Dynamic virtual network allocation is a promising traffic control model for cloud resident data center which offers virtual data centers for customers from the provider's substrate cloud. Unfortunately, dynamic virtual network allocation designed in the past was aimed to the Internet so it needs distributed control methods to scale with such a large network. The price for the scalability of the completely distributed control method at both virtual layer and substrate layer is the slow convergence of algorithm and the less stability of traffic. In this paper, we argue that the distributed controls in both virtual and substrate networks are not necessary for the cloud resident data center environment, because cloud resident data center uses centralized controller as the way to give network control features to customers. In fact, we can use the centralized algorithm in each virtual data center which is not very large network and the distributed algorithm is only needed in substrate network. Based on the specific properties of this model, we have used optimization theory to re-design the substrate algorithm for periodically re-adjusting virtual link capacity. Results from theoretical analysis, simulations, and experiments show that our algorithm has faster convergence time, simpler calculation and can make better use of the feedback information from virtual networks than the previous algorithm.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

A new paradigm for building Virtual Controller Model (VCM) for traffic flow simulator is developed. It is based on flight plan data and is applied to Traffic Flow Management System (TFMS) in China. The problem of interest is focused on the sectors of airspace and how restrictions to aircraft movement are applied by air traffic controllers and demand overages or capacity shortfalls in sectors of airspace. To estimate and assess the balance between the traffic flow and the capacity of sector in future, we apply Virtual Controller model, which models by the sectors airspace system and its capacity constraints. Numerical results are presented and illustrated by applying them to air traffic data for a typical day in the Traffic Flow Management System. The results show that the predictive capabilities of the model are successfully validated by showing a comparison between real flow data and simulated sector flow, making this method appropriate for traffic flow management system.

We introduce a new kind of P2P traffic localization technique, called Netpherd, benefiting from the network virtualization technique for its successful deployment. Netpherd exploits one feature of P2P applications, a peer selection adaptation (i.e., preferring peers who are likely to provide better performance) for the traffic localization. Netpherd tries to enable local peers (i.e., peers in target network domain) to communicate with each other by affecting the peer selection adaptation. To affect the peer selection adaptation, Netpherd adds artificial delay to inter-domain traffic going to local peers. Our experiment conducted over Internet testbed verifies that Netpherd achieves the traffic localization and also improves the content download performance with the network delay insertion. In addition, we show that how the network virtualization technique can be utilized for efficient and graceful implementation of Netpherd.

The current amplify and forward (AF) model causes interference at a mobile terminal (MT) because of relay delay or noise amplification. Therefore, this paper proposes a MIMO phase control relaying system without amplification. The proposed scheme enhances both the communication quality and the channel capacity. Computer simulations indicate the effectiveness of the proposed scheme.

Software FMEA is valuable and practically used for embedded software of safety-critical systems. In this paper, a novel method for Software FMEA is presented based on co-analysis of system model and software model. The method is hopeful to detect quantitative and dynamic effects by a targeted software failure. A typical application of the method is provided to illustrate the procedure and the applicable scenarios. In addition, a pattern is refined from the application for further reuse.

In this letter, non-orthogonal amplify-and-forward (NAF) is considered in a half-duplex two-way system. We derive the closed-form outage probability in the high signal-to-noise ratio (SNR) region, and approximate it with a simpler version to enable power allocation. Then a closed-form power allocation scheme is proposed to improve the outage performance; it uses only statistical channel knowledge (SCK). It is validated that our analyses agree with simulation results and the proposed power allocation approaches the optimal power allocation.

Reconfigurable computing system is a class of parallel architecture with the ability of computing in hardware to increase performance, while remaining much of flexibility of a software solution. This architecture is particularly suitable for running regular and compute-intensive tasks, nevertheless, most compute-intensive tasks spend most of their running time in nested loops. Polyhedron model is a powerful tool to give a reasonable transformation on such nested loops. In this paper, a number of issues are addressed towards the goal of optimization of affine loop nests for reconfigurable cell array (RCA), such as approach to make the most use of processing elements (PE) while minimizing the communication volume by loop transformation in polyhedron model, determination of tilling form by the intra-statement dependence analysis and determination of tilling size by the tilling form and the RCA size. Experimental results on a number of kernels demonstrate the effectiveness of the mapping optimization approaches developed. Compared with DFG-based optimization approach, the execution performances of 1-d jacobi and matrix multiplication are improved by 28% and 48.47%. Lastly, the run-time complexity is acceptable for the practical cases.

This paper proposes an efficient broadcast scheme based on traffic density measurement to mitigate broadcast storms in Vehicular Ad Hoc Networks (VANETs). In a VANET, the number of vehicles that rebroadcasts a message is closely related with the collision ratio of the message, so a well-designed broadcast scheme should consider traffic density when rebroadcasting a message. The proposed scheme introduces a traffic density measurement scheme and broadcast scheme for VANET. It is based on the slotted p-persistence scheme, but the rebroadcast procedure is enhanced and the rebroadcast probability p is controlled dynamically according to the estimated traffic density. Simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of the end-to-end delay and collision ratio.

In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost charged for bandwidth and the cost for network infrastructure, respectively. Traffic localization is an effective way of reducing network traffic. Network traffic is localized when a client can obtain the requested content files from other a near-by altruistic client instead of the source servers. The concept of the peer-assisted content distribution network (CDN) can reduce the overall traffic with this mechanism and enable service providers to minimize traffic without deploying or borrowing distributed storage. To localize traffic effectively, content files that are likely to be requested by many clients should be cached locally. This paper presents a novel traffic engineering scheme for peer-assisted CDN models. Its key idea is to control the behavior of clients by using content-oriented incentive mechanism. This approach enables us to optimize traffic flows by letting altruistic clients download content files that are most likely contributed to localizing traffic among clients. In order to let altruistic clients request the desired files, we combine content files while keeping the price equal to the one for a single content. This paper presents a solution for optimizing the selection of content files to be combined so that cross traffic in a network is minimized. We also give a model for analyzing the upper-bound performance and the numerical results.

Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.

The copper nitride surface characteristics according to atmospheric pressure plasma (APP) and excimer ultraviolet (EUV) treatment were compared using XPS and AFM. As the result of XPS analysis result, in C1s, the organic material removal effect was greater for EUV treatment than for APP, and the oxygen content was found to be low. In Cu (933 eV) area, the shoulder peak of Cu compound was detected, and the reduction was greater for EUV processing than for APP. In the AFM phase image which could be analyzed using the superficial viscoelasticity, the same trend was observed. On the copper nitride surface, the weak boundary O layer is formed according to the clean processing, and such phenomenon was interpreted as a factor for lowering the affinity with polymer.

In this paper, we examine a new P2P traffic localization approach that exploits peer selection adaptation (i.e., preferring peers who are likely to provide better performance), called Netpherd. Netpherd enables peers to communicate with local domain peers by manipulating networking performance across network domains (i.e., adding an artificial delay to inter-domain traffic). Our feasibility study shows that Netpherd reduces the inter-domain traffic by influencing peer selection adaptation. Netpherd also improves download performance of the peers who know many local domain peers. We discuss one guideline to improve Netpherd based on the feasibility study and verify the guideline with evaluation results.

In this letter, we derive a lower bound on the diversity multiplexing tradeoff (DMT) in multiple-input multiple-output (MIMO) nonorthogonal amplify-and-forward (NAF) cooperative channels with resolution-constrained channel state feedback. It is shown that power control based on the feedback improves the DMT performance significantly in contrast to the no-feedback case. For instance, the maximum diversity increase is exponential in K with K-level feedback.

In this letter, a Simple but Effective Congestion Control scheme (SECC) in VANET has been proposed to guarantee the successful transmissions for safety-related nodes. The strategy derive a Maximum Beacon Load Activity Indicator (MBLAI) to restrain the neighboring general periodical beacon load for the investigated safety-related “observation nodes”, i.e., the nodes associated with some emergent events. This mechanism actually reserves some bandwidth for the safety-related nodes to make them have higher priorities than periodical beacons to access channel. Different from the static congestion control scheme in IEEE802.11p, this strategy could provide dynamic control strength for congestion according to tolerant packets drop ratio for different applications.

In this paper, we present a new fault-tolerant, large-scale star network scheme called Scalable Autonomous Fault-tolerant Ethernet (SAFE). The primary goal of a SAFE scheme is to provide network scalability and autonomous fault detection and recovery. SAFE divides a large-scale, mission-critical network, such as the naval combatant network, into several subnets by limiting the number of nodes in each subnet. This network can be easily configured as a star network in order to meet fault recovery time requirements. For SAFE, we developed a novel mechanism for inter-subnet fault detection and recovery; a conventional Ethernet-based heartbeat mechanism is used in each subnet. Theoretical and experimental performance analyses of SAFE in terms of fail-over time were conducted under various network failure scenarios. The results validate our scheme.

We derive a closed-form expression for the outage probability (OP), which is an important performance metric used to measure the probability that the target error rate performance of wireless systems exceeds a specified value, of multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems with best antenna selection under independent, but not necessarily identical distributed Nakagami-m fading. To gain further insights on the performance, the asymptotic approximation for OP, which reveals the diversity gain, is presented. We show that the diversity gain is solely determined by the fading severity parameters and increases with number of antennas at all nodes.

The need for the OpenGL-family of the 3D rendering API's are highly increasing, especially for graphical human-machine interfaces on various systems. In the case of safety-critical market for avionics, military, medical and automotive applications, OpenGL SC, the safety critical profile of the OpenGL standard plays the major role for graphical interfaces. In this paper, we present an efficient way of implementing OpenGL SC 3D graphics API for the environments with hardware-supported OpenGL 1.1 and its multi-texture extension facility, which is widely available on recent embedded systems. Our approach achieved the OpenGL SC features at the low development cost on the embedded systems and also on general personal computers. Our final result shows its compliance with the OpenGL SC standard specification. From the efficiency point of view, we measured its execution times for various application programs, to show a remarkable speed-up.

We investigate the impact of traffic on the performance of large-scale NAT (LSN), since it has been attracting attention as a means of better utilizing the limited number of global IPv4 addresses. We focus on the number of active flows because they drive up the LSN memory requirements in two ways; more flows must be held in LSN memory, and more global IPv4 addresses must be prepared. Through traffic measurement data analysis, we found that more than 1% of hosts generated more than 100 TCP flows or 486 UDP flows at the same time, and on average, there were 1.43-3.99 active TCP flows per host, when the inactive timer used to clear the flow state from a flow table was set to 15 s. When the timer is changed from 15 s to 10 min, the number of active flows increases more than tenfold. We also investigate how to reduce the above impact on LSN in terms of saving memory space and accommodating more users for each global IPv4 address. We show that to save memory space, regulating network anomalies can reduce the number of active TCP flows on an LSN by a maximum of 48.3% and by 29.6% on average. We also discuss the applicability of a batch flow-arrival model for estimating the variation in the number of active flows, when taking into account that the variation is needed to prepare an appropriate memory space. One way to allow each global IPv4 address to accommodate more users is to better utilize destination IP address information when mapping a source IP address from a private address to a global IPv4 address. This can effectively reduce the required number of global IPv4 addresses by 85.9% for TCP traffic and 91.9% for UDP traffic on average.

Internet behavior is becoming more complex due to ever-changing networking technologies and applications. Thus, understanding and controlling the complex behavior of the Internet are important for designing future networks. One of the complex behaviors of the Internet is traffic dynamics. Previous studies revealed that flow control in the transport layer affects the traffic dynamics of the Internet. However, it is not clear how the topological structure impacts traffic dynamics. In this paper, we investigate packet delay dynamics and traffic fluctuation in ISP router-level topologies where the degree distribution exhibits a power-law nature, and the nodes interact via end-to-end feedback control functionality. We show the packet delay dynamics of the BA topologies generated by the Barabasi-Albert (BA) model and the ISP router-level topologies. Simulation results show that the end-to-end delay distributions exhibit a heavy tail in the TCP model. Moreover, the number of links with highly fluctuating queue length increases dramatically compared to that in the stop-and-wait model. Even in this case, the high-modularity structures of the ISP topologies reduce the number of highly fluctuating links compared with the BA topologies.