Industrial wireless sensor network (IWSN) has changed the information transmission way for existing industrial control system. In mobile sink-based industrial wireless sensor networks, the energy consumption optimization for data collection has always been a hot research issue. To meet the delay requirements and minimize energy consumption, a data collection strategy based on ant colony optimization with mobile sink is proposed for industrial wireless sensor networks. Firstly, in order to reduce the number of nodes directly accessed by sink and shorten the traversed path, the selection of rendezvous nodes based on entropy weight method is introduced according to the density of nodes, relative residual energy, and the degree of uniformity of distribution. Then, secondly, an ant colony optimization algorithm is proposed to obtain the optimal access path for mobile sink, which can achieve a trade-off between the energy consumption of the network and transmission delay. The simulation results show that, compared with the existing algorithms, the proposed algorithm can minimize the delay and prolong the lifetime of the network.
The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples.
In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network’s running and the degree of candidate nodes’ effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime.
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