A narrow bandwidth may lead to a large amount of redundant data, which further causes the interruptions of the communication network. In order to address this problem, an optimized clustering communication protocol based on intelligent computing (CCP-IC) is proposed in this paper. First, we adopt the intelligent algorithm to perform the optimization of the clustering in the sensor network. The adaptation function and the heuristic function are introduced to make a targeted choice on the cluster head for the next hop of the nodes in the network. Second, the controllable threshold parameter and variation coefficient are employed to optimize the shortest path chosen by the network routing. Therefore, the node energy consumption is lowered when the minimum network delay is guaranteed and the transmission efficiency is improved. Finally, it is verified via the simulation results and compared with other algorithms; the proposed protocol reduces the network energy consumption by 15.3% and prolongs the network lifetime by 18.72%, which proves the validity and effectiveness of the proposed protocol. INDEX TERMS Internet of Things, clustering communication protocol, intelligent computing, network lifetime.

Sensor networks will always suffer from load imbalance, which causes bottlenecks to the communication links. In order to address this problem, a multi-path routing algorithm based on data-fusion-mechanism (MR-DFM) is proposed in this work. In this algorithm, the Mobile Sink controls the clustered energy consumption of the nodes in the event domain according to the delay messages relayed by the neighbor nodes. Meanwhile, the optimal neighbor node in the candidate set is obtained according to the data stream of the neighbor nodes to perform the relay of the data packets. It is shown via simulation results that the proposed MR-DFM algorithm shows obvious improvement according to the energy consumption of the network throughput of the sensing data and the throughput of the sensing data and each hop of the neighbor nodes. Therefore, it is verified that the proposed MR-DFM algorithm shows remarkable data fusion effects and optimizes the network resources.

In the process of the wireless sensor network research, the issue on the energy consumption and coverage is an essential and critical one. According to the characteristic of the sensor nodes, it is homogeneous, and we proposed the kdegree coverage algorithm based on optimization nodes deployment. First, the algorithm gives the solving procedure of the maximum seamless coverage ratio, when the three-node joint coverage has been provided. Second, when the sensor nodes are covering the monitoring area, the algorithm gives the solving procedure of the expected coverage quality and the judgment methods of the coverage ratio, when the nodes are compared with the nearby ones. And when there is redundancy coverage in the given monitoring area, we have given the solving procedure of any sensor nodes that exist in the redundant nodes coverage. Finally, using the simulation experiment, the results of the coverage algorithm based on optimization nodes deployment are compared with other algorithms in terms of the coverage quality and the network lifetime, the performance indexes have enhanced to 13.36% and 12.92% on average. Thus, the effectiveness and viability of the coverage algorithm based on optimization nodes deployment have been proved.

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy.

International audienceA home network system consists of multiple networked appliances, intended to provide more convenient and comfortable living for home users. Before being deployed, one has to guarantee the correctness, the safety, and the security of the system. Here, we present the approach chosen to validate the Java implementation of a home network system. We rely on the Java Modelling Language to formally specify and validate an abstraction of the system

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With the increasing for function, scale, hierarchy and complexity of software project, the software life cycle and development stage show a trend of cross-cutting and fuzzy boundary. The non-technical factors, such as poor management and control during the implementation of software projects, are the major reason for causing the low success rate of software projects recently. Therefore, the software quality evaluation under complex environment should take the cross-influence between different stages of software life cycle and different quality evaluation standards into consideration. Our research is to construct a new software quality evaluation model by using the influence relationship and the influence intensity index between project management domain and project quality evaluation criteria including scope, cost, and time. First, we came up with the definition of software project management domain in the process of software project development and management. Second, we proposed a mathematical method for extracting the direct or indirect influence relation between them, and give a definition for the quantitative evaluation index and its calculation formula. At last we proposed to construct a neural network training model which includes evaluation model logic relationships and software quality quantitative evaluation index. Through study and training by simulated software project management data, we can discover some key data, such as normal threshold range of influence, factor weights, etc. Therefore, a complete evaluation system is built, and the scientific nature and accuracy of the proposal evaluation system will be improved. INDEX TERMS Software quality evaluation model, back propagation neural network, project management domain, project sub-management domain, SCT, CMMI.

This paper formalizes three kinds of safety to be satisfied by networked appliances and services in the emerging home network system (HNS). The local safety is defined by safety instructions of individual networked appliances. The global safety is specified as required properties of HNS services, which use multiple appliances simultaneously. The environment safety is derived from residential rules in home and surrounding environments. Based on the safety defined, we propose a modeling/validation framework for the safety. Specifically, we first introduce an object-oriented modeling technique to clarify the relationships among the appliances, the services and the home (environment) objects. We then employ the technique of Design by Contract with JML (Java Modeling Language), which achieves systematic safety validation through testing.