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Follow-Me Cloud: When Cloud Services Follow Mobile Users (2201.05068v1)

Published 5 Jan 2022 in cs.NI

Abstract: The trend towards the cloudification of the 3GPP LTE mobile network architecture and the emergence of federated cloud infrastructures call for alternative service delivery strategies for improved user experience and efficient resource utilization. We propose Follow-Me Cloud (FMC), a design tailored to this environment, but with a broader applicability, which allows mobile users to always be connected via the optimal data anchor and mobility gateways, while cloud-based services follow them and are delivered via the optimal service point inside the cloud infrastructure. FMC applies a Markov-Decision-Process-based algorithm for cost-effective, performance-optimized service migration decisions, while two alternative schemes to ensure service continuity and disruption-free operation are proposed, based on either Software Defined Networking technologies or the Locator/Identifier Separation Protocol. Numerical results from our analytic model for FMC, as well as testbed experiments with the two alternative FMC implementations we have developed, demonstrate quantitatively and qualitatively the advantages it can bring about.

Citations (196)

Summary

  • The paper introduces the FMC framework which uses a Markov Decision Process to dynamically migrate services based on mobile user locations.
  • It leverages technologies like LISP and SDN to maintain seamless service continuity and improve quality of experience.
  • Experimental results from SDN and LISP implementations demonstrate reduced latencies and efficient resource allocation.

An Analysis of the Follow-Me Cloud Framework for Mobile Network Efficiency

The proliferation of mobile data traffic imposes significant demands on mobile network operators to adopt decentralized architectures and enhance resource utilization. The paper "Follow-Me Cloud: When Cloud Services Follow Mobile Users" by Taleb, Ksentini, and Frangoudis introduces an innovative "Follow-Me Cloud" (FMC) concept that promises to optimize cloud service delivery by adapting dynamically to the mobility patterns of users. This essay examines the proposed FMC framework, underpinning algorithms, and architectural implementations to articulate its implications and potential applications.

The FMC design is rooted in the evolving architecture of 3GPP LTE mobile networks and the increasing reliance on federated cloud infrastructures. Its primary objective is to ensure that cloud services migrate seamlessly alongside mobile users, maintaining optimal connectivity and enhancing Quality of Experience (QoE). Central to this premise is a Markov Decision Process (MDP)-based algorithm that facilitates cost-effective service migration decisions, balancing migration costs against user experience improvements.

The framework employs assisted technologies such as the Locator/Identifier Separation Protocol (LISP) and Software Defined Networking (SDN) to ensure service continuity and mitigate disruptions during migrations. These technologies allow the FMC system to effectively manage locational data and connectivity states, underpinning its capability to dynamically allocate services across diverse data center infrastructures.

Numerically, the paper presents substantial evidence supporting FMC's effectiveness. The paper highlights significant improvements in user connectivity probabilities to optimal data centers, as evidenced by numerical simulations. The presented results indicate decreased latencies and enhanced user experiences when appropriate service migrations are executed. Specifically, scenarios with early-stage migrations lead to better alignment with optimal data center locations, consequently reducing service latency and improving QoE.

Practically, the research translates these theoretical models into two testbed implementations—an SDN-based architecture and a LISP-based approach. Both implementations illustrate the framework's feasibility and flexibility in varied network topologies. Experimental results confirm low service disruption times and effective resource allocation across distributed cloud systems. The LISP-based architecture showcases minimal latency impacts post-migration, whereas the SDN-based implementation demonstrates scalable migration processes with real-world delay scenarios.

The implications of the FMC are manifold. It addresses crucial aspects of mobile user experience management and resource optimization, facilitating advanced mobile services such as video streaming and real-time application hosting. Theoretically, this establishes a foundational approach for further explorations into mobile-cloud convergence, potentially informing standardization efforts in forthcoming network solutions.

Looking ahead, the FMC framework invites numerous development avenues, particularly in enhancing decision algorithms for higher-dimensional mobility models and dynamically adaptable SDN and LISP integrations. Furthermore, the growing prevalence of IoT devices and the evolving 5G deployments offer rich contexts for FMC's application, potentially transforming network cloud dynamics by making them inherently user-centric and adaptive.

In conclusion, Taleb et al. present a substantive, data-driven exploration of service migration within cloudified mobile network environments. By aligning cloud service delivery with mobile user patterns, the FMC framework emerges as a viable strategy for efficient and user-oriented network utilization, promising considerable enhancements in mobile service quality and cloud resource management.