Pub Date : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134073
Prakash Vaka, Feichen Shen, Mayanka Chandrashekar, Yugyung Lee
The growing affordability of smart phones and mobile devices has only added to this trend by encouraging prolonged durations of inactivity. In this paper, we present a middleware, called the Pervasive Middleware for Activity Recognition (PEMAR) that aims to increase the level of physical activity by creating a middleware for active games on mobile devices. For the PEMAR application, we present a human centered and adaptive approach that recognizes and learns human activities continuously by employing an activity library. The activity models in the library will be annotated with patterns of human activities and their contexts for general usage of activity models. This will be beneficial to many pervasive applications in terms of the availability of the accurate activity models as well as the reduction of burden for gesture training. The PEMAR middleware is composed of the following: (1) semantic models for human activity, (2) activity analysis, (3) activity recognition, (4) adaptation of motion models, and (5) motion based game applications. We evaluate the proposed PEMAR model in terms of its recognition accuracy and performance. In addition, we demonstrate the usage of the middleware through interactive activity gaming applications.
{"title":"PEMAR: A pervasive middleware for activity recognition with smart phones","authors":"Prakash Vaka, Feichen Shen, Mayanka Chandrashekar, Yugyung Lee","doi":"10.1109/PERCOMW.2015.7134073","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134073","url":null,"abstract":"The growing affordability of smart phones and mobile devices has only added to this trend by encouraging prolonged durations of inactivity. In this paper, we present a middleware, called the Pervasive Middleware for Activity Recognition (PEMAR) that aims to increase the level of physical activity by creating a middleware for active games on mobile devices. For the PEMAR application, we present a human centered and adaptive approach that recognizes and learns human activities continuously by employing an activity library. The activity models in the library will be annotated with patterns of human activities and their contexts for general usage of activity models. This will be beneficial to many pervasive applications in terms of the availability of the accurate activity models as well as the reduction of burden for gesture training. The PEMAR middleware is composed of the following: (1) semantic models for human activity, (2) activity analysis, (3) activity recognition, (4) adaptation of motion models, and (5) motion based game applications. We evaluate the proposed PEMAR model in terms of its recognition accuracy and performance. In addition, we demonstrate the usage of the middleware through interactive activity gaming applications.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123793314","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134014
Takuma Oide, Toru Abe, T. Suganuma
As miniaturized and high functional sensor devices like smartphones have spread, we can utilize large amounts of sensing data gathered from these devices. Participatory sensing is one of modern sensor-based application models in which users provide their sensing data including their personal data as well as get services. Current models, however, have limitations on flexible data flow based on provider's policy because it is difficult for providers to know how to be used their personal data when they upload data to clouds. In this paper, we propose a sensor-based application model without using clouds and discuss its advantages and drawbacks. We also simply design basic data flow protocols to negotiate conditions between providers and consumers and show their feasibility.
{"title":"A design of contract-oriented sensor application platform","authors":"Takuma Oide, Toru Abe, T. Suganuma","doi":"10.1109/PERCOMW.2015.7134014","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134014","url":null,"abstract":"As miniaturized and high functional sensor devices like smartphones have spread, we can utilize large amounts of sensing data gathered from these devices. Participatory sensing is one of modern sensor-based application models in which users provide their sensing data including their personal data as well as get services. Current models, however, have limitations on flexible data flow based on provider's policy because it is difficult for providers to know how to be used their personal data when they upload data to clouds. In this paper, we propose a sensor-based application model without using clouds and discuss its advantages and drawbacks. We also simply design basic data flow protocols to negotiate conditions between providers and consumers and show their feasibility.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130275706","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134033
Qian Zhao
Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of settings. Since most sensor nodes are powered by batteries, energy efficiency is critical. In this paper, we investigate problems that cause short battery life in WSNs from two perspectives. First, from the perspective of the execution forms of sensors in a sensor node, we note that simultaneous sensor activation generates high peak power consumption. Therefore, battery voltage drops quickly, and sensors stop working even though some useful charge remains in the battery. Second, from the perspective of wireless communication, communication distances must be considered in minimizing energy consumption. Moreover, the energy hole problem, which is known to cause non-uniform energy drains in many communication topologies, results in premature termination of entire networks. The goal of this paper, therefore, is to describe novel approaches for separately solving the aforementioned problems in order to extend the lifetime of WSNs.
{"title":"Extending the lifetime of wireless sensor networks from the perspective of sensor scheduling and wireless communication","authors":"Qian Zhao","doi":"10.1109/PERCOMW.2015.7134033","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134033","url":null,"abstract":"Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of settings. Since most sensor nodes are powered by batteries, energy efficiency is critical. In this paper, we investigate problems that cause short battery life in WSNs from two perspectives. First, from the perspective of the execution forms of sensors in a sensor node, we note that simultaneous sensor activation generates high peak power consumption. Therefore, battery voltage drops quickly, and sensors stop working even though some useful charge remains in the battery. Second, from the perspective of wireless communication, communication distances must be considered in minimizing energy consumption. Moreover, the energy hole problem, which is known to cause non-uniform energy drains in many communication topologies, results in premature termination of entire networks. The goal of this paper, therefore, is to describe novel approaches for separately solving the aforementioned problems in order to extend the lifetime of WSNs.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127776049","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134025
O. Günalp, C. Escoffier, P. Lalanda
Pervasive systems present stringent requirements that make software deployment especially challenging. The unknown and fluctuating environment in which pervasive applications are executed discards traditional approaches. As a result, there is an increasing need for a reproducible and dynamic deployment process. In last years, we developed several industrial pervasive platforms and applications. Based on these experiences we propose Rondo, a tool suite for deploying pervasive applications. Rondo includes a domain-specific language for declaratively describing applications, a deployment manager that can dynamically apply these descriptions and development tools for helping the description of applications. In this paper we present this tool suite and a set of deployment scenarios in which we validated our approach, including a web framework and a home automation platform.
{"title":"Demo abstract: Reproducible deployment of pervasive applications","authors":"O. Günalp, C. Escoffier, P. Lalanda","doi":"10.1109/PERCOMW.2015.7134025","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134025","url":null,"abstract":"Pervasive systems present stringent requirements that make software deployment especially challenging. The unknown and fluctuating environment in which pervasive applications are executed discards traditional approaches. As a result, there is an increasing need for a reproducible and dynamic deployment process. In last years, we developed several industrial pervasive platforms and applications. Based on these experiences we propose Rondo, a tool suite for deploying pervasive applications. Rondo includes a domain-specific language for declaratively describing applications, a deployment manager that can dynamically apply these descriptions and development tools for helping the description of applications. In this paper we present this tool suite and a set of deployment scenarios in which we validated our approach, including a web framework and a home automation platform.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128981087","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134023
P. Lalanda, J. Mccann, Catherine Hamon
In this paper, we present a novel learning environment that allows students to develop, execute, and test pervasive applications. This Java-based environment includes an execution platform built on top of Apache Felix OSGi and iPOJO, an Eclipse-based integrated environment, and a smart home simulator. Currently the environment challenges students to build five pervasive applications during the course. This system has been successfully tested by students enrolled in specially designed Masters courses.
在本文中，我们提出了一个新的学习环境，允许学生开发、执行和测试普及应用程序。这个基于java的环境包括一个构建在Apache Felix OSGi和iPOJO之上的执行平台、一个基于eclipse的集成环境和一个智能家居模拟器。目前的环境要求学生在课程中构建五个普及的应用程序。该系统已经在专门设计的硕士课程的学生中成功地进行了测试。
{"title":"Demo abstract: Teaching pervasing computing with an integrated environment","authors":"P. Lalanda, J. Mccann, Catherine Hamon","doi":"10.1109/PERCOMW.2015.7134023","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134023","url":null,"abstract":"In this paper, we present a novel learning environment that allows students to develop, execute, and test pervasive applications. This Java-based environment includes an execution platform built on top of Apache Felix OSGi and iPOJO, an Eclipse-based integrated environment, and a smart home simulator. Currently the environment challenges students to build five pervasive applications during the course. This system has been successfully tested by students enrolled in specially designed Masters courses.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127909305","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7133998
Francesco Restuccia, A. Saracino, Sajal K. Das, F. Martinelli
The Quality of Information (QoI) in Participatory Sensing (PS) systems largely depends on the location accuracy of participating users. However, users could easily provide false information through Location Spoofing Attacks (LSA). Existing PS systems are not able to efficiently validate the position of users in large-scale outdoor environments, thus being prone to reduced QoI. In this paper we present an efficient scheme to secure PS systems from LSAs. In particular, the user location is verified with the help of mobile WiFi hot spots (MHSs), which are users activating WiFi interface on their smart phones and waiting connections from nearby users, and thereby validating their position inside the sensing area. A reputation-based algorithm is proposed to rule out sensing reports of location-spoofing users, thereby increasing the reliability of the PS system. The effectiveness of our scheme is analyzed by real-world experiments and simulation study.
{"title":"Preserving QoI in participatory sensing by tackling location-spoofing through mobile WiFi hotspots","authors":"Francesco Restuccia, A. Saracino, Sajal K. Das, F. Martinelli","doi":"10.1109/PERCOMW.2015.7133998","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7133998","url":null,"abstract":"The Quality of Information (QoI) in Participatory Sensing (PS) systems largely depends on the location accuracy of participating users. However, users could easily provide false information through Location Spoofing Attacks (LSA). Existing PS systems are not able to efficiently validate the position of users in large-scale outdoor environments, thus being prone to reduced QoI. In this paper we present an efficient scheme to secure PS systems from LSAs. In particular, the user location is verified with the help of mobile WiFi hot spots (MHSs), which are users activating WiFi interface on their smart phones and waiting connections from nearby users, and thereby validating their position inside the sensing area. A reputation-based algorithm is proposed to rule out sensing reports of location-spoofing users, thereby increasing the reliability of the PS system. The effectiveness of our scheme is analyzed by real-world experiments and simulation study.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121482210","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7133985
Sviatoslav Edelev, Sunaina Nelamane Prasad, Hemanth Karnal, D. Hogrefe
The era of pervasive and ubiquitous computing has brought the learning far beyond the traditional classrooms to distant and mobile e-learning. Being easily accessible through time and place, e-learning systems rushed into masses and quickly appeared under the criticism as being uni-directional and fitting various learners under “one size”. In order to differentiate learners' needs and to apply the most suitable educational approach to the particular learner, researchers have introduced the Learner's context - a set of preferences defined by the learner's personal characteristics, technical capabilities of the user device, and the environment where learning takes place. Concerning the physical learning environment, the basic requirement is to distinguish between indoors and outdoors (IO). Existing approaches for IO-detection either apply pre-defined hard-coded thresholds to the sensing parameters or use machine-learning techniques. While the latter demonstrates a more adaptive approach for IO-detection over the former, decisions based on training data are not accurate once the environment is significantly changed, which is highly relevant for the modern learner with increased mobility. In this paper, we propose a novel knowledge-assisted location-adaptive technique for IO-detection in e-learning scenarios. The technique leverages data collected from various ambient sensors such as light, temperature, humidity, and noise and compares them with characteristics that the e-learning environment has at this point in time and in the current physical location being inside or outside. Here, we model the e-learning environment based on the empirical observations of the natural learning process augmented by the knowledge about current weather and environmental conditions collected from the weather web-service. The proposed approach is easily adaptable to the changing conditions in time and place with no need for the training phase. This work can be the first step towards robust location-adaptable IO-detection algorithms.
{"title":"Knowledge-assisted location-adaptive technique for indoor-outdoor detection in e-learning","authors":"Sviatoslav Edelev, Sunaina Nelamane Prasad, Hemanth Karnal, D. Hogrefe","doi":"10.1109/PERCOMW.2015.7133985","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7133985","url":null,"abstract":"The era of pervasive and ubiquitous computing has brought the learning far beyond the traditional classrooms to distant and mobile e-learning. Being easily accessible through time and place, e-learning systems rushed into masses and quickly appeared under the criticism as being uni-directional and fitting various learners under “one size”. In order to differentiate learners' needs and to apply the most suitable educational approach to the particular learner, researchers have introduced the Learner's context - a set of preferences defined by the learner's personal characteristics, technical capabilities of the user device, and the environment where learning takes place. Concerning the physical learning environment, the basic requirement is to distinguish between indoors and outdoors (IO). Existing approaches for IO-detection either apply pre-defined hard-coded thresholds to the sensing parameters or use machine-learning techniques. While the latter demonstrates a more adaptive approach for IO-detection over the former, decisions based on training data are not accurate once the environment is significantly changed, which is highly relevant for the modern learner with increased mobility. In this paper, we propose a novel knowledge-assisted location-adaptive technique for IO-detection in e-learning scenarios. The technique leverages data collected from various ambient sensors such as light, temperature, humidity, and noise and compares them with characteristics that the e-learning environment has at this point in time and in the current physical location being inside or outside. Here, we model the e-learning environment based on the empirical observations of the natural learning process augmented by the knowledge about current weather and environmental conditions collected from the weather web-service. The proposed approach is easily adaptable to the changing conditions in time and place with no need for the training phase. This work can be the first step towards robust location-adaptable IO-detection algorithms.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123081065","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134049
Alan Ferrari, D. Puccinelli, S. Giordano
Mocking is a standard technique in software testing; its main goal is to mimic the real object behavior in a controllable way. Recently, mocking techniques have been used in mobile environments to increase the user privacy and their goal is to allow users to select the kind of information they want to pass to the application (if real or randomly generated). This work presents MockingBird, a novel solution to mocking that uses recorded context-traces instead of randomly generated data, which is easily detected by applications. We also propose a flexible methodology to mock an Android application that does not require any changes at the operating system level and at the virtual machine level. MockingBird is a very promising solution; we are currently testing its performance and increasing its functionality.
{"title":"Managing your privacy in mobile applications with MockingBird","authors":"Alan Ferrari, D. Puccinelli, S. Giordano","doi":"10.1109/PERCOMW.2015.7134049","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134049","url":null,"abstract":"Mocking is a standard technique in software testing; its main goal is to mimic the real object behavior in a controllable way. Recently, mocking techniques have been used in mobile environments to increase the user privacy and their goal is to allow users to select the kind of information they want to pass to the application (if real or randomly generated). This work presents MockingBird, a novel solution to mocking that uses recorded context-traces instead of randomly generated data, which is easily detected by applications. We also propose a flexible methodology to mock an Android application that does not require any changes at the operating system level and at the virtual machine level. MockingBird is a very promising solution; we are currently testing its performance and increasing its functionality.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130743123","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134016
A. Miyamoto, Daniel J. Dubois, Yosuke Bando, Konosuke Watanabe, V. Bove
Under a situation where network infrastructures are interrupted by a devastating natural disaster, few communication channels left for survivors to request help are proximity-based communications on their mobile devices, for example Bluetooth and Wi-Fi direct. Since these technologies have a limited transmission range, rescue teams need to travel over a disaster area and physically come close to survivors to detect signals emitted from their devices. In this paper we demonstrate how to combine connectionless broadcast capabilities of existing mobile/wearable devices on the market, together with the high-mobility and proximity-based connectivity of drones (e.g., quadcopters), to help rescue teams discover signals from survivors.
{"title":"Demo abstract: A proximity-based aerial survivor locator based on connectionless broadcast","authors":"A. Miyamoto, Daniel J. Dubois, Yosuke Bando, Konosuke Watanabe, V. Bove","doi":"10.1109/PERCOMW.2015.7134016","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134016","url":null,"abstract":"Under a situation where network infrastructures are interrupted by a devastating natural disaster, few communication channels left for survivors to request help are proximity-based communications on their mobile devices, for example Bluetooth and Wi-Fi direct. Since these technologies have a limited transmission range, rescue teams need to travel over a disaster area and physically come close to survivors to detect signals emitted from their devices. In this paper we demonstrate how to combine connectionless broadcast capabilities of existing mobile/wearable devices on the market, together with the high-mobility and proximity-based connectivity of drones (e.g., quadcopters), to help rescue teams discover signals from survivors.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130979717","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 : 2015-03-23DOI: 10.1109/PERCOMW.2015.7134087
M. Casoni, Carlo Augusto Grazia, Martin Klapež, Natale Patriciello
When statistical multiplexing is used to provide connectivity to a number of client hosts through a high-delay link, the original TCP as well as TCP variants born to improve performance on those links often provide poor performance and sub-optimal QoS properties. To guarantee intra-protocol fairness, inter-protocol friendliness, low queues utilization and optimal throughput in mission-critical scenarios, Congestion Control Middleware Layer (C2ML) has been proposed as a tool for centralized and collaborative resource management. However, C2ML offers only very limited security guarantees. Because emergencies may be natural or man-provoked, in the latter case there may be interest to cut out legitimate users from the communication networks that support disaster recovery operations. In this paper we present Queue Rate Management (QRM), an Active Queue Management scheme able to provide protection from Resource Exhaustion Attacks in scenarios where access to the shared link is controlled by C2ML; the proposed algorithm checks whether a node is exceeding its allowed rate, and consequently decides whether to keep or drop packets coming from that node. We mathematically prove that with QRM the gateway queue size can never exceed the Bandwidth-Delay Product of the channel. Furthermore, we use the ns-3 simulator to compare QRM with CoDel and RED, showing how QRM provides better performance in terms of both throughput and QoS guarantees when employed with C2ML.
{"title":"Towards emergency networks security with per-flow queue rate management","authors":"M. Casoni, Carlo Augusto Grazia, Martin Klapež, Natale Patriciello","doi":"10.1109/PERCOMW.2015.7134087","DOIUrl":"https://doi.org/10.1109/PERCOMW.2015.7134087","url":null,"abstract":"When statistical multiplexing is used to provide connectivity to a number of client hosts through a high-delay link, the original TCP as well as TCP variants born to improve performance on those links often provide poor performance and sub-optimal QoS properties. To guarantee intra-protocol fairness, inter-protocol friendliness, low queues utilization and optimal throughput in mission-critical scenarios, Congestion Control Middleware Layer (C2ML) has been proposed as a tool for centralized and collaborative resource management. However, C2ML offers only very limited security guarantees. Because emergencies may be natural or man-provoked, in the latter case there may be interest to cut out legitimate users from the communication networks that support disaster recovery operations. In this paper we present Queue Rate Management (QRM), an Active Queue Management scheme able to provide protection from Resource Exhaustion Attacks in scenarios where access to the shared link is controlled by C2ML; the proposed algorithm checks whether a node is exceeding its allowed rate, and consequently decides whether to keep or drop packets coming from that node. We mathematically prove that with QRM the gateway queue size can never exceed the Bandwidth-Delay Product of the channel. Furthermore, we use the ns-3 simulator to compare QRM with CoDel and RED, showing how QRM provides better performance in terms of both throughput and QoS guarantees when employed with C2ML.","PeriodicalId":180959,"journal":{"name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131108925","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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