On-air access of individual sensor node (called remote control) is an indispensable function in operational wireless sensor networks, for purposes like network management and real-time information delivery. To realize reliable and efficient remote control in a wireless sensor network (WSN), however, is extremely challenging, due to the stringent resource constraints and intrinsically unrealizable wireless communication. In this paper, we propose TeleAdjusting, a ready-to-use protocol to remotely control any individual node in a WSN. We develop a coding scheme for addressing on the cost-optimal reverse routing tree. In the address of each node, all its upstream relaying nodes are implicitly encoded. Then through a distributed prefix matching process between the local address and the destination address, a packet used for remote control is forwarded along a cost-optimal path. Moreover, TeleAdjusting incorporates opportunistic forwarding into the addressing process, so as to improve the network performance in terms of reliability and energy efficiency. We implement TeleAdjusting with TinyOS and evaluate its performance through extensive simulations and experiments. The results demonstrate that compared to the existing protocols, TeleAdjusting can provide high performance of remote control, which is as reliable as network-wide flooding and much more efficient than remote control through a pre-determined path.
{"title":"Tele Adjusting: Using Path Coding and Opportunistic Forwarding for Remote Control in WSNs","authors":"Daibo Liu, Zhichao Cao, Xiaopei Wu, Yuan He, Xiaoyu Ji, Mengshu Hou","doi":"10.1109/ICDCS.2015.78","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.78","url":null,"abstract":"On-air access of individual sensor node (called remote control) is an indispensable function in operational wireless sensor networks, for purposes like network management and real-time information delivery. To realize reliable and efficient remote control in a wireless sensor network (WSN), however, is extremely challenging, due to the stringent resource constraints and intrinsically unrealizable wireless communication. In this paper, we propose TeleAdjusting, a ready-to-use protocol to remotely control any individual node in a WSN. We develop a coding scheme for addressing on the cost-optimal reverse routing tree. In the address of each node, all its upstream relaying nodes are implicitly encoded. Then through a distributed prefix matching process between the local address and the destination address, a packet used for remote control is forwarded along a cost-optimal path. Moreover, TeleAdjusting incorporates opportunistic forwarding into the addressing process, so as to improve the network performance in terms of reliability and energy efficiency. We implement TeleAdjusting with TinyOS and evaluate its performance through extensive simulations and experiments. The results demonstrate that compared to the existing protocols, TeleAdjusting can provide high performance of remote control, which is as reliable as network-wide flooding and much more efficient than remote control through a pre-determined path.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127202592","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}
Unlink ability and accountability are conflicting yet critical requirements for on-line transactions that need to be addressed in order to preserve users' privacy as well as to protect service providers in today identity ecosystems. In this poster paper we introduce a pseudonymous identity management system in which users can carry out unlink able on-line transactions without having to disclose their actual identity to the service providers. At the same time, the service providers have strong assurance about the authenticity of the identity and credentials. In our approach, users' identity is cryptographically encoded in pseudonymous identity tokens issued by trusted identity providers. Our system includes a lightweight policy language which enables users and service providers to express their requirements pertaining to pseudonymous identity verification and a suite of protocols based on zero-knowledge-proofs which enables the fulfillment of these requirements.
{"title":"RahasNym: Protecting against Linkability in the Digital Identity Ecosystem","authors":"Hasini Gunasinghe, E. Bertino","doi":"10.1109/ICDCS.2015.102","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.102","url":null,"abstract":"Unlink ability and accountability are conflicting yet critical requirements for on-line transactions that need to be addressed in order to preserve users' privacy as well as to protect service providers in today identity ecosystems. In this poster paper we introduce a pseudonymous identity management system in which users can carry out unlink able on-line transactions without having to disclose their actual identity to the service providers. At the same time, the service providers have strong assurance about the authenticity of the identity and credentials. In our approach, users' identity is cryptographically encoded in pseudonymous identity tokens issued by trusted identity providers. Our system includes a lightweight policy language which enables users and service providers to express their requirements pertaining to pseudonymous identity verification and a suite of protocols based on zero-knowledge-proofs which enables the fulfillment of these requirements.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124799229","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}
Mobile peer-to-peer applications require devices to network themselves on-the-fly to communicate directly with each another. This paper presents mQual, a framework to help create such networks that meet different application requirements, and is able to adjust the network to ensure that these requirements are met in dynamic environments. Our prototype mQual extends the current WiFi-Direct in Android, and the experimental results suggests that mobile apps built using mQual outperform those built using WiFi-Direct.
{"title":"mQual: A Mobile Peer-to-Peer Network Framework Supporting Quality of Service","authors":"Hongxu Zhang, Yufeng Wang, C. C. Tan, Yifan Zhang","doi":"10.1109/ICDCS.2015.93","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.93","url":null,"abstract":"Mobile peer-to-peer applications require devices to network themselves on-the-fly to communicate directly with each another. This paper presents mQual, a framework to help create such networks that meet different application requirements, and is able to adjust the network to ensure that these requirements are met in dynamic environments. Our prototype mQual extends the current WiFi-Direct in Android, and the experimental results suggests that mobile apps built using mQual outperform those built using WiFi-Direct.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125911079","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}
Lin Cui, Fung Po Tso, D. Pezaros, Weijia Jia, Wei Zhao
Policies play an important role in network configuration and, therefore, in offering secure and high performance services, especially over multi-tenant Cloud Data Center (DC) environments. At the same time, elastic resource provisioning through virtualization often disregards policy requirements, assuming that the policy implementation is handled by the underlying network infrastructure. In this paper, we define PLAN, a Policy-Aware virtual machine management scheme to jointly consider DC communication cost reduction through Virtual Machine (VM) migration while meeting network policy requirements.
{"title":"Policy-Aware Virtual Machine Management in Data Center Networks","authors":"Lin Cui, Fung Po Tso, D. Pezaros, Weijia Jia, Wei Zhao","doi":"10.1109/ICDCS.2015.81","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.81","url":null,"abstract":"Policies play an important role in network configuration and, therefore, in offering secure and high performance services, especially over multi-tenant Cloud Data Center (DC) environments. At the same time, elastic resource provisioning through virtualization often disregards policy requirements, assuming that the policy implementation is handled by the underlying network infrastructure. In this paper, we define PLAN, a Policy-Aware virtual machine management scheme to jointly consider DC communication cost reduction through Virtual Machine (VM) migration while meeting network policy requirements.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126347737","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}
This paper presents an Operational Transformation (OT) technique, named CSOT (Cloud Storage OT), that supports real-time file synchronization in cloud storage and achieve well-defined consistent combined-effects of concurrent file manipulation operations. We have developed and used a comprehensive suite of concurrency testing cases to derive and compare the results produced by CSOT and three industrial cloud storage systems and made interesting discoveries.
{"title":"Operational Transformation for Real-Time Synchronization of Cloud Storage","authors":"Agustina, Chengzheng Sun","doi":"10.1109/ICDCS.2015.90","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.90","url":null,"abstract":"This paper presents an Operational Transformation (OT) technique, named CSOT (Cloud Storage OT), that supports real-time file synchronization in cloud storage and achieve well-defined consistent combined-effects of concurrent file manipulation operations. We have developed and used a comprehensive suite of concurrency testing cases to derive and compare the results produced by CSOT and three industrial cloud storage systems and made interesting discoveries.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130042525","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}
Kazuya Sakai, Min-Te Sun, Wei-Shinn Ku, Jie Wu, T. Lai
The speedy advancement in computer hardware has caused data encryption to no longer be a 100% safe solution for secure communications. To battle with adversaries, a countermeasure is to avoid message routing through certain insecure areas, e.g., Malicious countries and nodes. To this end, avoidance routing has been proposed over the past few years. However, the existing avoidance protocols are single-path-based, which means that there must be a safe path such that no adversary is in the proximity of the whole path. This condition is difficult to satisfy. As a result, routing opportunities based on the existing avoidance schemes are limited. To tackle this issue, we propose an avoidance routing framework, namely Multi-Path Avoidance Routing (MPAR). In our approach, a source node first encodes a message into k different pieces, and each piece is sent via k different paths. The destination can assemble the original message easily, while an adversary cannot recover the original message unless she obtains all the pieces. We prove that the coding scheme achieves perfect secrecy against eavesdropping under the condition that an adversary has incomplete information regarding the message. The simulation results validate that the proposed MPAR protocol achieves its design goals.
{"title":"Multi-path Based Avoidance Routing in Wireless Networks","authors":"Kazuya Sakai, Min-Te Sun, Wei-Shinn Ku, Jie Wu, T. Lai","doi":"10.1109/ICDCS.2015.77","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.77","url":null,"abstract":"The speedy advancement in computer hardware has caused data encryption to no longer be a 100% safe solution for secure communications. To battle with adversaries, a countermeasure is to avoid message routing through certain insecure areas, e.g., Malicious countries and nodes. To this end, avoidance routing has been proposed over the past few years. However, the existing avoidance protocols are single-path-based, which means that there must be a safe path such that no adversary is in the proximity of the whole path. This condition is difficult to satisfy. As a result, routing opportunities based on the existing avoidance schemes are limited. To tackle this issue, we propose an avoidance routing framework, namely Multi-Path Avoidance Routing (MPAR). In our approach, a source node first encodes a message into k different pieces, and each piece is sent via k different paths. The destination can assemble the original message easily, while an adversary cannot recover the original message unless she obtains all the pieces. We prove that the coding scheme achieves perfect secrecy against eavesdropping under the condition that an adversary has incomplete information regarding the message. The simulation results validate that the proposed MPAR protocol achieves its design goals.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130146609","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}
We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings, provide a lower bound for the object availability they offer, show that these placements offer availability that is c-competitive with optimal, propose an efficient algorithm for computing combinations of t-packings that maximize their availability lower bound, and provide parameter selection strategies to concretely instantiate our schemes for different system sizes. We compare the availability offered by our approach to that of random replica placement, owing to the popularity of the latter approach in previous work. After quantifying the availability offered by random replica placement in our model, we show that our combinatorial strategy yields placements with better availability than random replica placement for many realistic parameter values.
{"title":"Replica Placement for Availability in the Worst Case","authors":"Peng Li, Debin Gao, M. Reiter","doi":"10.1109/ICDCS.2015.67","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.67","url":null,"abstract":"We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings, provide a lower bound for the object availability they offer, show that these placements offer availability that is c-competitive with optimal, propose an efficient algorithm for computing combinations of t-packings that maximize their availability lower bound, and provide parameter selection strategies to concretely instantiate our schemes for different system sizes. We compare the availability offered by our approach to that of random replica placement, owing to the popularity of the latter approach in previous work. After quantifying the availability offered by random replica placement in our model, we show that our combinatorial strategy yields placements with better availability than random replica placement for many realistic parameter values.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134348764","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}
Jialong Zhang, Sabyasachi Saha, G. Gu, Sung-Ju Lee, M. Mellia
HTTP is a popular channel for malware to communicate with malicious servers (e.g., Command & Control, drive-by download, drop-zone), as well as to attack benign servers. By utilizing HTTP requests, malware easily disguises itself under a large amount of benign HTTP traffic. Thus, identifying malicious HTTP activities is challenging. We leverage an insight that cyber criminals are increasingly using dynamic malicious infrastructures with multiple servers to be efficient and anonymous in (i) malware distribution (using redirectors and exploit servers), (ii) control (using C&C servers) and (iii) monetization (using payment servers), and (iv) being robust against server takedowns (using multiple backups for each type of servers). Instead of focusing on detecting individual malicious domains, we propose a complementary approach to identify a group of closely related servers that are potentially involved in the same malware campaign, which we term as Associated Server Herd (ASH). Our solution, SMASH (Systematic Mining of Associated Server Herds), utilizes an unsupervised framework to infer malware ASHs by systematically mining the relations among all servers from multiple dimensions. We build a prototype system of SMASH and evaluate it with traces from a large ISP. The result shows that SMASH successfully infers a large number of previously undetected malicious servers and possible zero-day attacks, with low false positives. We believe the inferred ASHs provide a better global view of the attack campaign that may not be easily captured by detecting only individual servers.
{"title":"Systematic Mining of Associated Server Herds for Malware Campaign Discovery","authors":"Jialong Zhang, Sabyasachi Saha, G. Gu, Sung-Ju Lee, M. Mellia","doi":"10.1109/ICDCS.2015.70","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.70","url":null,"abstract":"HTTP is a popular channel for malware to communicate with malicious servers (e.g., Command & Control, drive-by download, drop-zone), as well as to attack benign servers. By utilizing HTTP requests, malware easily disguises itself under a large amount of benign HTTP traffic. Thus, identifying malicious HTTP activities is challenging. We leverage an insight that cyber criminals are increasingly using dynamic malicious infrastructures with multiple servers to be efficient and anonymous in (i) malware distribution (using redirectors and exploit servers), (ii) control (using C&C servers) and (iii) monetization (using payment servers), and (iv) being robust against server takedowns (using multiple backups for each type of servers). Instead of focusing on detecting individual malicious domains, we propose a complementary approach to identify a group of closely related servers that are potentially involved in the same malware campaign, which we term as Associated Server Herd (ASH). Our solution, SMASH (Systematic Mining of Associated Server Herds), utilizes an unsupervised framework to infer malware ASHs by systematically mining the relations among all servers from multiple dimensions. We build a prototype system of SMASH and evaluate it with traces from a large ISP. The result shows that SMASH successfully infers a large number of previously undetected malicious servers and possible zero-day attacks, with low false positives. We believe the inferred ASHs provide a better global view of the attack campaign that may not be easily captured by detecting only individual servers.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114662342","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}
Rui Han, Junwei Wang, Siguang Huang, Chenrong Shao, Shulin Zhan, Jianfeng Zhan, J. L. Vázquez-Poletti
Large-scale interactive services usually divide requests into multiple sub-requests and distribute them to a large number of server components for parallel execution. Hence the tail latency (i.e. The slowest component's latency) of these components determines the overall service latency. On a cloud platform, each component shares and competes node resources such as caches and I/O bandwidths with its co-located jobs, hence inevitably suffering from their performance interference. In this paper, we study the short-running jobs in a 12k-node Google cluster to illustrate the dynamic resource demands of these jobs, resulting in both individual components' latency variability over time and across different nodes and hence posing a major challenge to maintain low tail latency. Given this motivation, this paper introduces a dynamic and interference-aware scheduler for large-scale, parallel cloud services. At each scheduling interval, it collects workload and resource contention information of a running service, and predicts both the component latency on different nodes and the overall service performance. Based on the predicted performance, the scheduler identifies straggling components and conducts near-optimal component-node allocations to adapt to the changing workloads and performance interferences. We demonstrate that, using realistic workloads, the proposed approach achieves significant reductions in tail latency compared to the basic approach without scheduling.
{"title":"Interference-Aware Component Scheduling for Reducing Tail Latency in Cloud Interactive Services","authors":"Rui Han, Junwei Wang, Siguang Huang, Chenrong Shao, Shulin Zhan, Jianfeng Zhan, J. L. Vázquez-Poletti","doi":"10.1109/ICDCS.2015.88","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.88","url":null,"abstract":"Large-scale interactive services usually divide requests into multiple sub-requests and distribute them to a large number of server components for parallel execution. Hence the tail latency (i.e. The slowest component's latency) of these components determines the overall service latency. On a cloud platform, each component shares and competes node resources such as caches and I/O bandwidths with its co-located jobs, hence inevitably suffering from their performance interference. In this paper, we study the short-running jobs in a 12k-node Google cluster to illustrate the dynamic resource demands of these jobs, resulting in both individual components' latency variability over time and across different nodes and hence posing a major challenge to maintain low tail latency. Given this motivation, this paper introduces a dynamic and interference-aware scheduler for large-scale, parallel cloud services. At each scheduling interval, it collects workload and resource contention information of a running service, and predicts both the component latency on different nodes and the overall service performance. Based on the predicted performance, the scheduler identifies straggling components and conducts near-optimal component-node allocations to adapt to the changing workloads and performance interferences. We demonstrate that, using realistic workloads, the proposed approach achieves significant reductions in tail latency compared to the basic approach without scheduling.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117304233","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}
Lack of an accurate and low-cost method to reconstruct indoor maps is the main reason behind the current sporadic availability of digital building floor plans. The conventional approach using professional equipment is very costly and only available in the most popular areas. In this paper, we propose and demonstrate CrowdMap, a crowd sourcing system utilizing sensor-rich video data from mobile users for indoor floor plan reconstruction with low-cost. The key idea of CrowdMap is to first jointly leverage crowd sourced sensory and video data to track user movements, then use the inferred user motion traces and context of the image to produce an accurate floor plan. In particular, we exploit the sequential relationship between each consecutive frame abstracted from the video to improve system performance. Our experiments in three college buildings show that CrowdMap achieves a precision of hallway shape around 88%, a recall around 93% and a F-measure around 90%. In addition, we achieve on average 9.8% room area error and on average 6.5% room aspect ratio error. The evaluation result demonstrates a significant improvement of accuracy compared with other crowd sourcing floor plan reconstruction systems.
{"title":"Crowd Map: Accurate Reconstruction of Indoor Floor Plans from Crowdsourced Sensor-Rich Videos","authors":"Si Chen, M. Li, K. Ren, C. Qiao","doi":"10.1109/ICDCS.2015.9","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.9","url":null,"abstract":"Lack of an accurate and low-cost method to reconstruct indoor maps is the main reason behind the current sporadic availability of digital building floor plans. The conventional approach using professional equipment is very costly and only available in the most popular areas. In this paper, we propose and demonstrate CrowdMap, a crowd sourcing system utilizing sensor-rich video data from mobile users for indoor floor plan reconstruction with low-cost. The key idea of CrowdMap is to first jointly leverage crowd sourced sensory and video data to track user movements, then use the inferred user motion traces and context of the image to produce an accurate floor plan. In particular, we exploit the sequential relationship between each consecutive frame abstracted from the video to improve system performance. Our experiments in three college buildings show that CrowdMap achieves a precision of hallway shape around 88%, a recall around 93% and a F-measure around 90%. In addition, we achieve on average 9.8% room area error and on average 6.5% room aspect ratio error. The evaluation result demonstrates a significant improvement of accuracy compared with other crowd sourcing floor plan reconstruction systems.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129962114","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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