A game-theoretic approach to computation offloading in mobile cloud computing

We consider a three-tier architecture for mobile and pervasive computing scenarios, consisting of a local tier ofmobile nodes, a middle tier (cloudlets) of nearby computing nodes, typically located at the mobile nodes access points but characterized by a limited amount of resources, and a remote tier of distant cloud servers, which have practically infinite resources. This architecture has been proposed to get the benefits of computation offloading from mobile nodes to external servers while limiting the use of distant servers whose higher latency could negatively impact the user experience. For this architecture, we consider a usage scenario where no central authority exists and multiple non-cooperative mobile users share the limited computing resources of a close-by cloudlet and can selfishly decide to send their computations to any of the three tiers. We define a model to capture the users interaction and to investigate the effects of computation offloading on the users’ perceived performance. We formulate the problem as a generalized Nash equilibrium problem and show existence of an equilibrium.We present a distributed algorithm for the computation of an equilibrium which is tailored to the problem structure and is based on an in-depth analysis of the underlying equilibrium problem. Through numerical examples, we illustrate its behavior and the characteristics of the achieved equilibria

Approximate Analysis of Blocking Queueing Networks with Temporal Dependence

Abstract—In this paper we extend the class of MAP queueing networks to include blocking models, which are useful to describe the performance of service instances which have a limited concurrency level. We consider two different blocking mechanisms: Repetitive Service-Random Destination (RS-RD) and Blocking After Service (BAS). We propose a methodology to evaluate MAP queueing networks with blocking based on the recently proposed Quadratic Reduction (QR), a state space transformation that decreases the number of states in the Markov chain underlying the queueing network model. From this reduced state space, we obtain boundable approximations on average performance indexes such as throughput, response time, utilizations. The two approximations that dramatically enhance the QR bounds are based on maximum entropy and on a novel minimum mutual information principle, respectively. Stress cases of increasing complexity illustrate the excellent accuracy of the proposed approximations on several models of practical interest. I