Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876092
Zonglin Guo, I. Harris, Yutong Jiang, L. Tsaur
As the need for mesh networks for Internet of Things (IoT) applications grows, research in this field attracts more and more attention. Because IoT devices are primarily battery-driven, Bluetooth Low Energy (BLE) networking is appealing to conserve battery life. The importance of battery life in a mobile ad hoc network increases the sensitivity of the network to cyber-attacks intended to impact battery life. A Battery Exhaustion Attack can overwhelmingly exhaust the batteries of network nodes by making malicious service requests. In this paper, we present an intrusion detection and prevention approach for this type of attack. This approach requires the suspicious nodes to switch connection to the neighbors of its connected nodes periodically. When a suspicious node is identified as malicious, it is blacklisted to prevent future attacks. Even when a malicious node cannot be detected, its impact is distributed across the network in order to extend the overall network lifetime.
{"title":"An efficient approach to prevent Battery Exhaustion Attack on BLE-based mesh networks","authors":"Zonglin Guo, I. Harris, Yutong Jiang, L. Tsaur","doi":"10.1109/ICCNC.2017.7876092","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876092","url":null,"abstract":"As the need for mesh networks for Internet of Things (IoT) applications grows, research in this field attracts more and more attention. Because IoT devices are primarily battery-driven, Bluetooth Low Energy (BLE) networking is appealing to conserve battery life. The importance of battery life in a mobile ad hoc network increases the sensitivity of the network to cyber-attacks intended to impact battery life. A Battery Exhaustion Attack can overwhelmingly exhaust the batteries of network nodes by making malicious service requests. In this paper, we present an intrusion detection and prevention approach for this type of attack. This approach requires the suspicious nodes to switch connection to the neighbors of its connected nodes periodically. When a suspicious node is identified as malicious, it is blacklisted to prevent future attacks. Even when a malicious node cannot be detected, its impact is distributed across the network in order to extend the overall network lifetime.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127027013","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876147
H. Rastegarfar, Kamran Keykhosravi, K. Szczerba, E. Agrell, L. LaComb, M. Glick
Hybrid networking, based on electronic packet switching and optical circuit switching, has been proposed to resolve the existing switching bottlenecks in data centers in an energy-efficient and cost-effective fashion. We consider the problem of resource provisioning in hybrid data centers in terms of optical circuit switching capacity and granularity. The number of fibers connected to server racks, the number of wavelengths per fiber, and the ratio of capacity provided by the optical circuit-switched portion of the network to that of the electronic packet-switched portion are crucial design parameters to be optimized during the data center planning phase. These parameters in conjunction with the additive-increase, multiplicative-decrease (AIMD) congestion control mechanism of the Transmission Control Protocol (TCP) pose a significant impact on data center network performance. In this paper, we examine the combined impact of optical bandwidth settings and TCP dynamics using event-driven simulations. Our analysis reveals the strong dependence of overall network throughput on channel capacity (i.e., the bit rate per wavelength channel) and points to the advantages of optical bandwidth consolidation employing higher-order modulation formats.
{"title":"Optical circuit granularity impact in TCP-dominant hybrid data center networks","authors":"H. Rastegarfar, Kamran Keykhosravi, K. Szczerba, E. Agrell, L. LaComb, M. Glick","doi":"10.1109/ICCNC.2017.7876147","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876147","url":null,"abstract":"Hybrid networking, based on electronic packet switching and optical circuit switching, has been proposed to resolve the existing switching bottlenecks in data centers in an energy-efficient and cost-effective fashion. We consider the problem of resource provisioning in hybrid data centers in terms of optical circuit switching capacity and granularity. The number of fibers connected to server racks, the number of wavelengths per fiber, and the ratio of capacity provided by the optical circuit-switched portion of the network to that of the electronic packet-switched portion are crucial design parameters to be optimized during the data center planning phase. These parameters in conjunction with the additive-increase, multiplicative-decrease (AIMD) congestion control mechanism of the Transmission Control Protocol (TCP) pose a significant impact on data center network performance. In this paper, we examine the combined impact of optical bandwidth settings and TCP dynamics using event-driven simulations. Our analysis reveals the strong dependence of overall network throughput on channel capacity (i.e., the bit rate per wavelength channel) and points to the advantages of optical bandwidth consolidation employing higher-order modulation formats.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348573","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876150
C. Callegari, S. Giordano, M. Pagano
Anomaly-based Intrusion Detection is a key research topic in network security due to its ability to face unknown attacks and new security threats. In this paper we propose a novel intrusion detection system that performs anomaly detection by studying the variation in the entropy associated to the network traffic. To this aim, the traffic is first aggregated by means of random data structures (namely three-dimension reversible sketches) and then the entropy of different traffic descriptors is computed by using several definitions of entropy. The experimental results obtained over the MAWILab dataset validate the system and demonstrate the effectiveness of our proposal.
{"title":"Entropy-based network anomaly Detection","authors":"C. Callegari, S. Giordano, M. Pagano","doi":"10.1109/ICCNC.2017.7876150","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876150","url":null,"abstract":"Anomaly-based Intrusion Detection is a key research topic in network security due to its ability to face unknown attacks and new security threats. In this paper we propose a novel intrusion detection system that performs anomaly detection by studying the variation in the entropy associated to the network traffic. To this aim, the traffic is first aggregated by means of random data structures (namely three-dimension reversible sketches) and then the entropy of different traffic descriptors is computed by using several definitions of entropy. The experimental results obtained over the MAWILab dataset validate the system and demonstrate the effectiveness of our proposal.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128783851","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876234
Max Hastings, Shuhui Yang
In this paper we demonstrate how limiting the number of copies each message that a node can send out as seen in Spray And Wait can be combined with probabilistic protocols such as Prophet, ProphetV2, and one that we created called Sparse. By limiting the number of copies that each node can send out we allow the routing protocols to scale much better than before when the number of nodes and messages created are increased.
在本文中，我们演示了如何限制节点可以发送的每个消息的副本数量，如Spray And Wait中所见，可以与概率协议(如Prophet, ProphetV2和我们创建的称为Sparse的协议)相结合。通过限制每个节点可以发送的副本数量，当创建的节点和消息数量增加时，我们允许路由协议比以前更好地扩展。
{"title":"Energy-efficient sparse routing protocol for Delay Tolerant Networks","authors":"Max Hastings, Shuhui Yang","doi":"10.1109/ICCNC.2017.7876234","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876234","url":null,"abstract":"In this paper we demonstrate how limiting the number of copies each message that a node can send out as seen in Spray And Wait can be combined with probabilistic protocols such as Prophet, ProphetV2, and one that we created called Sparse. By limiting the number of copies that each node can send out we allow the routing protocols to scale much better than before when the number of nodes and messages created are increased.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129188667","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876279
Mark Bilinski, Ryan Gabrys
In this work, we consider a variant of the set reconciliation problem where the estimate for the size of the symmetric difference may be inaccurate. Given this setup, we propose a new method to reconciling sets of data and we then compare our method to the Invertible Bloom Filter approach proposed by Eppstein et al. [2].
{"title":"Set reconciliation with an inaccurate oracle","authors":"Mark Bilinski, Ryan Gabrys","doi":"10.1109/ICCNC.2017.7876279","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876279","url":null,"abstract":"In this work, we consider a variant of the set reconciliation problem where the estimate for the size of the symmetric difference may be inaccurate. Given this setup, we propose a new method to reconciling sets of data and we then compare our method to the Invertible Bloom Filter approach proposed by Eppstein et al. [2].","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132863495","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876160
Seydou Ba, Bijoy Chand Chatterjee, E. Oki
The route partitioning scheme for hitless defragmentation have been introduced to increase the admissible traffic load in elastic optical networks. It facilitates the defragmentation of the spectrum through spectrum retuning. This paper further investigates the performance of the route partitioning scheme. For the heuristic algorithm, where we seek a maximum cut, we use the Goemans/Williamson relaxation algorithm, which has a 0.878 approximation factor for maximum cut. We implement the parallel retuning to speed up the retuning process, and investigate the effects of the network characteristics on the route partitioning performances. Results show that the approximation algorithm provides the optimal cut for most networks and that the route partitioning scheme with parallel retuning offers up to 9% added traffic load compared to the conventional one.
{"title":"Performance of route partitioning scheme for hitless defragmentation in elastic optical networks","authors":"Seydou Ba, Bijoy Chand Chatterjee, E. Oki","doi":"10.1109/ICCNC.2017.7876160","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876160","url":null,"abstract":"The route partitioning scheme for hitless defragmentation have been introduced to increase the admissible traffic load in elastic optical networks. It facilitates the defragmentation of the spectrum through spectrum retuning. This paper further investigates the performance of the route partitioning scheme. For the heuristic algorithm, where we seek a maximum cut, we use the Goemans/Williamson relaxation algorithm, which has a 0.878 approximation factor for maximum cut. We implement the parallel retuning to speed up the retuning process, and investigate the effects of the network characteristics on the route partitioning performances. Results show that the approximation algorithm provides the optimal cut for most networks and that the route partitioning scheme with parallel retuning offers up to 9% added traffic load compared to the conventional one.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127696984","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876161
Chengjun Li, W. Guo, Wei Wang, Weisheng Hu, Ming Xia
Passive optical network (PON) deployment requires significant capital and operational costs for operators to provide high network capacity and significant geographic coverage. Network sharing is desirable for operators to reduce the investment needed to deploy and operate PON networks. In this paper, we introduce a bandwidth resource sharing framework for XG-PONs among multiple operators. In this framework, each transmission convergence (TC) frame with fixed time slots (125us) is regarded as a bandwidth slice. We proposed two slice scheduling schemes for network infrastructure provider to assign slices to different operators. Our proposed scheme meets three key requirements of network virtualization: isolation, customization and efficient resource utilization. We analyze the details of this scheme and provide discrete event simulation results to support the analysis. Results show the efficacy in isolation and resource utilization and the flexibility of running different customized algorithms within slices on the same shared network equipment.
{"title":"PON bandwidth resource sharing schemes in a multi-operator scenario","authors":"Chengjun Li, W. Guo, Wei Wang, Weisheng Hu, Ming Xia","doi":"10.1109/ICCNC.2017.7876161","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876161","url":null,"abstract":"Passive optical network (PON) deployment requires significant capital and operational costs for operators to provide high network capacity and significant geographic coverage. Network sharing is desirable for operators to reduce the investment needed to deploy and operate PON networks. In this paper, we introduce a bandwidth resource sharing framework for XG-PONs among multiple operators. In this framework, each transmission convergence (TC) frame with fixed time slots (125us) is regarded as a bandwidth slice. We proposed two slice scheduling schemes for network infrastructure provider to assign slices to different operators. Our proposed scheme meets three key requirements of network virtualization: isolation, customization and efficient resource utilization. We analyze the details of this scheme and provide discrete event simulation results to support the analysis. Results show the efficacy in isolation and resource utilization and the flexibility of running different customized algorithms within slices on the same shared network equipment.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117032975","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876115
Mahdi H. Al-Badrawi, N. Kirsch, Bessam Z. Al-Jewad
In this paper, the filtering characteristics of Empirical Mode Decomposition (EMD) are used to create a blind and adaptive energy detector for single or multi-channel spectrum sensing. EMD is an adaptive tool that decomposes time-series signals into a set of modes called Intrinsic Mode Functions (IMF). Due to the EMD filtering behavior, the first IMF is mostly contaminated by noise from the received noisy signal. The proposed approach takes advantage of Cell Averaging Constant False Alarm Rate (CA-CFAR) as an optimal detector to enhance the probability of detection. Alternative to conventional CA-CFAR (which requires at least one nearby vacant channel for good noise estimation), the first IMF will be used as a training function for noise estimation purposes. Based on the first IMF characteristics in frequency domain, the noise floor of the received signal is estimated and a threshold is derived for a given false alarm rate. Simulations show the improvement of the proposed detector in comparison with other conventional detectors.
{"title":"An Intrinsic Mode Function based energy detector for spectrum sensing in cognitive radio","authors":"Mahdi H. Al-Badrawi, N. Kirsch, Bessam Z. Al-Jewad","doi":"10.1109/ICCNC.2017.7876115","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876115","url":null,"abstract":"In this paper, the filtering characteristics of Empirical Mode Decomposition (EMD) are used to create a blind and adaptive energy detector for single or multi-channel spectrum sensing. EMD is an adaptive tool that decomposes time-series signals into a set of modes called Intrinsic Mode Functions (IMF). Due to the EMD filtering behavior, the first IMF is mostly contaminated by noise from the received noisy signal. The proposed approach takes advantage of Cell Averaging Constant False Alarm Rate (CA-CFAR) as an optimal detector to enhance the probability of detection. Alternative to conventional CA-CFAR (which requires at least one nearby vacant channel for good noise estimation), the first IMF will be used as a training function for noise estimation purposes. Based on the first IMF characteristics in frequency domain, the noise floor of the received signal is estimated and a threshold is derived for a given false alarm rate. Simulations show the improvement of the proposed detector in comparison with other conventional detectors.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127386083","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876181
U. Hashmi, Arsalan Darbandi, A. Imran
Self-healing is a key desirable feature in emerging communication networks. While legacy self-healing mechanisms that are reactive in nature can minimize recovery time substantially, the recently conceived extremely low latency and high Quality of Experience (QoE) requirements call for self-healing mechanisms that are pro-active instead of reactive thereby enabling minimal recovery times. A corner stone in enabling proactive self-healing is predictive analytics of historical network failure logs (NFL). In current networks NFL data remains mostly dark, i.e., though they are stored but they are not exploited to their full potential. In this paper, we present a case study that investigates spatio-temporal trends in a large NFL database of a nationwide broadband operator. To discover hidden patterns in the data we leverage five different unsupervised pattern recognition and clustering along with density based outlier detection techniques namely: K-means clustering, Fuzzy C-means clustering, Local Outlier Factor, Local Outlier Probabilities and Kohonen's Self Organizing Maps. Results indicate that self-organizing maps with local outlier probabilities outperform K-means and Fuzzy C-means clustering in terms of sum of squared errors (SSE) and Davis Boulden index (DBI) values. Through an extensive data analysis leveraging a rich combination of the aforementioned techniques, we extract trends that can enable the operator to proactively tackle similar faults in future and improve QoE and recovery times and minimize operational costs, thereby paving the way towards proactive self-healing.
{"title":"Enabling proactive self-healing by data mining network failure logs","authors":"U. Hashmi, Arsalan Darbandi, A. Imran","doi":"10.1109/ICCNC.2017.7876181","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876181","url":null,"abstract":"Self-healing is a key desirable feature in emerging communication networks. While legacy self-healing mechanisms that are reactive in nature can minimize recovery time substantially, the recently conceived extremely low latency and high Quality of Experience (QoE) requirements call for self-healing mechanisms that are pro-active instead of reactive thereby enabling minimal recovery times. A corner stone in enabling proactive self-healing is predictive analytics of historical network failure logs (NFL). In current networks NFL data remains mostly dark, i.e., though they are stored but they are not exploited to their full potential. In this paper, we present a case study that investigates spatio-temporal trends in a large NFL database of a nationwide broadband operator. To discover hidden patterns in the data we leverage five different unsupervised pattern recognition and clustering along with density based outlier detection techniques namely: K-means clustering, Fuzzy C-means clustering, Local Outlier Factor, Local Outlier Probabilities and Kohonen's Self Organizing Maps. Results indicate that self-organizing maps with local outlier probabilities outperform K-means and Fuzzy C-means clustering in terms of sum of squared errors (SSE) and Davis Boulden index (DBI) values. Through an extensive data analysis leveraging a rich combination of the aforementioned techniques, we extract trends that can enable the operator to proactively tackle similar faults in future and improve QoE and recovery times and minimize operational costs, thereby paving the way towards proactive self-healing.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125241841","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}
Pub Date : 1900-01-01DOI: 10.1109/ICCNC.2017.7876155
Mihaela Lozonavu, Martha Vlachou-Konchylaki, Vincent A. Huang
In telecommunication network systems, there are a large number of interconnected components which also contain many subcomponents. Heavy rain, thunder or other factors can cause mal-function of the components or disconnections between the components which trigger alarms. Because of the interconnection of elements, triggered alarms may propagate to other components. This creates harsh challenges to network operators when it comes to root cause analysis. We address this issue by proposing a method on utilizing network alarms for automatic relation discovery between network nodes. By understanding how network elements or network problems are related to each other, a network operator can easily correlate the alarm events and treat clustered groups of alarms instead of specific events. In this study, we use the temporal and spatial aspects of alarm events to cluster network elements. Our results demonstrate that by analyzing the network alarms, a relationship graph showing the connections between different network elements and network problems can be automatically generated. Such relationship graphs can help network operators mining node dependencies and discovering insights within their network.
{"title":"Relation discovery of mobile network alarms with sequential pattern mining","authors":"Mihaela Lozonavu, Martha Vlachou-Konchylaki, Vincent A. Huang","doi":"10.1109/ICCNC.2017.7876155","DOIUrl":"https://doi.org/10.1109/ICCNC.2017.7876155","url":null,"abstract":"In telecommunication network systems, there are a large number of interconnected components which also contain many subcomponents. Heavy rain, thunder or other factors can cause mal-function of the components or disconnections between the components which trigger alarms. Because of the interconnection of elements, triggered alarms may propagate to other components. This creates harsh challenges to network operators when it comes to root cause analysis. We address this issue by proposing a method on utilizing network alarms for automatic relation discovery between network nodes. By understanding how network elements or network problems are related to each other, a network operator can easily correlate the alarm events and treat clustered groups of alarms instead of specific events. In this study, we use the temporal and spatial aspects of alarm events to cluster network elements. Our results demonstrate that by analyzing the network alarms, a relationship graph showing the connections between different network elements and network problems can be automatically generated. Such relationship graphs can help network operators mining node dependencies and discovering insights within their network.","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121813809","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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