Efficiency of integration between sensor networks and clouds

Numerous wireless sensor networks (WSN) applications include monitoring and controlling various conditions in the environment, industry, healthcare, medicine, military affairs, agriculture, etc. The life of sensor nodes largely depends on the power supply type, communication ability, energy storage capacity and energy management mechanisms. The collection and transmission of sensor data streams from sensor nodes lead to the depletion of their energy. At the same time, the storage and processing of this data require significant hardware resources. Integration between clouds and sensor networks is an ideal solution to the limited computing power of sensor networks, data storage and processing. One of the main challenges facing systems engineers is to choose the appropriate protocol for integrating sensor data into the cloud structure, taking into account specific system requirements. This paper presents an experimental study on the effectiveness of integration between sensor networks and the cloud, implemented through three protocols HTTP, MQTT and MQTT-SN. A model for studying the integration of sensor network - Cloud with the communication models for integration - request-response and publish- subscribe, implemented with HTTP, MQTT and MQTT-SN. The influence of the number of transmitted data packets from physical sensors to the cloud on the transmitted data delay to the cloud, the CPU and memory load was studied. After evaluating the results of sensor network and cloud integration experiments, the MQTT protocol is the most efficient in terms of data rate and power consumption

Selection of Protocols for Integration of Sensory Data Networks in Cloud Structures

The striving to obtain more detailed information about the environment and control various processes leads to an increase in the number of connected sensor devices in various industrial areas. The collected large amount of data can be analysed in real-time. The sensors that build up the WSN have limited hardware resources and cannot process large amounts of data. The integration between WSN and cloud structures is an excellent method for storing, processing, accessing data via the Internet and solves the issue of the limited capacity of WSN. The big challenge to designing the WSN - cloud systems is establishing a communication channel (through different protocols) between devices in the network and cloud platforms. This project executes/perform a real experiment on the XBee sensor network and the ThingSpeak cloud, and the data transmission between them is forwarded using different protocols (HTTP, HTTPS, MQTT and MQTT-SN). The influence of the parameters of the transmitted packet on the delay, the CPU, RAM load has been studied. The results give some advantages of MQTT over other protocols in terms of data rate, CPU and RAM load when working with XBee sensor modules and integration between WSN and cloud structures

Application of Sensor Networks for Measuring Insulin Levels

All WBANs are low-speed networks consisting of intelligent sensors and low-power actuators that can be placed on the body or implanted in humans. With the help of these networks, timely on-line data on unusual conditions of the human body can be provided, which leads to significant improvements in the quality of life. The implementation of these networks will save lives, reduce healthcare costs, and eliminate the need for costly monitoring of patients in the hospital. The paper analyzes the possibilities of the Internet of Things technology, communication standards, cloud technologies, and hardware components for developing a system for monitoring insulin levels in diabetic patients. A model and algorithm for design, construction, and management of a sensor network for monitoring insulin levels with simulation software based on the Internet of Things technology proposed. A system for monitoring insulin levels through a cloud structure has designed, which sends a message to a specialized health centre or the attending physician about the condition of diabetic patients. Simulation studies performed, and the operability of the system examined. The results give reason to believe that the considered model and the simulation project of a system for monitoring insulin levels in patients with diabetes is successful, gives realistic and reliable results for early diagnosis and prevention of various complications and can be implemented in practice

Application of Sensor Networks for Measuring Insulin Levels

All WBANs are low-speed networks consisting of intelligent sensors and low-power actuators that can be placed on the body or implanted in humans. With the help of these networks, timely on-line data on unusual conditions of the human body can be provided, which leads to significant improvements in the quality of life. The implementation of these networks will save lives, reduce healthcare costs, and eliminate the need for costly monitoring of patients in the hospital. The paper analyzes the possibilities of the Internet of Things technology, communication standards, cloud technologies, and hardware components for developing a system for monitoring insulin levels in diabetic patients. A model and algorithm for design, construction, and management of a sensor network for monitoring insulin levels with simulation software based on the Internet of Things technology proposed. A system for monitoring insulin levels through a cloud structure has designed, which sends a message to a specialized health centre or the attending physician about the condition of diabetic patients. Simulation studies performed, and the operability of the system examined. The results give reason to believe that the considered model and the simulation project of a system for monitoring insulin levels in patients with diabetes is successful, gives realistic and reliable results for early diagnosis and prevention of various complications and can be implemented in practice.</p

Molecular taxonomy and phylogeography of Miniopterus schreibersii (Kuhl, 1817) (Chiroptera : Vespertilionidae), in the Eurasian transition

WOS: 000236393000005Miniopterus schreibersii is a polytypic bat species, with one of the widest distribution ranges among the mammals. We studied the genetic differentiation and taxonomy of this species in the transition zone between south-eastern Europe and Anatolia (in Asia), where two subspecies have been described. The results indicated a sharp genetic break between the samples from western Anatolia and south-eastern Europe and those of eastern Anatolia. In addition, the samples from western Anatolia and south-eastern Europe were seen to be reciprocally monophyletic, although the differentiation was less drastic. These patterns of genetic differentiation suggest the presence of two distinct groups within the M. schreibersii complex in the region, concordant with previous subspecific recognition. The cause of this genetic break is most likely differentiation in separate glacial refugia followed by secondary contact. However, more samples are needed to assess whether these represent different species, as well as to understand more clearly the causes of this differentiation. (c) 2006 The Linnean Society of London