QoS-Aware Dynamic Resource Management in Heterogeneous Mobile Cloud Computing Networks

In mobile cloud computing(MCC) systems,both the mobile access network and the cloud computing network are heterogeneous,implying the diverse configurations of hardware,software,architecture,resource,etc.In such heterogeneous mobile cloud(HMC) networks,both radio and cloud resources could become the system bottleneck,thus designing the schemes that separately and independently manage the resources may severely hinder the system performance.In this paper,we aim to design the network as the integration of the mobile access part and the cloud computing part,utilizing the inherent heterogeneity to meet the diverse quality of service(QoS)requirements of tenants.Furthermore,we propose a novel cross-network radio and cloud resource management scheme for HMC networks,which is QoS-aware,with the objective of maximizing the tenant revenue while satisfying the QoS requirements.The proposed scheme is formulated as a restless bandits problem,whose "indexability" feature guarantees the low complexity with scalable and distributed characteristics.Extensive simulation results are presented to demonstrate the significant performance improvement of the proposed scheme compared to the existing ones.

An Enhanced Spectrum Resource Allocation Algorithm in Hetnets

Efficient spectrum resource allocation in wireless heterogeneous networks is important for improving the system throughput and guaranteeing the user's Quality-of-Service(QoS).In this paper,we propose an enhanced algorithm for spectrum resource allocation in heterogeneous networks.First,the bandwidth of each user is determined by the user's rate demand and the channel state.Second,graph theory is enhanced and used to improve the spectrum efficiency.Third,spectrum resource is dynamically split between macrocell and femtocells with the changes of users' conditions.Our simulation results show that the proposed algorithm improves the system throughput significantly and also guarantees the fairness for the users.

Genetic algorithm for autonomic joint radio resource management in end-to-end reconfigurable systems

This article presents the genetic algorithm （GA） as an autonomic approach for the joint radio resource management （JRRM） amongst heterogeneous radio access technologies （RATs） in the end-to-end reconfigurable systems. The joint session admission control （JOSAC） and the bandwidth allocation are combined as a specific decision made by the operations of the genetic algorithm with certain advisable modifications. The proposed algorithm is triggered on the following two conditions When a session is initiated, it is triggered for the session to camp on the most appropriate RAT and select the most suitable bandwidth for the desired service. When a session terminates, it is also used to adjust the distribution of the ongoing sessions through the handovers. This will increase the adjustment frequency of the JRRM controller for the best system performance. Simulation results indicate that the proposed autonomic JRRM scheme not only effectively reduces the handover times, but also achieves well trade-off between the spectrum utility and the blocking probability.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.