ACM SIGCOMM 2017 Workshop on Mobile Edge Communications (MECOMM’2017)
Workshop Program
- Opening and Welcome
- Keynote Presentation
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Motivating Examples and OpenNetVM as a Platform for Mobile Edge Computing
K. K. Ramakrishnan (University of California, Riverside)
- Session 1: Edge Infrastructure
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Virtualization and Programmability in Mobile Wireless Networks: Architecture and Resource Management
Kleber V. Cardoso (Universidade Federal de Goias), Mohammad J. Abdel-Rahman (Virginia Tech), Allen B. MacKenzie (Virginia Tech), Luiz A. DaSilva (Trinity College Dublin)
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Abstract: We present a high-level end-to-end architecture for virtualization and programmability in next-generation mobile wireless networks. Our architecture envisions three major players: Service Providers, who wish to orchestrate wireless networks with particular characteristics to support particular applications; Resource Providers, who contribute resources such as spectrum, access points, backhaul infrastructure, and computing; and Virtual Network Builders, who marshal resources into networks for Service Providers. We take into account resource sharing and investigate how virtualization and programmability affect resource management. We show that: (i) virtualization reduces cost signifcantly, (ii) this cost reduction does not degrade the user satisfaction, and (iii) non-virtualized networks need to keep a large amount of idle capacity to satisfy coverage.
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Dennis Grewe (Robert Bosch GmbH), Marco Wagner (Robert Bosch GmbH), Mayutan Arumaithurai (University of Goetingen), Ioannis Psaras (University College London), Dirk Kutscher (Huawei German Research Center)
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Abstract: Connected vehicle systems form the basis for future features of functions and applications within the automotive domain. In order to allow resource intensive services, cloud offloading and especially Mobile Edge Computing is a promising approach. In this paper, we present a detailed futuristic vehicular scenario – Electronic Horizon – and list the challenges. We argue that the resulting challenges are representative of many of the envisioned use-cases of Mobile Edge Computing. We then present how Information-Centric Networking in combination with Mobile Edge Computing has the potential to support such a futuristic scenario. Finally, we present research directions that could enhance the solution space.
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Wi-Stitch: Content Delivery in Converged Edge Networks
Aravindh Raman (King's College London), Nishanth Sastry (King's College London), Arjuna Sathiaseelan (University of Cambridge), Jigna Chandaria (BBC R&D), Andrew Secker (BBC R&D)
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Abstract: Wi-Fi, the most commonly used access technology at the very edge, supports download speeds that are orders of magnitude faster than the average home broadband or cellular data connection. Furthermore, it is extremely common for users to be within reach of their neighbours’ Wi-Fi access points. Given the skewed nature of interest in content items, it is likely that some of these neighbours are interested in the same items as the users. We sketch the design of Wi-Stitch, an architecture that exploits these observations to construct a highly efficient content sharing infrastructure at the very edge and show through analysis of a real workload that it can deliver substantial (up to 70%) savings in network traffic. The Wi-Stitch approach can be used both by clients of fixed-line broadband, as well as mobile devices obtaining indoors access in converged networks.
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Managing Data in Computational Edge Clouds
Nitinder Mohan (University of Helsinki), Pengyuan Zhou (University of Helsinki), Keerthana Govindaraj (Robert Bosch GmbH), Jussi Kangasharju (University of Helsinki)
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Abstract: Edge clouds handle data and computations closer to its source and users. Applications like industrial automation, bring new challenges and require solutions tailored for computation-centric edge cloud networks. In this paper we build on existing edge and fog computing models and develop a solution to predict and store data in edge resource caches for upcoming computations. Our solution is based on grouping caches according to the workloads they serve. We further develop methods for populating the caches and ensuring the coherence of the cached data. We evaluate the performance of our grouping mechanisms and show that they bring significant performance gains, both in terms of network traffic and access latency.
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- Coffee Break
- Invited Talk
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Platforms for Advanced Wireless Research (PAWR): Helping Define a New Edge Computing Paradigm
Abhimanyu Gosain (Technical Program Director of PAWR Project Office)
- Lunch Break
- Session 2: Protocol Optimisation for MEC
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Mobility-based Proactive Multicast for seamless mobility support in cellular network environments
Xenofon Vasilakos (Athens University of Economics and Business), Mohammed Q. Al-Khalidi (University of Essex Colchester), Vasilios A. Siris (Athens University of Economics and Business), Martin J. Reed (University of Essex Colchester), Nikolaos Thomos (University of Essex Colchester), George C. Polyzos (Athens University of Economics and Business)
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Abstract: Information-Centric Networking (ICN) is receiver driven, asynchronous and location-independent, hence it natively supports client-mobility. However, post-handover delay is a problem for delay-sensitive mobile applications, as they need to (re-)submit their subscriptions and wait for them to get resolved and (probably re-) transmitted before receiving the demanded data. To avoid this problem and optimize performance, this paper proposes a Mobility-based Proactive Multicast (MPM) scheme. Unlike reactive or blind multicast solutions proposed in the past, MPM takes autonomous decisions locally at various network access points (cells) prior to the movement of mobile clients, using a semi-Markov mobility prediction model that predicts next-cell transitions, along with anticipating the duration between the transitions for an arbitrary user in a cellular network. Since cellular backhaul links are typically a bottleneck, MPM trades-off effectively part of the capacity of the (congested) backhaul link for a decreased delay experienced by users after handovers thanks to a congestion pricing scheme used for backhaul capacity allocation. Our preliminary performance evaluation results show that MPM captures well the temporal locality of mobile requests due to the semi-Markov mobility prediction model, hence it achieves a better performance compared to both a (i) blind/naïve multicast and a (ii) content popularity-based proactive multicast.
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Optimization of Webpage Downloading Performance with Content-aware Mobile Edge Computing
Peng Qian (5G Innovation Centre, Institute for Communication Systems, University of Surrey), Ning Wang (5G Innovation Centre, Institute for Communication Systems, University of Surrey), Bong-Hwan Oh (5G Innovation Centre, Institute for Communication Systems, University of Surrey), Chang Ge (5G Innovation Centre, Institute for Communication Systems, University of Surrey), Rahim Tafazolli (5G Innovation Centre, Institute for Communication Systems, University of Surrey)
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Abstract: With increased complexity of webpages nowadays, computation latency incurred by webpage processing during downloading operations has become a newly identi�ed factor that may substantially aff�ect user experiences in a mobile network. In order to tackle this issue, we propose a simple but e�ective transport-layer optimization technique which requires necessary context information dissemination from the mobile edge computing (MEC) server to user devices where such an algorithm is actually executed. The key novelty in this case is the mobile edge’s knowledge about webpage content characteristics which is able to increase downloading throughput for user QoE enhancement. Our experiment results based on a real LTE-A test-bed show that, when the proportion of computation latency varies between 20% and 50% (which is typical for today’s webpages), the downloading throughput can be improved up to 34.5%, with reduced downloading time by up to 25.1%
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Realization of CDMA-based IoT Services with Shared Band Operation of LTE in 5G
Shweta S. Sagari (Huawei Research), Siddarth Mathur (WINLAB, Rutgers University), Dola Saha (University at Albany, SUNY), Syed Obaid Amin (Huawei Research), Ravishankar Ravindran (Huawei Research), Ivan Seskar (WINLAB, Rutgers University), Dipankar Raychaudhuri (WINLAB, Rutgers University), Guoqiang Wang (Huawei Research)
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Abstract: 5G network is geared towards massive deployment of Internet-of-Things (IoTs) with requirements of low end-to-end latency, low control overhead and low power transmissions. Current 4G network is optimized for large bandwidth applications and inefficient to handle short sporadic IoT messages. This paper focuses on low power underlay CDMA access for IoT devices considering event-driven and latency sensitive traffic profile, thus will significantly reduce the access time. We propose a PHY/MAC layer design for CDMA based communication for IoT devices. We evaluate coexisting operation of CDMA based IoT network in presence of the exiting LTE network. Our proposed protocol will integrate IoT traffic with legacy system by minimal modification at the edge network, essentially eNodeB. We show that the underlay CDMA IoT network meets IoT data traffic requirements with minimal degradation (~ 3%) to the LTE throughput. We also implement the proposed design using Software Defined Radios and show the viability of the proposal under different network scenarios.
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- Industrial Panel : Adoption Challenges and Prospects of Mobile Edge Computing and Communications
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Moderator
Martin J. Reed (Senior Lecturer, University of Essex)
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Panelist: IoT/Edge Computing
Bruce Maggs (Vice President, Research, Akamai Technologies)
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Panelist: Service and Platform Innovation
Dirk Trossen (Senior Principle Engineer, InterDigital Europe)
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Panelist: Core Networks
Joe Mambretti (Director at Metropolitan Research and Education Network, Northwestern University)
- Coffee Break
- Session 3: Edge Resource Allocation
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Geo-partitioning of MEC resources
Mathieu Bouet (Thales), Vania Conan (Thales)
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Abstract: Mobile Edge Computing (MEC) is an emerging technology that aims at pushing applications and content close to the users (e.g. at base stations, access points, aggregation networks) to reduce latency, improve quality of experience, and ensure highly efficient network operation and service delivery. It principally relies on virtualization-enabled MEC servers with limited capacity at the edge of the network. One key issue is to dimension such systems in terms of server size, server number and server operation area to meet MEC goals. In this paper, we propose a graph-based algorithm that, taking into account a maximum MEC server capacity, provides a partition of MEC clusters, which consolidates as many communications as possible at the edge. We use a dataset of mobile communications to evaluate it with real world spatio-temporal human dynamics. In addition to quantifying macroscopic MEC benets, the evaluation shows that our algorithm provides MEC area partitions that largely ofload the core, thus pushing the load at the edge (e.g., with 10 small MEC servers around 55% of the traffic stay at the edge), and that are well balanced through time.
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RAERA: A Robust Auctioning Approach for Edge Resource Allocation
Abhinandan S. Prasad (University of Goettingen), Mayutan Arumaithurai (University of Goettingen), David Koll (University of Goettingen), Xiaoming Fu (University of Goettingen, Germany)
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Abstract: In edge computing, content and service providers aim at enhancing user experience by providing services closer to the user. At the same time, infrastructure providers such as access ISPs aim at utilizing their infrastructure by selling edge resources to these content and service providers. In this context, auctions are widely used to set a price that reflects supply and demand in a fair way. In this work, we propose RAERA, the first robust auction scheme for edge resource allocation that is suitable to work with the market uncertainty typical for edge resources—here, customers typically have different valuation distribution for a wide range of heterogeneous resources. Additionally, RAERA encourages truthful bids and allows the infrastructure provider to maximize its break-even profit. Our preliminary evaluations highlight that REARA offers a time dependent fair price. Sellers can achieve higher revenue in the range of 5%-15% irrespective of varying demands and the buyers pay up to 20% lower than their top bid amount.
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SDLB: A Scalable and Dynamic Software Load Balancer for Fog and Mobile Edge Computing
Ye Yu (University of Kentucky), Xin Li (University of California, Santa Cruz), Chen Qian (University of California, Santa Cruz)
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Abstract: Mobile Edge Computing (MEC) provides computing/storage offloading and resource virtualization to mobile devices at the network edge. A load balancer is a necessary network function to determine the destination MEC host of each packet from a mobile device, for such virtualization. Due to the new characteristics of MEC, such as resource limitation and high dynamics, existing solutions of cloud load balancer cannot be directly applied to MEC. This paper presents a new design of a Scalable and Dynamic Load Balancer, called SDLB, that satisfies the require- ments of MEC. The core algorithm of SDLB is minimal perfect hashing, which provides two perfect features as a load balancer. Evaluation results show that SDLB is faster by 4x to 10x and uses much less (< 50%) memory, than a widely-used load balancer design for cloud.
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- Concluding Remarks
Call For Papers
Future mobile networks aim to support low latency, context-related service offering, personalised service delivery and highly flexible and efficient resource management. One attractive approach to these goals introduces virtualized storage and compute resources at the edge of the network, having closer proximity to mobile subscribers as a way of reducing end-to-end latency and time-to-response, while increasing the flexibility and agility of allocating resources. The Mobile Edge Computing (MEC) paradigm takes this approach facilitating computation and storage capabilities at the edge, with a particular focus on their interaction with applications and services. In a similar fashion, Network Function Virtualisation (NFV) brings advantages related to the flexible instantiation and management of network functionality on top of virtualized compute, storage and network resources.
The workshop focuses on the interplay between NFV and MEC domains; stimulating research efforts that marry the requirements of virtual computing with the requirements of virtual networking in a number of aspects, including: enabling application- and/or service-awareness in network functions (e.g., service-aware routing), distributing and networking compute resources, high-speed data planes, programmable control and management planes, resiliency and security of mobile edge clouds and networks. The outcomes of the workshop should levitate communication frameworks that have the ability to accommodate the expanding range of business models, applications and services, within future mobile networks.
The workshop will solicit papers that address aspects of the above areas; particularly, encouraging papers that address cross-layer research issues in any combination of these areas, bridging the gaps between network softwarization, virtualization and cloud/edge computing.
Topics of Interest
List of topics include (but not limited to):
- Inter-network resource management in future mobile networks
- Function and service allocation in mobile edge networks
- Compute and process distribution models in mobile edge networks
- Content Distribution Models in Mobile Edge Computing
- Application- and service-aware cloud models for mobile edge networks
- Algorithms and protocols to support the allocation of virtual resources
- Security challenges in Mobile Edge Computing
- Service abstraction and orchestration
- QoS and Traffic Engineering in Mobile Edge Networks networks
- Prototype platforms and trial deployment experience
- Data storage and networking in application- and/or service-aware cloud
- Network Function Virtualization in Mobile Edge Networks
- Management and orchestration across compute, storage and network resources in future mobile edge networks
- Service function chaining in mobile edge computing
- Content, function and result caching and replication in mobile edge networks
- Edge Analytics
- QoE in Mobile Edge Networks
- Access models for mobile edge networks
- Theoretical and experimental evaluations of mobile edge computing
- Self-organisation in mobile edge networks
- Edge computing for constrained mobile networks
- Slicing and multi-tenancy of Mobile Edge Networks
- Inter-service communications in mobile edge networks
- Switching designs for the mobile network core to support new mobile edge architectures
Sponsored By
Submission Instructions
Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM SIGCOMM conference proceedings. Workshop organizers reserve the right to exclude a paper from distribution after the workshop if the paper is not presented at the conference. Submitted papers should contain original material that have not be previously published, nor currently submitted for consideration elsewhere. All submissions should be written in English, with a maximum length limit of 6 printed pages, including all the figures, references and appendices. The ACM SIGCOMM LaTeX and Microsoft Word templates, as well as related information, can be found at the ACM SIG Proceedings website.
Specifically, please note the following format requirements:
- All papers submitted will be peer-reviewed (single-blind) and evaluated based on their suitability (i.e., within the workshop scope), novelty, and merit.
- All papers must be submitted in Portable Document Format (PDF) electronically. Whatever text processor or formatter you use to write your paper (LaTeX, Microsoft Word, FrameMaker, etc.), please convert the output to PDF before submission.
- Submissions must be limited to 6 pages, single-spaced, double-column, with each column 9.25” by 3.33”, 0.33” space between columns, use at least a 10pt font, and be correctly formatted to be printed on letter-sized (8.5” by 11”) paper.
Submissions that violate the formatting requirements may not be reviewed. - We must be able to print your paper once it is submitted. Therefore, all fonts used in the paper MUST be embedded in the submitted PDF file.
- The paper must be in a state where it can be printed clearly on standard black-and-white printers. Reviewers are not required to view your paper in color.
Please submit your paper via https://mecomm-sigcomm17.hotcrp.com/
Important Dates
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March 23, 2017March 31, 2017Submission deadline
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April 29, 2017May 5, 2017Acceptance notification
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May 29, 2017Camera ready deadline
Authors Take Note
The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to TWO WEEKS prior to the first day of your conference. The official publication date affects the deadline for any patent filings related to published work.
Committees
- Workshop Co-Chairs
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Jon Crowcroft
University of Cambridge
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Joe Mambretti
Northwestern University
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George Pavlou
University College London
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George Polyzos
Athens University of Economics and Business
- TPC Chairs
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Ioannis Psaras
University College London
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Kun Yang
University of Essex
- Organizing Committee
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Mays AL-Naday
University of Essex
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Konstantinos V. Katsaros
Intracom S.A. Telecom Solutions
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Martin J Reed
University of Essex
- Technical Program Committee
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Mohammed AL-Khalidi
University of Essex
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Mays AL-Naday
University of Essex
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Carolina Canales
Ericsson España S.A. (ES)
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Eduard Escalona
Fundacio Privada I2CAT, Internet Innovacio Digital A Catalunya (ES)
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Hamed Haddadi
Queen Mary University of London
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Toru Hasegawa
Osaka University
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Konstantinos V. Katsaros
Intracom S.A. Telecom Solutions
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Jiangchuan LIU
Simon Fraser University
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Chathura Magurawalage
University of Essex
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Christos Papadopoulos
Colorado State University
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Andrea Passarella
National Research Council of Italy
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Ioannis Psaras
University College London
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K.K. Ramakrishnan
University of California, Riverside
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Martin Reed
University of Essex
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Janne Riihijärvi
RWTH Aachen University
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Stefan Schmid
Aalborg University
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Sakir Sezer
Queen’s University Belfast
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Leandros Tassiulas
Yale University
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Nikos Thomos
University of Essex
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Dirk Trossen
InterDigital Europe
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Gareth Tyson
Queen Mary University of London
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Ning Wang
University of Surrey
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Ke XU
Tsinghua University
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George Xylomenos
Athens University of Economics and Business
