{"title":"Trainspotting, a WSN-Based Train Integrity System","authors":"H. Scholten, R. Westenberg, Manfred Schoemaker","doi":"10.1109/ICN.2009.59","DOIUrl":"https://doi.org/10.1109/ICN.2009.59","url":null,"abstract":"In contrast to classic train protection systems where most of the safety measures are built into the rail infrastructure, future versions of the European railway safety system ERTMS (European Railway Traffic Management System) require trains to check their own safety. One of the safety measures is the train integrity check, which checks whether all carriages are still in the train. The check has to be completed in a certain amount of time. This paper presents an overview for communication in such an integrity system, based on a wireless sensor network(WSN). Because a WSN with nodes in each carriage has a linear structure, existing communication protocols which assume a mesh-like topology do no suffice. Simulation shows that the proposed communication is feasible and has the necessary (soft) real-time properties to complete an integrity check in time. The protocol, based on the IEEE 802.15.4 network stack, is implemented and tested by Strukton.","PeriodicalId":299215,"journal":{"name":"2009 Eighth International Conference on Networks","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126076399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Self-Configurable Diagnosis Algorithm on an Isolation Network","authors":"Kwangjong Cho, Wonhyuk Lee, Dongkyun Kim","doi":"10.1109/ICN.2009.68","DOIUrl":"https://doi.org/10.1109/ICN.2009.68","url":null,"abstract":"Nowadays, with the exponential growth of Internet, the network complexity has been increased because of various network equipment and protocols. It makes network configuration management so hard. In order to settle out these problems, we propose the Topology Discovery Algorithm and the Self-Configurable Diagnosis Algorithm on Isolation network. We defined an Isolation Network as the unit of self-configurable network. The novelty of the former algorithm is the simplicity and decentralization of itself. And the latter algorithm diagnoses simultaneously node faults and links faults and doesn’t need to use another network management protocols such as SNMP and TL1 to diagnose network configuration. Essentially this is divide-and-conquer strategy for larger and complex network. Through simulations we verified the effect on the network by traffic, which is generated by Topology Discover Algorithm. These algorithms can be directly adapted to IP routing network or lambda exchange network.","PeriodicalId":299215,"journal":{"name":"2009 Eighth International Conference on Networks","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115201788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Model Based RL Admission Control Algorithm for Next Generation Networks","authors":"S. Mignanti, A. Giorgio, V. Suraci","doi":"10.1109/ICN.2009.39","DOIUrl":"https://doi.org/10.1109/ICN.2009.39","url":null,"abstract":"In this paper we study the call admission control problem to optimize the network operators revenue guaranteeing quality of service to the end users. We consider a network scenario where each class of service is characterized by a different constant bit rate and an associated revenue. We formulate the problem as a Semi-Markov Decision Process,and we use a model based Reinforcement Learning approach.Other traditional algorithms require an explicit knowledge of the state transition models while our solution learn it on-line.We will show how our policy provides better solution than a classic greedy algorithm.","PeriodicalId":299215,"journal":{"name":"2009 Eighth International Conference on Networks","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132507092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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