2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)最新文献_第4页

Scalable, Memory-efficient Pending Interest Table of Named Data Networking 可扩展、内存高效的命名数据网络未决兴趣表

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00071

Divya Saxena, V. Raychoudhury

{"title":"Scalable, Memory-efficient Pending Interest Table of Named Data Networking","authors":"Divya Saxena, V. Raychoudhury","doi":"10.1109/MASS50613.2020.00071","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00071","url":null,"abstract":"Named Data Networking (NDN) is a future Internet paradigm which allows user to retrieve and distribute content using their application names. Each NDN router maintains the state of each request packet in the Pending Interest Table (PIT) until corresponding data packet returns. The use of application name, i.e., variable-length key of unbounded length for communication instead of IP address increases memory consumption and lookup cost at the router. Therefore, the PIT should be able to store millions/billions of entries into on-chip memory. However, traditional hash and trie based methods cannot meet these requirements separately. In this paper, we present a scalable and memory-efficient name encoding based lookup scheme (CRT-PIT) leveraging the benefits of both hash and trie data structures for implementing the PIT at NDN forwarding daemon. In CRT-PIT, we calculate the fixed-length encoded names of the content name and then, encoded names are stored in the concurrent path-compressed trie to reduce the storage and lookup latency requirement by not maintaining the redundant information. Extensive experiments show that CRTPIT consumes only 4.84 MB memory for one million names which is an order of magnitude improvement over the baseline solutions.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133070136","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}

引用次数: 1

Service Function Chain Deployment with Guaranteed Resilience 弹性保证的业务功能链部署

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00077

Yang Chen, Jie Wu

{"title":"Service Function Chain Deployment with Guaranteed Resilience","authors":"Yang Chen, Jie Wu","doi":"10.1109/MASS50613.2020.00077","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00077","url":null,"abstract":"Network Function Virtualization (NFV) transforms the implementation of network functions from expensive hardwares to software middleboxes. These software middleboxes, also called Virtual Network Functions (VNFs), are executed on virtualization platforms, which makes them more prone to error compared to dedicated hardwares. One effective way of ensuring VNF robustness is to provision redundancy in the form of deploying backup instances. Flows usually request to be processed by a service chain, consisting of multiple chained VNFs in some order. This paper considers both the resilient VNF deployment and the routing of flows. We deploy both active and backup VNF instances while guaranteeing the required VNF service resilience. Our objective is to minimize the total expected transmission delay of all flows when the probabilistic prior failure information is given. We first formulate our problem mathematically. We discuss the solution for the general network setting. Then, we simplify some setups and propose performance-guaranteed solutions in various scenarios with detailed approximation ratio analysis: for the case of a single flow without backup instances, we propose four optimal solutions corresponding to the settings of link transmission delay and server capacity; for the case of a single flow with backup instances, we extend the algorithms; for the case of two flows without backup instances, we propose efficient algorithms with approximation ratios inspired by the solutions for a single flow.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114323331","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}

引用次数: 1

TinyCSI: A Rapid Development Framework for CSI-based Sensing Applications TinyCSI:基于csi的传感应用的快速开发框架

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00073

Yuxiang Lin, Wei Dong, Bingji Li, Yi Gao

{"title":"TinyCSI: A Rapid Development Framework for CSI-based Sensing Applications","authors":"Yuxiang Lin, Wei Dong, Bingji Li, Yi Gao","doi":"10.1109/MASS50613.2020.00073","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00073","url":null,"abstract":"Channel State Information (CSI)-based wireless sensing has recently attracted extensive attention from both academia and industry. However, it is still challenging and time-consuming to develop a CSI-based sensing application due to the use of complex signal processing algorithms and the requirements of accuracy and responsiveness. In this paper, we present TinyCSI, a rapid development framework for CSI-based sensing applications. With TinyCSI, developers only need to write a main script to determine the CSI collection settings and a callback function to process the collected CSI signals using the well-abstracted Matlab/C-based library, without dealing with the connection/transmission details of the sensing nodes. To achieve fast performance tuning, TinyCSI also provides three working modes for different deployment requirements: a remote mode for fast iteration of the sensing algorithms and their parameters, an efficient mode for making full use of computing resources and improving sensing responsiveness, and a standalone mode for offline running sensing systems on individual nodes. We implement three representative demos and conduct real-world user studies to show the workflows and benefits of TinyCSI. Experimental results show that TinyCSI helps reduce the lines of code significantly compared to the original implementation. More importantly, the efficient mode can generate an optimal computing resource allocation solution and significantly improve the sensing responsiveness.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726174","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}

引用次数: 1

Routing via Multiple Paths and Multiple Technologies in IoT Networks: Proof-of-Concept Demonstration 物联网网络中的多路径和多技术路由:概念验证演示

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00072

Vijeth J. Kotagi, S. P. Vinayaka, C. Murthy

{"title":"Routing via Multiple Paths and Multiple Technologies in IoT Networks: Proof-of-Concept Demonstration","authors":"Vijeth J. Kotagi, S. P. Vinayaka, C. Murthy","doi":"10.1109/MASS50613.2020.00072","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00072","url":null,"abstract":"With the invent of many new wireless technologies, the concept of Internet of Things (IoT) is becoming a reality and is generating an enormous amount of data collectively. To handle routing of this massive traffic in a wireless network we require specialized, cost-effective routing devices and protocols. Transmitting IoT data over a wireless back-haul network using a single technology may lead to low throughput and increased delay due to high congestion. Critical IoT applications may not tolerate such a low throughput and high delay. To tackle this problem, in this paper, we propose Routing via Multiple Paths and Multiple Technologies (RMPMT) protocol to realize the concept of Parallel opportunistic Routing (POR) where multiple paths and multiple technologies are exploited in an IoT network to route the data. We have implemented the proposed RMPMT protocol by mounting multiple wireless interfaces (technologies) on Raspberry Pi and measured the effectiveness of the proposed protocol by transmitting data in real-time. Furthermore, we also propose a split window automatic repeat request to provide guaranteed packet delivery in multi-path and multi-technology environment.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125006502","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}

引用次数: 1

A Data-Driven Reinforcement Learning Based Multi-Objective Route Recommendation System 基于数据驱动强化学习的多目标路径推荐系统

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00023

Ankur Sarker, Haiying Shen, Kamran Kowsari

{"title":"A Data-Driven Reinforcement Learning Based Multi-Objective Route Recommendation System","authors":"Ankur Sarker, Haiying Shen, Kamran Kowsari","doi":"10.1109/MASS50613.2020.00023","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00023","url":null,"abstract":"Driving route recommendation systems have been becoming popular due to high demands on such systems and their high socio-economic impacts. Existing route recommendation systems cannot provide a well-balanced route by considering the user preference on multiple criteria or make route recommendation in a short time. This paper presents a multi-objective route recommendation system considering three different attributes (i.e., fuel consumption, travel time, and air quality). The proposed route recommendation system uses the Q-learning based reinforcement learning algorithm to leverage the available datasets to make route recommendations in a timely manner. First, we build a road network graph using a publicly available map service (i.e., OpenStreetMap) and other real-world datasets on traffic, weather, and air substances. Second, we utilize the existing predictors for air quality, travel time, and fuel consumption estimations to update the road network graph periodically. Third, we design the route recommendation system using the Q-learning reinforcement learning approach considering the given user’s preference for travel time, fuel consumption, and air quality. To evaluate the proposed approach’s performance, we conduct experimental evaluations based on the real-world datasets with publicly available map service.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129710523","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}

引用次数: 4

Autonomous Reckless Driving Detection Using Deep Learning on Embedded GPUs 基于嵌入式gpu的深度学习自动鲁莽驾驶检测

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00063

Taewook Heo, Woojin Nam, Jeongyeup Paek, Jeonggil Ko

{"title":"Autonomous Reckless Driving Detection Using Deep Learning on Embedded GPUs","authors":"Taewook Heo, Woojin Nam, Jeongyeup Paek, Jeonggil Ko","doi":"10.1109/MASS50613.2020.00063","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00063","url":null,"abstract":"Reckless driving is dangerous, and must be monitored, detected, and law-enforced to assure road safety. For this purpose, this work presents an embedded system for monitoring and detecting reckless driving activities on the road autonomously in real-time. Using an embedded GPU (eGPU) platform, a camera, and a combination of light-weight deep learning models, we design a system that can identify abnormal vehicle motions on the road. Our system analyzes discrete per-frame images from vehicle detection algorithms, and creates a continuous trace of a vehicle’s motion trajectory. While doing so, a virtual grid is generated on the road to obtain positions of vehicles with less overhead and accurately track a vehicle’s movement even with low frame rate (5fps) videos. Vehicle’s motion trajectory is then compared against the surrounding to identify abnormal behavior through driving activity classification, which can be provided to law enforcement personnel for final validation. The key challenge is the fundamental resource constraints of embedded platforms, and we design algorithms to overcome their limitations. Evaluation results show that our scheme can wellextract the horizontal and vertical movements of a vehicle (100% recall and 67% precision) and show the potential for truly autonomous reckless driving activity detection systems.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"72 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120849916","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}

引用次数: 3

Request and Share then Assign (RASTA): Task Assignment for Networked Multi-Robot Teams 请求和共享然后分配(RASTA):网络化多机器人团队的任务分配

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00058

Sam Friedman, Qi Han

引用次数: 0

ZCNET: Achieving High Capacity in Low Power Wide Area Networks ZCNET:实现低功耗广域网的高容量

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00090

Zhenghao Zhang

引用次数: 5

Online Trip Planning for Public Bike Systems 公共自行车系统的在线出行规划

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00069

Jiawei Mu, Jianhui Zhang, Tianyu Zhang, Bei Zhao, Wanqing Zhang

{"title":"Online Trip Planning for Public Bike Systems","authors":"Jiawei Mu, Jianhui Zhang, Tianyu Zhang, Bei Zhao, Wanqing Zhang","doi":"10.1109/MASS50613.2020.00069","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00069","url":null,"abstract":"Public Bike System (PBS) not only provides convenient travel service but also alleviates the last-mile problem. With the increasing awareness of environmental protection and green commuting, people prefer to use the public bike as transportation for short-distance travel. However, the explosion of users in PBS leads to new congestion problems. To relieve the pressure of PBS, there are many types of research on system prediction, operation, and trip planning. However, there is few work focusing on the online trip planning problem. To study the case, we propose an Online Matching Trip Planning algorithm (OMTP), and we prove the theoretical lower bound of OMTP is 1 - 1/e. And then, we consider the short-term conflicts among users and design an Online Group Trip Planning algorithm (OGTP). We design two kinds of experiments- Generated Data Based and Real Data Based. In the generated data based experiment, we reveal the impact of different parameters with the generated trip data. In the real data based experiment, we validate our proposed algorithms with the real trip data set in New York City. The results show that OMTP and OGTP save time per trip on average.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115912141","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}

引用次数: 0

FSDM: Fast Recovery Saturation Attack Detection and Mitigation Framework in SDN FSDM: SDN快速恢复饱和攻击检测和缓解框架

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00048

Xuanbo Huang, Kaiping Xue, Yitao Xing, Dingwen Hu, Ruidong Li, Qibin Sun

{"title":"FSDM: Fast Recovery Saturation Attack Detection and Mitigation Framework in SDN","authors":"Xuanbo Huang, Kaiping Xue, Yitao Xing, Dingwen Hu, Ruidong Li, Qibin Sun","doi":"10.1109/MASS50613.2020.00048","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00048","url":null,"abstract":"The whole Software-Defined Networking (SDN) system might be out of service when the control plane is overloaded by control plane saturation attacks. In this attack, a malicious host can manipulate massive table-miss packets to exhaust the control plane resources. Even though many studies have focused on this problem, systems still suffer from more influenced switches because of centralized mitigation policies, and long recovery delay because of the remaining attack flows. To solve these problems, we propose FSDM, a Fast recovery Saturation attack Detection and Mitigation framework. For detection, FSDM extracts the distribution of Control Channel Occupation Rate (CCOR) to detect the attack and locates the port that attackers come from. For mitigation, with the attacker’s location and distributed Mitigation Agents, FSDM adopts different policies to migrate or block attack flows, which influences fewer switches and protects the control plane from resource exhaustion. Besides, to reduce the system recovery delay, FSDM equips a novel functional module called Force_Checking, which enables the whole system to quickly clean up the remaining attack flows and recovery faster. Finally, we conducted extensive experiments, which show that, with the increasing of attack PPS (Packets Per Second), FSDM only suffers a minor recovery delay increase. Compared with traditional methods without cleaning up remaining flows, FSDM saves more than 81% of ping RTT under attack rate ranged from 1000 to 4000 PPS, and successfully reduced the delay of 87% of HTTP requests time under large attack rate ranged from 5000 to 30000 PPS.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132029556","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}

引用次数: 11