Pub Date : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013327
Bin Li
With the rapid growth of wireless compute-intensive services (such as image recognition, real-time language translation, or other artificial intelligence applications), efficient wireless algorithm design should not only address when and which users should transmit at each time instance (referred to as wireless scheduling) but also determine where the computation should be executed (referred to as offloading decision) with the goal of minimizing both computing latency and energy consumption. Despite the presence of a variety of earlier works on the efficient offloading design in wireless networks, to the best of our knowledge, there does not exist a work on the realistic user- level dynamic model, where each incoming user demands a heavy computation and leaves the system once its computing request is completed. To this end, we formulate a problem of an optimal offloading design in the presence of dynamic compute-intensive applications in wireless networks. Then, we show that there exists a fundamental logarithmic energy- workload tradeoff for any feasible offloading algorithm, and develop an optimal threshold-based offloading algorithm that achieves this fundamental logarithmic bound.
{"title":"Optimal Offloading for Dynamic Compute-Intensive Applications in Wireless Networks","authors":"Bin Li","doi":"10.1109/GLOBECOM38437.2019.9013327","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013327","url":null,"abstract":"With the rapid growth of wireless compute-intensive services (such as image recognition, real-time language translation, or other artificial intelligence applications), efficient wireless algorithm design should not only address when and which users should transmit at each time instance (referred to as wireless scheduling) but also determine where the computation should be executed (referred to as offloading decision) with the goal of minimizing both computing latency and energy consumption. Despite the presence of a variety of earlier works on the efficient offloading design in wireless networks, to the best of our knowledge, there does not exist a work on the realistic user- level dynamic model, where each incoming user demands a heavy computation and leaves the system once its computing request is completed. To this end, we formulate a problem of an optimal offloading design in the presence of dynamic compute-intensive applications in wireless networks. Then, we show that there exists a fundamental logarithmic energy- workload tradeoff for any feasible offloading algorithm, and develop an optimal threshold-based offloading algorithm that achieves this fundamental logarithmic bound.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"7 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73537551","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013167
Harmanjeet Kaur, Neeraj Kumar, J. Rodrigues
The multi-set intersection cardinality operation is used for calculation of similarity between two sets which has various applications such as cluster analysis, image segmentation, social network analysis, etc. The need of Privacy Preserving Computation of Multi-set Intersection Cardinality (PPCMIC) operation is raised when two parties want to compute similarities between their datasets without disclosing their data to each other. Existing methods for PPCMIC are either insecure or inefficient. In our work, to address this gap, PPCMIC protocol based on lightweight randomization protocol is proposed which is secure and efficient in terms of computation cost. The experimental work has been done on simulated and real datasets to show that proposed protocols are more efficient then the existing techniques.
{"title":"An Efficient Privacy Preserving Computation of Multiset Intersection Cardinality","authors":"Harmanjeet Kaur, Neeraj Kumar, J. Rodrigues","doi":"10.1109/GLOBECOM38437.2019.9013167","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013167","url":null,"abstract":"The multi-set intersection cardinality operation is used for calculation of similarity between two sets which has various applications such as cluster analysis, image segmentation, social network analysis, etc. The need of Privacy Preserving Computation of Multi-set Intersection Cardinality (PPCMIC) operation is raised when two parties want to compute similarities between their datasets without disclosing their data to each other. Existing methods for PPCMIC are either insecure or inefficient. In our work, to address this gap, PPCMIC protocol based on lightweight randomization protocol is proposed which is secure and efficient in terms of computation cost. The experimental work has been done on simulated and real datasets to show that proposed protocols are more efficient then the existing techniques.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"41 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73554229","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013813
Di Wu, Xiang Sun, N. Ansari
Multiple drone-mounted base stations (DBSs) are used to be deployed over a disaster struck area to help mobile users (MUs) communicate with working BSs, which are located beyond the disaster-struck area. DBSs are considered as relay nodes between MUs and working BSs. In order to relax the bottleneck in wireless backhaul links, we propose a cooperative drone assisted mobile access network architecture by enabling DBSs (whose backhaul links are congested) to offload their traffic to other DBSs (whose backhaul links are not congested) via DBS-to-DBS communications. We formulate the DBS placement and channel allocation problem in the context of the cooperative drone assisted mobile access network architecture, and design a COoperative DBS plAcement and CHannel allocation (COACH) algorithm to solve the problem. The performance of COACH is demonstrated via extensive simulations.
在灾区上空部署多个无人机基站(drone-mounted base station, dbs)，帮助移动用户(mu)与位于灾区以外的正常基站进行通信。DBSs被认为是mu和工作BSs之间的中继节点。为了缓解无线回程链路的瓶颈，我们提出了一种协作式无人机辅助移动接入网架构，使回程链路拥塞的dbs能够通过DBS-to-DBS通信将其流量分流给其他dbs(回程链路不拥塞)。在协同无人机辅助移动接入网架构背景下，提出了DBS布局与信道分配问题，并设计了一种协同DBS布局与信道分配(COACH)算法来解决该问题。通过大量的仿真验证了COACH的性能。
{"title":"A Cooperative Drone Assisted Mobile Access Network for Disaster Emergency Communications","authors":"Di Wu, Xiang Sun, N. Ansari","doi":"10.1109/GLOBECOM38437.2019.9013813","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013813","url":null,"abstract":"Multiple drone-mounted base stations (DBSs) are used to be deployed over a disaster struck area to help mobile users (MUs) communicate with working BSs, which are located beyond the disaster-struck area. DBSs are considered as relay nodes between MUs and working BSs. In order to relax the bottleneck in wireless backhaul links, we propose a cooperative drone assisted mobile access network architecture by enabling DBSs (whose backhaul links are congested) to offload their traffic to other DBSs (whose backhaul links are not congested) via DBS-to-DBS communications. We formulate the DBS placement and channel allocation problem in the context of the cooperative drone assisted mobile access network architecture, and design a COoperative DBS plAcement and CHannel allocation (COACH) algorithm to solve the problem. The performance of COACH is demonstrated via extensive simulations.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"10 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73903798","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}
In this paper, we study some of the security pitfalls present in the OpenFlow protocol, which plays a central role in Software Defined Networks. Specifically, we introduce information disclosure attacks capable of identifying idle and hard timeout values, and the number of free entries in the flow tables at SDN switches. We then leverage this information to mount Denial of Service (DoS) attacks using a small number of packets and without flooding the SDN network, making it harder to detect. Experimental results indicate that mounting the proposed attack leads to delays and packet losses for legitimate flows. We further propose solutions to detect and mitigate similar attacks.
{"title":"SDN Security: Information Disclosure and Flow Table Overflow Attacks","authors":"Aditya Patwardhan, Deepthi Jayarama, Nitish Limaye, Shivaji Vidhale, Zarna Parekh, K. Harfoush","doi":"10.1109/GLOBECOM38437.2019.9014048","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9014048","url":null,"abstract":"In this paper, we study some of the security pitfalls present in the OpenFlow protocol, which plays a central role in Software Defined Networks. Specifically, we introduce information disclosure attacks capable of identifying idle and hard timeout values, and the number of free entries in the flow tables at SDN switches. We then leverage this information to mount Denial of Service (DoS) attacks using a small number of packets and without flooding the SDN network, making it harder to detect. Experimental results indicate that mounting the proposed attack leads to delays and packet losses for legitimate flows. We further propose solutions to detect and mitigate similar attacks.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"18 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75625429","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9014104
Maram Bani Younes, A. Boukerche, Rodolfo W. L. Coutinho
Freeways have been known over decades as high-speed multi-lane roads, where the opposite traffic directions are completely separated. No intersections, pedestrians, or bicycles are expected on these road scenarios, besides specific ramps are designed to facilitate the entrance and exit of vehicles. Although freeway driving is considered safer and faster for experienced drivers, it can be more demanding and difficult for fresh or exhausted ones. Entering and existing the freeway road are considered the most critical situations where the driver needs to achieve high synchronizations with the surrounding traffic there. In this work, we introduce a freeway driving assistance protocol for drivers aiming to reduce the difficulties for fresh drivers and enhance the safety and efficiency conditions over the freeway road scenarios. This proposed protocol can also be used by the autonomous vehicles where no drivers control the vehicle. We evaluate the performance of the proposed protocol using several simulated driving scenarios. It shows a good performance in terms of increasing the safety of traffic and smoothing the traffic speed of vehicles.
{"title":"An Efficient Freeway Driving Assistance Protocol in Vehicular Networks","authors":"Maram Bani Younes, A. Boukerche, Rodolfo W. L. Coutinho","doi":"10.1109/GLOBECOM38437.2019.9014104","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9014104","url":null,"abstract":"Freeways have been known over decades as high-speed multi-lane roads, where the opposite traffic directions are completely separated. No intersections, pedestrians, or bicycles are expected on these road scenarios, besides specific ramps are designed to facilitate the entrance and exit of vehicles. Although freeway driving is considered safer and faster for experienced drivers, it can be more demanding and difficult for fresh or exhausted ones. Entering and existing the freeway road are considered the most critical situations where the driver needs to achieve high synchronizations with the surrounding traffic there. In this work, we introduce a freeway driving assistance protocol for drivers aiming to reduce the difficulties for fresh drivers and enhance the safety and efficiency conditions over the freeway road scenarios. This proposed protocol can also be used by the autonomous vehicles where no drivers control the vehicle. We evaluate the performance of the proposed protocol using several simulated driving scenarios. It shows a good performance in terms of increasing the safety of traffic and smoothing the traffic speed of vehicles.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"102 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75795523","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013977
Abdellah Kaci, A. Rachedi
In this paper, we propose Mc-Track, a new secure data oriented Cloud based vehicular tracking system. We introduced in Mc-Track an adaptive approach which consists in selection of security level according to data kinds. The architecture of the Mc-Track is composed of three levels: the vehicular network, the Cloud service, and proxies called Tracking Authorities, in charge of performing Attribute Based Encryption (ABE). We provided selective encryption and adaptive security in the Tracking Authority (TA), using the machine learning classifier k-Nearest Neighbours (k-NN). We conducted experimental study to evaluate the efficiency of the proposed k-NN classifier in selective encryption and adaptive security. So we compared the accuracy of the predictions of k-NN classifier to the accuracy of predictions using Support Vector Machine (SVM) classifier. Experimental results, has shown that the k-NN classifier is more accurate than SVM classifier.
{"title":"Mc-Track: A Cloud Based Data Oriented Vehicular Tracking System with Adaptive Security","authors":"Abdellah Kaci, A. Rachedi","doi":"10.1109/GLOBECOM38437.2019.9013977","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013977","url":null,"abstract":"In this paper, we propose Mc-Track, a new secure data oriented Cloud based vehicular tracking system. We introduced in Mc-Track an adaptive approach which consists in selection of security level according to data kinds. The architecture of the Mc-Track is composed of three levels: the vehicular network, the Cloud service, and proxies called Tracking Authorities, in charge of performing Attribute Based Encryption (ABE). We provided selective encryption and adaptive security in the Tracking Authority (TA), using the machine learning classifier k-Nearest Neighbours (k-NN). We conducted experimental study to evaluate the efficiency of the proposed k-NN classifier in selective encryption and adaptive security. So we compared the accuracy of the predictions of k-NN classifier to the accuracy of predictions using Support Vector Machine (SVM) classifier. Experimental results, has shown that the k-NN classifier is more accurate than SVM classifier.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"248 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75830811","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013513
Shuo Peng, Wei Gong, Baoxian Zhang, Cheng Li
With the widespread of smart devices, mobile crowdsensing has become an attractive way to perceive and collect sensing data. In this paper, we focus on studying AP-assisted task assignment in mobile crowdsensing. The objective is to effectively reduce the average or worst-case makespan of tasks. We focus on a scenario that a task requester needs the assistance of mobile users for task accomplishment while they can meet directly or via APs in an opportunistic manner. We model the crowdsensing system and then formulate the problems under study. We then propose an AP-assisted average makespan sensitive online task assignment (AP-AOTA) algorithm and an AP-assisted largest makespan sensitive online task assignment (AP-LOTA) algorithm. In the proposed algorithms, task assignment at each step considers both the inter-encountering time between requester and each user and that between them while going through APs. We present design details of the proposed algorithms. We derive their computational complexities to be $O(mn^2)$, where $m$ is the number of tasks and $n$ is the number of users. Finally, trace-driven simulation results show that the proposed algorithms outperform existing work.
{"title":"AP-Assisted Online Task Assignment for Mobile Crowdsensing","authors":"Shuo Peng, Wei Gong, Baoxian Zhang, Cheng Li","doi":"10.1109/GLOBECOM38437.2019.9013513","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013513","url":null,"abstract":"With the widespread of smart devices, mobile crowdsensing has become an attractive way to perceive and collect sensing data. In this paper, we focus on studying AP-assisted task assignment in mobile crowdsensing. The objective is to effectively reduce the average or worst-case makespan of tasks. We focus on a scenario that a task requester needs the assistance of mobile users for task accomplishment while they can meet directly or via APs in an opportunistic manner. We model the crowdsensing system and then formulate the problems under study. We then propose an AP-assisted average makespan sensitive online task assignment (AP-AOTA) algorithm and an AP-assisted largest makespan sensitive online task assignment (AP-LOTA) algorithm. In the proposed algorithms, task assignment at each step considers both the inter-encountering time between requester and each user and that between them while going through APs. We present design details of the proposed algorithms. We derive their computational complexities to be $O(mn^2)$, where $m$ is the number of tasks and $n$ is the number of users. Finally, trace-driven simulation results show that the proposed algorithms outperform existing work.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"32 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74549493","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013832
Peiyao Li, Heyang Cao, Mingsheng Wang
Ciphertext-policy attribute-based encryption (CP- ABE) with verifiable outsourced decryption is a mechanism for secure fine-grained access control over encrypted data, and it is suitable for cloud computing applications. However, there exists a risk in CP-ABE with verifiable outsourced decryption that can lead to serious consequences and may limit its wide applications: the key generation center may have misbehavior. In this paper, we present BSA, the blockchain-based specification for ABE to mitigate this risk. We introduce the specification to regulate the data access control and a proof mechanism to supervise whether the key generation center has misbehavior. Also, we can provide decentralized and automated incentives with BSA by smart contracts and blockchain-based consensus.
{"title":"BSA: Enhancing Attribute-Based Encryption in Cloud Computing with Decentralized Specification","authors":"Peiyao Li, Heyang Cao, Mingsheng Wang","doi":"10.1109/GLOBECOM38437.2019.9013832","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013832","url":null,"abstract":"Ciphertext-policy attribute-based encryption (CP- ABE) with verifiable outsourced decryption is a mechanism for secure fine-grained access control over encrypted data, and it is suitable for cloud computing applications. However, there exists a risk in CP-ABE with verifiable outsourced decryption that can lead to serious consequences and may limit its wide applications: the key generation center may have misbehavior. In this paper, we present BSA, the blockchain-based specification for ABE to mitigate this risk. We introduce the specification to regulate the data access control and a proof mechanism to supervise whether the key generation center has misbehavior. Also, we can provide decentralized and automated incentives with BSA by smart contracts and blockchain-based consensus.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"22 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73031133","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013850
D. Kaur, Rahul Kumar, Neeraj Kumar, M. Guizani
With the rapid increase in the energy demands from different sectors across the globe, there is lot of pressure on the power grid to maintain a balance between the demand and supply. In this context, smart grid (SG) may play a vital role as it provides the bidirectional energy flow between utilities and end users. Contrary to the traditional power grid, it has advanced switching and sensing devices (for example, sensors and actuators) for load balancing and peak shaving. In SG systems, various smart devices and electrical appliances which are placed in the smart buildings regularly generate data related to energy usage, occupancy patterns, or movements of the end users. By applying an efficient data pre-processing and data analytics technique, this data can be analyzed to extract important energy patterns which can be used in demand response management, load forecasting, and peak shaving. But, one of the main challenges in SG systems is to have an integrated approach to pre-process and analyze the data with minimum error rates and higher accuracy. To tackle the aforementioned challenges, an unified scheme based upon the deep learning and recurrent neural networks (RNN) is proposed in this paper. The data collected from smart homes is pre-processed and decomposed using high-order singular value decomposition (HOSVD) and then long short-term memory (LSTM) model is applied on it. As the data collected from SG is time series-based data so LSTM based regression model gives minimum root mean square (RMSE) and mean absolute percentage error (MAPE) values as compared to the other techniques reported in the literature. A case study of 112 smart homes with hourly basis data is considered for evaluation of the proposed scheme in which energy patterns are predicted with least RMSE and MAPE. The results obtained clearly show that the proposed scheme has superior performance in comparison to the other existing schemes
{"title":"Smart Grid Energy Management Using RNN-LSTM: A Deep Learning-Based Approach","authors":"D. Kaur, Rahul Kumar, Neeraj Kumar, M. Guizani","doi":"10.1109/GLOBECOM38437.2019.9013850","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013850","url":null,"abstract":"With the rapid increase in the energy demands from different sectors across the globe, there is lot of pressure on the power grid to maintain a balance between the demand and supply. In this context, smart grid (SG) may play a vital role as it provides the bidirectional energy flow between utilities and end users. Contrary to the traditional power grid, it has advanced switching and sensing devices (for example, sensors and actuators) for load balancing and peak shaving. In SG systems, various smart devices and electrical appliances which are placed in the smart buildings regularly generate data related to energy usage, occupancy patterns, or movements of the end users. By applying an efficient data pre-processing and data analytics technique, this data can be analyzed to extract important energy patterns which can be used in demand response management, load forecasting, and peak shaving. But, one of the main challenges in SG systems is to have an integrated approach to pre-process and analyze the data with minimum error rates and higher accuracy. To tackle the aforementioned challenges, an unified scheme based upon the deep learning and recurrent neural networks (RNN) is proposed in this paper. The data collected from smart homes is pre-processed and decomposed using high-order singular value decomposition (HOSVD) and then long short-term memory (LSTM) model is applied on it. As the data collected from SG is time series-based data so LSTM based regression model gives minimum root mean square (RMSE) and mean absolute percentage error (MAPE) values as compared to the other techniques reported in the literature. A case study of 112 smart homes with hourly basis data is considered for evaluation of the proposed scheme in which energy patterns are predicted with least RMSE and MAPE. The results obtained clearly show that the proposed scheme has superior performance in comparison to the other existing schemes","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"3 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73262008","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 : 2019-12-01DOI: 10.1109/GLOBECOM38437.2019.9013258
Robert Schmidt, Chia-Yu Chang, N. Nikaein
Future mobile networks are supposed to handle a variety of services with different requirements. Network slicing is considered to be a key enabler to cope with the increasing complexity of these networks. This includes slicing of the radio resources in order to use them efficiently. In this paper, we propose a radio resource slicing system for three types of slices with specific radio resource/quality of service (QoS) requirements. It enables co-existence of (1) rate-based/efficiency-oriented and (2) low-latency slices, as well as (3) slices with fixed allocations. Slice scheduling is based on utility functions with a priority-based resource allocation. Using simulations, we validate the applicability of the proposed system, and demonstrate that both a guaranteed throughput and low delay for different slices at the same time is possible. Our system outperforms existing slicing solutions in terms of delay requirement satisfaction and efficient resource utilization.
{"title":"Slice Scheduling with QoS-Guarantee Towards 5G","authors":"Robert Schmidt, Chia-Yu Chang, N. Nikaein","doi":"10.1109/GLOBECOM38437.2019.9013258","DOIUrl":"https://doi.org/10.1109/GLOBECOM38437.2019.9013258","url":null,"abstract":"Future mobile networks are supposed to handle a variety of services with different requirements. Network slicing is considered to be a key enabler to cope with the increasing complexity of these networks. This includes slicing of the radio resources in order to use them efficiently. In this paper, we propose a radio resource slicing system for three types of slices with specific radio resource/quality of service (QoS) requirements. It enables co-existence of (1) rate-based/efficiency-oriented and (2) low-latency slices, as well as (3) slices with fixed allocations. Slice scheduling is based on utility functions with a priority-based resource allocation. Using simulations, we validate the applicability of the proposed system, and demonstrate that both a guaranteed throughput and low delay for different slices at the same time is possible. Our system outperforms existing slicing solutions in terms of delay requirement satisfaction and efficient resource utilization.","PeriodicalId":6868,"journal":{"name":"2019 IEEE Global Communications Conference (GLOBECOM)","volume":"80 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74053730","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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