For the last decades, we have witnessed new technological evolutions in the Internet, wireless networks, and sensors fields. Currently, we are able to build smart systems that improve quality of life and enhance environment management. However, most available smart systems are implemented based on proprietary hardware/software solutions, restricting interoperation, which is required for large-scale Smart City solutions. To enable the implementation of a general Smart City solution, a platform is needed to fulfill the communication requirements between heterogeneous access technologies. In this paper, we address the requirements and design aspects of a reference Machine-to-Machine (M2M) communication platform as an enabler for Smart Cities.
The current trend in operator networking is towards supporting the communication of devices which do not require human intervention for information gathering, processing and exchange over the network, generically named Machine Type Communication (MTC). This paradigm aims to increase the level of system automation in which the devices and systems can exchange and share data, facilitating the communication for other industry branches resulting in new services such as smart cities, smart grids etc. This paper introduces the OpenMTC platform a software reference implementation of the ETSI M2M standards including advanced features for machine communication, application integration, remote management and integration with available sensors and actuators. OpenMTC in addition to fostering research and development enables academic and industry researchers to rapidly realize testbeds and demonstrations in the MTC communication area
Advances in the field of wireless sensors in particular and machine-to-machine communication in general are converging into the Internet of Things (IoT). Real and virtual 'things' will create a pervasive information space that will hold vast amounts of data. The challenge is to give mobile users an on-demand access to this space, to discover and gather data dynamically from available sensors in the surroundings and enable collaboration by allowing the sharing of own data. Open M2M Data is a new paradigm in usage and delivery of (machine) data. The information space described above will be made accessible on-demand by bringing device-to-device (D2D) and machine type communication (MTC) together and introducing Linked Data principles into the machine-to-machine (M2M) platforms
Context provisioning refers to the trend of gathering, transporting and processing context in order to promote context awareness in Future Internet services. Context awareness enables services to become adaptive, personalized, and accessible in dynamically changing environments. In various scenarios of Internet of things (IoT), connected objects shall be able to negotiate and adapt to their environment. Consequently, the context awareness is an essential feature for Machine-to-Machine (M2M) platforms in order to realize the IoT and enable the management of Context providers (connected objects) and Context information. This paper proposed an abstraction layer to interface ETSI compatible M2M platforms with NGSI Context Management standards interface. The aim of this approach is to promote M2M services adaptation to the ambient environment
In this paper, we solve the problem of candidate access point selection in 802.11 networks, when there is more than one access point available to a station. We use the QBSS (quality of service enabled basic service set) Load Element of the new WLAN standard 802.11e as prior information and deploy a decision making algorithm based on reinforcement learning. We show that using reinforcement learning, wireless devices can reach more efficient decisions compared to static methods of decision making which opens the way to a more autonomic communication environment. We also present how the reinforcement learning algorithm reacts to changing situations enabling self adaptation. The authors Burak Simsek and Katinka Wolter would like to thank German Research Foundation (DFG) for support of this work under grant number WO 898/1-2.
Self-monitoring is one of the key expected capabilities of an autonomic systenm An autonomic system can be a single network node or the entire network as an entity, having the ability to automatically adjust its behaviour based on the conditions in which the system and its components work.Self-monitoring for the purposes of self-configuration, cooperative event detection by a number of systems in a network, knowledge/imformation distribution, service-diagnosis and selfprotection requires a number of challenges/questions to be addressed. In this paper, we present the concepts behind selfmonitoring as a capability of a single node and as a capability of a network that is considered as an entity. We also discuss the challenges and questions to be addressed when designing and deploying self-monitoring mechanism for a single node and for an entire network and, we present some solutions to these chaUenges. Because self-monitoring is broad, we imit our focus to self-monitoring applied to inbound/outbound protocolspecific traffic at some point(s). As part of the solution to some challenges we try to address, we introduce the concept of On-Demand Monitoring (ODM) of protocol-specific traffic.Index Terms-Self-monitoring, on-demand monitoring, dynanic on-demand SNMP micro MIBs for exploiting the power of protocol/traffic analysers.
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