The wireless sensor network (WSN) consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potenti...The wireless sensor network (WSN) consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living (SHAAL)to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM (industrial, scientific, and medical) band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate (PRR) above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.展开更多
SG (smart grids) is an intelligent power grid in which the diverse nodes should communicate different types of information which have different communication requirements with CS (control stations). There exist se...SG (smart grids) is an intelligent power grid in which the diverse nodes should communicate different types of information which have different communication requirements with CS (control stations). There exist several RATs (radio access technologies), with diversification in quality of service character which respect to the SG nodes communication requirements. On the other side, spectrum is becoming a rare source and its demands request is increasing exponentially. Therefore, resource allocation to support different types of SG nodes should be elaborated so that the resource efficiency is maximized while the SG communication requirements are respected. Using a CF (cost function) based on the SG node requirements and RATs characteristics to find the desirability value of every RATs for a certain node type accomplish this goal in combination with prioritizing the different SG nodes types based on SG goals by creating a priority table for RATs and different SG node types. The main node communication requirements are formulized to be used in the CF in this paper. The numerical results show that the proposed method defines the desirability value of each RAT for a certain SG node type that helps to make a priority table by using the SG node prioritization table.展开更多
The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring d...The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring data of large-scale smart grids are massive, dynamic and highly dimensional, so global query, the method widely adopted in continuous queries in Wireless Sensor Networks(WSN), is rendered not suitable for its high energy consumption. The situation is even worse with increasing application complexity. We propose an energy-efficient query technique for large-scale smart grids based on variable regions. This method can query an arbitrary region based on variable physical windows, and optimizes data retrieve paths by a key nodes selection strategy. According to the characteristics of sensing data, we introduce an efficient filter into the each query subtree to keep non-skyline data from being retrieved. Experimental results show that our method can efficiently return the overview situation of any query region. Compared to TAG and ESA, the average query efficiency of our approach is improved by 79% and 46%, respectively; the total energy consumption of regional query is decreased by 82% and 50%, respectively.展开更多
基金supported by the Ministry of Higher Education,Malaysia under Grant No.R.J130000.7823.4L626
文摘The wireless sensor network (WSN) consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living (SHAAL)to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM (industrial, scientific, and medical) band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate (PRR) above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.
文摘SG (smart grids) is an intelligent power grid in which the diverse nodes should communicate different types of information which have different communication requirements with CS (control stations). There exist several RATs (radio access technologies), with diversification in quality of service character which respect to the SG nodes communication requirements. On the other side, spectrum is becoming a rare source and its demands request is increasing exponentially. Therefore, resource allocation to support different types of SG nodes should be elaborated so that the resource efficiency is maximized while the SG communication requirements are respected. Using a CF (cost function) based on the SG node requirements and RATs characteristics to find the desirability value of every RATs for a certain node type accomplish this goal in combination with prioritizing the different SG nodes types based on SG goals by creating a priority table for RATs and different SG node types. The main node communication requirements are formulized to be used in the CF in this paper. The numerical results show that the proposed method defines the desirability value of each RAT for a certain SG node type that helps to make a priority table by using the SG node prioritization table.
基金supported by the National Natural Science Foundation of China (NO. 61472072, 61528202, 61501105, 61472169)the Foundation of Science Public Welfare of Liaoning Province in China (NO. 2015003003)
文摘The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring data of large-scale smart grids are massive, dynamic and highly dimensional, so global query, the method widely adopted in continuous queries in Wireless Sensor Networks(WSN), is rendered not suitable for its high energy consumption. The situation is even worse with increasing application complexity. We propose an energy-efficient query technique for large-scale smart grids based on variable regions. This method can query an arbitrary region based on variable physical windows, and optimizes data retrieve paths by a key nodes selection strategy. According to the characteristics of sensing data, we introduce an efficient filter into the each query subtree to keep non-skyline data from being retrieved. Experimental results show that our method can efficiently return the overview situation of any query region. Compared to TAG and ESA, the average query efficiency of our approach is improved by 79% and 46%, respectively; the total energy consumption of regional query is decreased by 82% and 50%, respectively.