ENORM: A Framework For Edge NOde Resource Management

Current computing techniques using the cloud as a centralised server will become untenable as billions of devices get connected to the Internet. This raises the need for fog computing, which leverages computing at the edge of the network on nodes, such as routers, base stations and switches, along with the cloud. However, to realise fog computing the challenge of managing edge nodes will need to be addressed. This paper is motivated to address the resource management challenge. We develop the first framework to manage edge nodes, namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for provisioning and auto-scaling edge node resources are proposed. The feasibility of the framework is demonstrated on a PokeMon Go-like online game use-case. The benefits of using ENORM are observed by reduced application latency between 20% - 80% and reduced data transfer and communication frequency between the edge node and the cloud by up to 95\%. These results highlight the potential of fog computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12 September 201

Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-latency

In this paper, we study the coexistence and synergy between edge and central cloud computing in a heterogeneous cellular network (HetNet), which contains a multi-antenna macro base station (MBS), multiple multi-antenna small base stations (SBSs) and multiple single-antenna user equipment (UEs). The SBSs are empowered by edge clouds offering limited computing services for UEs, whereas the MBS provides high-performance central cloud computing services to UEs via a restricted multiple-input multiple-output (MIMO) backhaul to their associated SBSs. With processing latency constraints at the central and edge networks, we aim to minimize the system energy consumption used for task offloading and computation. The problem is formulated by jointly optimizing the cloud selection, the UEs' transmit powers, the SBSs' receive beamformers, and the SBSs' transmit covariance matrices, which is {a mixed-integer and non-convex optimization problem}. Based on methods such as decomposition approach and successive pseudoconvex approach, a tractable solution is proposed via an iterative algorithm. The simulation results show that our proposed solution can achieve great performance gain over conventional schemes using edge or central cloud alone. Also, with large-scale antennas at the MBS, the massive MIMO backhaul can significantly reduce the complexity of the proposed algorithm and obtain even better performance.Comment: Accepted in IEEE Transactions on Wireless Communication

CLOUDIO: a cloud computing-oriented multi-tenant architecture for business information systems.

Proceedings of: 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010, 5-10 July, Miami, Florida, USACloud Computing is evolving from a mere "storage" technology to a new vehicle for Business Information Systems (BIS) to manage, organize and provide added-value strategies to current business models. However, the underlying infrastructure for Software-as-a-Service (SaaS) to become a new platform for trading partners and transactions must rely on intelligent, flexible, context-aware Multi-Tenant Architectures. In this paper, we present Cloudio, a Cloud Computing-based metadata-powered Multi-Tenant Architecture, backed with a proof-of-concept J2EE implementation.This work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the project GODO2 (TSI- 020100-2008-564), SONAR2 (TSI-020100-2008-665), and SITIO (TSI-0204000-2009-148), under the PIBES (TEC2006-12365-C02-01) and MID-CBR (TIN2006-15140- C03-02) projects of the Spanish Committee of Education & Science.Publicad

Generic Construction of Dual-Server Public Key Authenticated Encryption with Keyword Search

Chen et al. (IEEE Transactions on Cloud Computing 2022) introduced dual-server public key authenticated encryption with keyword search (DS-PAEKS), and proposed a DS-PAEKS scheme under the decisional Diffie-Hellman assumption. In this paper, we propose a generic construction of DS-PAEKS from PAEKS, public key encryption, and signatures. By providing a concrete attack, we show that the DS-PAEKS scheme of Chen et al. is vulnerable. That is, the proposed generic construction yields the first DS-PAEKS schemes. Our attack with a slight modification works against the Chen et al. dual-server public key encryption with keyword search (DS-PEKS) scheme (IEEE Transactions on Information Forensics and Security 2016). Moreover, we demonstrate that the Tso et al. generic construction of DS-PEKS from public key encryption (IEEE Access 2020) is also vulnerable. We also analyze other pairing-free PAEKS schemes (Du et al., Wireless Communications and Mobile Computing 2022 and Lu and Li, IEEE Transactions on Mobile Computing 2022). Though we did not find any attack against these schemes, we show that at least their security proofs are wrong

Fault Injection Analytics: A Novel Approach to Discover Failure Modes in Cloud-Computing Systems

Cloud computing systems fail in complex and unexpected ways due to unexpected combinations of events and interactions between hardware and software components. Fault injection is an effective means to bring out these failures in a controlled environment. However, fault injection experiments produce massive amounts of data, and manually analyzing these data is inefficient and error-prone, as the analyst can miss severe failure modes that are yet unknown. This paper introduces a new paradigm (fault injection analytics) that applies unsupervised machine learning on execution traces of the injected system, to ease the discovery and interpretation of failure modes. We evaluated the proposed approach in the context of fault injection experiments on the OpenStack cloud computing platform, where we show that the approach can accurately identify failure modes with a low computational cost.Comment: IEEE Transactions on Dependable and Secure Computing; 16 pages. arXiv admin note: text overlap with arXiv:1908.1164