Pub Date : 2020-05-01DOI: 10.1109/dcoss49796.2020.00008
{"title":"DCOSS 2020 Committees","authors":"","doi":"10.1109/dcoss49796.2020.00008","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00008","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127298743","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 : 2020-05-01DOI: 10.1109/dcoss49796.2020.00011
{"title":"Message from the Workshop Chairs","authors":"","doi":"10.1109/dcoss49796.2020.00011","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00011","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"17 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141207379","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 : 2020-05-01DOI: 10.1109/dcoss49796.2020.00012
{"title":"Message from the Workshop General Chair","authors":"","doi":"10.1109/dcoss49796.2020.00012","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00012","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132278486","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00023
Francesco Betti Sorbelli, Federico Coró, Sajal K. Das, A. Navarra, M. C. Pinotti
In this paper, we study the Orienteering Aisle-graphs Single-column Problem (OASP), which is a variant of the route planning problem for an entity/robot moving along a specific aisle-graph consisting of a set of rows connected via just one column at one endpoint of the rows. Such constrained aisle-graph may model, for instance, a vineyard or warehouse, where each vertex is assigned with a reward that a robot gains when visiting it for accomplishing a task. As the robot is energy limited, it must visit a subset of vertices before going back to the depot for recharging, while maximizing the total reward gained. It is known that the OASP for constrained aisle-graphs composed by m rows of length n is polynomially solvable in $mathcal{O}left( {{m^2}{n^2}} right)$ time, which can be prohibitive for graphs of large dimensions. With the goal of designing more time efficient solutions, we propose four algorithms that iteratively build the solution in a greedy manner. These solutions take at most $mathcal{O}(mn(m + n))$ time, thus improving the optimal solution by a factor of n. Experimentally, we show that these algorithms collect more than 80% of the optimum reward. For two of them, we also guarantee an approximation ratio of $frac{1}{2}left( {1 - frac{1}{e}} right)$ on the reward function by exploiting the submodularity property, where e is the base of the natural logarithm.
本文研究了定向通道图单列问题(OASP)，该问题是实体/机器人沿特定通道图移动的路径规划问题的一个变体，该通道图由一组行组成，在这些行的一个端点仅通过一列连接。这种受约束的通道图可以建模，例如，一个葡萄园或仓库，其中每个顶点被分配一个奖励，当机器人完成任务访问它时获得奖励。由于机器人的能量有限，它必须在返回仓库充电之前访问一个顶点子集，同时最大化获得的总奖励。已知由m行长度为n的受限通道图的OASP在$mathcal{O}left( {{m^2}{n^2}} right)$时间内多项式可解，这对于大维度的图来说可能是禁止的。为了设计更省时的解决方案，我们提出了四种算法，以贪婪的方式迭代构建解决方案。这些解决方案最多花费$mathcal{O}(mn(m + n))$时间，从而将最优解决方案提高了n倍。实验表明，这些算法收集了80多个% of the optimum reward. For two of them, we also guarantee an approximation ratio of $frac{1}{2}left( {1 - frac{1}{e}} right)$ on the reward function by exploiting the submodularity property, where e is the base of the natural logarithm.
{"title":"Speeding-up Routing Schedules on Aisle-Graphs","authors":"Francesco Betti Sorbelli, Federico Coró, Sajal K. Das, A. Navarra, M. C. Pinotti","doi":"10.1109/DCOSS49796.2020.00023","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00023","url":null,"abstract":"In this paper, we study the Orienteering Aisle-graphs Single-column Problem (OASP), which is a variant of the route planning problem for an entity/robot moving along a specific aisle-graph consisting of a set of rows connected via just one column at one endpoint of the rows. Such constrained aisle-graph may model, for instance, a vineyard or warehouse, where each vertex is assigned with a reward that a robot gains when visiting it for accomplishing a task. As the robot is energy limited, it must visit a subset of vertices before going back to the depot for recharging, while maximizing the total reward gained. It is known that the OASP for constrained aisle-graphs composed by m rows of length n is polynomially solvable in $mathcal{O}left( {{m^2}{n^2}} right)$ time, which can be prohibitive for graphs of large dimensions. With the goal of designing more time efficient solutions, we propose four algorithms that iteratively build the solution in a greedy manner. These solutions take at most $mathcal{O}(mn(m + n))$ time, thus improving the optimal solution by a factor of n. Experimentally, we show that these algorithms collect more than 80% of the optimum reward. For two of them, we also guarantee an approximation ratio of $frac{1}{2}left( {1 - frac{1}{e}} right)$ on the reward function by exploiting the submodularity property, where e is the base of the natural logarithm.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133161275","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 : 2020-05-01DOI: 10.1109/dcoss49796.2020.00013
{"title":"Message from the ISIoT 2020 Workshop Chairs","authors":"","doi":"10.1109/dcoss49796.2020.00013","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00013","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115638734","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00044
George Drosatos, K. Rantos, D. Karampatzakis, T. Lagkas, P. Sarigiannidis
Industrial Internet of Things (IIoT) is a relatively new area of research that utilises multidisciplinary and holistic approaches to develop smart solutions for complex problems in industrial environments. Designing applications for the IIoT is a non trivial issue and requires to address, among many others, technology concerns, the protection of personal data, and the privacy of individuals. In this review paper, we identify privacy-preserving solutions that have been proposed in the literature to safeguard the privacy of individuals being part, or interacting with, the IIoT environment. As such, it considers two main categories of the analysed protocols, i.e., the privacy-preserving data management and processing solutions, and the privacy-preserving authentication methods.
{"title":"Privacy-preserving solutions in the Industrial Internet of Things","authors":"George Drosatos, K. Rantos, D. Karampatzakis, T. Lagkas, P. Sarigiannidis","doi":"10.1109/DCOSS49796.2020.00044","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00044","url":null,"abstract":"Industrial Internet of Things (IIoT) is a relatively new area of research that utilises multidisciplinary and holistic approaches to develop smart solutions for complex problems in industrial environments. Designing applications for the IIoT is a non trivial issue and requires to address, among many others, technology concerns, the protection of personal data, and the privacy of individuals. In this review paper, we identify privacy-preserving solutions that have been proposed in the literature to safeguard the privacy of individuals being part, or interacting with, the IIoT environment. As such, it considers two main categories of the analysed protocols, i.e., the privacy-preserving data management and processing solutions, and the privacy-preserving authentication methods.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120824484","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00079
Rohit Kumar, S. Darak, M. Hanawal
The opportunistic spectrum access (OSA) algorithms allow secondary users (SUs) to exploit vacant channels with an aim to maximize overall spectrum utilization/throughput. The design of OSA algorithm is challenging for ad hoc networks due to lack of coordination among SUs and unknown channel statistics. It becomes even more challenging for the dynamic networks where the SUs can enter or leave the network any time without prior agreement. Most of the existing algorithms assume either prior knowledge of the number of SUs or need wideband sensing to sense all channels simultaneously to guarantee optimal channel allocation among SUs. Our goal in this paper is to develop distributed OSA algorithm for dynamic ad hoc networks that offers higher throughput without compromising on the number of SUs collisions. The proposed distributed algorithm is based on multi-player multi-arm bandit framework and they allow SUs to independently estimate the number of other SUs and channel statistics. We derive the upper bounds on the throughput loss (regret) and number of collisions. Exhaustive synthetic results and experimental results on universal software radio peripherals (USRP) based testbed validate our claims and superiority of the proposed algorithm.
{"title":"Distributed Algorithm for Opportunistic Spectrum Access in Dynamic Ad Hoc Networks","authors":"Rohit Kumar, S. Darak, M. Hanawal","doi":"10.1109/DCOSS49796.2020.00079","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00079","url":null,"abstract":"The opportunistic spectrum access (OSA) algorithms allow secondary users (SUs) to exploit vacant channels with an aim to maximize overall spectrum utilization/throughput. The design of OSA algorithm is challenging for ad hoc networks due to lack of coordination among SUs and unknown channel statistics. It becomes even more challenging for the dynamic networks where the SUs can enter or leave the network any time without prior agreement. Most of the existing algorithms assume either prior knowledge of the number of SUs or need wideband sensing to sense all channels simultaneously to guarantee optimal channel allocation among SUs. Our goal in this paper is to develop distributed OSA algorithm for dynamic ad hoc networks that offers higher throughput without compromising on the number of SUs collisions. The proposed distributed algorithm is based on multi-player multi-arm bandit framework and they allow SUs to independently estimate the number of other SUs and channel statistics. We derive the upper bounds on the throughput loss (regret) and number of collisions. Exhaustive synthetic results and experimental results on universal software radio peripherals (USRP) based testbed validate our claims and superiority of the proposed algorithm.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120974992","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00033
M. Kawamoto, T. Hamamoto
This paper presents a method to identify sound sources for structural monitoring, known as building health monitoring. This method allows to evaluate deterioration and damage of buildings by analyzing environmental sounds. The proposed method determines the location and features of sounds generated within a building, with its main characteristics being: (1) planar direction and height estimation; (2) visualization of sound features according to loudness, continuity, and pitch. The capabilities of the proposed building health monitoring method are verified using environmental sound data acquired at a building in Gunkanjima, which is a world heritage site from Japan.
{"title":"Building Health Monitoring Using Computational Auditory Scene Analysis","authors":"M. Kawamoto, T. Hamamoto","doi":"10.1109/DCOSS49796.2020.00033","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00033","url":null,"abstract":"This paper presents a method to identify sound sources for structural monitoring, known as building health monitoring. This method allows to evaluate deterioration and damage of buildings by analyzing environmental sounds. The proposed method determines the location and features of sounds generated within a building, with its main characteristics being: (1) planar direction and height estimation; (2) visualization of sound features according to loudness, continuity, and pitch. The capabilities of the proposed building health monitoring method are verified using environmental sound data acquired at a building in Gunkanjima, which is a world heritage site from Japan.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125946516","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00069
G. Filios, Ioannis Katsidimas, Emmanouil Kerimakis, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis
With solar parks being established as one of the most important renewable energy systems, there is a strong need for more efficient use of the services they provide, as well as error detection and performance issues confrontation. Internet of Things (IoT) technology, aims to fill the gap, by offering low cost and sustainable solutions towards the efficient operation of these parks. In this paper, we present an in situ monitoring and alerting system, based on WSN technologies, regarding the early detection of Potential Induced Degradation (PID) and Hotspots failures, that can cause a significant drop in solar panels’ performance. In order to do so, specific non-trivial attributes such as temperature, humidity, irradiance, current and voltage are continuously monitored at panel level, and processed in a cloud based platform to early identify these phenomena. In particular, sensor nodes send data to a centralized local sink module using a multi-hop WSN architecture, in order to establish a robust and large coverage area. Afterwards, the information is propagated to the cloud server, where deterministic diagnostic algorithms are applied. We present the reference architecture of our approach, alongside the corresponding hardware and software structural, individual components, as well as the integration process and the use case that runs over a real solar park.
{"title":"An IoT based Solar Park Health Monitoring System for PID and Hotspots Effects","authors":"G. Filios, Ioannis Katsidimas, Emmanouil Kerimakis, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis","doi":"10.1109/DCOSS49796.2020.00069","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00069","url":null,"abstract":"With solar parks being established as one of the most important renewable energy systems, there is a strong need for more efficient use of the services they provide, as well as error detection and performance issues confrontation. Internet of Things (IoT) technology, aims to fill the gap, by offering low cost and sustainable solutions towards the efficient operation of these parks. In this paper, we present an in situ monitoring and alerting system, based on WSN technologies, regarding the early detection of Potential Induced Degradation (PID) and Hotspots failures, that can cause a significant drop in solar panels’ performance. In order to do so, specific non-trivial attributes such as temperature, humidity, irradiance, current and voltage are continuously monitored at panel level, and processed in a cloud based platform to early identify these phenomena. In particular, sensor nodes send data to a centralized local sink module using a multi-hop WSN architecture, in order to establish a robust and large coverage area. Afterwards, the information is propagated to the cloud server, where deterministic diagnostic algorithms are applied. We present the reference architecture of our approach, alongside the corresponding hardware and software structural, individual components, as well as the integration process and the use case that runs over a real solar park.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116637030","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00045
G. Filios, Ioannis Katsidimas, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis, Ioannis Tsenempis
A lot of research has been contributed towards smart energy harvesting, efficient energy management and energy storage/supply capabilities, as they are considered a major bottleneck in Wireless Sensor Networks (WSNs). Similarly, there is an extreme interest to design new algorithms and protocols regarding energy harvesting prediction, load's energy consuming profiling, etc. Although those techniques improve energy efficiency, it still remains to solve the fundamental problem of energy provisioning in a more practical, real-life manner, as the majority of the hardware solutions choose to produce simple and robust implementations. In this paper, we present a smart energy management platform for low-power IoT systems that implements both energy harvesting and storage technologies but dynamically sets different power modes based on online monitoring measurements and energy harvesting prediction. With respect to power specifications our solution succeeds to both supply and inform the load system for future energy provisioning capability. Thus, our prototype can be characterised as a load agnostic device w.r.t. specification values, that can adjust to different conditions and use cases towards an effective system energy provisioning.
{"title":"A smart energy management power supply unit for low-power IoT systems","authors":"G. Filios, Ioannis Katsidimas, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis, Ioannis Tsenempis","doi":"10.1109/DCOSS49796.2020.00045","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00045","url":null,"abstract":"A lot of research has been contributed towards smart energy harvesting, efficient energy management and energy storage/supply capabilities, as they are considered a major bottleneck in Wireless Sensor Networks (WSNs). Similarly, there is an extreme interest to design new algorithms and protocols regarding energy harvesting prediction, load's energy consuming profiling, etc. Although those techniques improve energy efficiency, it still remains to solve the fundamental problem of energy provisioning in a more practical, real-life manner, as the majority of the hardware solutions choose to produce simple and robust implementations. In this paper, we present a smart energy management platform for low-power IoT systems that implements both energy harvesting and storage technologies but dynamically sets different power modes based on online monitoring measurements and energy harvesting prediction. With respect to power specifications our solution succeeds to both supply and inform the load system for future energy provisioning capability. Thus, our prototype can be characterised as a load agnostic device w.r.t. specification values, that can adjust to different conditions and use cases towards an effective system energy provisioning.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121709424","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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