skip to main content


Title: APECS: A Distributed Access Control Framework for Pervasive Edge Computing Services
Edge Computing is a new computing paradigm where applications operate at the network edge, providing low-latency services with augmented user and data privacy. A desirable goal for edge computing is pervasiveness, that is, enabling any capable and authorized entity at the edge to provide desired edge services--pervasive edge computing (PEC). However, efficient access control of users receiving services and edge servers handling user data, without sacrificing performance is a challenge. Current solutions, based on "always-on" authentication servers in the cloud, negate the latency benefits of services at the edge and also do not preserve user and data privacy. In this paper, we present APECS, an advanced access control framework for PEC, which allows legitimate users to utilize any available edge services without need for communication beyond the network edge. The APECS framework leverages multi-authority attribute-based encryption to create a federated authority, which delegates the authentication and authorization tasks to semi-trusted edge servers, thus eliminating the need for an "always-on" authentication server in the cloud. Additionally, APECS prevents access to encrypted content by unauthorized edge servers. We analyze and prove the security of APECS in the Universal Composability framework and provide experimental results on the GENI testbed to demonstrate the scalability and effectiveness of APECS.  more » « less
Award ID(s):
1800088 1914635 2028797 1757207
NSF-PAR ID:
10302516
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  
Date Published:
Journal Name:
2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. New breed of applications, such as autonomous driving and their need for computation-aided quick decision making has motivated the delegation of compute-intensive services (e.g., video analytic) to the more powerful surrogate machines at the network edge–edge computing (EC). Recently, the notion of pervasive edge computing (PEC) has emerged, in which users’ devices can join the pool of the computing resources that perform edge computing. Inclusion of users’ devices increases the computing capability at the edge (adding to the infrastructure servers), but in comparison to the conventional edge ecosystems, it also introduces new challenges, such as service orchestration (i.e., service placement, discovery, and migration). We propose uDiscover, a novel user-driven service discovery and utilization framework for the PEC ecosystem. In designing uDiscover, we considered the Named-Data Networking architecture for balancing users workloads and reducing user-perceived latency. We propose proactive and reactive service discovery approaches and assess their performance in PEC and infrastructure-only ecosystems. Our simulation results show that (i) the PEC ecosystem reduces the user-perceived delays by up to 70%, and (ii) uDiscover selects the most suitable server–"accurate" delay estimates with less than 10% error–to execute any given task. 
    more » « less
  2. The proliferation of innovative mobile services such as augmented reality, networked gaming, and autonomous driving has spurred a growing need for low-latency access to computing resources that cannot be met solely by existing centralized cloud systems. Mobile Edge Computing (MEC) is expected to be an effective solution to meet the demand for low-latency services by enabling the execution of computing tasks at the network-periphery, in proximity to end-users. While a number of recent studies have addressed the problem of determining the execution of service tasks and the routing of user requests to corresponding edge servers, the focus has primarily been on the efficient utilization of computing resources, neglecting the fact that non-trivial amounts of data need to be stored to enable service execution, and that many emerging services exhibit asymmetric bandwidth requirements. To fill this gap, we study the joint optimization of service placement and request routing in MEC-enabled multi-cell networks with multidimensional (storage-computation-communication) constraints. We show that this problem generalizes several problems in literature and propose an algorithm that achieves close-to-optimal performance using randomized rounding. Evaluation results demonstrate that our approach can effectively utilize the available resources to maximize the number of requests served by low-latency edge cloud servers. 
    more » « less
  3. The rapid growth in technology and wide use of internet has increased smart applications such as intelligent transportation control system, and Internet of Things, which heavily rely on an efficient and reliable connectivity network. To overcome high bandwidth work load on the network, as well as minimize latency for real-time applications, the computation can be moved from the central cloud to a distributed edge cloud. The edge computing benefits various smart applications that uses distributed network for data analytics and services. Different from the existing cloud management solutions, edge computing needs to move cloud management services towards distributed heterogeneous edge nodes for multi-tenant user applications. However, existing cloud management services do not offer remote deployment of multi-tenant user applications on the cloud of edge nodes. In this paper, we propose a practical edge cloud software framework for deploying multi-tenant distributed smart applications. Having multiple distributed end nodes, auto discovery of all active end nodes is required for deploying multi-tenant user applications. However, existing cloud solutions require either private network or fixed IP address, which is not achievable for the distributed edge nodes. Most of the edge nodes connected through the public internet without fixed IP, and some of them even connect through IEEE 802.15 based sensor networks. We propose to build a software platform to manage the distributed edge nodes as well as support services to deploy and launch isolated, multi-tenant user applications through a lightweight container. We propose an architectural solution to remotely access edge cloud management services through intermittent internet connections. We open sourced our whole set of software solutions, and analyzed the major performance metrics of the edge cloud platform. 
    more » « less
  4. Next-generation distributed computing networks (e.g., edge and fog computing) enable the efficient delivery of delay-sensitive, compute-intensive applications by facilitating access to computation resources in close proximity to end users. Many of these applications (e.g., augmented/virtual reality) are also data-intensive: in addition to user-specific (live) data streams, they require access to shared (static) digital objects (e.g., im-age database) to complete the required processing tasks. When required objects are not available at the servers hosting the associated service functions, they must be fetched from other edge locations, incurring additional communication cost and latency. In such settings, overall service delivery performance shall benefit from jointly optimized decisions around (i) routing paths and processing locations for live data streams, together with (ii) cache selection and distribution paths for associated digital objects. In this paper, we address the problem of dynamic control of data-intensive services over edge cloud networks. We characterize the network stability region and design the first throughput-optimal control policy that coordinates processing and routing decisions for both live and static data-streams. Numerical results demonstrate the superior performance (e.g., throughput, delay, and resource consumption) obtained via the novel multi-pipeline flow control mechanism of the proposed policy, compared with state-of-the-art algorithms that lack integrated stream processing and data distribution control. 
    more » « less
  5. Many have predicted the future of the Web to be the integration of Web content with the real-world through technologies such as Augmented Reality (AR). This has led to the rise of Extended Reality (XR) Web Browsers used to shorten the long AR application development and deployment cycle of native applications especially across different platforms. As XR Browsers mature, we face new challenges related to collaborative and multi-user applications that span users, devices, and machines. These collaborative XR applications require: (1) networking support for scaling to many users, (2) mechanisms for content access control and application isolation, and (3) the ability to host application logic near clients or data sources to reduce application latency. In this paper, we present the design and evaluation of the AR Edge Networking Architecture (ARENA) which is a platform that simplifies building and hosting collaborative XR applications on WebXR capable browsers. ARENA provides a number of critical components including: a hierarchical geospatial directory service that connects users to nearby servers and content, a token-based authentication system for controlling user access to content, and an application/service runtime supervisor that can dispatch programs across any network connected device. All of the content within ARENA exists as endpoints in a PubSub scene graph model that is synchronized across all users. We evaluate ARENA in terms of client performance as well as benchmark end-to-end response-time as load on the system scales. We show the ability to horizontally scale the system to Internet-scale with scenes containing hundreds of users and latencies on the order of tens of milliseconds. Finally, we highlight projects built using ARENA and showcase how our approach dramatically simplifies collaborative multi-user XR development compared to monolithic approaches. 
    more » « less