Yujie Peng, Xiaoqin Song, F. Liu, Guoliang Xing, Tiecheng Song
{"title":"Joint Task Partition and Computation Offloading for Latency-Sensitive Services in Mobile Edge Networks","authors":"Yujie Peng, Xiaoqin Song, F. Liu, Guoliang Xing, Tiecheng Song","doi":"10.1109/MSN57253.2022.00042","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00042","url":null,"abstract":"With the development of Internet of Things (IoT), wireless communication networks and Artificial Intelligence (AI), more and more real-time applications such as online games and autonomous driving have emerged. However, due to limited computing power and battery capacity, it has become increasingly difficult for local user devices to take on the full range of computing tasks under tight timing constraints. The emerging Mobile Edge Computing (MEC) technology is widely considered to be an important technology for achieving ultra-low latency. However, most of the existing work is focused on non-splittable computation tasks. In fact, data partitioning-oriented applications can be split into multiple subtasks for parallel processing. In this paper, we study the partial computation offloading of multiple detachable tasks in MEC networks, focusing on minimizing the total user device latency in the multi-MEC multi-user scenarios. Considering the dynamic partitioning of tasks, we adopt the barrel theory to construct a linear system of equations to find the optimal solutions and propose an approach for distributed computation offloading based on numerical methods. The simulation results show that the proposed algorithm can reduce the average user device latency by 31 % compared with the binary offloading method.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129011699","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}
{"title":"Alz-Sense+: An Auto Time-synchronized Multi-class Algorithm for Dementia Detection","authors":"S. M. Shovan, Sajal Kumar Das","doi":"10.1109/MSN57253.2022.00108","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00108","url":null,"abstract":"Dementia, a cognitive disease that affects more than 50 million people, causes some degree of disability in remembering simple things and following basic instructions with unusual delays. Researchers proposed different pre-clinical methods with mediocre performance leaving the door open for further improvement. One of the most successful pre-clinical tests, SLUMS (Saint Louis University Mental Status), incorpo-rates verbal responses in the form of standardized questionnaires. It involves expert judgment to label patients such as dementia, MCI (Mild Cognitive Impairment), or healthy based on an overall score. However, a nonverbal stress response is also taken into account in the Alz-Sense algorithm, which has a few underlying false assumptions, i) uniformity of answering duration, ii) equity of questions stress level, and iii) unfair stress penalty while discarding healthy patient detection. Moreover, the stress data of the corresponding question is manually synchronized using the examiner's hand-shaken data of the wearable device. As a goal to improve the original Alz-Sense algorithm, Alz-Sense+ is proposed to handle these three assumptions by incorporating the windowing process, statistical and visual approach. Be-sides, it also automated the synchronization between questions and corresponding sensor data by estimating time slots while proposing an optimal ordering of questions that mitigates the unintended consequences. Alz-Sense+ achieved 81.39%, 80.76%, and 82.35 % accuracy, sensitivity, and specificity, respectively, which is 7.39%, 0.01 %, and 15.75% improvement over the original Alz-Sense algorithm. In a nutshell, the new Alz-Sense+ algorithm outperformed the existing algorithm by addressing a few underlying assumptions while eliminating a few limitations of the original algorithm.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128784632","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}
Eduardo C. Oliveira, Stephanie M. Soares, Marcelo M. Carvalho
{"title":"K-Means Based Grouping of Stations with Dynamic AID Assignment in IEEE 802.11ah Networks","authors":"Eduardo C. Oliveira, Stephanie M. Soares, Marcelo M. Carvalho","doi":"10.1109/MSN57253.2022.00034","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00034","url":null,"abstract":"The IEEE 802.11ah amendment extends the success of traditional IEEE 802.11 networks to sub-GHz frequency bands by allowing higher signal coverage and introducing new capabilities to handle a massive number of stations in applications for the Internet of Things. The restricted access window (RAW) mechanism is the key technique to limit contention by dividing stations into RAW groups and RAW time slots according to AID numbers that can be changed dynamically via AID Switch Response frames. To date, however, such feature has not been investigated, especially in cooperation with some grouping scheme. This paper presents the first investigation on the use of AID Switch Response frames to implement dynamic grouping. The goal is to improve throughput fairness among stations that are geographically distributed over some area. The grouping scheme is based on the K-Means algorithm, which takes as input the length and signal strength of data frames received by the AP, and the modulation and coding schemes (MCS) adopted by stations. Simulation results show significant gains in throughput fairness obtained with the proposed grouping scheme compared to random grouping over different network scenarios.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"430 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116001581","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}
Xiongfeng Hu, Yibo Jin, Kefeng Wu, Zhuzhong Qian, Sanglu Lu
{"title":"User-Perceived QoE Adaptation for Accelerated Playback in Mobile Video Streaming","authors":"Xiongfeng Hu, Yibo Jin, Kefeng Wu, Zhuzhong Qian, Sanglu Lu","doi":"10.1109/MSN57253.2022.00033","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00033","url":null,"abstract":"User-perceived quality of experience (QoE) is critical as mobile video streaming experiences a substantial growth. User's demands are becoming diversified where accelerated play-back is the preference of a considerable part of users. However, the limited and fluctuate mobile bandwidth is often not capable of satisfying user's demand of watching video at 2x or higher speed because of consequential frequent rebuffering. Previous adaptive bitrate (ABR) algorithms hardly consider the variety of user playback rates. In this work, we fully exploit the relation between user-perceived, i.e., subjective video quality and the characteristic of video content. The result of our motivational experiments shows that viewers are less sensitive to the bitrate variation and playback rate alternation if there is higher degree of motion in the video. With above guidelines, we adaptively adjust the quality configuration and playback rate to significantly reduce the rebuffering while achieving similar or even higher subjective quality. Then we formulate subjective quality and playback rate adaption as a QoE maximization problem and propose the content based subjective quality and playback rate adaptation algorithm (CSP) utilizing Lyapunov optimization technique. Via rigorous proof, the time-average QoE achieved by CSP is in $O(1/V)$ gap compared to optimal value, where $V$ is the control parameter. Extensive evaluations confirm the superiority of our proposed algorithm over other state-of-the-art algorithms under both normal and accelerated playback rate.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114383184","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}
{"title":"An atomic member addition mechanism for permissioned blockchain based on autonomous rollback","authors":"Qihui Zhou, Xianglin Dang, Yazhe Wang, Zhen Xu, Penghui Lv","doi":"10.1109/MSN57253.2022.00068","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00068","url":null,"abstract":"As a distributed ledger technology, the addition of new members in permissioned blockchain is usually composed of several steps among distributed nodes. The addition can not be considered successful until all of the steps are completed. In other words, these steps are an atomic operation. However, there is no solution for the atomic operation in existing permissioned blockchain, leading to an inconsistent state when the addition of new members is partially completed. To implement the atomic member addition in permissioned blockchain, we propose a method targeting at the atomic addition of new members based on distributed and autonomous rollback. After member addition starts, distributed nodes of existing members detect the new node and decide whether to rollback or not, instead of getting commands from the coordinator. After deciding to rollback, a new configuration block is added to achieve rollback of the uncompleted member addition. In order for the new configuration block to pass the policy validation of orderers, we set a rollback mode for orderers. The evaluation results show that our method can actually implement atomic member addition and has little impact on performance.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114776836","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}
{"title":"PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework","authors":"Zhengxin Yu, Yang Lu, P. Angelov, N. Suri","doi":"10.1109/MSN57253.2022.00086","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00086","url":null,"abstract":"With the advancement in Machine Learning (ML) techniques, a wide range of applications that leverage ML have emerged across research, industry, and society to improve application performance. However, existing ML schemes used within such applications struggle to attain high model accuracy due to the heterogeneous and distributed nature of their generated data, resulting in reduced model performance. In this paper we address this challenge by proposing PPFM: an adaptive and hierarchical Peer-to-Peer Federated Meta-learning framework. Instead of leveraging a conventional static ML scheme, PPFM uses multiple learning loops to dynamically self-adapt its own architecture to improve its training effectiveness for different generated data characteristics. Such an approach also allows for PPFM to remove reliance on a fixed centralized server in a distributed environment by utilizing peer-to-peer Federated Learning (FL) framework. Our results demonstrate PPFM provides significant improvement to model accuracy across multiple datasets when compared to contemporary ML approaches.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123772615","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}
{"title":"Crowdsourcing Mobile Data for A Passive Indoor Positioning System - The MAA Case Study","authors":"R. Guan, R. Harle","doi":"10.1109/MSN57253.2022.00024","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00024","url":null,"abstract":"Crowdsourcing radio signal fingerprints to build a radio map for indoor positioning system is an emerging alternative to conventional labour-costly manual survey. However, existing crowdsourced systems heavily rely on ground-truth location inputs or unrealistic constraints on the contributors, deterring a wider adaption of crowdsourced systems. Our work exploits three generic constraints of mobile data to retrieve the locations of the crowdsourced fingerprints and builds a completely passive indoor positioning system that assumes no manual intervention or unnatural constraints on the contributors. The proposed system was further evaluated in the Museum of Archaeology and Anthropology (MAA) with passively crowd- sourced data contributed by actual visitors while visitors can behave naturally without catering to crowdsourcing. Results show that the proposed system can achieve positioning accuracy comparable to traditional manual survey-based system with essentially no extra manual effort.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121799753","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}
{"title":"Space-Air-Ground-Aqua Integrated Intelligent Network: Vision, and Potential Techniques","authors":"Jinhui Huang, Junsong Yin, Shuangshuang Wang","doi":"10.1109/MSN57253.2022.00164","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00164","url":null,"abstract":"The space-air-ground-aqua integrated network will become the basic form of the next generation network. Various technologies, including artificial intelligence, big data, cloud computing, edge computing, etc., will be deeply integrated into the network to form an integrated intelligent network of land, sea, air and space. In this article, we will present the vision for the development of the space-air-ground-aqua integrated intelligent network and describe its main features. We put forward a network architecture which integrated sub-networks of space, air, land and sea while emphasizing network interconnection, resources sharing, cooperative control and service reuse. We also discussed several promising technologies, including the THz, free space optical communication, software defined network, network function virtualization, edge intelligent, digital twins, physical layer security and blockchains.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121985909","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}
{"title":"Three-dimensional Key Distribution Scheme in Wireless Sensor Networks","authors":"Wanqing Wu, Ziyang Zhang, Yahua Dong, Caixia Ma","doi":"10.1109/MSN57253.2022.00138","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00138","url":null,"abstract":"One of the major security challenges faced by wireless sensor networks(WSNs) is establishing a secure link for communication between neighboring sensor nodes. Finding a balance between connection, overhead, and resilience against node capture attacks is difficult due to the resource limits of sensor nodes. We propose a new three-dimensional key distribution scheme for wireless sensor networks based on polynomial and random key distribution schemes. The key pool is divided into two sections in the proposed scheme: key pool 1 is generated by the polynomial pool, and key pool 2 is generated by key pool 1. A three-dimensional key distribution model is constructed using the key pool and the coefficients of the polynomials. It can enhance network resilience while maintaining good connectivity by dynamically adjusting the degree of polynomials and the size of the polynomial pool. This paper analyzes the performance of the proposed scheme and compares it with other schemes. The results show that the proposed scheme has better local connectivity and resilience against node capture attacks when compared with the previous schemes.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130605981","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}
{"title":"Web Attack Payload Identification and Interpretability Analysis Based on Graph Convolutional Network","authors":"Yijia Xu, Yong Fang, Zhonglin Liu","doi":"10.1109/MSN57253.2022.00071","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00071","url":null,"abstract":"Web attack payload identification is a significant part of the Web defense system. The current Web attack payload identification usually combines natural language processing and deep learning to automatically build a detection model to intercept malicious payloads. However, these detection methods ignore the bidirectional association between fields and is prone to the payload dilution problem for long strings. In addition, the weak interpretability of deep learning models makes it difficult for researchers to solve the problem of model pollution and adjust the model according to the prediction logic. Therefore, this paper proposes a new Web attack payload identification method based on Graph Convolutional Network (GCN), which can effectively extract Web payload features and help model interpretability analysis. The core of this method is to transform the text feature problem into a graph feature extraction problem and to understand the structure and content of the Web payload from the graph perspective. The method performs node embedding on the Web payload graph through GCN, then converts the embedding vector into a graph feature vector through a feature fusion method. The node ablation method is used to analyze malicious payloads' interpretability and calculate the predicted impact rate of nodes inside the graph structure. The experiments on the CSIC 2010 v2 HTTP dataset show that the method proposed in this paper has high accuracy for identifying Web attack payloads, and the node embedding of the Relational Graph Convolutional Network (RGCN) method is more suitable for identifying Web attack payloads than other GCN methods. The research results of the paper show that the model interpretability analysis based on the Web payload graph is reasonable and can effectively assist researchers in adjusting the model and preventing the problem of model pollution.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121105524","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}