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Nowadays, with the development of computer science and technology, computer intelligent algorithms are more and more widely used in various industries. Every calculation formula in the computer intelligent algorithm has systematic logic and singleness, in order to expound the dynamic algorithm of football training optimized by the computer intelligent algorithm in detail. In this paper, the monitoring system using the computer intelligent algorithm can dynamically observe people or objects and systematically analyze them. This paper mainly studies the research of a football training dynamic monitoring system based on the computer intelligent algorithm and the design and optimization of the computer intelligent dynamic monitoring system in football training. Finally, the overall composition of the computer intelligent dynamic monitoring system and the application of the optimized computer intelligent dynamic monitoring system to the analysis of sample data are studied. [ABSTRACT FROM AUTHOR]

For some time it has been known that the standard method for collecting link-traffic measurements in IP networks-the Simple Network Management Protocol or SNMP-is flawed. It has often been noted that SNMP is subject to missing data, and that its measurements contain errors. However, very little work has been aimed at assessing the magnitude of these errors. This paper develops a simple, easily applicable technique for measuring SNMP errors, and uses it in a case study to assess errors in a common SNMP collection tool. The results indicate that most link-load measurement errors are relatively small, but the distribution has a heavy-tail, and that a few measurement errors can be as large as the measurements themselves. The approach also allows us to go some way towards explaining the cause of the errors. [ABSTRACT FROM AUTHOR]

Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of ship-borne WSN based on research on structure of ship and work environment of ship-borne WSN. The whole location process consists of two steps: one is location algorithm among cabins (LAAC), and the other one is location algorithm in the cabin (LAIC). LAAC refers to location with the topology of ship-borne WSN. We can learn which cabin the node lies in. LAIC refers to location based on received signal strength indication (RSSI), we can get distance relationship between nodes by RSSI, and then obtain the specific location by solving this distance relationship. In the last part, this paper verifies the designed location algorithm by experimenting on "A" ship. Experiments show that the location algorithm designed by this paper is feasible. [ABSTRACT FROM AUTHOR]

Big data and distributed computing are of great importance in wireless sensor networks (WSNs).They are always bonded together, and the latter one upholds the former one. In distributed computing, mobile agent model is the mainstream technology. With autonomy, communicativeness, mobility, and role, mobile agent model is more suitable for large-scale, resources-restrained WSN to deal with big data. This paper mainly studies migration schemes for mobile agents, determines core factors of migration strategy, and proposes SMLA and DMLA algorithms. And aiming at revealing the characteristics of target tracking, this paper puts forward pid-DMLA algorithm; and considering multiple agents' cooperation, it presents Mpid-DMLA algorithm. Moreover, this paper evaluates and analyzes the advantages and disadvantages of the above-mentioned four algorithms by simulations. [ABSTRACT FROM AUTHOR]

This paper presents a partitioning method based on topological ordering and levelization. The proposed method, termed RPL, performs multi-FPGA partitioning by taking into account six different partitioning constraints. We also compare RPL to two existing algorithms. The first approach is a hierarchical partitioning method based on topological ordering (HP). The second approach is a recursive algorithm based on the Fiduccia and Mattheyses bipartitioning heuristic (RP). Experimental results on seven application benchmarks mapped onto three different hardware architectures demonstrated that the proposed RPL approach achieved fewer partitions in less time when compared to the RP and HP algorithms. [ABSTRACT FROM AUTHOR]

The simplicity of the maximum satisfiability problem (MAX-SAT) combined with its applicability in many areas of artificial intelligence and computing science made it one of the fundamental optimization problems. This NP-complete problem refers to the task of finding a variable assignment that satisfies the maximum number of clauses (or the sum of weights of satisfied clauses) in a Boolean formula. The Walksat algorithm is considered to be the main skeleton underlying almost all local search algorithms for MAX-SAT. Most local search algorithms including Walksat rely on the 1-flip neighborhood structure. This paper introduces a variable neighborhood walksat-based algorithm. The neighborhood structure can be combined easily using any local search algorithm. Its effectiveness is compared with existing algorithms using 1-flip neighborhood structure and solvers such as CCLS and Optimax from the eighth MAX-SAT evaluation. [ABSTRACT FROM AUTHOR]

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. This paper presents research on the existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency, and superior network monitoring quality. [ABSTRACT FROM AUTHOR]

Mobility is a common character of the emerging RFID-based internet-of-things. However, most of prior RFID anticollision algorithms ignore the movement of tags, which can degrade the identification performance seriously and even result in tag starvation problem. This paper presents a novel anticollision algorithm named Query Splitting-based Anticollision (QSA) for mobile RFID-based internet-of-things. By designing adaptive query, QSA reduces the number of collisions efficiently and makes it possible to identify multiple mobile tags without rollback. In QSA, we propose a query stack technology to avoid the rollback operation caused by new arriving tags, which solves the tag starvation problem under mobile environments. The performance evaluation shows that the proposed algorithm takes fewer timeslots and has better performance in identifying mobile tags. [ABSTRACT FROM AUTHOR]

Optimizing the path planning to reduce the time and cost is an essential consideration in modern society, and existing research has mostly concentrated on static path planning and real-time data information in vehicle navigational applications. Using dynamic path planning to adjust and update the path information in time is a challenging approach to reduce road congestion and traffic accidents. In this paper, we present a data analysis algorithmthat determines an efficient dynamic path for vehicle repair-scrap sites and navigates more flexibly to avoid obstacles, where the key idea is to design the sensor wireless network that helps to obtain data fromdifferent devices. Firstly, the data processing scheme for real-time data with regional cluster and node division can be obtained fromdifferent sensor devices through the wireless senor network. Secondly, the search space and the relevant road information are restricted to a strongly connected graph. The most important strategy for an optimal solution to find the shortest path is the search method. Finally, to validate the performance of our design and algorithm, we have conducted a simulation based on necessary traffic variables. The performance simulation results show that real-time dynamic path planning can be significantly optimized using our data processing scheme. [ABSTRACT FROM AUTHOR]

Real-time Online Interactive Application (ROIA) is an emerging distributed application recently. ROIA needs a highly robust and efficient architecture to cope with the huge concurrent users. Previous works are almost based on the C/S or P2P mode, and their scalability and resource utilization are relatively low. So we try to take advantage of the cloud computing technologies to achieve higher scalability and resource utilization. However, as ROIA servers focused on several data centers in cloud computing rather than being scattered in many areas, it will increase in part users' network delays and affect their user experiences in ROIA. To cope with this problem, we propose an improved Dead Reckoning (DR) algorithm. Traditional DR algorithm is mostly based on the classic formula of physics to predict, without taking the influence of the user's target under the different situations into account, so there are some limitations. This paper proposes an improved DR algorithm based on target-extrapolating in a cloud platform for ROIA, elaborates the basic idea of the improved algorithm and the computational model formula, and then carries out a simulation experiment. The analyses of the simulation results show that the improved algorithm is superior to traditional one. [ABSTRACT FROM AUTHOR]

This paper presents a novel data validation algorithm for wireless sensor network. We applied qualitative methods such as heuristic rule, temporal correlation, spatial correlation, Chauvenet's criterion, and modified z-score as algorithms for validating sensor data samples for faults. Performance of the algorithms is evaluated using real data samples of WSNs prototype for environment monitoring injected with different types of data faults such as out-of-range faults, struck-at faults, and outliers and spike faults. Results show heuristic rule, temporal correlation, spatial correlation, chauvenet's criterion, and modified z-score method sit at different point on accuracy, no single method is perfect in detecting different types of data faults and reports false positives when sensor data samples contain different types of data faults. Selected effective methods such as heuristic rule, temporal correlation, and modified z-score are applied successively to data set for detecting different types of data faults but report false positives due to masking effects and increased fault rate. Finally we propose a novel data validation algorithm that uses novel approach in applying heuristic rule, temporal correlation, and modified z-score to data set for detecting different types of data faults. Compared to other methods, the proposed novel data validation algorithm is effective in detecting different types of data faults and reports high fault detection rate by eliminating false positives. [ABSTRACT FROM AUTHOR]

We study the impact of scheduling algorithms on the provision of multiple services in the long term evolution (LTE) system. In order to measure how well the services are provided by the system, we use the definition of joint system capacity. In this context, we claim that scheduling strategies should consider the current satisfaction level of each service and the offered load to the system by each service. We propose a downlink-scheduling strategy according to these ideas named capacity-driven resource allocation (CRA). The CRA scheduler dynamically controls the resource sharing among flows of different services such as delay-sensitive and rate demanding ones. Moreover, CRA scheduler exploits the channel-quality knowledge to utilize the system resources efficiently. Simulation results in a multicell scenario show that the CRA scheduler is robust regarding channel quality knowledge and that it provides significant gains in joint system capacity in single and mixed service scenarios. [ABSTRACT FROM AUTHOR]