{"title":"A Request Scheduling Optimization Mechanism Based on Deep Q-Learning in Edge Computing Environments","authors":"Yaqiang Zhang, Rengang Li, Yaqian Zhao, Ruyang Li","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484512","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484512","url":null,"abstract":"While there have been many explorations about the offloading and scheduling of atomic user requests, the incoming requests with task-dependency, which can be represented as Directed Acyclic Graphs (DAG), are rarely investigated in recent works. In this paper, an online-based concurrent request scheduling mechanism is proposed, where the user requests are split into a set of tasks and are assigned to different edge servers in terms of their status. To optimize the requests scheduling policy in each time slot for minimizing the long term average system delay, we model it as an Markov Decision Process (MDP). Further, a Deep Reinforcement Learning (DRL)-based mechanism is applied to promote the scheduling policy and make decision in each step. Extensive experiments are conducted, and evaluation results demonstrate that our proposed DRL-based technique can effectively improve the long-term performance of scheduling system, compared with the baseline mechanism.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123167150","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}
J. Ayala-Romero, Andres Garcia-Saavedra, X. Costa, G. Iosifidis
{"title":"Demonstrating a Bayesian Online Learning for Energy-Aware Resource Orchestration in vRANs","authors":"J. Ayala-Romero, Andres Garcia-Saavedra, X. Costa, G. Iosifidis","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484585","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484585","url":null,"abstract":"Radio Access Network Virtualization (vRAN) will spearhead the quest towards supple radio stacks that adapt to heterogeneous infrastructure: from energy-constrained platforms deploying cells-on-wheels (e.g., drones) or battery-powered cells to green edge clouds. We demonstrate a novel machine learning approach to solve resource orchestration problems in energy-constrained vRANs. Specifically, we demonstrate two algorithms: (i) BP-vRAN, which uses Bayesian online learning to balance performance and energy consumption, and (ii) SBP-vRAN, which augments our Bayesian optimization approach with safe controls that maximize performance while respecting hard power constraints. We show that our approaches are data-efficient— converge an order of magnitude faster than other machine learning methods—and have provably performance, which is paramount for carrier-grade vRANs. We demonstrate the ad-vantages of our approach in a testbed comprised of fully-fledged LTE stacks and a power meter, and implementing our approach into O-RAN’s non-real-time RAN Intelligent Controller (RIC).","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125223401","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}
Jorge Eduardo Rivadeneira, J. Silva, Ricardo Colomo Palacios, A. Rodrigues, J. Fernandes, F. Boavida
{"title":"A Privacy-Aware Framework Integration into a Human-in-the-Loop IoT System","authors":"Jorge Eduardo Rivadeneira, J. Silva, Ricardo Colomo Palacios, A. Rodrigues, J. Fernandes, F. Boavida","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484634","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484634","url":null,"abstract":"The progressive incorporation of humans as active players within the Internet of Things domain, has positioned the smartphone as one of the main elements of this environment. The multiple functionalities that this device offers, along with its rapid evolution, have benefited usability, thus improving user experience, making this appliance a versatile pocket assistant. Nowadays, these devices comprise a large number of special-purpose sensors capable of collecting a variety of information, that along with the data from other mobile applications such as online social networks, is the fuel for new IoT systems. Much of this data is used to offer innovative services in several areas, making the smartphone an ideal medium for acquiring information. Unfortunately, the control of data flows between smartphones and new IoT systems is scarce, triggering concerns around users’ privacy. Also, we could add to the list the limited privacy preservation mechanisms in current mobile operating systems. It is for this reason that this article aims to propose a privacy-preserving framework that can be integrated into people-centric IoT systems. Besides introducing the architecture of our PACHA framework, the manuscript will present the new vision of our ISABELA platform derived from the integration with the privacy-preserving model.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125183533","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}
Jincheng Wang, Zhuohua Li, John C.S. Lui, Mingshen Sun
{"title":"Topology-Theoretic Approach To Address Attribute Linkage Attacks In Differential Privacy","authors":"Jincheng Wang, Zhuohua Li, John C.S. Lui, Mingshen Sun","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484499","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484499","url":null,"abstract":"Differential Privacy (DP) is well-known for its strong privacy guarantee. In this paper, we show that when there are correlations among attributes in the dataset, only relying on DP is not sufficient to defend against the \"attribute linkage attack\", which is a well-known privacy attack aiming at deducing participant’s attribute information. Our contributions are ① we show that the attribute linkage attack can be initiated with high probability even when data are protected under DP, ② we propose an enhanced DP standard called \"APL-Free ϵ-DP\", ③ by leveraging on topology theory, we design an algorithm \"APLKiller\" which satisfies this standard. Finally, experiments show that our algorithm not only eliminates the attribute linkage attack, but also achieves better data utility.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123260103","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":"A lightweight Data Sharing Scheme with Resisting Key Abuse in Mobile Edge Computing","authors":"Jianhong Zhang, Menglong Wu, Qijia Zhang, Chenggen Peng","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484455","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484455","url":null,"abstract":"To achieve large-scale access control over the shared data, attribute-based encryption(ABE) is a good choice. However, in the existing ABE schemes, a data user which possessing a decryption-key can regenerate a new key since key randomization technique is introduced, which will incur key abuse without any responsibility. In addition, to decrypt the ciphertext, computational complexity of a user is linear to the size of attribute set, it is a formidable challenge for the resource-constrained users. To overcome the problem above, we proposed a lightweight data sharing scheme with Resisting Key Abuse in MEC base on CP-ABE. By using transforming key technique and unforgeability of signature, the proposed scheme can not only resist decryption-key regeneration but also offload decryption computation to MEC server in order to reduce the computation complexity of data user. For a data user, it only takes two exponential operations to decrypt the ciphertext. Security proofs show that our proposed scheme can provide data confidentiality and strong key unforgeability. Compared to several schemes, the proposed scheme is show to have more advantages in terms of computational cost and communication overhead by experiment simulation.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294465","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":"Privacy Policies of Mobile Apps - A Usability Study","authors":"M. Anikeev, Haya Shulman, Hervais Simo","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484434","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484434","url":null,"abstract":"We perform the first post EU General Data Protection Regulation (GDPR) usability study of privacy policies for mobile apps. For our analysis, we collect a dataset of historical (prior to GDPR implementation in May 2018) and contemporary privacy policies in different categories. In contrast to the common belief, that after the GDPR most of the privacy policies are easier to understand, our analysis shows that this is not so.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116427822","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}
Omar Sami Oubbati, Mohammed Atiquzzaman, Abderrahmane Lakas, A. Baz, H. Alhakami, Wajdi Alhakami
{"title":"Multi-UAV-enabled AoI-aware WPCN: A Multi-agent Reinforcement Learning Strategy","authors":"Omar Sami Oubbati, Mohammed Atiquzzaman, Abderrahmane Lakas, A. Baz, H. Alhakami, Wajdi Alhakami","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484496","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484496","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) have been deployed in virtually all tasks of enabling wireless powered communication networks (WPCNs). To ensure sustainable energy support and timely coverage of terrestrial Internet of Things (IoT) devices, a UAV needs to continuously hover and transmit wireless energy signals to charge these devices in the downlink. Then, the devices send their independent information to the UAV in the uplink. However, it was noted that the majority of existing schemes related to UAV-enabled WPCN are mainly based on a single UAV and cannot meet the requirements of a large-scale WPCN. In this paper, we design a separated UAV-assisted WPCN system, where two UAVs are deployed to behave as a UAV data collector (UAV-DC) and UAV energy transmitter (UAV-ET), respectively. Thus, the collection of fresh information and energy transfer are treated separately at the level of the two corresponding UAVs. These two tasks could be enhanced by optimizing the UAVs’ trajectories. For this purpose, we leverage a multi-agent deep Q-network (MADQN) strategy to provide appropriate UAVs’ trajectories that jointly minimize the expected age of information (AoI), enhance the energy transfer to devices, and minimize the energy consumption of UAVs. Simulation results show that our system enhances the performance of our strategy significantly in terms of AoI and energy transfer compared with baseline methods.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122626056","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}
Esteban Municio, Mert Cevik, P. Ruth, J. Márquez-Barja
{"title":"Achieving End-to-End Connectivity in Global Multi-Domain Networks","authors":"Esteban Municio, Mert Cevik, P. Ruth, J. Márquez-Barja","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484534","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484534","url":null,"abstract":"Current trends on 5G network programmability evidence the need for end-to-end flexibility from the node and edge all the way to the cloud. Such multi-domain scenarios require realistic testbeds where different task-offloading algorithms, scheduling functions, and service orchestration techniques can be deployed and tested. While many of these research components can be often explored locally in small and isolated testbeds, new 5G demands are requesting for inter-operable platforms with a wider and a more global scope. The goal for these global platforms is that they can cope with multi-tier hierarchical architectures that are capable to face intense computational processes and heavy network traffic loads, while preserving dependability and keeping a low latency on the task executions and data transmission. In this paper we demonstrate a world-wide attempt to integrate different high-performance testing facilities, located in USA, Belgium, and The Netherlands, to enable experimentation on top of such large and complex architectures. In order to do this, we describe and deploy a multi-domain use case that can benefit from a global hierarchical infrastructure. Finally, we detail the performance characteristics of the deployment, discussing the experiences and technical challenges, and presenting the lessons learned we obtained when building and testing such experimental use case.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121881826","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":"DeepMix: A Real-time Adaptive Virtual Content Registration System with Intelligent Detection","authors":"Yongjie Guan, Xueyu Hou, Tao Han, Shenmin Zhang","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484583","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484583","url":null,"abstract":"This demo proposes a novel virtual content registration system (DeepMix) for MR applications, which integrates state-of-the-art computer vision technology and allows real-time interaction between virtual contents and arbitrary real objects in the physical environment for MR devices. DeepMix effectively utilizes different sensors on MR devices to measure the dimension and spatial location of real objects in the physical environment and improves the quality of experience (QoE) of users adaptively under various situations. Compared with state-of-the-art virtual content registration methods, DeepMix is a light-weight registration system with more flexibility, higher intelligence, and stronger adaptability.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122156105","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":"Machine Learning Toolkit for System Log File Reduction and Detection of Malicious Behavior","authors":"Ralph P. Ritchey, R. Perry","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484572","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484572","url":null,"abstract":"The increasing use of encryption blinds traditional network-based intrusion detection systems (IDS) from performing deep packet inspection. An alternative data source for detecting malicious activity is necessary. Log files found on servers and desktop systems provide an alternative data source containing information about activity occurring on the device and over the network. The log files can be sizeable, making the transport, storage, and analysis difficult. Malicious behavior may appear as normal events in logs, not triggering an error or another obvious indicator, making automated detection challenging. The research described here utilizes a Python-based toolkit approach with unsupervised machine learning to reduce log file sizes and detect malicious behavior.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116595495","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}