367results about How to "Balanced energy consumption" patented technology

Proposed are a mobile terminal and an application program control method and device therefor. The method comprises the following steps: monitoring screen locking state information about a mobile terminal; when the mobile terminal enters a screen locking state, acquiring one or more application programs running in the background; acquiring the frequency of use of each application program within a first preset time period; and if the frequency of use of the application program is less than a first preset threshold, according to a preset policy, controlling the application program to be closed. According to the method in the embodiments of the present invention, while guaranteeing the user's usage experience, the power consumption of the mobile terminal can be reduced, and the standby time of the mobile terminal can be prolonged, thereby effectively increasing the memory usage efficiency, achieving the balance between the user's usage habit and the energy consumption of the mobile terminal, and improving the user experience.

The invention relates to a topology control method for wireless sensor network based on uneven cluster, belong to sensor technical field, comprising: during the topology generating stage, introducing an uneven minimum mean square subtraction clustering mechanism on a finished cluster in order to reduce energy consumption of in-cluster node; using a strategy based on cluster head energy consumption for setting cluster head changing time, in order to equalize energy consumption on each cluster head node in the network; establishing a cluster head-cluster head energy sensing route, in order to avoid remote wireless transmission; during topology maintenance stage, using a cluster head selection scheme based on node surplus energy and in-cluster node distribution, and using the same strategy to set cluster changing time. With the realization of the method, it can reduce total network energy consumption and equalize energy consumption on each node, in order to prolong cooperative working time of most nodes in the network.

The invention discloses a data aggregation method based on non-uniform grids; the method comprises the steps: randomly distributing a certain number of isostructural sensor nodes in a deployment area and dividing the deployment area into grids with different areas; choosing a cluster head node of the grid in each grid according to the residual energy of the nodes and selectively adding the rest nodes into a cluster according to the principle of proximity; judging whether the data gathered by the member nodes in the cluster comply to Labus criterions; if so, considering that the nodes are valid and sending the data to the cluster head node; or else, not sending the data; aggregating the data of the valid member nodes and the generated data by the cluster head node according to the self-adaption aggregation algorithm; sending data to the nodes by the cluster head node in a multi-hop manner and knowing given round number at the end of the operation. The data aggregation method based on non-uniform grids has the advantages of long network life cycle and strong data effectiveness and can be widely applied to big-data collection and transmission of different-scale wireless sensor network.

The invention discloses a cluster routing method based on a multi-factor trust mechanism developed for a wireless sensor network. The multi-factor trust mechanism is adopted for guaranteeing safety and reliability of nodes. Trust factors are selected by angles of communication, data and energy by the trust mechanism. A 'low-return and high-punishment' mechanism is adopted for preventing malicious nodes from increasing trust values rapidly through short-period lawful actions or surviving in the network in long terms by utilizing low trust values. Meanwhile, when a network topology is established, comprehensive trust values of the nodes are combined with cluster head election values and route communication cost to guarantee trusted cluster head election and trusted route selection. In the process of data transmission, the malicious nodes, selfish nodes and low-competitive nodes are removed according to the comprehensive trust values of the nodes, and thus, a safe and trusted network environment is established.

The invention discloses a wireless sensor network clustering routing method based on particle swarm optimization and ant colony optimization, and belongs to the technical field of wireless sensor networks. The method is characterized in that the method comprises the steps that the optimal cluster quantity of an animal breeding environment detection system is decided dynamically; factors influencing energy consumption are analyzed earnestly; an adaptive value function is constructed; clustering is optimized by using a particle swarm optimization algorithm; and then routing between clusters is optimized by operating an ant colony algorithm in a cluster head node. Therefore, the energy consumption of a sensor node in a network is equalized; the survival time of the network is prolonged; a path with small communication delay is selected; the flow of the network is equalized; and a utilization ratio of a wireless sensor network for animal breeding environment detection is increased.

The invention relates to a construction method of a time-delay-constrained energy consumption balance data acquisition tree in a WSN (Wireless Sensor Network). The construction method comprises the following steps: a data sink node calculates a weight of a node pair subjected to symmetrical network communication according to network topology information; the data sink node calculates shortest weighted paths from all nodes in the network to the data sink node, wherein a set of the shortest weighted paths forms a minimum weighted energy consumption generation tree; finding out the nodes in the minimum weighted energy consumption generation tree, which do not meet network time-delay limit, and calculating a corresponding topology adjusting scheme for each node as a candidate topology adjusting scheme; finding out one scheme with minimum adjustment on node transmission power from all the candidate topology adjusting schemes, and reconstructing the generation tree; and judging whether the nodes which do not meet hop count limit exist in the network, if so, continuously adjusting, and if not, ending the algorithm, wherein the generated generation tree is the final network topology result. According to the construction method disclosed by the invention, data effectiveness requirement is met, and energy consumptions of the nodes in the network are balanced.

Disclosed in the invention is an ant colony algorithm-based high-energy efficiency wireless sensor network routing method. The method comprises three parts: cluster establishment, transmission in cluster, and transmission between clusters. When a multi-hop relay node is selected, a heuristic ant colony intelligent algorithm is employed to search a multi-hop transmission route; and during the searching process, an expectation importance influence is eliminated and a probability for node selection is completely decided by the link pheromone concentration. And when a local link pheromone is updated, a dump energy minimum value of a collaboration zone node is multiplied by link pheromone increasing degree Q and then the result is divided by transmission energy consumption, thereby completing updating. According to the new pheromone updating method, the dump energy and the transmission energy consumption of the node are scaled appropriately and then are introduced to the link pheromone updating; and when the dump energy of the collaboration zone node at the next hop is increased and the transmission energy consumption is reduced, the node can be selected. Therefore, when the routing method is used, total energy consumption of the network can be reduced; the dump energy of the network nodes can be balanced; and the working life of the network can be prolonged.

The invention discloses an annulus-based node energy consumption balancing method in a heterogeneous sensor network. The method comprises the following steps of: determining the cluster head level by dividing a monitoring region by rings, and arranging two types of sensor nodes with different hardware configurations in the sensor network, wherein the cluster head uses a communication mode with optimal single hop and multi-hop proportion. In the method, a sensor node energy consumption model is used, based on the difference of the energy consumption increasing speeds when transmitting data packets for different distances, and in combination with the disadvantages and advantages of the single hop and multi-hop communication modes, the single hop and multi-hop optimal proportion related to the radius of the monitoring region in a cluster head mixed communication mode is obtained, the load on the node is balanced, and the lifecycle of a wireless sensor network is prolonged effectively.

The invention discloses a multi-sense unequal-radius wireless sensor network route implementing method includes a design phase and an implementation phase. The design phase includes a zoning phase, a cluster head selecting and cluster forming phase, a multi-hop route setting phase and a stable communication phase. The multi-sense unequal-radius wireless sensor network route implementing method has beneficial effects of reducing node communication cost effectively and balancing network energy consumption. Energy consumption of different nodes is balanced and energy conservation during a working process is achieved, which are attributed to a though of double cluster head and non-balancing clustering. The clustering radiuses are comparatively large and the scales of clusters are comparatively large in zones away from Sink nodes. Two cluster heads can be used for sharing energy consumption of data collection and communication. The clustering radiuses are comparatively small in zones adjacent to the Sink nodes and clusters in the zones adjacent to the Sink nodesare more than those in the zones away from the Sink nodes. Therefore, transceiving energy consumption due to inter-cluster multi-hop can be shared by the clusters of a large number and energy consumption in the network can be balanced well. By using the method provided by the invention, network energy consumption can be balanced well and network service lifetime of the network can be prolonged.

The invention provides a clustering routing protocol based on K-mean clustering and ant colony optimization (ACO), i.e., a K-mean clustering and ACO optimal routing (KCAOR) protocol. In multi-level heterogeneous wireless sensor network environment, the best cluster domain number in a monitoring region is determined by an optimal cluster first-number formula firstly, and nodes in a network are then naturally gathered into corresponding cluster domains through adoption of a K-means clustering method; a uniform optimization strategy of the cluster domains is provided, uniform distribution of network energy consumption is achieved, and cluster heads are voted according to residual energy values of the nodes in clusters then; multihop optimal routes between the cluster heads and base stations are determined through adoption of the ant colony optimization, and energy consumption between the cluster heads is balanced; and, in a tail cycle of data transmission, through increasement of node state packages, the base stations can master an operation condition of the network in real time, and optimization of the protocol is achieved. The energy consumption of the network can be effectively balanced, survival time is prolonged, and performance of the wireless sensor network is improved.

The invention provides a simulated annealing-based WSN hierarchical routing method. The method is based on a hierarchical network topology. The hierarchical structure is maintained by cluster nodes, cluster head nodes and sink nodes in a network. The method comprises the steps of firstly, dividing levels of the WSN, constructing the hierarchical structure of nodes, and then conducting data transmission. In the constructing phase of the hierarchical structure of nodes, cluster head nodes are elected and backed up according to energy. In the data transmission phase, a combination of a negotiation mechanism, a multi-hop energy multi-path routing mechanism and a simulated annealing algorithm is used, cluster nodes use the negotiation mechanism to transmit data to cluster head nodes, after data fusion is conducted by cluster head nodes, the data are transmitted to sink nodes, the multi-hop energy multi-path routing mechanism is used between cluster head nodes and sink nodes, the simulated annealing algorithm is used for seeking out an optimal path, and the data are transmitted from cluster head nodes to sink nodes along the optimal path.

The invention relates to a multi-agent anomaly detection method based on the Internet of things, which is an anomaly detection method for a wireless multimedia sensor network. In the method, the multi-agent technology is introduced mainly to solve the problem of the abnormal situation in the operating process of the wireless multimedia sensor network. The scheme of the multi-agent anomaly detection system is characterized in that: coordinating through a local agent, and monitoring a local sensor network autonomously, independently and promptly; when the terminal finds that the audio/video and other data are abnormal or the network needs regular maintenance, detecting whether the network is abnormal through issuing global agency; and if the abnormal situation occurs to the network, repairing the network dynamically and autonomously to ensure the correct operation of the network. The method of the invention can promptly detect whether the abnormal situation occurs to the network, and repair the network within a limited period to restore the normal operation of the network. Moreover, the invention can reduce the network congestion rate, balance the energy consumption of the network, efficiently utilize resources of the total network, improve the fault tolerance of the network and ultimately prolong the life cycle of the entire network.

The invention discloses a tree structure-based data aggregation method with reliability assurance. The aggregation method comprises the following steps: generating a tree creating module, an in-tree data aggregation module and a data detection module, and generating a tree revising module. The aggregation method adopts the tree structure to realize fast aggregation of data in the network, ensure that data can be conveniently found and used in the entire network, reduce the communications of the network in the data aggregation process and prolong the service life of the entire network; and the data detection method and the method of generating tree revise are both adopted and the phenomenons such as the damage and death of node can be monitored and found, thus increasing the accuracy and effectiveness of data transmission in the network and the reliability of the entire network.

The invention discloses an energy-saving-oriented high-reliability data storage method in a data center environment, aiming at solving the technical problem that a hybrid high-reliability data storage method is provided under the condition of an energy-saving-oriented closed node. In the method, a large number of nodes are allowed to be closed so as to reduce power consumption, and at least one copy of all data is ensured to be stored on active nodes, thus availability of the data is kept. The method comprises the following steps of: firstly dividing clusters and numbering nodes in racks to form logical rings as well as numbering the nodes among the racks to form mutually non-intersected rings; then dividing files to be stored and determining backup quantity of data; and determining a copy placement position of each data block in a queue by adopting a hybrid data storage method. In the method, large-scale node closure and reduction of the power consumption can be supported, reliability of the data can be ensured, and data recovery capability is strong, thus the problems of the energy consumption of a data center and the reliability of the data are effectively solved.