Pub Date : 2018-04-15DOI: 10.1109/WCNCW.2018.8369009
Michał Kozłowski, D. Byrne, Raúl Santos-Rodríguez, R. Piechocki
This paper offers an approach for the combining of signals from multiple sensors observing everyday activities in a digital health care monitoring context. The IoT environment presents a number of advantages for indoor localisation. The amalgamation of several passive sensors can be used to provide an accurate location. This location often bears unique signatures of activity, especially when considering residential environments. However, it is only the basic human instincts, such as periodicity and routine, that make this possible. The fact that behaviours and actions recur naturally is an important assumption in this paper. The study proposes a method, whereby semantic information about the location is learned from an additional source. This method deals with the question of robust indoor localisation prediction by extracting additional activity information available from a wrist worn acceleration sensor. A number of different fusion models are considered, before choosing and validating the model which provides highest improvement in accuracy and robustness over the baseline example. The performance of the methods is examined on different unique datasets, which closely resemble residential living scenarios.
{"title":"Data fusion for robust indoor localisation in digital health","authors":"Michał Kozłowski, D. Byrne, Raúl Santos-Rodríguez, R. Piechocki","doi":"10.1109/WCNCW.2018.8369009","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8369009","url":null,"abstract":"This paper offers an approach for the combining of signals from multiple sensors observing everyday activities in a digital health care monitoring context. The IoT environment presents a number of advantages for indoor localisation. The amalgamation of several passive sensors can be used to provide an accurate location. This location often bears unique signatures of activity, especially when considering residential environments. However, it is only the basic human instincts, such as periodicity and routine, that make this possible. The fact that behaviours and actions recur naturally is an important assumption in this paper. The study proposes a method, whereby semantic information about the location is learned from an additional source. This method deals with the question of robust indoor localisation prediction by extracting additional activity information available from a wrist worn acceleration sensor. A number of different fusion models are considered, before choosing and validating the model which provides highest improvement in accuracy and robustness over the baseline example. The performance of the methods is examined on different unique datasets, which closely resemble residential living scenarios.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128639390","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8369000
Henrik Rydén, J. Berglund, Martin Isaksson, Rickard Cöster, F. Gunnarsson
There is a rapid evolution in telecommunication with denser networks and systems operating on an increasing number of frequency bands. Also in the next generation 5G networks, even further densification is needed to be able to reach the tight requirements, implying more nodes on each carrier. Denser networks and more frequencies makes it challenging to ensure the best possible cell and frequency carrier assignment to a User Equipment (UE), without the UE needing to perform an excessive amount of inter-frequency measurements and reporting. In this paper, we propose a procedure of predicting the strongest cell of a secondary carrier, and the procedure is exemplified in a UE load-balancing use case. The prediction is based on only measurements on the primary carrier cells, avoiding costly inter-frequency measurements. Simulations of a realistic network deployment show that a UE selection based on the proposed secondary carrier prediction is significantly better than a random UE selection for load balancing.
{"title":"Predicting strongest cell on secondary carrier using primary carrier data","authors":"Henrik Rydén, J. Berglund, Martin Isaksson, Rickard Cöster, F. Gunnarsson","doi":"10.1109/WCNCW.2018.8369000","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8369000","url":null,"abstract":"There is a rapid evolution in telecommunication with denser networks and systems operating on an increasing number of frequency bands. Also in the next generation 5G networks, even further densification is needed to be able to reach the tight requirements, implying more nodes on each carrier. Denser networks and more frequencies makes it challenging to ensure the best possible cell and frequency carrier assignment to a User Equipment (UE), without the UE needing to perform an excessive amount of inter-frequency measurements and reporting. In this paper, we propose a procedure of predicting the strongest cell of a secondary carrier, and the procedure is exemplified in a UE load-balancing use case. The prediction is based on only measurements on the primary carrier cells, avoiding costly inter-frequency measurements. Simulations of a realistic network deployment show that a UE selection based on the proposed secondary carrier prediction is significantly better than a random UE selection for load balancing.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121435745","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8368972
Stephen S. Mwanje, Janne Ali-Tolppa
Energy consumption in mobile networks rises with increase in cell density. This trend will only continue in the future multi-layer 5G-related Ultra-Dense Networks (UDN) that are characterized by high number and density of cells in multiple radio technologies each in one or more layers. Several Energy Saving Management (ESM) solutions have been published, but none adequately address the UDN scenario. UDNs require a distributed solution that allows each cell to individually decide when to deactivate or reactivate itself while considering the amount of network-wide traffic and the need to minimize signaling between the cells. This paper describes such a solution and its implementation, as well as a case study in a typical 5G UDN scenario with multiple cell layers of different cell sizes.
{"title":"Distributed energy saving management in multi-layer 4G/5G ultra-dense networks","authors":"Stephen S. Mwanje, Janne Ali-Tolppa","doi":"10.1109/WCNCW.2018.8368972","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8368972","url":null,"abstract":"Energy consumption in mobile networks rises with increase in cell density. This trend will only continue in the future multi-layer 5G-related Ultra-Dense Networks (UDN) that are characterized by high number and density of cells in multiple radio technologies each in one or more layers. Several Energy Saving Management (ESM) solutions have been published, but none adequately address the UDN scenario. UDNs require a distributed solution that allows each cell to individually decide when to deactivate or reactivate itself while considering the amount of network-wide traffic and the need to minimize signaling between the cells. This paper describes such a solution and its implementation, as well as a case study in a typical 5G UDN scenario with multiple cell layers of different cell sizes.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128978612","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8369032
J. Sheu, Yiying Pu, R. Jagadeesha, Yeh-Cheng Chang
Edge computing refers to data storage and processing at the edge of a network instead of cloud data centers. In edge computing, user data can be preprocessed to reduce the network traffic and load of the cloud system. Module deployment scheme is vital in edge computing since it has a significant effect on the performance and the resource utilization of the edge computing system. Our objective is to maximize satisfied user requests under the constraints of limited communication bandwidth and storage capacity of devices where the modules are deployed. Since the optimization problem is NP-hard, we propose a heuristic algorithm based on relaxation and rounding techniques to solve this problem. The simulation results show that our algorithm satisfies more user requests than previous work.
{"title":"An efficient module deployment algorithm in edge computing","authors":"J. Sheu, Yiying Pu, R. Jagadeesha, Yeh-Cheng Chang","doi":"10.1109/WCNCW.2018.8369032","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8369032","url":null,"abstract":"Edge computing refers to data storage and processing at the edge of a network instead of cloud data centers. In edge computing, user data can be preprocessed to reduce the network traffic and load of the cloud system. Module deployment scheme is vital in edge computing since it has a significant effect on the performance and the resource utilization of the edge computing system. Our objective is to maximize satisfied user requests under the constraints of limited communication bandwidth and storage capacity of devices where the modules are deployed. Since the optimization problem is NP-hard, we propose a heuristic algorithm based on relaxation and rounding techniques to solve this problem. The simulation results show that our algorithm satisfies more user requests than previous work.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133549921","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8368998
Meilin Gao, B. Ai, Yong Niu, Z. Zhong, Yiru Liu, Guoyu Ma, Zhewei Zhang, Dapeng Li
With the worldwide deployment of the railway, high-speed railway (HSR) tends to evolve into an intelligent transportation system with efficient and green transportation characteristics. To meet the explosive growth of wireless data traffic in “smart rail”, millimeter-wave (mmWave) communications are used to offer several Gbps data rate via beamforming structures by utilizing huge unlicensed bandwidth. In this paper, the beam tracking strategies for mmWave HSR communications are investigated, and a dynamic beam tracking strategy is proposed by adjusting the beam direction and beam width jointly, where the main idea is to maximize the sum-rate capacity while satisfying the critical quality of service (QoS) requirements. Then it boils down to a demanding non-convex problem, and a near-optimal solution is provided based on the problem decomposition and the genetic algorithm. Finally, along with the moving trains the proposed beam tracking scheme can provide near-optimal capacity performance with a low outage probability, and reduce the implementation complexity.
{"title":"Dynamic mmWave beam tracking for high speed railway communications","authors":"Meilin Gao, B. Ai, Yong Niu, Z. Zhong, Yiru Liu, Guoyu Ma, Zhewei Zhang, Dapeng Li","doi":"10.1109/WCNCW.2018.8368998","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8368998","url":null,"abstract":"With the worldwide deployment of the railway, high-speed railway (HSR) tends to evolve into an intelligent transportation system with efficient and green transportation characteristics. To meet the explosive growth of wireless data traffic in “smart rail”, millimeter-wave (mmWave) communications are used to offer several Gbps data rate via beamforming structures by utilizing huge unlicensed bandwidth. In this paper, the beam tracking strategies for mmWave HSR communications are investigated, and a dynamic beam tracking strategy is proposed by adjusting the beam direction and beam width jointly, where the main idea is to maximize the sum-rate capacity while satisfying the critical quality of service (QoS) requirements. Then it boils down to a demanding non-convex problem, and a near-optimal solution is provided based on the problem decomposition and the genetic algorithm. Finally, along with the moving trains the proposed beam tracking scheme can provide near-optimal capacity performance with a low outage probability, and reduce the implementation complexity.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132789427","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8369012
Anique Akhtar, H. Arslan
5G New Radio (NR) is moving towards flexibility and adaptability and is expected to provide optimized support for diverse 5G use case categories. With the introduction of flexible waveforms and numerologies in 5G, there is a need for new scheduling and resource allocation techniques. Using different non-orthogonal numerologies in the network complicates the resource allocation process since it introduces numerology multi-plexing. In this paper, we propose a channel quality and Quality of Service (QoS) aware resource allocation scheme for multi-numerology 5G networks. We implement a frequency domain packet scheduler which allocates packets to Resource Blocks to achieve higher spectral efficiency, maintain fairness, and satisfying the QoS requirements of users with different non-orthogonal numerologies. The results show that our algorithm achieves high throughput in different traffic mixes with different numerology QoS requirements over varying number of users.
{"title":"Downlink resource allocation and packet scheduling in multi-numerology wireless systems","authors":"Anique Akhtar, H. Arslan","doi":"10.1109/WCNCW.2018.8369012","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8369012","url":null,"abstract":"5G New Radio (NR) is moving towards flexibility and adaptability and is expected to provide optimized support for diverse 5G use case categories. With the introduction of flexible waveforms and numerologies in 5G, there is a need for new scheduling and resource allocation techniques. Using different non-orthogonal numerologies in the network complicates the resource allocation process since it introduces numerology multi-plexing. In this paper, we propose a channel quality and Quality of Service (QoS) aware resource allocation scheme for multi-numerology 5G networks. We implement a frequency domain packet scheduler which allocates packets to Resource Blocks to achieve higher spectral efficiency, maintain fairness, and satisfying the QoS requirements of users with different non-orthogonal numerologies. The results show that our algorithm achieves high throughput in different traffic mixes with different numerology QoS requirements over varying number of users.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130690080","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8369018
Hind Zaaraoui, Z. Altman, S. B. Jemaa, E. Altman, T. Jiménez
Forecast Scheduling (FS) is a scheduling concept that utilizes rate prediction along the users' trajectories in order to optimize the scheduler allocation. The rate prediction is based on Signal to Interference plus Noise Ratio (SINR) or rate maps provided by a Radio Environment Map (REM). The FS has been formulated as a convex optimization problem namely the maximization of an α-fair utility function of the cumulated rates of the users along their trajectories [1]. This paper proposes a fast heuristic for the FS problem based on two FS users' scheduling. Furthermore, it is shown that in the case of two users, the FS problem can be solved analytically, making the heuristic computationally very efficient. Numerical results illustrate the throughput gain brought about by the scheduling solution.a
{"title":"Heuristic approach for forecast scheduling","authors":"Hind Zaaraoui, Z. Altman, S. B. Jemaa, E. Altman, T. Jiménez","doi":"10.1109/WCNCW.2018.8369018","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8369018","url":null,"abstract":"Forecast Scheduling (FS) is a scheduling concept that utilizes rate prediction along the users' trajectories in order to optimize the scheduler allocation. The rate prediction is based on Signal to Interference plus Noise Ratio (SINR) or rate maps provided by a Radio Environment Map (REM). The FS has been formulated as a convex optimization problem namely the maximization of an α-fair utility function of the cumulated rates of the users along their trajectories [1]. This paper proposes a fast heuristic for the FS problem based on two FS users' scheduling. Furthermore, it is shown that in the case of two users, the FS problem can be solved analytically, making the heuristic computationally very efficient. Numerical results illustrate the throughput gain brought about by the scheduling solution.a","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124446416","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8368973
P. Amadori, C. Masouros
A novel low-complexity transmission scheme for Massive Multiuser Multi-Input Multi-Output (M-MU-MIMO) is proposed, where Transmit Antenna Selection (TAS) and beam-forming are jointly performed to exploit multiuser interference. Two separate solutions to the deriving optimization problem are proposed: a mixed-integer programming approach that can optimally solve the TAS-beamforming problem and a heuristic convex approach, based on the assumption of matched filtering beamforming. Numerical results prove that the proposed multiuser interference exploiting approaches are able to greatly outperform previous state-of-the-art schemes, where TAS and beamforming are disjointedly solved.
{"title":"A mixed-integer programming approach to interference exploitation for massive-MIMO","authors":"P. Amadori, C. Masouros","doi":"10.1109/WCNCW.2018.8368973","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8368973","url":null,"abstract":"A novel low-complexity transmission scheme for Massive Multiuser Multi-Input Multi-Output (M-MU-MIMO) is proposed, where Transmit Antenna Selection (TAS) and beam-forming are jointly performed to exploit multiuser interference. Two separate solutions to the deriving optimization problem are proposed: a mixed-integer programming approach that can optimally solve the TAS-beamforming problem and a heuristic convex approach, based on the assumption of matched filtering beamforming. Numerical results prove that the proposed multiuser interference exploiting approaches are able to greatly outperform previous state-of-the-art schemes, where TAS and beamforming are disjointedly solved.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131453952","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8368986
M. Vahabi, H. Faragardi, H. Fotouhi
Nowadays, the Industrial Internet of Things (IIoT) has the potential to be implemented in factories and supply chains to improve manufacturing efficiency. It is becoming more common to use mobile robots in such factories for further improvements. Adding data collection capability to the mobile robots would realize the mobile sink deployment in future factories. As it is important to reduce the deployment cost, we are aiming at a network with minimum number of mobile sinks while ensuring network reliability and timeliness. In this paper, we analytically model a given trajectory for the motion of mobile sinks and the routing of mobile sinks along the trajectory in an IIoT system. We introduce an optimization problem in the form of Integer Linear Programming (ILP) to specify the minimum number of required mobile sinks to reduce deployment cost of an IIoT system, and also to identify the routing of multiple mobile sinks along a given trajectory. The proposed ILP model can be solved by several existing off-the-shelf ILP-solvers.
{"title":"An analytical model for deploying mobile sinks in industrial Internet of Things","authors":"M. Vahabi, H. Faragardi, H. Fotouhi","doi":"10.1109/WCNCW.2018.8368986","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8368986","url":null,"abstract":"Nowadays, the Industrial Internet of Things (IIoT) has the potential to be implemented in factories and supply chains to improve manufacturing efficiency. It is becoming more common to use mobile robots in such factories for further improvements. Adding data collection capability to the mobile robots would realize the mobile sink deployment in future factories. As it is important to reduce the deployment cost, we are aiming at a network with minimum number of mobile sinks while ensuring network reliability and timeliness. In this paper, we analytically model a given trajectory for the motion of mobile sinks and the routing of mobile sinks along the trajectory in an IIoT system. We introduce an optimization problem in the form of Integer Linear Programming (ILP) to specify the minimum number of required mobile sinks to reduce deployment cost of an IIoT system, and also to identify the routing of multiple mobile sinks along a given trajectory. The proposed ILP model can be solved by several existing off-the-shelf ILP-solvers.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134233862","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 : 2018-04-15DOI: 10.1109/WCNCW.2018.8368985
James Pope, Antonis Vafeas, Atis Elsts, G. Oikonomou, R. Piechocki, I. Craddock
The Internet of Things promises to enable numerous future applications spanning many domains, including health care, and is comprised of devices that are constrained in terms of computational and energy resources. A specific health care application is to ascertain patients' activity of daily living while at home using accelerometer data from non-invasive wearables. It is often necessary to store this data on the device to be retrieved later for analysis. However, the devices typically store far more data than can be transmitted with commonly used low power radios. To mitigate the problem, this paper proposes an energy efficient, lossless compression algorithm that uses an offline frequency distribution to create a symbol-code lookup table. Using an extensive set of data from a previous study, an analysis of the entropy of activities of daily living accelerometer data is presented. The compression algorithm is compared against this estimated entropy. Energy being critical for IoT devices, the trade-off between energy cost for compression versus energy saved during transmission is also analysed.
{"title":"An accelerometer lossless compression algorithm and energy analysis for IoT devices","authors":"James Pope, Antonis Vafeas, Atis Elsts, G. Oikonomou, R. Piechocki, I. Craddock","doi":"10.1109/WCNCW.2018.8368985","DOIUrl":"https://doi.org/10.1109/WCNCW.2018.8368985","url":null,"abstract":"The Internet of Things promises to enable numerous future applications spanning many domains, including health care, and is comprised of devices that are constrained in terms of computational and energy resources. A specific health care application is to ascertain patients' activity of daily living while at home using accelerometer data from non-invasive wearables. It is often necessary to store this data on the device to be retrieved later for analysis. However, the devices typically store far more data than can be transmitted with commonly used low power radios. To mitigate the problem, this paper proposes an energy efficient, lossless compression algorithm that uses an offline frequency distribution to create a symbol-code lookup table. Using an extensive set of data from a previous study, an analysis of the entropy of activities of daily living accelerometer data is presented. The compression algorithm is compared against this estimated entropy. Energy being critical for IoT devices, the trade-off between energy cost for compression versus energy saved during transmission is also analysed.","PeriodicalId":122391,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115086755","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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