Cooperation between the fog and the cloud in mobile cloud computing environments could offer improved offloading services to smart mobile user equipment (UE) with computation intensive tasks. In this paper, we tackle the computation offloading problem in a mixed fog/cloud system by jointly optimizing the offloading decisions and the allocation of computation resource, transmit power and radio bandwidth, while guaranteeing user fairness and maximum tolerable delay. This optimization problem is formulated to minimize the maximal weighted cost of delay and energy consumption (EC) among all UEs, which is a mixed-integer non-linear programming problem. Due to the NP-hardness of the problem, we propose a low-complexity suboptimal algorithm to solve it, where the offloading decisions are obtained via semidefinite relaxation and randomization and the resource allocation is obtained using fractional programming theory and Lagrangian dual decomposition. Simulation results are presented to verify the convergence performance of our proposed algorithms and their achieved fairness among UEs, and the performance gains in terms of delay, EC and the number of beneficial UEs over existing algorithms. Index Terms-Computation offloading, cloud computing, fog computing, resource allocation, min-max fairness.

⎯This letter considers the problem of resource sharing among a relay and multiple user nodes in cooperative transmission networks. We formulate this problem as a sellers' market competition and use a noncooperative game to jointly consider the benefits of the relay and the users. We also develop a distributed algorithm to search the Nash equilibrium, the solution of the game. The convergence of the proposed algorithm is analyzed. Simulation results demonstrate that the proposed game can stimulate cooperative diversity among the selfish user nodes and coordinate resource allocation among the user nodes effectively.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. Takedown AbstractToday, billions of communication devices connecting to wireless networks impose serious challenges in network deployment, management, and data processing. Amongst all emerging technologies tackling these challenges, software defined networks (SDNs) decouple control plane from data plane to provide network programmability and virtualization, which can share network and radio resources among various applications. On the other hand, fog computing offloads computing services from cloud to the edge of networks, offering real time data services to nearby data terminals. In this paper, we present an integrated architecture for software defined and virtualized radio access networks with fog computing. We propose a design of software-as-a-service (SaaS) called OpenPipe, which enables network level virtualizaiton. To integrate SDNs and network virtualization with fog computing, we adopt a hybrid control model with two hierarchical control levels, where a SDN controller forms the higher level, and local controllers comprise the lower level. Typical user cases of the proposed network architecture are validated through laboratory demonstrations.

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Enabling low-latency applications in LTE-A based mixed fog/cloud computing systems. IEEE Transactions on Vehicular Technology.

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This paper investigates an integrated wireless communication system including non-orthogonal multiple access, fullduplex relaying, and energy harvesting techniques (named as EH-FD-NOMA). In this scheme, an energy-limited full-duplex relay harvests energy from a source at the first stage. Then, the relay detects the superimposed signal from the source and transmits the decoded signal to destination. Closed-form outage probabilities and ergodic rates at the relay and destination are derived. Numerical results verify the analytical results and show the superior performance of the EH-FD-NOMA if compared to its counterparts.

In this paper, we consider the problem of stimulating cooperation and resource allocation in cooperative transmission networks. We formulate this problem as a sellers' market competition where a relay is willing to share its resource with multiple users. We use a Stackelberg game to jointly consider the benefits of the relay and the users. Firstly, the relay determines the price of relaying according to the user demand. Secondly, the users purchase the optimal amount of resources to maximize their utilities. Although the Nash equilibrium, i.e., the solution of the game, can be obtained in a centralized manner, we develop a distributed algorithm to search the Nash equilibrium, which is more applicable in practical systems. Also, the convergence conditions of the algorithm are analyzed. Simulation results show, by using the distributed algorithm, the relay and the users could determine what price should ask for and how much bandwidth should buy, respectively.