M3: Machine-to-Machine Management Framework Heikki Mahkonen 1 , Tony Jokikyyny 1 , Jaime Jimenéz 1 and Sławomir Kukliński 2 1 Ericsson Research, Kirkkonummi, Finland 2 Orange Labs, Warsaw, Poland Keywords: Machine-to-Machine, Internet of Things, Cognitive Network Management, Distributed Hash Tables, Publish Subscribe Networking. Abstract: The number of deployed sensor devices with Internet connection is expected to exceed 50 billion units. Many of these devices spend most of their time in sleep mode to conserve energy. This sets new kinds of requirements for network management, and creates the need of redesigning conventional network management. Hence, most of the manual deployment, configuration and operation tasks need to be automated in a scalable fashion, using protocols that can deal with the uncertainty caused by the intermittent nature of the devices. For scalability reasons, the network management logic needs to be distributable in the network management architecture. In this document we describe our management framework for M2M networks. It is also shown, how the framework has been implemented as a prototype testbed. We have used the testbed to study centralized and de-centralized M2M network management logic for different management scenarios. 1 INTRODUCTION In future networks the amount of users and M2M devices are growing. This sets new requirements for network management. Typical users do not have the expertise to deploy and configure M2M networks by themselves. Neither ISPs have the manpower to manually configure all the expected Machine-to- Machine (M2M) network deployments. For this reason, new automated and scalable ways of deploying and managing network equipment are required. This work is related to a CELTIC project, called COgnitive network ManageMent under UNcErtainty (COMMUNE) (COMMUNE, 2013), which studies cognitive network management under uncertainty. The main goal of the project is to design a network management architecture that can distribute programmable network management algorithms to different parts of the network. In a typical case, these algorithms are cognitive in nature, allowing them to learn and adapt to changes in the environment where they are running. We have implemented a M2M management testbed as part of COMMUNE work. The purpose of the testbed is to study different network management algorithms in a real M2M networking environment. In this paper, we describe the current state of our testbed and evaluate some of the implemented network management functionality. The paper is structured as follows. In Section 2 we give background on M2M networks, and current work on network management. Section 3 discusses our cognitive M2M network management framework. Section 4 describes the testbed implementation and experimented scenarios. Finally, Section 5 concludes the work. 2 BACKGROUND 2.1 M2M Networks European Telecommunications Standards Institute (ETSI) describes a high level architecture (TS- 102.690, 2011) for M2M networking and for Internet of Things (IoT) services and applications. In this architecture, a functional split can be made between the constrained M2M devices, a middleware layer with more logic and processing power, and an IoT service and the application layer. M2M devices may use multiple different communications protocols e.g. 6LoWPAN (Montenegro, 2007), CoAP (Z. Shelby K. H., 2013). 139 Mahkonen H., Jokikyyny T., Jimenéz J. and Kukli´ nski S.. M3: Machine-to-Machine Management Framework. DOI: 10.5220/0004806501390144 In Proceedings of the 3rd International Conference on Sensor Networks (SENSORNETS-2014), pages 139-144 ISBN: 978-989-758-001-7 Copyright c  2014 SCITEPRESS (Science and Technology Publications, Lda.)