The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks....The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.展开更多
An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference...An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference plus noise ratio （SINR） effects, analytic hierarchy process （AHP） and infor- mation entropy （SAE） weight method were introduced into the algorithm. Handoff decision meeting the multi-attribute quality of service （QoS） requirement is made according to an attribute matrix and weight vector using the TOPSIS algorithm. The simulation results have shown that the proposed algo- rithm can provide satisfactory performance fitted to the characteristics of the traffic.展开更多
基金funded by the Enterprise Ireland Innovation Partnership Programme with Ericsson under grant agreement IP/2011/0135[6]supported by the National Natural Science Foundation of China(No.61373131,61303039,61232016,61501247)+1 种基金the PAPDCICAEET funds
文摘The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.
基金Supported by the National Natural Science Foundation of China （No. 60872018）, the Natural Science Foundation of Education Committee of Jiangsu Province （ No. 11KJB510014） and Scientific Research Foundation of NUPT （ No. NY210004）.
文摘An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference plus noise ratio （SINR） effects, analytic hierarchy process （AHP） and infor- mation entropy （SAE） weight method were introduced into the algorithm. Handoff decision meeting the multi-attribute quality of service （QoS） requirement is made according to an attribute matrix and weight vector using the TOPSIS algorithm. The simulation results have shown that the proposed algo- rithm can provide satisfactory performance fitted to the characteristics of the traffic.
