Dynamic resource management has become an active area of research in the Cloud Computing paradigm. Cost of resources varies significantly depending on configuration for using them. Hence efficient management of resources is of prime interest to both Cloud Providers and Cloud Users. In this work we suggest a probabilistic resource provisioning approach that can be exploited as the input of a dynamic resource management scheme. Using a Video on Demand use case to justify our claims, we propose an analytical model inspired from standard models developed for epidemiology spreading, to represent sudden and intense workload variations. We show that the resulting model verifies a Large Deviation Principle that statistically characterizes extreme rare events, such as the ones produced by “buzz/flash crowd effects” that may cause workload overflow in the VoD context. This analysis provides valuable insight on expectable abnormal behaviors of systems. We exploit the information obtained using the Large Deviation Principle for the proposed Video on Demand use-case for defining policies (Service Level Agreements). We believe these policies for elastic resource provisioning and usage may be of some interest to all stakeholders in the emerging context of cloud networking.

Recently, server virtualization technology, which is one of the key technologies to support cloud computing, has been making progress and gaining in maturity, resulting in an increase in the provision of cloud-based services and the integration of servers in enterprise networks. However, the progress in network virtualization technology, which is needed for the efficient and effective construction and operation of clouds, is lagging behind. It is only recently that all the required technical areas have started to be covered. This paper identifies network-related issues in cloud environments, describes the needs for network virtualization, and presents the recent trends in, and application fields of, network virtualization technology.

When computing resources are consolidated in a few huge data centers, a massive amount of data is transferred to each data center over a wide area network (WAN). This results in increased power consumption in the WAN. A distributed computing network (DCN), such as a content delivery network, can reduce the traffic from/to the data center, thereby decreasing the power consumed in the WAN. In this paper, we focus on the energy-saving aspect of the DCN and evaluate its effectiveness, especially considering traffic locality, i.e., the amount of traffic related to the geographical vicinity. We first formulate the problem of optimizing the DCN power consumption and describe the DCN in detail. Then, numerical evaluations show that, when there is strong traffic locality and the router has ideal energy proportionality, the system's power consumption is reduced to about 50% of the power consumed in the case where a DCN is not used; moreover, this advantage becomes even larger (up to about 30%) when the data center is located farthest from the center of the network topology.

In the literature, two connectivity-based distributed clustering schemes exist: CDC (Connectivity-based Distributed node Clustering scheme) and SDC (SCM-based Distributed Clustering). While CDC and SDC have mechanisms for maintaining clusters against nodes joining and leaving, neither method assumes that frequent changes occur in the network topology. In this paper, we propose a lightweight distributed clustering method that we term SBDC (Schelling-Based Distributed Clustering) since this scheme is derived from Schelling's model – a popular segregation model in sociology. We evaluate the effectiveness of the proposed SBDC in an environment where frequent changes arise in the network topology. Our simulation results show that SBDC outperforms CDC and SDC under frequent changes in network topology caused by high node mobility.

Cloud data center services, such as video on demand (VoD) and sensor data monitoring, have become popular. The quality of service (QoS) between a client and a cloud data center should be assured by satisfying each service's required bandwidth and delay. Multipath traffic engineering is effective for dispersing traffic flows on a network; therefore, an improved k-shortest paths first (k-SPF) algorithm is applied to these cloud data center services to satisfy their required QoS. k-SPF can create a set of multipaths between a cloud data center and all edge routers, to which client nodes are connected, within one algorithm process. Thus, k-SPF can produce k shortest simple paths between a cloud data center and every access router faster than with conventional Yen's algorithm. By using a parameter in the algorithm, k-SPF can also impartially use links on a network and shorten the average hop-count and number of necessary MPLS labels for multiple paths that comprise a multipath.

In this paper, a novel charge coupled device matched filter (CCD-MF) for Electrical code division multiplexing (ECDM) decoder is proposed and experimentally demonstrated. Simulation results clarify the influence of low charge transfer efficiency (CTE) and the validity of a parallel CCD-MF we proposed. A 15-channel ECDM system using a 2 Gchip/s, 2-parallel CCD-MF is experimentally demonstrated.

To reduce the cost of fault management in all-optical networks, it is a promising approach to detect the degradation of optical signal quality solely at the terminal points of all-optical monitoring paths. The all-optical monitoring paths must be routed so that all single-link failures can be localized using route information of monitoring paths where signal quality degradation is detected. However, route computation for the all-optical monitoring paths that satisfy the above condition is time consuming. This paper proposes a procedure for deriving the lower bounds of the required number of monitoring paths to localize all single-link failures, and proposes an efficient monitoring path computation method based on the derived lower bounds. The proposed method repeats the route computation for the monitoring paths until feasible routes can be found, while the assumed number of monitoring paths increases, starting from the lower bounds. With the proposed method, the minimum number of monitoring paths with the overall shortest routes can be obtained quickly by solving several small-scale integer linear programming problems when the possible terminal nodes of monitoring paths are arbitrarily given. Thus, the proposed method can minimize the required number of monitors for detecting the degradation of signal quality and the total overhead traffic volume transferred through the monitoring paths.

We propose a primary traffic based multihop relaying algorithm with cooperative transmission (PTBMR-CT). It enlarges the hop transmission distances to reduce the number of cognitive relays on the route from the cognitive source (CS) to the cognitive destination (CD). In each hop, from the cognitive nodes in a specified area depending on whether the primary source (PS) transmits data to the primary destination (PD), the cognitive node that is farthest away from the cognitive relay that sends data is selected as the other one that receives data. However, when the PS is transmitting data to the PD, from the cognitive nodes in a specified area, another cognitive node is also selected and prepared to be the cognitive relay that receives data of cooperative transmission. Cooperative transmission is performed if the PS is still transmitting data to the PD when the cognitive relay that receives data of the next hop transmission is being searched. Simulation results show that the average number of cognitive relays is reduced by PTBMR-CT compared to conventional primary traffic based farthest neighbor relaying (PTBFNR), and PTBMR-CT outperforms conventional PTBFNR in terms of the average end-to-end reliability, the average end-to-end throughput, the average required transmission power of transmitting data from the CS to the CD, and the average end-to-end transmission latency.

Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

This paper presents the basic characteristics of a beam tilting slot antenna element whose forced resonance is realized by reactance loading; its structure complements that of a dipole antenna element. The radiation pattern is tilted using a properly determined driving point position; a single loading reactance is used to obtain the forced resonance without great changes in the tilt angle. Numerical results show that the reactance element needs to be loaded near the driving point in order to obtain the forced resonance of the antenna and the minimum changes in the beam tilt angle at the same time. When the proposed forced resonant beam tilting slot antenna with a 0.8 λ length is driven at -0.2 λ from the center, the main beam tilt angle of 57.7 degrees and the highest power gain of 3.8 dB are obtained. This slot element has a broad bandwidth, unlike the complementary dipole element.

This paper proposes a novel satellite channel allocation algorithm for a demand assigned multiple access (DAMA) controller. In satellite communication systems, the channels' total bandwidth and total power are limited by the satellite's transponder bandwidth and transmission power (satellite resources). Our algorithm is based on multi-carrier transmission and adaptive modulation methods. It optimizes channel elements such as the number of sub-carriers, modulation level, and forward error correction (FEC) coding rate. As a result, the satellite's transponder bandwidth and transmission power can be simultaneously used to the maximum and the overall system capacity, i.e., total transmission bit rate, will increase. Simulation results show that our algorithm increases the overall system capacity by 1.3 times compared with the conventional fixed modulation algorithm.

The power of laser radar received echoes varies over a large range due to many factors such as target distance, size, reflection ratio, etc, which leads to the difficulty of decoding codes from the received noise buried signals for spectrum code modulated laser radar. Firstly, a pseudo-random noise (PN) code modulated laser radar model is given, and the problem to be addressed is discussed. Then, a novel method based on Inter Symbol Interference (ISI) is proposed for resolving the problem, providing that only Additive White Gaussian Noise (AWGN) exists. The ISI effect is introduced by using a high pass filter (HPF). The results show that ISI improves laser radar receiver decoding ratio, thus the peak of the correlation function of decoded codes and modulation codes. Finally, the effect of proposed method is verified by a simple experiment.

We investigate in detail the scattering properties and heating characteristics in various commercially available optical fibers and fiber cables when a bubble train forms in the middle of the fiber as a result of the fiber fuse phenomenon that occurs when a high power signal is launched into the fiber. We found theoretically and experimentally that almost all the optical light is scattered at the top of the bubble train. The scattered light heats UV coated fiber, nylon jacketed silica fiber, fire-retardant jacketed fiber (PVC or FRPE jacketed fiber) and fire-retardant fiber cable (PVC or FRPE fiber cable), to around 100, over 200 and over 600, respectively, and finally the fiber burns and is destroyed at a launched optical power of 3 W. Furthermore, it is confirmed that the combustion does not spread when we use fire retardant jacketed fibers.

One of the most important constraints in wireless sensor networks (WSN) is that their nodes, in most of the cases, are powered by batteries, which cannot be replaced or recharged easily. In these types of networks, data transmission is one of the processes that consume a lot of energy, and therefore the embedded routing algorithm should consider this issue by establishing optimal routes in order to avoid premature death and eventually having partitioned nodes network. This paper proposes a new routing algorithm for WSN called Micro-Economic Routing Algorithm (MERA), which is based on the microeconomic model of supply-demand. In such algorithm each node comprising the network fixes a cost for relay messages according to their residual battery energy; and before sending information to the base station, the node searches for the most economical route. In order to test the performance of MERA, we varied the initial conditions of the system such as the network size and the number of defined thresholds. This was done in order to measure the time span for which the first node dies and the number of information messages received by the base station. Using the NS-2 simulator, we compared the performance of MERA against the Conditional Minimum Drain Rate (CMDR) algorithm reported in the literature. An optimal threshold value for the residual battery is estimated to be close to 20%.

We propose a novel scheme that aims to determine the optimal number of clusters based on the field conditions and the positions of mobile sink nodes. In addition, we merge algorithms of tree-based index structures to form an energy-efficient cluster structure. A performance evaluation shows that the proposed method produces highly-balanced clusters that are energy efficient and achieves up to 1.4 times higher survival rates than the previous clustering schemes, under various operational conditions.

In this paper, we propose a novel in-network aggregation scheduling scheme for forest fire monitoring in a wireless sensor network. This adaptively configures both the timeout and the collecting period according to the potential level of a fire occurrence. At normal times, the proposed scheme decreases a timeout that is a wait time for packets sent from child nodes and makes the collecting period longer. That reduces the dissipated energy of the sensor node. Conversely, the proposed scheme increases the timeout and makes the collecting period shorter during fire occurrences in order to achieve more accurate data aggregation and early fire detection.

In the IEEE 802.11e standard, a reference scheduler is presented. The reference scheduler uses the same service interval (SI) to poll all stations in a polling list, and uses separate scheduling and admission algorithms. This increases the polling overhead and decreases TXOP utilization. Many papers have attempted to enhance the reference scheduler, but its admission control is similar to reference scheduler. In this paper, we propose a scheduling and admission algorithm that assigns each station an SI close to its maximum SI (MSI). As a result, the proposed algorithm shows higher performance than that of the reference scheduler.

This paper proposes a novel routing algorithm that constructs position-based k-disjoint paths to realize greater resiliency to patterned failure. The proposed algorithm constructs k-disjoint paths that are spatially distributed by using the hop-count based positioning system. Simulation results reveal that the proposed algorithm is more resilient to patterned failure than other routing algorithms, while it has low power consumption and small delay.

The propagation of messages among a group of people, which forms opportunistic Disruption Tolerant Networking (DTN), can be modeled as dynamic graph with links joining every two nodes up and down at a stationary speed. As people in DTN might have different probabilities of sending messages to each other, they should be divided into distinct groups with different link generate speed λ and link perish speed µ. In this letter, we focus on the two-group case, and apply Edge-Markovian Dynamic Graphs to present an analysis framework to evaluate the average delay for the information dissemination in DTN. We also give extensive simulation and numerical results revealing the influence of various parameters.

This letter presents an efficient method for the maritime Loran-C additional secondary factor (ASF) correction based on equivalent ground conductivity inversion. Using the proposed method, the accuracy of Loran-C system on maritime positioning, navigation, and timing (PNT) can be improved significantly with a limited number of surveys. Comparison with measured ASF results shows a root-mean-square error (RMSE) of less than 100 ns in most areas.

Cooperative relay selection, in which one of multiple relays is selected to retransmit the source signal to the destination, has received considerable attention in recent years, because it is a simple way to obtain cooperative diversity in wireless networks. The exact expression of outage probability for a decode-and-forward cooperative relay selection with multiple source and destination antennas over Rayleigh fading channels was recently derived in [9]. In this letter, we derive the exact expressions of outage probability and diversity-multiplexing tradeoff over independent and non-identically distributed Nakagami-m fading channels as an extension of [9]. We then analyze the effects of various parameters such as fading conditions, number of relays, and number of source and destination antennas on the outage probability.

Orthogonal space-time block code (OSTBC) can achieve full diversity with a simple MLD, but OSTBC only achieves 3/4 of the maximum rate if more than two transmit antennas are used. To solve this problem, a quasi-orthogonal STBC (QOSTBC) scheme has been proposed. Even though a QOSTBC scheme can achieve the full rate, there are interference terms resulting from neighboring signals during detection. The existing QOSTBC using the pairs of transmitted symbols can be detected with two parallel MLD. Therefore, MLD based QOSTBC has higher complexity than OSTBC. To reduce the detection complexity, in this paper, we propose the heterogeneous constellation based QOSTBC for improving the detection property of QRD-MLD with maintaining a simple decoding structure.