Pub Date : 2014-12-01DOI: 10.1109/PADSW.2014.7097862
Qingqing Dang, Shengen Yan, Ren Wu
Integral image, also known as summed area table is a two-dimensional table generated from an input image. Each entry in the table stores the sum of all pixels which locate on the top-left corner of the entry in the input image. Integral image is a very popular and important algorithm in computer vision and computer graphics applications. Especially in real-time computer vision, it is usually used to accelerate calculating the sum of a rectangular area. Integral image algorithm is memory-bounded. There are two typical existed image integral algorithms on GPUs. The first is the Scan-Scan algorithm. The second is the Scan-Transpose-Scan algorithm, which adopts three steps to generate the integral image. The first and the third steps are scan. In order to achieve coalesced global memory access in the third step, a transpose step is added. In this paper, we propose a novel blocked integral algorithm, which has three stages. The first stage is intra-block reduction. The second stage is auxiliary matrix scan and the third stage is intra-block scan. Compared with the Scan-Scan algorithm, our proposed scheme reduces the global memory accesses. At the same time, less local synchronizations and less load imbalance are achieved. Compared with the Scan-Transpose-Scan algorithm, our proposed algorithm only needs about half of the global memory accesses. At the same time, coalesced memory access is achieved. We implemented these three algorithms with OpenCL so that they can run on both Nvidia and AMD GPUs. We also designed an auto-tuning framework to search optimal parameters for different size of input matrix on those two platforms. The experiment result shows that our proposed algorithm gets the best performance compared with the two existed typical integral algorithms.
{"title":"A fast integral image generation algorithm on GPUs","authors":"Qingqing Dang, Shengen Yan, Ren Wu","doi":"10.1109/PADSW.2014.7097862","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097862","url":null,"abstract":"Integral image, also known as summed area table is a two-dimensional table generated from an input image. Each entry in the table stores the sum of all pixels which locate on the top-left corner of the entry in the input image. Integral image is a very popular and important algorithm in computer vision and computer graphics applications. Especially in real-time computer vision, it is usually used to accelerate calculating the sum of a rectangular area. Integral image algorithm is memory-bounded. There are two typical existed image integral algorithms on GPUs. The first is the Scan-Scan algorithm. The second is the Scan-Transpose-Scan algorithm, which adopts three steps to generate the integral image. The first and the third steps are scan. In order to achieve coalesced global memory access in the third step, a transpose step is added. In this paper, we propose a novel blocked integral algorithm, which has three stages. The first stage is intra-block reduction. The second stage is auxiliary matrix scan and the third stage is intra-block scan. Compared with the Scan-Scan algorithm, our proposed scheme reduces the global memory accesses. At the same time, less local synchronizations and less load imbalance are achieved. Compared with the Scan-Transpose-Scan algorithm, our proposed algorithm only needs about half of the global memory accesses. At the same time, coalesced memory access is achieved. We implemented these three algorithms with OpenCL so that they can run on both Nvidia and AMD GPUs. We also designed an auto-tuning framework to search optimal parameters for different size of input matrix on those two platforms. The experiment result shows that our proposed algorithm gets the best performance compared with the two existed typical integral algorithms.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115450910","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097824
Yuede Ji, Yukun He, Xinyang Jiang, Qiang Li
Social botnet utilizing online social network (OSN) as Command and Control channel (C&C) has caused enormous threats to Internet security. Server-side detection approaches mainly target on suspicious accounts, which cannot identify the specific bot hosts or processes. Host-side approaches target on suspicious process behaviors which are not robust enough to face the challenges of frequent variants and novel social bots. In this paper, we propose a novel social bot behavior detecting approach in the end host. Because social bot binaries or source codes are not easy to collect, we first design a novel social botnet, named wbbot, based on Sina Weibo. We analyze it from two aspects, wbbot architecture and wbbot behaviors. Second, we analyze the host behaviors of existing social botnets which come from public websites, other researchers, and our implementations. We identify six critical phases: infection, pre-defined host behaviors, establishment of C&C, receive the commands of botmaster, execution of social bot commands, and return the results. Third, we present our detection system which consists of three components: host behavior monitor, host behavior analyzer, and detection approach. We present behavior tree-based approach to detect social bot. After constructing the suspicious behavior tree, we match it with the template library to generate detection result. Finally, we collect real-world social botnet traces to evaluate the performance. We would like to share them for academic research. The results indicate that our system has an acceptable false positive rate of 29.6% and remarkable false negative rate of 4.5%. However, compared with other detection tools, our detection result is still remarkable.
{"title":"Towards social botnet behavior detecting in the end host","authors":"Yuede Ji, Yukun He, Xinyang Jiang, Qiang Li","doi":"10.1109/PADSW.2014.7097824","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097824","url":null,"abstract":"Social botnet utilizing online social network (OSN) as Command and Control channel (C&C) has caused enormous threats to Internet security. Server-side detection approaches mainly target on suspicious accounts, which cannot identify the specific bot hosts or processes. Host-side approaches target on suspicious process behaviors which are not robust enough to face the challenges of frequent variants and novel social bots. In this paper, we propose a novel social bot behavior detecting approach in the end host. Because social bot binaries or source codes are not easy to collect, we first design a novel social botnet, named wbbot, based on Sina Weibo. We analyze it from two aspects, wbbot architecture and wbbot behaviors. Second, we analyze the host behaviors of existing social botnets which come from public websites, other researchers, and our implementations. We identify six critical phases: infection, pre-defined host behaviors, establishment of C&C, receive the commands of botmaster, execution of social bot commands, and return the results. Third, we present our detection system which consists of three components: host behavior monitor, host behavior analyzer, and detection approach. We present behavior tree-based approach to detect social bot. After constructing the suspicious behavior tree, we match it with the template library to generate detection result. Finally, we collect real-world social botnet traces to evaluate the performance. We would like to share them for academic research. The results indicate that our system has an acceptable false positive rate of 29.6% and remarkable false negative rate of 4.5%. However, compared with other detection tools, our detection result is still remarkable.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124680786","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097853
Jia Cui, Weiping Wang, Dan Meng, Zhenyan Liu
Similarity join plays an important role in many applications, such as data cleaning and integration, to address the poor data quality problem. Most of the existing studies focused on performing similarity join on static datasets but few studies realized running it on dynamic data streams. With the development of network technology, the data accessing paradigm has transferred from disk-oriented mode to online data streams, which makes performing similarity join in continuous query on data streams become a novel query processing paradigm. Different from static dataset, data stream is unbounded, continuous and unpredictable. The significant differences pose serious challenges, such as real-time query performance. To this end, we study the problem of continuous similarity join on data streams in this paper, which is based on edit distance metric and filter-and-verify framework with sliding-window semantics. Two subcases of this problem are studied, including self similarity join on a single data stream and similarity join on two streams. We introduced the basic window based sliding window model to facilitate the update of sliding window and its index. More details of our method, including signature extraction schemes, filtering and verification algorithms, re-evaluation strategies are discussed respectively. Finally, extensive experimental results show that our method works efficiently on real data streams.
{"title":"Continuous similarity join on data streams","authors":"Jia Cui, Weiping Wang, Dan Meng, Zhenyan Liu","doi":"10.1109/PADSW.2014.7097853","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097853","url":null,"abstract":"Similarity join plays an important role in many applications, such as data cleaning and integration, to address the poor data quality problem. Most of the existing studies focused on performing similarity join on static datasets but few studies realized running it on dynamic data streams. With the development of network technology, the data accessing paradigm has transferred from disk-oriented mode to online data streams, which makes performing similarity join in continuous query on data streams become a novel query processing paradigm. Different from static dataset, data stream is unbounded, continuous and unpredictable. The significant differences pose serious challenges, such as real-time query performance. To this end, we study the problem of continuous similarity join on data streams in this paper, which is based on edit distance metric and filter-and-verify framework with sliding-window semantics. Two subcases of this problem are studied, including self similarity join on a single data stream and similarity join on two streams. We introduced the basic window based sliding window model to facilitate the update of sliding window and its index. More details of our method, including signature extraction schemes, filtering and verification algorithms, re-evaluation strategies are discussed respectively. Finally, extensive experimental results show that our method works efficiently on real data streams.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068239","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097894
Chih-Wei Hsieh, Yu-Fen Cheng, C. Chou
The scientific computing is important research for industrial and society. And, the linear system becomes more important in scientific computing. However, the linear system solvers have many combinations. How to rapidly selecting a best method to solving matrices is expensive. In this paper, we present a linear system solvers platform, which offer easily and quickly interface to users.
{"title":"Construct a simply and quickly platform to solving linear systems","authors":"Chih-Wei Hsieh, Yu-Fen Cheng, C. Chou","doi":"10.1109/PADSW.2014.7097894","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097894","url":null,"abstract":"The scientific computing is important research for industrial and society. And, the linear system becomes more important in scientific computing. However, the linear system solvers have many combinations. How to rapidly selecting a best method to solving matrices is expensive. In this paper, we present a linear system solvers platform, which offer easily and quickly interface to users.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121151553","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097909
Minki Choi, Jooyong Kim
Twisted Copper Filaments (TCF) have been made by a yarn covering process in order to transmit signals and powers for electronic textiles. The 560 den. polyurethane filaments were covered in S-twist direction by urethane-coated copper wires. Final filaments were found to be changed in resonance frequency mainly due to the change of di-electricity and thus capacitance caused by PET covered on it. It have been concluded that while resonance frequency was primarily determined by filament length and dielectric constant of covering yarns, S11 and S21 were mainly determined by measurement length and ply number.
{"title":"Transmission characteristics of hybrid structure yarns for e-textiles","authors":"Minki Choi, Jooyong Kim","doi":"10.1109/PADSW.2014.7097909","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097909","url":null,"abstract":"Twisted Copper Filaments (TCF) have been made by a yarn covering process in order to transmit signals and powers for electronic textiles. The 560 den. polyurethane filaments were covered in S-twist direction by urethane-coated copper wires. Final filaments were found to be changed in resonance frequency mainly due to the change of di-electricity and thus capacitance caused by PET covered on it. It have been concluded that while resonance frequency was primarily determined by filament length and dielectric constant of covering yarns, S11 and S21 were mainly determined by measurement length and ply number.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122985114","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097870
Yu Tang, Hailong Sun, Xu Wang, Xudong Liu
To attain high performance and remain available during network partitions or node failures, modern distributed systems often sacrifice recency guarantees, which can provide a uniform view on recent versions of data items for different clients. In this work, we consider the problem of increasing the probability of data recency while preserving low response latency and maintaining high availability on top of an eventually consistent data store. To solve the problem, we propose HARP, an approach that can enhance data recency in a highly available way. Based on HARP, we implement an agent layer to detect stale reads and resolve the conflicts, and by leveraging widely deployed data store technologies, we build a data storage system. We compare the prototype system to Cassandra, and experimentally prove that our method produces low overhead (less than 10%) based on the eventually consistent configuration and, for most workloads, achieves better performance than the Cassandra's strong “read your writes” configurations.
{"title":"HARP: Towards enhancing data recency for eventually consistent data stores","authors":"Yu Tang, Hailong Sun, Xu Wang, Xudong Liu","doi":"10.1109/PADSW.2014.7097870","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097870","url":null,"abstract":"To attain high performance and remain available during network partitions or node failures, modern distributed systems often sacrifice recency guarantees, which can provide a uniform view on recent versions of data items for different clients. In this work, we consider the problem of increasing the probability of data recency while preserving low response latency and maintaining high availability on top of an eventually consistent data store. To solve the problem, we propose HARP, an approach that can enhance data recency in a highly available way. Based on HARP, we implement an agent layer to detect stale reads and resolve the conflicts, and by leveraging widely deployed data store technologies, we build a data storage system. We compare the prototype system to Cassandra, and experimentally prove that our method produces low overhead (less than 10%) based on the eventually consistent configuration and, for most workloads, achieves better performance than the Cassandra's strong “read your writes” configurations.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126493083","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097815
Kun Liu, Tianyu Wo, Lei Cui, Bin Shi, Jie Xu
Virtual networking is vital to efficient resource management in Clouds, and it is in fact one of the main services provided by many Cloud Computing platforms. Virtual network management needs to meet specific requirements, including tenant isolation and adaption to virtual machines' lifecycle. Most of the existing schemes for virtual network management are based on the use of overlay networks in order to achieve a desirable degree of flexibility. However, these schemes suffer from a common limit, i.e. relatively high performance penalty due to a complicated forwarding process. We address this performance concern by developing a new management scheme, FENet, which makes use of Software-Defined Networks (SDN) to create virtual networks and manage them via the SDN controller programs. We present the design of an SDN controller, with the definition of flow entry rules based on the OpenFlow protocol and the specification of a routing algorithm. The results from our experimental evaluation show that our SDN-based prototype can control virtual network interconnections and tenant isolation appropriately. FENet achieves about 30% better network performance than the management scheme based on OpenVPN and lower latency in comparison with the traditional bridging scheme.
{"title":"FENet: An SDN-based scheme for virtual network management","authors":"Kun Liu, Tianyu Wo, Lei Cui, Bin Shi, Jie Xu","doi":"10.1109/PADSW.2014.7097815","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097815","url":null,"abstract":"Virtual networking is vital to efficient resource management in Clouds, and it is in fact one of the main services provided by many Cloud Computing platforms. Virtual network management needs to meet specific requirements, including tenant isolation and adaption to virtual machines' lifecycle. Most of the existing schemes for virtual network management are based on the use of overlay networks in order to achieve a desirable degree of flexibility. However, these schemes suffer from a common limit, i.e. relatively high performance penalty due to a complicated forwarding process. We address this performance concern by developing a new management scheme, FENet, which makes use of Software-Defined Networks (SDN) to create virtual networks and manage them via the SDN controller programs. We present the design of an SDN controller, with the definition of flow entry rules based on the OpenFlow protocol and the specification of a routing algorithm. The results from our experimental evaluation show that our SDN-based prototype can control virtual network interconnections and tenant isolation appropriately. FENet achieves about 30% better network performance than the management scheme based on OpenVPN and lower latency in comparison with the traditional bridging scheme.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116017686","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097817
Wei Wu, Xiang Li, Lei He, Dongxiao Zhang
Modern petroleum reservoir simulation serves as a primary tool for quantitatively managing reservoir production and planning new fields. It involves repeatedly solving the Jacobian of a set of strong nonlinear partial differential equations governing the mass and energy conduction and conservation. Most of the existing reservoir simulators adopt iterative solver with multiple stages of preconditioners, in which the incomplete LU (ILU) factorization is an outstanding universal smoother. However, it turns out that when the degree of freedom of each grid grows, ILU usually becomes the bottleneck of the solver. Moreover, ILU is difficult to parallelize due to its inherent data dependency. In this paper, we developed a sparse iterative solver with parallelized ILU and triangular solve using block-wise data structure. Compared with the state of art iterative solver on 14 industrial reservoir simulation matrices, the proposed ILU is 5.2x faster (on average) than the state of art iterative solver because of the block-wise data structure, which leads to 2.2x speedup on the total solver runtime. In addition, parallel ILU and triangular solve are developed to further accelerate the solver. To tackle the strong data dependency in ILU and triangular solve, we first partition the algorithm into separated tasks and construct a data flow graph to represent the data dependency. Then, tasks are scheduled in parallel according to the topological order of the data flow graph. On an 8-thread multicore architecture, we achieved another 3.6x speedup on ILU factorization, and 3.3x on triangular solve with good scalability.
{"title":"Accelerating the iterative linear solver for reservoir simulation on multicore architectures","authors":"Wei Wu, Xiang Li, Lei He, Dongxiao Zhang","doi":"10.1109/PADSW.2014.7097817","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097817","url":null,"abstract":"Modern petroleum reservoir simulation serves as a primary tool for quantitatively managing reservoir production and planning new fields. It involves repeatedly solving the Jacobian of a set of strong nonlinear partial differential equations governing the mass and energy conduction and conservation. Most of the existing reservoir simulators adopt iterative solver with multiple stages of preconditioners, in which the incomplete LU (ILU) factorization is an outstanding universal smoother. However, it turns out that when the degree of freedom of each grid grows, ILU usually becomes the bottleneck of the solver. Moreover, ILU is difficult to parallelize due to its inherent data dependency. In this paper, we developed a sparse iterative solver with parallelized ILU and triangular solve using block-wise data structure. Compared with the state of art iterative solver on 14 industrial reservoir simulation matrices, the proposed ILU is 5.2x faster (on average) than the state of art iterative solver because of the block-wise data structure, which leads to 2.2x speedup on the total solver runtime. In addition, parallel ILU and triangular solve are developed to further accelerate the solver. To tackle the strong data dependency in ILU and triangular solve, we first partition the algorithm into separated tasks and construct a data flow graph to represent the data dependency. Then, tasks are scheduled in parallel according to the topological order of the data flow graph. On an 8-thread multicore architecture, we achieved another 3.6x speedup on ILU factorization, and 3.3x on triangular solve with good scalability.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"600 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131966209","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}
Data aggregation in wireless sensor networks is widely used to collect data in an energy efficient manner to eliminate redundant data transmission so that prolong the network lifetime. To meet the data aggregation needs in wireless sensor networks, this paper proposes a novel multi-path routing algorithm, called EAD, to process in-network data aggregation. For each sensor on the routing paths, EAD evaluates its neighbors based on the residual energy, deviation angle and distance, and selects the k neighbors with the minimal evaluation costs as its forwarding nodes in order to balance energy consumption of the wireless sensor network on the premise of ensuring the reliability and performance. Simulation results show that EAD can effectively prolong network lifetime, reduce latency and ensure the reliability by adjusting the weight of each influencing factor.
{"title":"Energy-aware multipath routing for data aggregation in wireless sensor networks","authors":"Yingyuan Xiao, Xinrong Zhao, Hongya Wang, Ching-Hsien Hsu","doi":"10.1109/PADSW.2014.7097890","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097890","url":null,"abstract":"Data aggregation in wireless sensor networks is widely used to collect data in an energy efficient manner to eliminate redundant data transmission so that prolong the network lifetime. To meet the data aggregation needs in wireless sensor networks, this paper proposes a novel multi-path routing algorithm, called EAD, to process in-network data aggregation. For each sensor on the routing paths, EAD evaluates its neighbors based on the residual energy, deviation angle and distance, and selects the k neighbors with the minimal evaluation costs as its forwarding nodes in order to balance energy consumption of the wireless sensor network on the premise of ensuring the reliability and performance. Simulation results show that EAD can effectively prolong network lifetime, reduce latency and ensure the reliability by adjusting the weight of each influencing factor.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132164968","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 : 2014-12-01DOI: 10.1109/PADSW.2014.7097791
Cong Wang, Songtao Guo, Yuanyuan Yang
Environmental energy harvesting technologies have provided potential for battery-powered wireless sensor networks to have perpetual network operations. To design a robust network that can adapt to not only temporal but also spatial variations of ambient energy sources, in this paper, we utilize mobility to circumvent communication bottlenecks, by employing a mobile data collector, called SenCar. We propose a two-stage approach for mobile data collection. In the first stage, SenCar makes stops at a subset of selected sensor locations to collect data packets in a multi-hop fashion. We provide a selection algorithm to search for sensor locations with most residual energy while guaranteeing a bounded tour length. Then we design a distributed data gathering algorithm to achieve maximum network utility by adjusting data rates, link scheduling and flow routing that adapts to spatial temporal environmental energy variations. The effectiveness and efficiency of the proposed algorithms are validated by extensive numerical results.
{"title":"Energy-efficient mobile data collection in energy-harvesting wireless sensor networks","authors":"Cong Wang, Songtao Guo, Yuanyuan Yang","doi":"10.1109/PADSW.2014.7097791","DOIUrl":"https://doi.org/10.1109/PADSW.2014.7097791","url":null,"abstract":"Environmental energy harvesting technologies have provided potential for battery-powered wireless sensor networks to have perpetual network operations. To design a robust network that can adapt to not only temporal but also spatial variations of ambient energy sources, in this paper, we utilize mobility to circumvent communication bottlenecks, by employing a mobile data collector, called SenCar. We propose a two-stage approach for mobile data collection. In the first stage, SenCar makes stops at a subset of selected sensor locations to collect data packets in a multi-hop fashion. We provide a selection algorithm to search for sensor locations with most residual energy while guaranteeing a bounded tour length. Then we design a distributed data gathering algorithm to achieve maximum network utility by adjusting data rates, link scheduling and flow routing that adapts to spatial temporal environmental energy variations. The effectiveness and efficiency of the proposed algorithms are validated by extensive numerical results.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133758938","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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