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Energy-efficient task allocation for service provisioning in machine-to-machine systems

机译:机对机系统中用于服务供应的节能任务分配

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Machine-to-Machine (M2M) communication systems enable autonomous communication between heterogeneous devices. In many applications, those devices are used to obtain measurements from sensors connected to them. By integrating M2M with the Internet of things paradigm, sensors and the data they obtain can be easily accessed via Internet infrastructure. This novelty, along with the advancement of processing power on small devices and the possibility to connect more sensors to one sensing device, poses new challenges and opens new opportunities in the area. This paper presents an algorithm and a protocol devised for task allocation to nodes of the M2M architecture where M2M devices are battery powered. The presented mechanism tackles some of the identified challenges within the area. First challenge is to determine the right node for performing data analysis. Certain data analysis tasks can be performed on device, instead of only on servers, which is a traditional approach. Another challenge is to relate the process of obtaining measurements with user needs, i.e. to collect data only when users have interest in it. The last identified challenge is to extend lifetime of services with higher priority, instead of prolonging lifetime of all devices within the network. Adoption of the proposed mechanism is justified on specific services in a smart home environment.
机译:机器对机器(M2M)通信系统可实现异构设备之间的自主通信。在许多应用中,这些设备用于从与其连接的传感器获取测量值。通过将M2M与物联网范例集成,可以轻松地通过Internet基础结构访问传感器及其获取的数据。这种新颖性,再加上小型设备上处理能力的提高以及将更多传感器连接到一个传感设备上的可能性,给该领域带来了新的挑战并带来了新的机遇。本文提出了一种算法和协议,旨在将任务分配给M2M设备由电池供电的M2M体系结构的节点。提出的机制解决了该区域内一些已确定的挑战。第一个挑战是确定执行数据分析的正确节点。某些数据分析任务可以在设备上执行,而不是仅在服务器上执行,这是传统方法。另一个挑战是将获得测量的过程与用户需求相关联,即仅在用户感兴趣时才收集数据。最后确定的挑战是延长具有更高优先级的服务的寿命,而不是延长网络中所有设备的寿命。对于智能家居环境中的特定服务,采用建议的机制是合理的。

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