AR.Drone

An Architecture for an Infrastructure as a Service for the Internet of Things

Internet of things (IoT) refers to things such as sensors and actuators interacting with each other to reach common goals. It enables multiple applications in sectors ranging from agriculture to health. Nowadays, applications and IoT infrastructure are tightly coupled and this may lead to the deployment of redundant IoT infrastructures, thus, cost inefficiency. Cloud computing can help in tackling the problem. It is a paradigm to quickly provision configured resources (computing, network, memory) on demand for cost efficiency. It has three layers, the infrastructure as a service (IaaS), the platform as a service (PaaS) and the software as a service (SaaS). Through the IaaS, configured hardware resources (CPU, storage, etc.) are provisioned on demand. However, designing and implementing an IoT IaaS architecture for the provisioning of IoT resource on demand remains very challenging. An example of a challenge is using the appropriate publishing and discovery mechanism suitable for IoT devices. Orchestrating a virtualized IoT device over several physical IoT devices is another challenge that needs to be addressed. The main contribution of this thesis is twofold. First, a novel IoT IaaS architecture is proposed where IoT devices can be provisioned as a configured infrastructure resource on demand via node virtualization. Second, the architecture is prototyped and evaluated using real-life sensors that support node virtualization. Node level virtualization achieves resource efficiency in contrast to middleware solutions. The essential architectural features, such as publication, discovery, and orchestration are identified and proposed. Two sets of a high-level interface are also introduced. A low-level uniform interface is suggested to decouple the IoT devices from the applications by allowing the applications to access the heterogeneous devices in a uniform way. In addition, a cloud management interface is proposed to expose the IoT IaaS to the cloud consumers (for example - the PaaS, the application, etc.) and allow them to provision the IoT resources. By allowing the capability sharing of the IoT devices using the node virtualization, the cost efficiency and energy efficiency are achieved in the proposed architecture. Addressing other challenges allowed the proposed architecture to expose the IoT devices to the IaaS in a more abstract manner. Thus allowing the application to provision the IoT resources on demand as well as handling the IoT device heterogeneity in the IaaS

Softwarization of Large-Scale IoT-based Disasters Management Systems

The Internet of Things (IoT) enables objects to interact and cooperate with each other for reaching common objectives. It is very useful in large-scale disaster management systems where humans are likely to fail when they attempt to perform search and rescue operations in high-risk sites. IoT can indeed play a critical role in all phases of large-scale disasters (i.e. preparedness, relief, and recovery). Network softwarization aims at designing, architecting, deploying, and managing network components primarily based on software programmability properties. It relies on key technologies, such as cloud computing, Network Functions Virtualization (NFV), and Software Defined Networking (SDN). The key benefits are agility and cost efficiency. This thesis proposes softwarization approaches to tackle the key challenges related to large-scale IoT based disaster management systems. A first challenge faced by large-scale IoT disaster management systems is the dynamic formation of an optimal coalition of IoT devices for the tasks at hand. Meeting this challenge is critical for cost efficiency. A second challenge is an interoperability. IoT environments remain highly heterogeneous. However, the IoT devices need to interact. Yet another challenge is Quality of Service (QoS). Disaster management applications are known to be very QoS sensitive, especially when it comes to delay. To tackle the first challenge, we propose a cloud-based architecture that enables the formation of efficient coalitions of IoT devices for search and rescue tasks. The proposed architecture enables the publication and discovery of IoT devices belonging to different cloud providers. It also comes with a coalition formation algorithm. For the second challenge, we propose an NFV and SDN based - architecture for on-the-fly IoT gateway provisioning. The gateway functions are provisioned as Virtual Network Functions (VNFs) that are chained on-the-fly in the IoT domain using SDN. When it comes to the third challenge, we rely on fog computing to meet the QoS and propose algorithms that provision IoT applications components in hybrid NFV based - cloud/fogs. Both stationary and mobile fog nodes are considered. In the case of mobile fog nodes, a Tabu Search-based heuristic is proposed. It finds a near-optimal solution and we numerically show that it is faster than the Integer Linear Programming (ILP) solution by several orders of magnitude

An infrastructure for robotic applications as cloud computing services

Robotic applications are becoming ubiquitous. They are widely used in several areas (e.g., healthcare, disaster management, and manufacturing). However, their provisioning still faces several challenges such as cost and resource usage efficiency. Cloud computing is an emerging paradigm that may aid in tackling these challenges. It has three main facets: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). This paper focuses on the IaaS aspects of robotic applications as cloud computing services. It proposes an architecture that enables cost efficiency through virtualization and dynamic task delegation to robots, including robots that might belong to other clouds. Overlays and RESTful Web services are used as cornerstones. A prototype is built using LEGO Mindstorms NXT as the robotic platform, and JXTA as the overlay middleware. Related work is reviewed, the functional entities and interfaces of the architecture are described, and the prototype architecture is presented along with the implemented scenario. © 2014 IEEE