To reduce power consumption of smartphones, this work proposes a novel discontinuous reception (DRX)-based power saving mechanism for LTE-A networks supporting multi-services. The novel designs of the proposed mechanism mainly include the highest priority-controlled DRX (HPC-DRX) and traffic regulation plus time slicing (TRTS) schemes. In our proposed HPC-DRX/TRTS, lower priority traffic never wakes user equipments (UEs) up and all incoming traffic for UEs is temporarily buffered at the evolved Node B (eNB) and then transmitted in bursts using the overall bandwidth, yielding much better power saving performance. To support multiple users with multi-services, this paper proposes the resource allocation and burst scheduling algorithms for the HPC-DRX/TRTS. The power saving ratios of the proposed mechanisms were theoretically analyzed based on an M/G/1 busy period model. Both the percentage of sleep period and actual power consumption model were used in calculating the power saving ratio. Numerical results show that our analytical results are accurate and the proposed HPC-DRX/TRTS significantly outperforms the conventional DRX, dynamic and adjustable DRX (DADRX), and coalesced DRX in terms of power saving ratio. In addition to significantly reducing power consumption of UEs with video streaming services and diverse data applications (DDA), the proposed HPC-DRX/TRTS preserves the video playout quality at UEs as well.

To improve bandwidth efficiency, multicast is used for mobile IPTV services. However, conventional multicast employs the most robust (lowest rate) modulation and coding scheme (MCS) for all multicasting channels to ensure that all users in a cell can receive videos with acceptable quality, leading to the worst spectral efficiency. To improve spectral efficiency, the adaptive MCS multicasting (aMCSm) scheme, which dynamically adjusts the MCS of each multicasting channel according to channel users' received signal-to-noise ratios (SNRs), was proposed. In this paper, the blocking rate, dropping rate, and bandwidth usage of mobile IPTV services under the aMCSm and the proposed admission control mechanism were analyzed based on a Markovian queueing model. The proposed mathematical model considers adaptive modulation and coding (AMC), time-varying link characteristics, channel popularity, and channel switching behavior. Numerical results demonstrate that our mathematical analyses are accurate and the aMCSm achieves better blocking rate and bandwidth usage performance, compared with the conventional multicast and multi-partition multicast schemes. The impact of channel switching or MCS variation on the performance of mobile IPTV services was investigated as well.

Video streaming uploading service over Vehicular Networks is very useful as it can support many applications. Due to the vehicle's high mobility and roadside access point (AP)'s sparse deployment, how to provide a high-quality video service with a low-price charge still remains an open question. To address this issue, a novel video uploading scheme based on vehicle moving prediction is proposed, in which the vehicle-to-infrastructure (V2I) and vehicle-to-vehicle communications (V2V) are cooperated to forward video streaming continuously from the moving vehicles to a fixed network. We make use of vehicle mobility prediction to find the stable relay nodes and reduce the link failure frequency, while an adaptive selection algorithm is used for roadside APs and gateway-vehicles to reduce the charge for video uploading. Experimental results show that the proposed scheme can achieve good performance while keeping a low application charge.

In virtualized data centers, live virtual machine (VM) migration can increase energy efficiency by consolidating VMs on fewer servers. This problem is usually considered as Bin Packing Problem with the server capacity constraints, such as CPU, memory and network bandwidth. In order to minimize the communication traffic in data center network, existing works proposed correlation-aware VM consolidation algorithms. VMs with high inter traffic will be consolidated as close as possible (e.g. Within a physical server). However, the traffic load of virtual switches causes a certain number of CPU cycles of physical servers to move traffic through virtual switches. This increases the risk that VMs running on servers are not allocated enough resource, and consequently reduces VMs' performance. In this work, we conduct experiments to estimate the server CPU overhead caused by virtual switching, and based on the experiment results, we propose virtual-switching-aware VM consolidation algorithm to solve this problem. Experiments on representative data center workloads show that the overhead can occupy 10% to 30% of server's CPU resources. Besides, our algorithm has a sharp decrease of the server capacity violation probability compared with the state-of-the-art baseline.

In recent years, virtualization technologies are applied to data centers for resource sharing. Virtual Machine Monitor (VMM) can consolidate virtual machines (VMs) running on multiple physical servers onto a single one via live VM migration, consequently improving energy efficiency of data centers. VM consolidation is usually modeled as a bin packing problem aiming at minimizing the number of servers being used. However, resource consumption overhead of consolidating VMs is seldom considered in existing approaches. In this paper, the overhead is defined as the resource consumption difference between the server and all the VMs running on it. We theoretically and experimentally prove that under the realistic constrains, this overhead exists and remains steady with the increasing of consolidating VMs. We also propose Margin Reserved Consolidation (MRC) algorithm to supplement existing works. Besides, we conduct experiments to validate the overhead. Experiments based on a representative benchmark show that 11.7% of the server's CPU resource is occupied by the overhead averagely.

The proposed GCRA traffic shaper consists of a regulator and a scheduler. It can shape multiple incoming variable bit rate (VBR) cell streams simultaneously to be strictly conforming according to the GCRA algorithm when the cells depart for the ATM output link. The impact of cell emission conflicts is considered and resolved by using a feedback signal from the scheduler to the regulator. The call admission control condition and the cell delay bound are derived. Simulation results demonstrate that the output cell streams of the proposed GCRA traffic shaper do not contain any non-conforming cells and the output queue size is significantly reduced.

A LAN environment in which two token rings are interconnected via remote bridges is considered. Traffic streams of two priority classes are supported. An approach is presented to characterize the output process of one token ring with a bridge node, using a three-phase Markov modulated Poisson process. Numerical results indicate that this approximate process can be much more accurate than the Poisson process for the performance analysis of the bridge node.