Search

Recent research trends exhibit a growing imbalance between the demands of tenants’ software applications and the provisioning of hardware resources. Misalignment of demand and supply gradually hinders workloads from being efficiently mapped to fixed-sized server nodes in traditional data centers. The incurred resource holes not only lower infrastructure utilization but also cripple the capability of a data center for hosting large-sized workloads. This deficiency motivates the development of a new rack-wide architecture referred to as the composable system . The composable system transforms traditional server racks of static capacity into a dynamic compute platform. Specifically, this novel architecture aims to link up all compute components that are traditionally distributed on traditional server boards, such as central processing unit (CPU), random access memory (RAM), storage devices, and other application-specific processors. By doing so, a logically giant compute platform is created and this platform is more resistant against the variety of workload demands by breaking the resource boundaries among traditional server boards. In this paper, we introduce the concepts of this reconfigurable architecture and design a framework of the composable system for cloud data centers. We then develop mathematical models to describe the resource usage patterns on this platform and enumerate some types of workloads that commonly appear in data centers. From the simulations, we show that the composable system sustains nearly up to 1.6 times stronger workload intensity than that of traditional systems and it is insensitive to the distribution of workload demands. This demonstrates that this composable system is indeed an effective solution to support cloud data center services. [ABSTRACT FROM AUTHOR]

With the recent emergence of naked-eye 3D mobile devices and various 3D-enabled laptops, service providers now afford the opportunity to provide mobile 3D video streaming in LTE-Advanced networks. Differing from traditional single-view 3D videos, multi-view 3D videos allow users to choose preferred view angles and thus are promising for new applications, such as free-viewpoint television (FTV). Nevertheless, enabling multi-view 3D video services may overwhelm the network resource when transmitting all views of every video. Fortunately, Depth-Image-Based Rendering (DIBR) allows each mobile client to synthesize the desired view from a nearby left view and right view, so that not all views of a video are necessarily transmitted. A new challenge with DIBR, however, is to carefully choose the transmitted views to limit the video distortion and minimize the bandwidth consumption. In this paper, therefore, we first formulate a new optimization problem, called View and MCS Selection (VMS) Problem, to minimize the bandwidth consumption for multi-view 3D video multicast in LTE networks. An algorithm, called View and MCS Aggregation (VMAG) is proposed to find the optimal solution to VMS. For Carrier Aggregation (CA) in LTE-Advanced networks, we formulate a new View, MCS and Carrier Selection (VMCS) Problem and prove that the problem is NP-Hard. We first design a dynamic programming algorithm, called the View Assignment with MCS and Carrier (VAMC) algorithm, to find the optimal solution for small instances. We then propose the View and MCS Aggregation with Carrier (VMAGC) algorithm based on VMAG to effectively find the near-optimal solution to VMCS. The simulation results show that bandwidth consumption can be effectively reduced by over 30 percent in VMS and VMCS. [ABSTRACT FROM PUBLISHER]

Ultra-dense network is a promising technology for 5G cellular networks, and its approach is to densify the network to enhance system throughput via universal frequency reuse. Traditionally, macro cells and small cells usually operate on separate dedicated channels in the ultra-dense environment. This dedicated channel approach leads to resource underutilization because base stations may not be able to fully utilize their radio resource with fixed partitioning when the traffic load in the network is fluctuating. In this paper, we study this underutilization problem in ultra-dense heterogeneous networks, and propose two adaptive channel partitioning schemes to enhance the system throughput: D2CP and D2CP-C. Both schemes require the coordination between macrocell and small cells, and D2CP-C takes advantage of cross-tier cooperation to further enhance the system throughput. We analyze the proposed schemes based on stochastic geometry, and evaluate the performance via simulations. The simulation results show that D2CP and D2CP-C outperform fixed channel partitioning by 33.37% and 76.01%, respectively, demonstrating that base station coordination and cross-tier cooperation can achieve better radio resource utilization in ultra-dense heterogeneous networks. [ABSTRACT FROM AUTHOR]

Network virtualization is an essential technique for data center operators to provide traffic isolation, differentiated service, and security enforcement for multi-tenant services. However, traditional protocols used in local area networks may not be applicable for data center networks due to the difference in network topology. Recent research suggests that layer-2-in-layer-3 tunneling protocols may be the solution to address the challenges. In this article, we find via testbed experiments that directly applying these tunneling protocols toward network virtualization only results in poor performance due to the scalability problems. Specifically, we observe that the bottlenecks actually reside inside the servers. We then propose a CPU offloading mechanism that exploits a packet steering function to balance packet processing among available CPU threads, thus greatly improving network performance. Compared to a virtualized network created based on VXLAN, our scheme improves the bandwidth for up to almost 300 percent on a 10 Gb/s link between a pair of tunnel endpoints. [ABSTRACT FROM AUTHOR]

Depth-Image-Based Rendering (DIBR) is a popular technology and enables the viewers to watch multi-view 3D videos via TV or smart phone. In this paper, we propose a game-theoretical framework over a multi-view and multi-video network where one server delivers multiple multi-view 3D videos to multiple viewers. In a mobile network, any individual viewers can subscribe to a video with any viewing angle within a specified viewing range in 3D-enabled mobile handsets. To facilitate efficient resource allocation for multi-view 3D videos, we formulate a new resource allocation problem, named Price-based 3D Viewing Range Control problem (PVRC), as a Stackelberg game in Game Theory, in which the server and the viewers are modeled as the leader and the followers, respectively, to jointly consider the revenue of the server and the utilities of the viewers. We analyze the price setting problem by investigating the Stackelberg equilibrium between the server and viewers. Simulation results demonstrate that compared to popular uniform-price setting, non-uniform pricing is an effective approach for reducing the difference of utilities among the viewers, effectively controlling the viewing ranges and avoiding starvation of the network resources to only few viewers. Moreover, we also derive the social optimum in the problem, and the simulation results show that the derived Stackelberg equilibrium is close to the social optimum. [ABSTRACT FROM AUTHOR]