A store and fordward speech interpolation telephonic concentrator system is introduced. This paper presents first the system, describes its main parts and components and using typical parameters the probable system operation is outlined. Following, a study on capacity and delay of transmission of each voice packet is done by supposing that a M/D/1 model can be applied to the system. As voice has special characteristics and packets don't arrive randomly as supposed in the M/D/1 model, an analysis using a computer simulation is done. The source generating speech is closely matched with human voice by using a model with good resolution specially for small pauses of talkers during the active generation of speech. Using this source, simulations representing 120 or 180 sec. of actual time are done. As its results are different of those predicted by the M/D/1 model, the capacity of the system is forecasted again through examples. To increase even more the capacity without impairing the frozen out fraction of the speech or increasing the delay of each packed, a different method to decrease congestion in those short moments of high arrival rate of packets is intended. This method consist in to transmit from each voice sample only 7 bits during the high congestion moments, creating new capacity by shortening packets. Results of parameters obtained by simulation and probable capacity of the system are again shown.

Multicast ATM switch is in great demand for the future communication network. We have proposed the Batcher banyan network with cell copy preparation stages as a transit switch. It performs cell replication with small hardware increase. On the trunkline, multicast traffic is quite little, thus hardware for cell copy can be sustained small. In those previous works, the effect of the external blocking was omitted. In this paper, we propose a multicast switching network which adopts the incomplete copy network that we have proposed, and examine several strategies to prevent the external blocking for this switching network. Namely, the input buffer method with an arbitration network is applied. For multicast usage, we propose two modifications. One is to arbitrate after cell replication for the sake of simple control and small hardware. The other is to annex a cell distribution network for smoothing biased cell arrival. Biased cell arrival occurs because the output of the incomplete copy network is not uniform. Simulation results show the effectiveness of the proposed method.

In wireless multi-hop networks such as ad hoc networks and sensor networks, backoff-based opportunistic routing protocols, which make a forwarding decision based on backoff time, have been proposed. In the protocols, each potential forwarder calculates the backoff time based on the product of a weight and global scaling factor. The weight prioritizes potential forwarders and is calculated based on hop counts to the destination of a sender and receiver. The global scaling factor is a predetermined value to map the weight to the actual backoff time. However, there are three common issues derived from the global scaling factor. First, it is necessary to share the predetermined global scaling factor with a centralized manner among all terminals properly for the backoff time calculation. Second, it is almost impossible to change the global scaling factor during the networks are being used. Third, it is difficult to set the global scaling factor to an appropriate value since the value differs among each local surrounding of forwarders. To address the aforementioned issues, this paper proposes a novel decentralized local scaling factor control without relying on a predetermined global scaling factor. The proposed method consists of the following three mechanisms: (1) sender-centric local scaling factor setting mechanism in a decentralized manner instead of the global scaling factor, (2) adaptive scaling factor control mechanism which adapts the local scaling factor to each local surrounding of forwarders, and (3) mitigation mechanism for excessive local scaling factor increases for the local scaling factor convergence. Finally, this paper evaluates the backoff-based opportunistic routing protocol with and without the proposed method using computer simulations.

Many new multimedia applications involve multiple dynamically changing participants, have stringent source-to-end delay requirements, and consume large amounts of network resources. A conventional algorithm that allows "two coming paths," where nodes in a multicast tree transmit several identical data flows, is therefore not practical. We have developed an algorithm for delay-constrained dynamic routing. This algorithm uses a QoS label to prevent the occurrence of "two coming paths," and can construct an efficient multicast tree for any traffic volume. The proposed algorithm was superior to conventional routing algorithms in terms of cost when nodes were added to or removed from the multicast group during a steady-state simulation.

With the arrival of B-ISDN, point-to-point routing alone is no longer adequate. A new class of computer and video related services, such as mass mailing, TV broadcasting, teleconferencing, and video 900 service, requires the network to handle multiple destination routing (MDR). Multiple destination routing enables widespread usage of multipoint services at a lower cost than networks using point-to-point routing. With this in mind, network providers are researching more into MDR algorithms. However, the MDR problem itself is very complex. Furthermore, its optimal solution, the Steiner tree problem, is NP-complete and thus not suitable for real-time applications. Recently, various algorithms which approximate the Steiner tree problem have been proposed and, in this invited paper, we will summarize the simulation results of these algorithms. But first, we will define the MDR problem, the issues involved, and the benchmark used to compare MDR algorithms. Then, we will categorize the existing MDR algorithms into a five-level classification tree. Lastly, we will present various published results of static algorithms and our own simulation results of quasi-static algorithms.

Recent studies have shown that the traffic load is often distributed unevenly among the access points. Such load imbalance results in an ineffective bandwidth utilization. The load imbalance and the consequent ineffective bandwidth utilization could be alleviated via intelligently selecting user-AP associations. In this paper, the diversity in users' utilities is sufficiently taken into account, and a Stackelberg leader-follower game is formulated to obtain the optimal user-AP association. The effectiveness of the proposed algorithm on improving the degree of load balance is evaluated via simulations. Simulation results show that the performance of the proposed algorithm is superior to or at least comparable with the best existing algorithms.

With the arrival of B-ISDN, widespread usage of multicast services such as TV broadcasting and video 900 services will increase the possibility of network congestion unless efficient multiple destination routing (MDR) algorithms are used. Current MDR algorithms using link cost based on bandwidth usage or distance to compute the minimum cost routing tree do not take into account the vast amount of information collected by intelligent network (IN) databases. In this paper, we propose a multicast routing algorithm which modifies the way the cost is calculated by using the predicted traffic statistics collected by IN databases. We also show that the traffic handling characteristics vastly improved over conventional MDR algorithms.

This paper focuses on learning the economic behaviour of the access point (AP) and users in wireless local area networks (WLANs), and using a game theoretic approach to analyze the interactions among them. Recent studies have shown that the AP would adopt a simple, yet optimal, fixed rate pricing strategy when the AP has an unlimited uplink bandwidth to the Internet and the channel capacity of WLAN is unlimited. However, the fixed rate strategy fails to be optimal if a more realistic model with limited capacity is considered. A substitute pricing scheme for access service provisioning is hence proposed. In particular, the AP first estimates the probable utility degradation of existing users consequent upon the admission of an incoming user. Second, the AP decides: (i) whether the incoming user should be accepted; and (ii) the price to be announced in order to try to maximize the overall revenue. The condition, under which the proposed scheme results in a perfect Bayesian equilibrium (PBE), is investigated.

Traditional traffic analysis is can be performed online only when detection targets are well specified and are fairly primitive. Local processing at measurement point is discouraged as it would considerably affect major functionality of a network device. When traffic is analyzed at flow level, the notion of flow timeout generates differences in flow lifespan and impedes unbiased monitoring, where only n-top flows ordered by a certain metric are considered. This paper proposes an alternative manner of traffic analysis based on source IP aggregation. The method uses flows as basic building blocks but ignores timeouts, using short monitoring intervals instead. Multidimensional space of metrics obtained through IP aggregation, however, enhances capabilities of traffic analysis by facilitating detection of various anomalous conditions in traffic simultaneously.

Multicast routing with Quality-of-Service (QoS) guarantees is the key to efficient content distribution and sharing. Developing QoS-aware multicast routing algorithm is an important open topic. This paper investigates QoS-aware multicast routing problem with K constraints where K > 2. The contributions made in this paper include a heuristic that employs the concept of nonlinear combination to extend the existing well-known algorithm for fast computation of a QoS multicast tree, and a Fully Polynomial Time Approximation Scheme (FPTAS) to approximate a multicast routing tree with QoS guarantees. The theoretical analyses and simulations conducted on both algorithms show that the algorithms developed in this paper are general and flexible, thus are applicable to the various networking systems.

This paper proposes a new dynamic multicast routing algorithm for layered streams. Since a layered multicast technique accommodates different types of users in the same multicast group, it helps to provide multicast services in a heterogeneous environment. However, this makes it difficult to construct an efficient routing tree when receivers join or leave a multicast session dynamically. In the proposed algorithm, we adopt a pre-determined path approach to handle such dynamic membership of a layered multicast session without the burden of much additional traffic. Simulation results show that the proposed algorithm can minimize the average multicast tree cost, and that it works well on large-scale networks and those with traffic heterogeneity and a small number of routing control messages.

This paper studies a video storage problem that occurs in Video-on-Demand (VOD) networks and in other distributed database systems. Videos should be stored in order to respect various constraints, especially available storage and transmission capacities. We show there exists an algorithm to solve this combinatorial problem through a pricing mechanism and that it converges to a solution under some general conditions. Simulation results with up to 43-node networks and up to 300 videos show that the algorithm is fast.

It is believed that the wavelength switched optical network (WSON) technology is moving towards being adopted by large-scale networks. Wavelength conversion and signal regeneration through reamplifying, reshaping, and retiming (3R) are beneficial to support the expansion of WSON. In many cases, these two functions can be technically integrated into a single shared physical component, namely the wavelength convertible 3R regenerator (WC3R). However, fully deploying such devices is infeasible due to their excessive cost. Thus, this topic serves as a motivation behind the investigation of the sparse placement issue of WC3Rs presented in this paper. A series of strategies are proposed based on knowledge of the network. Moreover, a novel adaptive routing and joint resource assignment algorithm is presented to provision the lightpaths in WSON with sparsely placed WC3Rs. Extensive simulation trials are conducted under even and uneven distribution of WC3R resource. Each strategic feature is examined for its efficiency in lowering the blocking probability. The results reveal that carefully designed sparse placement of WC3Rs can achieve performance comparable to that of full WC3R placement scenario. Furthermore, the expenditure of WC3R deployment also depends on the type of used WC3Rs characterized by the wavelength convertibility, i.e., fixed WC3R or tunable WC3R. This paper also investigates WSON from the perspective of cost and benefit by employing different types of WC3Rs in order to find the possibility of more efficient WC3R investment.

WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.

Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

With conventional dynamic routing algorithms, many query messages are required in a distributed environment for efficient multicast routing of any traffic volume. We have developed a dynamic routing algorithm that uses a predetermined path search in which an appropriate multicast path is dynamically constructed by searching only a few nodes. This algorithm can construct an efficient multicast tree for any traffic volume. Simulation has shown that the proposed algorithm is advantageous compared with conventional dynamic routing algorithms when nodes are added to or removed from the multicast group during steady-state simulation.

In NGN standards, End Host, also referred to as Terminal Equipment (TE), holds an important place in end-to-end path performance. However, most researchers neglect TE performance when considering performance of end-to-end paths. As far as the authors' knowledge goes, no previous study has proposed a model for TE performance. This paper proposes a method for measuring performance of TE and model extraction based on measurement data. The measurement was made possible with the use of a special NPU (Network Processing Unit) implemented as a programmable NIC. Along with the probing itself, a framework for removing the skew between the NPU and OS is developed in this paper. The multidimensional analysis includes method of probing, packet size and background traffic volume, and studies their effect on TE performance. A method for extracting a generic TE model is proposed. The outcome of this research can be used for modelling TE in simulations and in modelling end-to-end performance when considering QoS in NGN.

The demand for wireless traffic is increasing rapidly, which has posed huge challenges to mobile network operators (MNOs). A heterogeneous network (HetNet) framework, composed of a marcocell and femtocells, has been proved to be an effective way to cope with the fast-growing traffic demand. In this paper, we assume that both the macrocell and femtocells are owned by the same MNO, with revenue optimization as its ultimate goal. We aim to propose a pricing strategy for macro-femto HetNets with a user centric vision, namely, mobile users would have their own interest to make rational decisions on selecting between the macrocell and femtocells to maximize their individual benefit. We formulate a Stackelberg game to analyze the interactions between the MNO and users, and obtain the equilibrium solution for the Stackelberg game. Via extensive simulations, we evaluate the proposed pricing strategy in terms of its efficiency with respect to the revenue optimization.