Department of Information Engineering, University of Pisa, L.go Lazzarino 1, I-56122 Pisa, Italy.
Sensors (Basel). 2019 Feb 8;19(3):693. doi: 10.3390/s19030693.
The Internet of Things (IoT) is becoming real, and recent studies highlight that the number of IoT devices will significantly grow in the next decade. Such massive IoT deployments are typically made available to applications as a service by means of IoT platforms, which are aware of the characteristics of the connected IoT devices⁻usually constrained in terms of computation, storage and energy capabilities⁻and dispatch application's service requests to appropriate devices based on their capabilities. In this work, we develop an energy-aware allocation policy that aims at maximizing the lifetime of all the connected IoT devices, whilst guaranteeing that applications' Quality of Service (QoS) requirements are met. To this aim, we formally define an IoT service allocation problem as a non-linear Generalized Assignment Problem (GAP). We then develop a time-efficient heuristic algorithm to solve the problem, which is shown to find near-optimal solutions by exploiting the availability of equivalent IoT services provided by multiple IoT devices, as expected especially in the case of massive IoT deployments.
物联网（IoT）正在成为现实，最近的研究强调，物联网设备的数量将在未来十年内大幅增长。这种大规模的物联网部署通常通过物联网平台作为服务提供给应用程序，物联网平台了解连接的物联网设备的特性——通常在计算、存储和能源能力方面受到限制——并根据设备的能力将应用程序的服务请求分配到合适的设备上。在这项工作中，我们开发了一种节能分配策略，旨在最大限度地延长所有连接的物联网设备的寿命，同时保证应用程序的服务质量（QoS）要求得到满足。为此，我们将物联网服务分配问题正式定义为非线性广义分配问题（GAP）。然后，我们开发了一种高效的启发式算法来解决这个问题，该算法通过利用多个物联网设备提供的等效物联网服务的可用性来找到接近最优的解决方案，这在大规模物联网部署的情况下尤其可以预期。
