Privacy-Aware Load Balancing in Fog Networks: A Reinforcement Learning Approach

Fog Computing has emerged as a solution to support the growing demands of real-time Internet of Things (IoT) applications, which require high availability of these distributed services. Intelligent workload distribution algorithms are needed to maximize the utilization of such Fog resources while minimizing the time required to process these workloads. These load balancing algorithms are critical in dynamic environments with heterogeneous resources and workload requirements along with unpredictable traffic demands. In this paper, load balancing is provided using a Reinforcement Learning (RL) algorithm, which optimizes the system performance by minimizing the waiting delay of IoT workloads. Unlike previous studies, the proposed solution does not require load and resource information from Fog nodes, which makes the algorithm dynamically adaptable to possible environment changes over time. This also makes the algorithm aware of the privacy requirements of Fog service providers, who might like to hide such information to prevent competing providers from calculating better pricing strategies. The proposed algorithm is interactively evaluated on a Discrete-event Simulator (DES) to mimic a practical deployment of the solution in real environments. In addition, we evaluate the algorithm's generalization ability on simulations longer than what it was trained on, which, to the best of our knowledge, has never been explored before. The results provided in this paper show how our proposed approach outperforms baseline load balancing methods under different workload generation rates.Comment: 9 pages, 9 figures, 1 tabl

Active Versus Passive: Receiver Model Transforms for Diffusive Molecular Communication

This paper presents an analytical comparison of active and passive receiver models in diffusive molecular communication. In the active model, molecules are absorbed when they collide with the receiver surface. In the passive model, the receiver is a virtual boundary that does not affect molecule behavior. Two approaches are presented to derive transforms between the receiver signals. As an example, two models for an unbounded diffusion-only molecular communication system with a spherical receiver are unified. As time increases in the three-dimensional system, the transform functions have constant scaling factors, such that the receiver models are effectively equivalent. Methods are presented to enable the transformation of stochastic simulations, which are used to verify the transforms and demonstrate that transforming the simulation of a passive receiver can be more efficient and more accurate than the direct simulation of an absorbing receiver.Comment: 6 pages, 3 figures, 3 tables. Will be presented at IEEE Globecom 201

Navigating Quantum Security Risks in Networked Environments: A Comprehensive Study of Quantum-Safe Network Protocols

The emergence of quantum computing poses a formidable security challenge to network protocols traditionally safeguarded by classical cryptographic algorithms. This paper provides an exhaustive analysis of vulnerabilities introduced by quantum computing in a diverse array of widely utilized security protocols across the layers of the TCP/IP model, including TLS, IPsec, SSH, PGP, and more. Our investigation focuses on precisely identifying vulnerabilities susceptible to exploitation by quantum adversaries at various migration stages for each protocol while also assessing the associated risks and consequences for secure communication. We delve deep into the impact of quantum computing on each protocol, emphasizing potential threats posed by quantum attacks and scrutinizing the effectiveness of post-quantum cryptographic solutions. Through carefully evaluating vulnerabilities and risks that network protocols face in the post-quantum era, this study provides invaluable insights to guide the development of appropriate countermeasures. Our findings contribute to a broader comprehension of quantum computing's influence on network security and offer practical guidance for protocol designers, implementers, and policymakers in addressing the challenges stemming from the advancement of quantum computing. This comprehensive study is a crucial step toward fortifying the security of networked environments in the quantum age

Hierarchical Negotiation for Distributed Multimedia Applications in A Multi-Domain Environment

: The new quality of multimedia (MM) applications concerns the handling of a various types of media, particularly continuous media, which are timely combined for use in presentation for the user. This implies stringent requirements from the underlying systems to support requested quality of service (QoS). Thus to support the new emerging services end-to-end QoS management is required. This paper proposes a loosely hierarchical architecture to support QoS management functions such as QoS negotiation, monitoring, and adaptation. The domain QoS manager and QoS agent concepts are introduced to build the proposed architecture. A hierarchical negotiation protocol which can be supported by the proposed management architecture is presented. Keywords: multimedia applications, quality of service, management, hierarchical negotiation 1. Introduction Due to increasing demands of distributed multimedia (MM) applications, efficient and effective support of quality of service (QoS) has become inc..

A Multi-agent Architecture for Cooperative QoS Management

The QoS management approaches developed so far are usually not suitable any more for applications which involve too large a number of communicating entities; for instance, negotiation of QoS parameters between the sender and every single receiver becomes impossible (in case of thousands of receivers). To solve this problem, we developed a QoS management approach, we called Cooperative QoS management, which allows a decentralized cooperative management of QoS; it does not limit the number of users of the application. In this paper we present a multi-agent architecture that implements the cooperative QoS management approach. Agents are installed on system components, such as routers and endsystems; when a user asks for a service with specific QoS requirements a kind of cooperation is initiated between agents to (\"best\") serve the user

A Multi-Agent Architecture for Cooperative Quality of Service Management

The QoS management approaches developed so far are usually not suitable any more for applications which involve too large a number of communicating entities; for instance, negotiation of QoS parameters between the sender and every single receiver becomes impossible (in case of thousands of receivers). To solve this problem, we developed a QoS management approach, we called Cooperative QoS management, which allows a decentralized cooperative management of QoS; it does not limit the number of users of the application. In this paper we present a multiagent architecture that implements the cooperative QoS management approach. Agents are installed on system components, such as routers and end-systems; when a user asks for a service with specific QoS requirements a kind of cooperation is initiated between agents to ("best") serve the user. Keywords QoS, QoS management, agent, multimedia 1 INTRODUCTION Much work on Quality of Service (QoS) has been done in the context of high-speed networ..

Some Principles for Quality of Service Management

Distributed multimedia applications require a variety of levels of quality of service (QoS) from communication networks and end-systems which realize the multimedia interface with the human users or provide remotely accessed multimedia information. The management of these services has to take into account the available resources and the user's wishes concerning the desired quality and costs. Based on our experience with the construction of a News-on-Demand prototype, we present in this paper a few simple principles applying to QoS management for distributed multimedia applications. We discuss in particular ways in which an application can adapt to reduced network performance related to throughput, loss, delay or jitter, and we consider the situation where the configuration of the distributed application can be selected dynamically and be revised during the running of the application. We also comment on the handling of QoS in a layered system architecture, the use of performance model..