Pub Date : 2017-05-01DOI: 10.23919/INM.2017.7987287
Young-Jin Kim, J. Simsarian, M. Thottan
For interconnection between geographically-separated data centers, network carriers typically implement multiple optical paths in a wide-area network. For example, when transmission wavelengths have 100 Gb/s granularity, three 100 Gb/s wavelength paths are provisioned to satisfy a customer demand of 300 Gb/s. Over the multiple provisioned paths, interconnection traffic is typically distributed using per-flow hashing, which results in an uneven distribution of traffic caused by hash collisions. For a relatively-few number of high-bandwidth traffic flows (> 1 Gb/s) between data center locations, per-flow hashing can perform poorly in terms of bandwidth utilization and availability. We propose new software-defined traffic load balancer, SD-TLB, that performs measurement-based flow distribution over multiple optical paths, with an implicit impairment detection method using per-port statistics on available paths and a flow redistributor that is immediately adjusted to the current network state. While our approach does not provide the same level of protection as 1+1 optical protection, it can provide the necessary redundancy for data center inter-connection at a lower cost. We experimentally implement the SD-TLB using ASIC-based switches and open virtual switches interconnected by wavelength-division multiplexed transport network test-bed. The experimental results show that SD-TLB outperforms today's hashing-based alternatives in balancing, throughput, and restoration in the presence of outages and impairments and as a result achieves improved cost-efficiency.
{"title":"Software-defined traffic load balancing for cost-effective data center interconnection service","authors":"Young-Jin Kim, J. Simsarian, M. Thottan","doi":"10.23919/INM.2017.7987287","DOIUrl":"https://doi.org/10.23919/INM.2017.7987287","url":null,"abstract":"For interconnection between geographically-separated data centers, network carriers typically implement multiple optical paths in a wide-area network. For example, when transmission wavelengths have 100 Gb/s granularity, three 100 Gb/s wavelength paths are provisioned to satisfy a customer demand of 300 Gb/s. Over the multiple provisioned paths, interconnection traffic is typically distributed using per-flow hashing, which results in an uneven distribution of traffic caused by hash collisions. For a relatively-few number of high-bandwidth traffic flows (> 1 Gb/s) between data center locations, per-flow hashing can perform poorly in terms of bandwidth utilization and availability. We propose new software-defined traffic load balancer, SD-TLB, that performs measurement-based flow distribution over multiple optical paths, with an implicit impairment detection method using per-port statistics on available paths and a flow redistributor that is immediately adjusted to the current network state. While our approach does not provide the same level of protection as 1+1 optical protection, it can provide the necessary redundancy for data center inter-connection at a lower cost. We experimentally implement the SD-TLB using ASIC-based switches and open virtual switches interconnected by wavelength-division multiplexed transport network test-bed. The experimental results show that SD-TLB outperforms today's hashing-based alternatives in balancing, throughput, and restoration in the presence of outages and impairments and as a result achieves improved cost-efficiency.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130780847","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 : 2017-05-01DOI: 10.23919/INM.2017.7987263
Satoru Kobayashi, K. Fukuda, H. Esaki
Network log message (e.g., syslog) is valuable information to detect unexpected or anomalous behavior in a large scale network. However, pinpointing failures and their causes is not an easy problem because of a huge amount of system log data in daily operation. In this study, we propose a method extracting failures and their causes from network syslog data. The main idea of the method relies on causal inference that reconstructs causality of network events from a set of the time series of events. Causal inference allows us to reduce the number of correlated events by chance, thus it outputs more plausible causal events than a traditional cross-correlation based approach. We apply our method to 15 months network syslog data obtained in a nation-wide academic network in Japan. Our method significantly reduces the number of pseudo correlated events compared with the traditional method. Also, through two case studies and comparison with trouble ticket data, we demonstrate the effectiveness of our method for network operation.
{"title":"Mining causes of network events in log data with causal inference","authors":"Satoru Kobayashi, K. Fukuda, H. Esaki","doi":"10.23919/INM.2017.7987263","DOIUrl":"https://doi.org/10.23919/INM.2017.7987263","url":null,"abstract":"Network log message (e.g., syslog) is valuable information to detect unexpected or anomalous behavior in a large scale network. However, pinpointing failures and their causes is not an easy problem because of a huge amount of system log data in daily operation. In this study, we propose a method extracting failures and their causes from network syslog data. The main idea of the method relies on causal inference that reconstructs causality of network events from a set of the time series of events. Causal inference allows us to reduce the number of correlated events by chance, thus it outputs more plausible causal events than a traditional cross-correlation based approach. We apply our method to 15 months network syslog data obtained in a nation-wide academic network in Japan. Our method significantly reduces the number of pseudo correlated events compared with the traditional method. Also, through two case studies and comparison with trouble ticket data, we demonstrate the effectiveness of our method for network operation.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130831018","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 : 2017-05-01DOI: 10.23919/INM.2017.7987440
Pulkit Rustgi, Carol J. Fung, Bahman Rashidi, Bridget T. McInnes
In current Android systems, the application recommendation function is an important feature that users can use to find a similar application to replace a targeted one. The current recommendation system provided through Google and the Google Play store presumably recommends applications similar to a target application while accounting for the popularity of each application. However, it does not take the security features of each application or users preferences into consideration when doing so. In this paper, we propose DroidVisor, an Android tool that provides users with fine-grained and customizable application recommendations. Compared to the Google store recommendation function, DroidVisor does not only use the similarity to a preselected target application, but also considers other metrics such as popularity, security, and usability. More specifically, DroidVisor provides an interface for users to configure the weight of each metric and a recommendation algorithm that generates a list of recommended applications based on the combined scores. We evaluate our proposed criteria and the quality of recommendation through use case studies. Finally, we present our findings through a discussion of accuracy as well as possible ways to improve our recommendation results.
{"title":"DroidVisor: An Android secure application recommendation system","authors":"Pulkit Rustgi, Carol J. Fung, Bahman Rashidi, Bridget T. McInnes","doi":"10.23919/INM.2017.7987440","DOIUrl":"https://doi.org/10.23919/INM.2017.7987440","url":null,"abstract":"In current Android systems, the application recommendation function is an important feature that users can use to find a similar application to replace a targeted one. The current recommendation system provided through Google and the Google Play store presumably recommends applications similar to a target application while accounting for the popularity of each application. However, it does not take the security features of each application or users preferences into consideration when doing so. In this paper, we propose DroidVisor, an Android tool that provides users with fine-grained and customizable application recommendations. Compared to the Google store recommendation function, DroidVisor does not only use the similarity to a preselected target application, but also considers other metrics such as popularity, security, and usability. More specifically, DroidVisor provides an interface for users to configure the weight of each metric and a recommendation algorithm that generates a list of recommended applications based on the combined scores. We evaluate our proposed criteria and the quality of recommendation through use case studies. Finally, we present our findings through a discussion of accuracy as well as possible ways to improve our recommendation results.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123152750","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 : 2017-05-01DOI: 10.23919/INM.2017.7987372
Swatesh Pakhare, D. Medhi
It is a challenging task for network administrators to properly monitor and manage an institution's incoming and outgoing network traffic patterns. While NetFlow is useful to gather flow-level data, its feature is limited to traditional flow-level information such as the source IP address, destination IP address, source port number, destination port number, and the protocol type. Thus, if we are to understand geographic dynamics of any flow connected to hosts at an institution from the outside world, it is not currently possible with NetFlow. To address the geo-location information of such flows, we developed the tool, GoLCoNDa, for use by campus network administrators. This tool allows the correlation of IP addresses with the geo-location information to visualize the geo-location of incoming and outgoing flows. Our tool handles millions of records quickly.
{"title":"GoLCoNDa: Geo-IP Lookup for campus network NetFlow data","authors":"Swatesh Pakhare, D. Medhi","doi":"10.23919/INM.2017.7987372","DOIUrl":"https://doi.org/10.23919/INM.2017.7987372","url":null,"abstract":"It is a challenging task for network administrators to properly monitor and manage an institution's incoming and outgoing network traffic patterns. While NetFlow is useful to gather flow-level data, its feature is limited to traditional flow-level information such as the source IP address, destination IP address, source port number, destination port number, and the protocol type. Thus, if we are to understand geographic dynamics of any flow connected to hosts at an institution from the outside world, it is not currently possible with NetFlow. To address the geo-location information of such flows, we developed the tool, GoLCoNDa, for use by campus network administrators. This tool allows the correlation of IP addresses with the geo-location information to visualize the geo-location of incoming and outgoing flows. Our tool handles millions of records quickly.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131124670","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 : 2017-05-01DOI: 10.23919/INM.2017.7987430
T. Hossfeld, M. Fiedler, Jorgen Gustafsson
Most Quality of Experience (QoE) studies report only the mean opinion scores (MOS) and existing models typically map Quality of Service (QoS) parameters to the MOS. However, service providers may be interested in the share of users that are not at all satisfied, and their corresponding QoE levels. From the QoE management point of view, the circumstances leading to the QoE levels perceived by a certain percentage of users, e.g. the 10% most annoyed users, are of utmost importance. Proper metrics are the 10%-quantiles of QoE values. Knowledge of those quantiles helps service providers to estimate the need for countermeasures in order to prevent annoyed users from churning on one hand, and to avoid overprovisioning on the other hand. The contribution of this paper is the derivation of quantiles from existing MOS-QoS relations. This allows to reuse existing subjective MOS results and MOS models without rerunning the experiments. We consider exemplary the IQX model (describing the MOS-QoS relation) for the derivation of the quantile-QoS relation. A practical guideline for the computation of the quantiles is provided.
{"title":"Betas: Deriving quantiles from MOS-QoS relations of IQX models for QoE management","authors":"T. Hossfeld, M. Fiedler, Jorgen Gustafsson","doi":"10.23919/INM.2017.7987430","DOIUrl":"https://doi.org/10.23919/INM.2017.7987430","url":null,"abstract":"Most Quality of Experience (QoE) studies report only the mean opinion scores (MOS) and existing models typically map Quality of Service (QoS) parameters to the MOS. However, service providers may be interested in the share of users that are not at all satisfied, and their corresponding QoE levels. From the QoE management point of view, the circumstances leading to the QoE levels perceived by a certain percentage of users, e.g. the 10% most annoyed users, are of utmost importance. Proper metrics are the 10%-quantiles of QoE values. Knowledge of those quantiles helps service providers to estimate the need for countermeasures in order to prevent annoyed users from churning on one hand, and to avoid overprovisioning on the other hand. The contribution of this paper is the derivation of quantiles from existing MOS-QoS relations. This allows to reuse existing subjective MOS results and MOS models without rerunning the experiments. We consider exemplary the IQX model (describing the MOS-QoS relation) for the derivation of the quantile-QoS relation. A practical guideline for the computation of the quantiles is provided.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133483906","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 : 2017-05-01DOI: 10.23919/INM.2017.7987310
Teodora Sandra Buda, H. Assem, Lei Xu
Proactive anomaly detection refers to anticipating anomalies or abnormal patterns within a dataset in a timely manner. Discovering anomalies such as failures or degradations before their occurrence can lead to great benefits such as the ability to avoid the anomaly happening by applying some corrective measures in advance (e.g., allocating more resources for a nearly saturated system in a data centre). In this paper we address the proactive anomaly detection problem through machine learning and in particular ensemble learning. We propose an early Anomaly Detection Ensemble approach, ADE, which combines results of state-of-the-art anomaly detection techniques in order to provide more accurate results than each single technique. Moreover, we utilise a a weighted anomaly window as ground truth for training the model, which prioritises early detection in order to discover anomalies in a timely manner. Various strategies are explored for generating ground truth windows. Results show that ADE shows improvements of at least 10% in earliest detection score compared to each individual technique across all datasets considered. The technique proposed detected anomalies in advance up to ∼16h before they actually occurred.
{"title":"ADE: An ensemble approach for early Anomaly Detection","authors":"Teodora Sandra Buda, H. Assem, Lei Xu","doi":"10.23919/INM.2017.7987310","DOIUrl":"https://doi.org/10.23919/INM.2017.7987310","url":null,"abstract":"Proactive anomaly detection refers to anticipating anomalies or abnormal patterns within a dataset in a timely manner. Discovering anomalies such as failures or degradations before their occurrence can lead to great benefits such as the ability to avoid the anomaly happening by applying some corrective measures in advance (e.g., allocating more resources for a nearly saturated system in a data centre). In this paper we address the proactive anomaly detection problem through machine learning and in particular ensemble learning. We propose an early Anomaly Detection Ensemble approach, ADE, which combines results of state-of-the-art anomaly detection techniques in order to provide more accurate results than each single technique. Moreover, we utilise a a weighted anomaly window as ground truth for training the model, which prioritises early detection in order to discover anomalies in a timely manner. Various strategies are explored for generating ground truth windows. Results show that ADE shows improvements of at least 10% in earliest detection score compared to each individual technique across all datasets considered. The technique proposed detected anomalies in advance up to ∼16h before they actually occurred.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134216404","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 : 2017-05-01DOI: 10.23919/INM.2017.7987315
Jiacong Li, Ying Wang, Wenjing Li, Xue-song Qiu
software-defined networking (SDN) uses a centralized control plane to manage the whole network. If the scale of the network is large, it is necessary to divide it into multiple domains. Since the network scale becomes larger, the probability of failure occurrences is higher. Therefore, it is important to guarantee the control plane resilience in multi-domain SDN. However, the existing approaches cannot store the network state in real time, and do not consider the backup controllers placement problem in multi-domain SDN. In order to ensure the resilience of the control plane in multi-domain SDN, we propose a sharing data store and backup controllers based approach. Sharing data store is used to ensure that each master controller has a view of the whole network and data store can save the network state during the failure time. The sharing backup controllers are used to guarantee the resilience of control plane with minimum cost. Simulations show that our approach can use as less backup controllers as possible to ensure the resilience of control plane.
SDN (software-defined networking)通过集中控制平面对整个网络进行管理。如果网络规模较大，则需要将其划分为多个域。随着网络规模的扩大，故障发生的概率也越来越高。因此，在多域SDN中保证控制平面的弹性是非常重要的。然而，现有的方法不能实时存储网络状态，也没有考虑多域SDN中备份控制器的放置问题。为了保证多域SDN控制平面的弹性，提出了一种基于共享数据存储和备份控制器的方法。共享数据存储是为了保证每个主控制器都能看到整个网络，并且数据存储可以保存故障时的网络状态。采用共享备份控制器，以最小的成本保证控制平面的弹性。仿真结果表明，该方法可以使用尽可能少的备份控制器来保证控制平面的弹性。
{"title":"Sharing data store and backup controllers for resilient control plane in multi-domain SDN","authors":"Jiacong Li, Ying Wang, Wenjing Li, Xue-song Qiu","doi":"10.23919/INM.2017.7987315","DOIUrl":"https://doi.org/10.23919/INM.2017.7987315","url":null,"abstract":"software-defined networking (SDN) uses a centralized control plane to manage the whole network. If the scale of the network is large, it is necessary to divide it into multiple domains. Since the network scale becomes larger, the probability of failure occurrences is higher. Therefore, it is important to guarantee the control plane resilience in multi-domain SDN. However, the existing approaches cannot store the network state in real time, and do not consider the backup controllers placement problem in multi-domain SDN. In order to ensure the resilience of the control plane in multi-domain SDN, we propose a sharing data store and backup controllers based approach. Sharing data store is used to ensure that each master controller has a view of the whole network and data store can save the network state during the failure time. The sharing backup controllers are used to guarantee the resilience of control plane with minimum cost. Simulations show that our approach can use as less backup controllers as possible to ensure the resilience of control plane.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114372661","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 : 2017-05-01DOI: 10.23919/INM.2017.7987306
Liam Fallon, J. Keeney, S. Meer
The formal structure of information models and the controlled manner of accessing and changing such models brings both flexibility and control when managing network elements. However, keeping information models synchronized and consistent across network elements and management systems is a challenging task. Today this problem is exasperated with the advent of ephemeral network functions and elements and also by the need for distributed scalable cooperating management functions running in containerized cloud deployments.
{"title":"Distributed Management Information Models","authors":"Liam Fallon, J. Keeney, S. Meer","doi":"10.23919/INM.2017.7987306","DOIUrl":"https://doi.org/10.23919/INM.2017.7987306","url":null,"abstract":"The formal structure of information models and the controlled manner of accessing and changing such models brings both flexibility and control when managing network elements. However, keeping information models synchronized and consistent across network elements and management systems is a challenging task. Today this problem is exasperated with the advent of ephemeral network functions and elements and also by the need for distributed scalable cooperating management functions running in containerized cloud deployments.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114849592","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 : 2017-05-01DOI: 10.23919/INM.2017.7987319
Binh Nguyen, Nakjung Choi, M. Thottan, J. Merwe
In future mobile networks, e.g., 5G, emerging IoT services are expected to support billions of IoT devices with unique characteristics and traffic patterns. In this paper we propose an SDN-based IoT Mobile Edge Cloud Architecture (SIMECA1) which can deploy diverse IoT services at the mobile edge by leveraging distributed, lightweight control and data planes optimized for IoT communications. We prototyped our architecture using a pre-commercial mobile networking software stack to demonstrate the feasibility and utility of our approach.
{"title":"SIMECA: SDN-based IoT Mobile Edge Cloud Architecture","authors":"Binh Nguyen, Nakjung Choi, M. Thottan, J. Merwe","doi":"10.23919/INM.2017.7987319","DOIUrl":"https://doi.org/10.23919/INM.2017.7987319","url":null,"abstract":"In future mobile networks, e.g., 5G, emerging IoT services are expected to support billions of IoT devices with unique characteristics and traffic patterns. In this paper we propose an SDN-based IoT Mobile Edge Cloud Architecture (SIMECA1) which can deploy diverse IoT services at the mobile edge by leveraging distributed, lightweight control and data planes optimized for IoT communications. We prototyped our architecture using a pre-commercial mobile networking software stack to demonstrate the feasibility and utility of our approach.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123097901","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 : 2017-05-01DOI: 10.23919/INM.2017.7987348
Tareq Hayajna, Miochdel Kaldoching
To increase mobile ad hoc network reliability, virtually decrease the packets loss to zero, and to support multimedia communications multi-route is required. In order to ensure the availability of two routes, node density must be above a certain value. To the best our knowledge, this paper is the first paper that mathematically determines the required node density to ensure the availability of two routes between any randomly chosen source and destination pair in mobile ad hoc networks with random waypoint mobility model. To this end, a complete probabilistic model is provided. The obtained results reveal that the increase in the node density exponentially increases the probability of having two routes. This exponential increase is limited by a certain threshold, after this threshold the increase is negligible. An interesting conclusion from this paper is that the required node densities to ensure two routes connectivity are the same for both mobile nodes moving according to the generalized random waypoint mobility model and static nodes that are uniformly distributed in the network area. This work can be used by mobile ad hoc network designers to study the network reliability and connectivity.
{"title":"Ensuring two routes connectivity in mobile ad hoc networks with Random Waypoint mobility","authors":"Tareq Hayajna, Miochdel Kaldoching","doi":"10.23919/INM.2017.7987348","DOIUrl":"https://doi.org/10.23919/INM.2017.7987348","url":null,"abstract":"To increase mobile ad hoc network reliability, virtually decrease the packets loss to zero, and to support multimedia communications multi-route is required. In order to ensure the availability of two routes, node density must be above a certain value. To the best our knowledge, this paper is the first paper that mathematically determines the required node density to ensure the availability of two routes between any randomly chosen source and destination pair in mobile ad hoc networks with random waypoint mobility model. To this end, a complete probabilistic model is provided. The obtained results reveal that the increase in the node density exponentially increases the probability of having two routes. This exponential increase is limited by a certain threshold, after this threshold the increase is negligible. An interesting conclusion from this paper is that the required node densities to ensure two routes connectivity are the same for both mobile nodes moving according to the generalized random waypoint mobility model and static nodes that are uniformly distributed in the network area. This work can be used by mobile ad hoc network designers to study the network reliability and connectivity.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858656","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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