Impatient Queuing for Intelligent Task Offloading in Multi-Access Edge Computing

Multi-access edge computing (MEC) emerges as an essential part of the upcoming Fifth Generation (5G) and future beyond-5G mobile communication systems. It adds computational power towards the edge of cellular networks, much closer to energy-constrained user devices, and therewith allows the users to offload tasks to the edge computing nodes for low-latency applications with very-limited battery consumption. However, due to the high dynamics of user demand and server load, task congestion may occur at the edge nodes resulting in long queuing delay. Such delays can significantly degrade the quality of experience (QoE) of some latency-sensitive applications, raise the risk of service outage, and cannot be efficiently resolved by conventional queue management solutions. In this article, we study a latency-outage critical scenario, where users intend to limit the risk of latency outage. We propose an impatience-based queuing strategy for such users to intelligently choose between MEC offloading and local computation, allowing them to rationally renege from the task queue. The proposed approach is demonstrated by numerical simulations to be efficient for generic service model, when a perfect queue status information is available. For the practical case where the users obtain only imperfect queue status information, we design an optimal online learning strategy to enable its application in Poisson service scenarios.Comment: To appear in IEEE Transactions on Wireless Communication

EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

Impact of Mobility and Wireless Channel on the Performance of Wireless Networks

This thesis studies the impact of mobility and wireless channel characteristics, i. e. , variability and high bit-error-rate, on the performance of integrated voice and data wireless systems from network, transport protocol and application perspectives. From the network perspective, we study the impact of user mobility on radio resource allocation. The goal is to design resource allocation mechanisms that provide seamless mobility for voice calls while being fair to data calls. In particular, we develop a distributed admission control for a general integrated voice and data wireless system. We model the number of active calls in a cell of the network as a Gaussian process with time-dependent mean and variance. The Gaussian model is updated periodically using the information obtained from neighboring cells about their load conditions. We show that the proposed scheme guarantees a prespecified dropping probability for voice calls while being fair to data calls. Furthermore, the scheme is stable, insensitive to user mobility process and robust to load variations. From the transport protocol perspective, we study the impact of wireless channel variations and rate scheduling on the performance of elastic data traffic carried by TCP. We explore cross-layer optimization of the rate adaptation feature of cellular networks to optimize TCP throughput. We propose a TCP-aware scheduler that switches between two rates as a function of TCP sending rate. We develop a fluid model of the steady-state TCP behavior for such a system and derive analytical expressions for TCP throughput that explicitly account for rate variability as well as the dependency between the scheduler and TCP. The model is used to choose RF layer parameters that, in conjunction with the TCP-aware scheduler, improve long-term TCP throughput in wireless networks. A distinctive feature of our model is its ability to capture variability of round-trip-time, channel rate and packet error probability inherent to wireless communications. From the application perspective, we study the performance of wireless messaging systems. Two popular wireless applications, the short messaging service and multimedia messaging service are considered. We develop a mathematical model to evaluate the performance of these systems taking into consideration the fact that each message tolerates only a limited amount of waiting time in the system. Using the model, closed-form expressions for critical performance parameters such as message loss, message delay and expiry probability are derived. Furthermore, a simple algorithm is presented to find the optimal temporary storage size that minimizes message delay for a given set of system parameters

Maximizing Real-Time Video QoE via Bandwidth Sharing under Markovian setting

We consider the problem of optimizing Quality of Experience (QoE) of clients streaming real-time video, served by networks managed by different operators that can share bandwidth with each other. The abundance of real-time video traffic is evident in the popularity of applications like video conferencing and video streaming of live events, which have increased significantly since the recent pandemic. We model the problem as a joint optimization of resource allocation for the clients and bandwidth sharing across the operators, with special attention to how the resource allocation impacts clients' perceived video quality. We propose an online policy as a solution, which involves dynamically sharing a portion of one operator's bandwidth with another operator. We provide strong theoretical optimality guarantees for the policy. We also use extensive simulations to demonstrate the policy's substantial performance improvements (of up to ninety percent), and identify insights into key system parameters (e.g., imbalance in arrival rates or channel conditions of the operators) that dictate the improvements.Comment: arXiv admin note: substantial text overlap with arXiv:2211.0666

Proactive seeding for information cascades in cellular networks

Abstract—Online social networks (OSNs) play an increasingly important role today in informing users about content. At the same time, mobile devices provide ubiquitous access to this content through the cellular infrastructure. In this paper, we exploit the fact that the interest in content spreads over OSNs, which makes it, to a certain extent, predictable. We propose Proactive Seeding– a technique for minimizing the peak load of cellular networks, by proactively pushing (“seeding”) content to selected users before they actually request it. We develop a family of algorithms that take as input information primarily about (i) cascades on the OSN and possibly about (ii) the background traffic load in the cellular network and (iii) the local connectivity among mobiles; the algorithms then select which nodes to seed and when. We prove that Proactive Seeding is optimal when the prediction of information cascades is perfect. In realistic simulations, driven by traces from Twitter and cellular networks, we find that Proactive Seeding reduces the peak cellular load by 20%-50%. Finally, we combine Proactive Seeding with techniques that exploit local mobile-to-mobile connections to further reduce the peak load. I