Pub Date : 2020-11-16DOI: 10.1109/LCN48667.2020.9314829
F. Yucel, E. Bulut
Finding efficient task assignments is key to the success of mobile crowdsensing campaigns. Many studies in the literature focus on this problem and propose solutions that optimize the goals of mobile crowdsensing platform, but disregard user preferences. On the other hand, in a few recent studies that consider user preferences, workers are assigned a single task at a time, and the effect of these assignments to their prospective utilities is ignored. In this paper, we address these issues and study the task assignment problem considering both the user preferences and impact of each task assignment on the long-term utility of workers given the spatio-temporal characteristics of tasks. We propose a dynamic programming based task assignment algorithm that guarantees the satisfaction of users with their assignments. Through simulations, we compare it with a state-of-the-art algorithm and show the superiority of our algorithm in various aspects.
{"title":"Time-dependent Stable Task Assignment in Participatory Mobile Crowdsensing","authors":"F. Yucel, E. Bulut","doi":"10.1109/LCN48667.2020.9314829","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314829","url":null,"abstract":"Finding efficient task assignments is key to the success of mobile crowdsensing campaigns. Many studies in the literature focus on this problem and propose solutions that optimize the goals of mobile crowdsensing platform, but disregard user preferences. On the other hand, in a few recent studies that consider user preferences, workers are assigned a single task at a time, and the effect of these assignments to their prospective utilities is ignored. In this paper, we address these issues and study the task assignment problem considering both the user preferences and impact of each task assignment on the long-term utility of workers given the spatio-temporal characteristics of tasks. We propose a dynamic programming based task assignment algorithm that guarantees the satisfaction of users with their assignments. Through simulations, we compare it with a state-of-the-art algorithm and show the superiority of our algorithm in various aspects.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116759993","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 : 2020-11-16DOI: 10.1109/lcn48667.2020.9314845
{"title":"LCN 2020 Sponsors and Supporters","authors":"","doi":"10.1109/lcn48667.2020.9314845","DOIUrl":"https://doi.org/10.1109/lcn48667.2020.9314845","url":null,"abstract":"","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550033","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 : 2020-11-16DOI: 10.1109/lcn48667.2020.9314790
{"title":"LCN 2020 Keynote 3 - Real-Time Distributed Contextual Intelligence in the Era of Ubiquitous Connectivity","authors":"","doi":"10.1109/lcn48667.2020.9314790","DOIUrl":"https://doi.org/10.1109/lcn48667.2020.9314790","url":null,"abstract":"","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124495905","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314855
M. Tummala, Sudipta Saha
Many-to-many data sharing protocols serve a very important role in many information management services. For low power decentralised systems such as IoT/WSN, the protocols need to be both fast and energy efficient. In this paper, we present our work on improving the speed and energy efficiency of an existing many-to-many data sharing protocol MiniCast. MiniCast uses a large and fixed TDMA schedule to carry out the data sharing operation. However, depending on the structure of the network, a large part of the schedule may remain unused leading to wastage of time and energy. We reduce this wastage by using different schedules at different time points in the data sharing process. Through simulation based study we show that such simple variations in schedule can bring up to 48% and 35% improvement in the latency and radio-on time, respectively, over the base protocol.
{"title":"Concurrent Transmission Based Data Sharing with Run-Time Variation of TDMA Schedule","authors":"M. Tummala, Sudipta Saha","doi":"10.1109/LCN48667.2020.9314855","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314855","url":null,"abstract":"Many-to-many data sharing protocols serve a very important role in many information management services. For low power decentralised systems such as IoT/WSN, the protocols need to be both fast and energy efficient. In this paper, we present our work on improving the speed and energy efficiency of an existing many-to-many data sharing protocol MiniCast. MiniCast uses a large and fixed TDMA schedule to carry out the data sharing operation. However, depending on the structure of the network, a large part of the schedule may remain unused leading to wastage of time and energy. We reduce this wastage by using different schedules at different time points in the data sharing process. Through simulation based study we show that such simple variations in schedule can bring up to 48% and 35% improvement in the latency and radio-on time, respectively, over the base protocol.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763051","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314795
Jing Li, W. Liang, Zichuan Xu, Wanlei Zhou
We are embracing an era of Internet of Things (IoTs). However, the latency brought by unstable wireless networks and computation failures caused by limited resources on IoT devices seriously impacts the quality of service of user experienced. To address these shortcomings, the Mobile Edge Computing (MEC) platform provides a promising solution for the service provisioning of IoT applications, where edge-clouds (cloudlets) are co-located with wireless access points in the proximity of IoT devices, and the service response latency can be significantly reduced. Meanwhile, each IoT application usually imposes a service function chain enforcement for its data transmission, which consists of different service functions in a specified order, and each data packet transfer in the network from the gateways of IoT devices to the destination must pass through each of the service functions in order.In this paper, we study IoT-driven service provisioning in an MEC network for various IoT applications with service function chain requirements, where an IoT application consists of multiple data streams from different IoT sources that will be uploaded to the MEC network for aggregation, processing, and storage. We first formulate a novel cost minimization problem for IoT-driven service provisioning in MEC networks. We then show that the problem is NP-hard, and propose an IoT-driven service provisioning framework for IoT applications, which consists of streaming data uploading from multiple IoT sources to the MEC network, data stream aggregation and routing, and Virtual Network Function (VNF) instance placement and sharing in cloudlets in the MEC network. In addition, we devise an efficient algorithm for the problem, built upon the proposed service framework. We finally evaluate the performance of the proposed algorithm through experimental simulations. Experimental results demonstrate that the proposed algorithm is promising, compared with the lower bound on the optimal solution of the problem and another comparison heuristic.
{"title":"Service Provisioning for IoT Applications with Multiple Sources in Mobile Edge Computing","authors":"Jing Li, W. Liang, Zichuan Xu, Wanlei Zhou","doi":"10.1109/LCN48667.2020.9314795","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314795","url":null,"abstract":"We are embracing an era of Internet of Things (IoTs). However, the latency brought by unstable wireless networks and computation failures caused by limited resources on IoT devices seriously impacts the quality of service of user experienced. To address these shortcomings, the Mobile Edge Computing (MEC) platform provides a promising solution for the service provisioning of IoT applications, where edge-clouds (cloudlets) are co-located with wireless access points in the proximity of IoT devices, and the service response latency can be significantly reduced. Meanwhile, each IoT application usually imposes a service function chain enforcement for its data transmission, which consists of different service functions in a specified order, and each data packet transfer in the network from the gateways of IoT devices to the destination must pass through each of the service functions in order.In this paper, we study IoT-driven service provisioning in an MEC network for various IoT applications with service function chain requirements, where an IoT application consists of multiple data streams from different IoT sources that will be uploaded to the MEC network for aggregation, processing, and storage. We first formulate a novel cost minimization problem for IoT-driven service provisioning in MEC networks. We then show that the problem is NP-hard, and propose an IoT-driven service provisioning framework for IoT applications, which consists of streaming data uploading from multiple IoT sources to the MEC network, data stream aggregation and routing, and Virtual Network Function (VNF) instance placement and sharing in cloudlets in the MEC network. In addition, we devise an efficient algorithm for the problem, built upon the proposed service framework. We finally evaluate the performance of the proposed algorithm through experimental simulations. Experimental results demonstrate that the proposed algorithm is promising, compared with the lower bound on the optimal solution of the problem and another comparison heuristic.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126338722","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314799
Sina Keshvadi, Mehdi Karamollahi, C. Williamson
Over the past decade, Instant Messaging (IM) apps have become an extremely popular tool for billions of people to communicate online. In this paper, we use a combination of active and passive measurement techniques to study one week of IM app traffic on a large campus edge network. Despite the challenges of end-to-end encryption, user privacy, NAT, DHCP, and high traffic volumes, we identify the key characteristics of four popular IM apps: Facebook Messenger, Google Hangouts, Snapchat, and WeChat. The main observations from our study indicate a rich ecosystem of IM apps, many of which exhibit strong diurnal patterns, complex user interactions, and heavy-tailed distributions for connection durations and transfer sizes. Collectively, these four IM apps contribute about 650 GB of daily traffic volume on our campus network.
{"title":"Traffic Characterization of Instant Messaging Apps: A Campus-Level View","authors":"Sina Keshvadi, Mehdi Karamollahi, C. Williamson","doi":"10.1109/LCN48667.2020.9314799","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314799","url":null,"abstract":"Over the past decade, Instant Messaging (IM) apps have become an extremely popular tool for billions of people to communicate online. In this paper, we use a combination of active and passive measurement techniques to study one week of IM app traffic on a large campus edge network. Despite the challenges of end-to-end encryption, user privacy, NAT, DHCP, and high traffic volumes, we identify the key characteristics of four popular IM apps: Facebook Messenger, Google Hangouts, Snapchat, and WeChat. The main observations from our study indicate a rich ecosystem of IM apps, many of which exhibit strong diurnal patterns, complex user interactions, and heavy-tailed distributions for connection durations and transfer sizes. Collectively, these four IM apps contribute about 650 GB of daily traffic volume on our campus network.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130219743","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314836
Connor Egbert, Fawaz Alhenaki, Daryl Johnson
Covert communication enables the hidden transfer of data. Unlike encrypted communication, where the goal is to make the transmitted data unreadable, covert communication aims to hide the existence of the communication. There have been research efforts on developing and preventing numerous types of channels. We present a novel storage covert channel by leveraging a music streaming platform and take an in depth look into its inner workings. The channel aims to enable data transmission between one sender and multiple receivers. The channel, presented in two different methods of encoding, utilizes a public music streaming platform playlists and encodes data by selectively adding music tracks. The first method of encoding leverages song names while the second uses data embedded within the song track id. We were successful in implementing both encoding schemes, thus demonstrating the covert channels’ feasibility.
{"title":"Leveraging a Music Streaming Platform in Establishing a Novel Storage Covert Channel","authors":"Connor Egbert, Fawaz Alhenaki, Daryl Johnson","doi":"10.1109/LCN48667.2020.9314836","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314836","url":null,"abstract":"Covert communication enables the hidden transfer of data. Unlike encrypted communication, where the goal is to make the transmitted data unreadable, covert communication aims to hide the existence of the communication. There have been research efforts on developing and preventing numerous types of channels. We present a novel storage covert channel by leveraging a music streaming platform and take an in depth look into its inner workings. The channel aims to enable data transmission between one sender and multiple receivers. The channel, presented in two different methods of encoding, utilizes a public music streaming platform playlists and encodes data by selectively adding music tracks. The first method of encoding leverages song names while the second uses data embedded within the song track id. We were successful in implementing both encoding schemes, thus demonstrating the covert channels’ feasibility.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130259741","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314791
Samira Chouikhi, L. Khoukhi, S. Ayed, Marc Lemercier
In this paper, we investigate the concept of reputation to improve the resistance of vehicular networks against malicious and misbehaving vehicles. We propose a robust reputation management system, which consists of a model for reputation calculation and a credibility model to enhance network efficiency. The reputation score or value reflects the behavior of a vehicle towards other vehicles and network services (selfish, cooperative, malicious, misbehaving, etc.); while the credibility of vehicles is used to determine whether a reputation score given by a vehicle is correct to deal with malicious vehicles that use reputation calculation to spoil the network operation. We first describe how the reputation score of each vehicle is determined. Then, we introduce a non-cooperative game, where each vehicle aims to maximize its credibility. The effectiveness of the proposed model is demonstrated through extensive simulations.
{"title":"An Efficient Reputation Management Model based on Game Theory for Vehicular Networks","authors":"Samira Chouikhi, L. Khoukhi, S. Ayed, Marc Lemercier","doi":"10.1109/LCN48667.2020.9314791","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314791","url":null,"abstract":"In this paper, we investigate the concept of reputation to improve the resistance of vehicular networks against malicious and misbehaving vehicles. We propose a robust reputation management system, which consists of a model for reputation calculation and a credibility model to enhance network efficiency. The reputation score or value reflects the behavior of a vehicle towards other vehicles and network services (selfish, cooperative, malicious, misbehaving, etc.); while the credibility of vehicles is used to determine whether a reputation score given by a vehicle is correct to deal with malicious vehicles that use reputation calculation to spoil the network operation. We first describe how the reputation score of each vehicle is determined. Then, we introduce a non-cooperative game, where each vehicle aims to maximize its credibility. The effectiveness of the proposed model is demonstrated through extensive simulations.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132293600","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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