Hybrid Cloud Model Checking Using the Interaction Layer of HARMS for Ambient Intelligent Systems

Soon, humans will be co-living and taking advantage of the help of multi-agent systems in a broader way than the present. Such systems will involve machines or devices of any variety, including robots. These kind of solutions will adapt to the special needs of each individual. However, to the concern of this research effort, systems like the ones mentioned above might encounter situations that will not be seen before execution time. It is understood that there are two possible outcomes that could materialize; either keep working without corrective measures, which could lead to an entirely different end or completely stop working. Both results should be avoided, specially in cases where the end user will depend on a high level guidance provided by the system, such as in ambient intelligence applications. This dissertation worked towards two specific goals. First, to assure that the system will always work, independently of which of the agents performs the different tasks needed to accomplish a bigger objective. Second, to provide initial steps towards autonomous survivable systems which can change their future actions in order to achieve the original final goals. Therefore, the use of the third layer of the HARMS model was proposed to insure the indistinguishability of the actors accomplishing each task and sub-task without regard of the intrinsic complexity of the activity. Additionally, a framework was proposed using model checking methodology during run-time for providing possible solutions to issues encountered in execution time, as a part of the survivability feature of the systems final goals

IoRT cloud survivability framework for robotic AALs using HARMS

International audienceThe Internet of Robotic Things, which includes ambient assisted living systems has been pushed to be developed by the research community for reasons such as the population gap between elderly people and their caregivers. Due to the critical mission that is assigned to those systems; interruptions, failures, worse still, full malfunction should not be allowed to materialize. Such systems ought to keep running in a proper way notwithstanding problems caused either by internal and external system collapses or bad intentioned actions in their surroundings. Therefore, including survivability features must be insured to Ambient Assisted Living systems (AALs) using Humans, software Agents, Robots, Machines, and Sensors (HARMS). HARMS stands for the model that allows through the indistinguishability feature to any type of actor to communicate and interact. This work proposes a framework which takes advantage of the Cloud to overcome the state explosion problem encountered when using model checking. Model checking techniques are used to find a possible solution when a problem is already faced by the system — instead of its original purpose to detect errors on the systems during the design stage. This paper presents the implementation of the proposed framework and validates the functionality with experiments. The conducted experiments evaluate the advantages of using cloud tools to offload the model checking capability for applications such as multi-agent systems